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Abstract

The cardiovascular apparatus supplies blood to the body’s organs and responds to sudden changes in demand for nutrients according to the organism’s activity. Blood velocity and pressure can be associated with kinetic and potential energy, respectively.

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Notes

  1. 1.

    Coronary perfusion can be modeled using a poroelastic model for the myocardial microcirculation and a Darcy solver using the arbitrary Lagrangian–Eulerian (ALE) formulation.

  2. 2.

    A semi-implicit coupling scheme that exhibits a good stability has been proposed [4]. The pressure stress is implicitly coupled with the structure to ensure stability; remaining terms are explicitly treated. The implicit–explicit splitting can be conveniently performed using a Chorin–Temam projection scheme. A stabilized explicit coupling scheme based on Nitsche’s method can be used, stability being independent of the fluid–structure density ratio [5].

  3. 3.

    Heart valve motions rely on a multibody contact problem with attachment constraints due to chordæ tendinæ [7]. The fluid and immersed valve meshes do not match; the kinematic continuity is imposed using Lagrange multipliers. The method relies on a fictitious domain, which allows very large displacements, combined with the ALE formalism to manage both elastic valve and wall motions. A partitioned fluid–structure algorithm associates independent fluid and structure solvers.

  4. 4.

    Valve cusps do not evert into the atrium during the ventricular systole by contraction of the papillary muscles, which are related to ventricular myocardium.

  5. 5.

    In 1895, Frank found that under isovolumetric conditions, the larger the EDV, the greater the developed tension and pressure. Starling’s later experiments demonstrated that the heart intrinsically responds to venous return (to EDV) increases by increasing the stroke volume (heart autoregulation). The relationship between EDV and stroke volume is associated with the relationship between sarcomere length and calcium ion influx and sensitivity. Myofilament length-dependent activation is explained by the separation distance between actin and myosin along the sarcomeric filament axis. The intrinsic ability of the heart to develop greater tension at longer myocardial fiber lengths over a finite range of fiber lengths is due to sliding filament arrangement in cardiomyocytes, with increase of cross-bridge number between actin and myosin filaments. The Frank–Starling mechanism refers to the heart’s intrinsic capability of increasing inotropy and stroke volume in response to venous-return increase. The Frank–Starling effect describes static filling mechanisms in an isolated motionless heart. It works for high filling pressure and low flow rate (cardiac failure); however, cardiac functioning is an unsteady phenomenon.

  6. 6.

    This frequency-dependent enhanced contractility helps to offset the decreased ventricular filling time at higher cardiac frequencies by shortening the systole time duration, thereby increasing the time available for diastole.

  7. 7.

    Positive chronotropy (C+) induces positive inotropy (I+).

  8. 8.

    During systole, the heart moves downward.

  9. 9.

    The mitral annulus descends about 1.3 cm during the left ventricular ejection phase in normal subjects [16].

  10. 10.

    Cardiac β-myosin is a mechanoenzyme that converts the energy from ATP hydrolysis for muscle contraction. Two cardiac myosin heavy chains (α MHC–β MHC) have different levels of ATPase activity. The β MHC and α MHC subtypes are predominantly expressed in late fetal life and adults, respectively. The former is encoded by the MYH7 gene.

  11. 11.

    The resting transmembrane potential is higher (less negative) in cardiofibroblasts than that of cardiomyocytes. During action potential upstroke, the transmembrane potential of cardiomyocytes becomes higher than that of cardiofibroblasts, which then can act as current sinks, which slows down cardiomyocyte activation and can attenuate maximum upstroke velocity and peak amplitude of the action potential [18].

  12. 12.

    The conduction velocity generally increases initially and then decreases when cardiofibroblast density and/or coupling increase.

  13. 13.

    \(\updelta \upupsilon \upalpha \varsigma\): couple, pair, binary number.

  14. 14.

    In the myocardium, a diad means that a T tubule is associated with a single terminal cisterna. On the other hand, in the skeletal muscle, a triad is formed by a T tubule flanked on either side by the junctional sarcoplasmic reticulum, at the level of the Z line.

  15. 15.

    The principal cardiac pore-forming α subunit isoform NaV1.5 preferentially localizes to intercalated discs, whereas the brain-type α subunit isoforms NaV1.1, NaV1.3, and NaV1.6 reside in transverse tubules [26]. They contribute to the coupling of sarcolemmal depolarization to contraction. On the other hand, NaV1.5 in intercalated discs is primarily responsible for action potential conduction between cardiomyocytes.

  16. 16.

    Cardiac inward rectifier K + currents (i K1) through channels of the KIR2 category participate in the maintenance of resting membrane potential as well as late phase repolarization. In rabbits, KIR2.1 and KIR2.2, which lodge in T tubules, but not KIR2.3, are synthesized in ventriculomyocytes [27]. Current i K1 is predominantly due to KIR2.1–KIR2.2 heterotetramers. In mice, i K1 also crosses KIR2.1–KIR2.2 heterotetramers. In guinea pigs, KIR2.1, KIR2.2, and KIR2.3, but not KIR2.4 are produced in ventriculomyocytes [28]. Three different inward rectifier conductances are linked to KIR2.1, KIR2.2, and KIR2.3 homotetrameric channels, intermediate-conductance KIR2.1 and large-conductanceIR2.2 being the primary determinants of i K1 current with little contribution from low-conductance KIR2.3 channel [28]. In humans, KIR2.1 resides in ventriculomyocytes, KIR2.1 and KIR2.2 in atrial cells, and KIR2.3 in ventricular cells (cells including not only cardiomyocytes, but also endotheliocytes, vascular smooth myocytes, cardiofibroblasts, and neurons, among others). In the guinea pig heart, KIR2.1, KIR2.2, and KIR2.3 are expressed in both cardiomyocytes and capillary endotheliocytes. Subunit KIR2.4 is restricted to cardiac parasympathetic and postganglionic sympathetic neurons as well as sensory nerve fibers [28].

  17. 17.

    The lumen of T tubules varies within a given mammalian species. Using confocal microscopy, it was assessed to be about 400 nm in humans [22]. However, stimulated emission depletion (STED) imaging that has a better spatial resolution detects a lower caliber.

  18. 18.

    Although the volume density of the T-tubule network is only 1 to 3%, it represents about one-third of the entire plasma membrane area [22]. Transverse tubule density varies among ventriculomyocytes from different animal species.

  19. 19.

    P110αPI3K and P110βPI3K are required for the maintenance of the organized network of T tubules, as they regulate junctophilin-2 localization [30]. The 4 junctophilins tether the plasma membrane to the endoplasmic reticulum in excitable cells. The major cardiac junctophilin isoform JP2 has a C-terminal transmembrane domain that anchors the protein in the SR membrane and 8 N-terminal membrane occupation and recognition nexus (MORN) motifs that interact with the plasma membrane to stabilize the junction between the plasma and SR membrane.

  20. 20.

    A.k.a. mortalin Mot2, peptide-binding protein PBP74, mitochondrial stress protein-70, 75-kDa mitochondrial heat shock protein mtHSP75, and 75-kDa glucose-regulated protein GRP75.

  21. 21.

    Reactive oxygen species comprise free radicals with an unpaired electron (e.g., membrane-impermeable O2 •−, and extremely short lifetime OH ) and nonradical derivatives (e.g., more stable, membrane-permeable H2O2). The main reactive nitrogen species is the free radical NO .

  22. 22.

    Only Nox1, Nox2, and Nox4 isoforms are synthesized in the heart. Among them, Nox2 localized to T tubules is the predominant isoform in the adult cardiomyocyte.

  23. 23.

    Subtype NOS3 preferentially lodges in caveolae of the sarcolemma at T tubules and crests. Isoform NOS2 resides in caveolae and SR membrane.

  24. 24.

    Calcium ion signaling ability derives almost entirely from its binding to and unbinding from target proteins and its fluxes through permeable carriers that depolarize the plasma membrane. The cyclic rise and fall of intracellular Ca 2+ concentration engages and disengages the molecular machinery of contractile myofilaments.

  25. 25.

    During restoration, cytosolic Ca 2+ ions reenter the sarcoplasmic reticulum through sarco(endo)plasmic reticulum Ca 2+ ATPase (SERCA) and is extruded to the extracellular space by sarcolemmal Na +–Ca 2+ exchanger (NCX) and plasma membrane Ca 2+ ATPase (PMCA).

  26. 26.

    Myokinase converts ATP and AMP into 2 ADP molecules.

  27. 27.

    Oxidation of NADH at ETCcomplex-I is indirectly coupled to ATP production. Oxidation of FADH2 bypasses ETCcomplex-I, thereby pumping fewer H + across the inner mitochondrial membrane. Therefore, in addition to a greater oxygen requirement than that using glucose as input substrate, fatty acids are less efficient for the generation of ATP than glucose [38].

  28. 28.

    Most exogenous triacylglycerols derive from chylomicrons; a minor part originates from VLDL particles. A significant proportion of fatty acids from VLDLs is taken up by cardiac VLDL–apoE receptors. VLDL-derived fatty acids are equally distributed between β-oxidation and deposition into intramyocardial lipids.

  29. 29.

    Concentration of FFAs can vary from very low values in the fetal circulation to more than 2 mmol during myocardial ischemia and uncontrolled diabetes [38]. Activated sympathetic nervous system can rapidly increase circulating FFA concentration, primarily via stimulation by β-adrenoceptors of hormone-sensitive lipase in adipose tissue. Lipoprotein lipase is responsible for most FFAs from chylomicrons used for fatty acid β-oxidation.

  30. 30.

    Uncoupling proteins (UCP1–UCP5) are mitochondrial transport proteins that serve for the reentry of protons from the intermembrane space to the mitochondrial matrix uncoupled to ATP synthesis. Subtype UCP1 is highly expressed in brown adipose tissue, but not in the heart. Ubiquitous UCP2 minimizes generation of mitochondrion-derived reactive oxygen species. Isoform UCP3, a fatty acid anion transporter, is highly produced in the heart, skeletal muscle, and brown adipose tissue.

  31. 31.

    Fatty acid anions are also generated in the cytosol during hydrolysis of cytosolic fatty acylCoA by cytosolic thioesterases.

  32. 32.

    Pyruvate dehydrogenase is phosphorylated (inactivated) by pyruvate dehydrogenase kinase (PDHK) and dephosphorylated (activated) by pyruvate dehydrogenase phosphatase (PDHP). Among the 4 isoforms (PDHK1–PDHK4), PDHK4 is the predominant cardiac isoform. Pyruvate dehydrogenase kinase is inhibited by pyruvate and reduced acetylCoA/CoA and NADH/NAD + ratios [38]. A high level of circulating free fatty acids and intracellular accumulation of long-chain fatty acids support NR1c1-mediated PDHK4 synthesis. Pyruvate dehydrogenase phosphatase is activited by Ca 2+ and Mg 2+ ions.

  33. 33.

    Pyruvate is the usual mitochondrial fuel produced by glycolysis.

  34. 34.

    Mutations in the OPA1 gene cause autosomal dominant type-1 optic atrophy. Optic atrophy protein OPA1, a.k.a. mitochondrial genome maintenance protein MGM1 and mitochondrial nucleoid protein, contains a mitochondrial targeting signal, hence localizing to mitochondria.

  35. 35.

    Methyltransferases of the NOL1–NOP2–SUn (Sad1P [Schizosaccharomyces pombe] and Unc84 [Caenorhabditis elegans)] domain-containing protein family catalyzes the methylation of cytosine to 5-methylcytosine. The proteic domain refers to ribosomal RNA methyltransferase nucleolar protein homolog NoL1, also called NoP2 and NSun1, which is found in archaeal, bacterial, and eukaryotic proteins.

  36. 36.

    Subunit Med13 is also targeted by miR208a and other muscle-specific miRNAs encoded by introns of myosin heavy-chain genes.

  37. 37.

    Pyruvate dehydrogenase enables entry from glycolysis to oxidative phosphorylation. Glycogen processing by glycogen phosphorylase is the early metabolic response to cardiac work change.

  38. 38.

    Adenine nucleotide transport occurs as an electroneutral divalent exchange of MgATP 2− for HPO4 2− anion. In biology, phosphorus is found as a free phosphate ion in solution and is called inorganic phosphate (generally denoted P i ) to distinguish it from phosphates bound in various phosphate compounds, especially adenosine phosphates (AMP, ADP, and ATP). In a dilute aqueous solution, phosphate exists in 4 forms. The phosphate ion (PO4 3−) is the conjugate base of the hydrogen phosphate divalent ion (HPO4 2−) that is the conjugate base of the dihydrogen phosphate monovalent ion (H2PO4 ), which in turn is the conjugate base of phosphoric acid (H3PO4). In humans, H +- and Na +-dependent renal type-2a sodium–phosphate cotransporter also has a preferential affinity for the inorganic phosphate species HPO4 2− [52].

  39. 39.

    Electrogenic ATP 4−–ADP 3− exchange. The charge imbalance associated with the adenine nucleotide carrier leads to a large difference in the ATP/ADP ratio between the mitochondrial matrix space and cytosol. The transport of ATP, ADP, and phosphate across the inner mitochondrial membrane costs additional energy (about 1/3 of the minimum required for ATP synthesis within the mitochondrial matrix) supplied by the respiratory chain.

  40. 40.

    I.e., ONOO reacts nucleophilically with carbon dioxide. In vivo, the concentration of CO2 is about 1 mmol; its reaction with ONOO occurs quickly to form nitrosoperoxycarbonate (ONOOCO2 ).

  41. 41.

    An adduct (Latin adductus: strict) is a product of a direct addition of at least 2 distinct molecules forming a single reaction product that contains all atoms of all components.

  42. 42.

    Dissociation of a molecule generating 2 free radicals.

  43. 43.

    In chemistry, the cage effect describes influence of its surroundings on properties of a molecule. In a solvent, a molecule is often supposed existing in a cage of solvent molecules, the so-called solvent cage. Reactions occur when a molecule occasionally exits and meets another molecule.

  44. 44.

    Hydrogen peroxide carries out a 2-electron oxidation of heme-peroxidase produced compound-1 (obtained by monovalent reaction from NO2 into NO2 ) and compound 2 (result of another NO2 molecule forming a second molecule of NO2 ). Nitrogen dioxide can promote nitration of free and protein tyrosine, performing Tyr oxidation to tyrosine, followed by the addition of a second NO2 molecule [58]. However, nitrogen dioxide alone is an inefficient nitrating catalyst, as 2 NO2 molecules are needed to nitrate one tyrosine and because NO2 -mediated oxidation of tyrosine is slow w.r.t. oxidation of thiols.

  45. 45.

    SCOT-knockout mice develop hyperketonemic hypoglycemia and die within 48 h of extrauterine life [71].

  46. 46.

    D3-Hydroxy[3-14C]butyrate is incorporated into lipid in lactating mammary glands of rats, a major site of ketone body utilization. This incorporation decreases in short-term insulin deficiency (2 h) and starvation (24 h), but increases again on refeeding (2 h) [72]. The activity of cytosolic acetoacetylCoA synthase follows changes in nutritional state, but is not affected by short-term insulin deficiency.

  47. 47.

    β-Oxidation is the sequential derivation of 2 carbon units in the form of acetylCoA from fatty acyl chains. It mainly occurs within the mitochondrial matrix and sometimes in peroxisomes.

  48. 48.

    I.e., synthesis of new lipids from acetylCoA using acetylCoA carboxylase and fatty acid synthase.

  49. 49.

    In obesity, lipolysis is deregulated. The basal lipolysis rate rises. The concentration of circulating free fatty acids augments, hence provoking insulin resistance. Stimulation of lipolysis by catecholamines as well as its inhibition by insulin are precluded.

  50. 50.

    Nicotinic acid, also termed niacin, vitamin-B3, and vitamin-PP, is used in the treatment of dyslipidemia. It increases the concentration of high-density lipoproteins and decreases that of very-low-density and low-density lipoproteins [73]. Nicotinic acid also lowers plasma concentrations of free fatty acids and triglycerides. It decreases lipolysis in adipocytes, as it impedes cAMP accumulation via the Gi–ACase axis and hormone-sensitive triglyceride lipase [74].

  51. 51.

    Two subtypes of GPR109 exist (GPR109a–GPR109b) that are also called nicotinic acid and niacin receptor-1 and -2 (NiacR1–NiacR2) as well as protein upregulated in macrophages by interferon-γ (PUMaγ) in mice and HM74a and HM74b (HM74) in humans. NiacR1 and NiacR2 are high- and low-affinity receptor for nicotinic acid, respectively [73]. Receptor NiacR1 is highly expressed in adipose tissue and spleen. In fact, NiacR1 is also detected in the lung and trachea, whereas NiacR2 resides in the lung, adipose tissue, and spleen, as well as leukocytes. The ligand-inducible nuclear receptor NR1c3 (or PPARγ) is necessary and sufficient for adipogenesis, as it controls the differentiation, maintenance, and function of adipocytes. It also regulates numerous genes of the adipocytic phenotype, such as those involved in lipid uptake (e.g., lipoprotein lipase, scavenger receptor ScaRb3, and oxidized LDL receptor) and synthesis, lipid storage and lipid droplet stabilization (e.g., perilipin), glycerol and fatty acid recycling (i.e., reesterification of fatty acids and glycerol to triglycerides), and fatty acid oxidation [75]. The transcription factor NR1c3 has 2 isoforms, NR1c3a (PPARγ1) and NR1c3b (PPARγ2). The latter that has a longer N-terminus is restricted to adipocytes. The former is more widely distributed (e.g., adipocytes, enterocytes, monocytes, and macrophages). Polyunsaturated fatty acids and eicosanoids activate NR1c3 factor. Factor NR1c3 heterodimerizes with retinoic acid X receptors (NR2b) and binds to PPAR-responsive elements (PPREs). The human antilipolytic G-protein-coupled receptors comprise GPR81, GPR109a, and human-specific GPR109b. The genes that possess a NR1c–NR2b-binding site in their promoter, such as those encoding GPR81, GPR109a, and GPR109b, contribute to the reduction of circulating free fatty acids [75]. The Gpr81, Gpr109A, and Gpr109B genes colocalize in chromosome 12q24.31. In addition, certain aromatic Damino acids, including Dphenylalanine, Dtryptophan, and the metabolite of the latter, Dkynurenine, connect to GPR109b, which abounds in human neutrophils, but not GPR109a [76]. DIsomers may operate as hormonal, antibacterial, or modulatory peptides of immunity, or neuropeptides. They serves as chemoattractants for neutrophils via activated GPR109b. They diminish the activity of adenylate cyclase and elicit a transient influx of calcium ions. The potent chemotactic factor for eosinophils and neutrophils, 5-oxo-eicosatetraenoic acid, links to GPR48 receptor, which has high sequence similarity to GPR109b. Other chemotactic GPCRs comprise GPCRs for leukocyte chemoattractants CXCL8, C5a, Nformyl methionyl-leucyl-phenylalanine (fMLP), platelet-activating factor, and leukotriene-B4), as well as human, neutrophil-specific, Gi/o- and Gq-coupled GPR43 receptor for short chain fatty acids, such as sodium acetate and sodium propionate, which are by-products of anaerobic bacteria.

  52. 52.

    Acetate is rapidly taken up by cells and is transformed to acetylCoA in both the cytosol and mitochondria by acetylCoA synthase. AcetylCoA is a common metabolic intermediate for synthesis of cholesterol and fatty acids, which are incorporated into membranes. In mitochondria, acetylCoA is also oxidized in the tricarboxylic acid cycle to carbon dioxide and water. The radiochemical acetate is used as a positron emission tomography (PET) tracer for studying myocardial oxidative metabolism and regional myocardial blood flow.

  53. 53.

    In tumoral cells, overexpressed fatty acid synthase converts most of the acetate into fatty acids that are incorporated into intracellular phosphatidylcholine-based membrane nanodomains.

  54. 54.

    A.k.a. ankyrin-R, R standing for restricted expression and RBC-related isoform.

  55. 55.

    A.k.a. ankyrin-B referring to broad expression and brain-related isoform.

  56. 56.

    A.k.a. ankyrin-G (general expression).

  57. 57.

    Interacting proteins include PKA, CamK2, methylase, cytosolic protein Tyr phosphatase PTPn3, glycerol-3-phosphate dehydrogenase 1-like protein (GPD1L), α-actinin, ankyrin-3, calcium ion, calmodulin, caveolin-3, N-cadherin, connexin-43, disc large homolog DLg1, fibroblast growth factor FGF12, Nedd4-2 ubiquitin ligase, plakophilin-2, RanGRF, syntrophin-α1, -β1, -β2, and -γ2, telethonin, and 14-3-3η [89]. N-glycosylation of NaV1.5 associated with glycogenes (i.e., glycosyltransferases, glycosidases, and sugar nucleotide synthesis and transporters) modulates its electrical signaling. It is phosphorylated by PKA, PKC, CamK2, Fyn, and dephosphorylated by PTPn3 [89].

  58. 58.

    In addition to SucnR1, extracellular succinate is actively transported through sodium–dicarboxylate cotransporters. These cotransporters are not produced in the heart.

  59. 59.

    Current models use local tensors representing electrical conductivity and mechanical stiffness parameters in 3 orthogonal directions (myofiber, in-sheet transverse, and sheet-normal axis) in few parietal layers.

  60. 60.

    Typically, it consists of a periodic train of brief pulses (duration 1 ms; magnitude ∼ twice the amplitude required to excite fully recovered tissue).

  61. 61.

    The mean arterial pressure is underestimated using 0.333 as a multiplier rather than 0.412 [121]:

    $$\mathrm{mAP} = p_{\mathtt{d}} + 0.412(p_{\mathtt{s}} - p_{\mathtt{d}}).$$
  62. 62.

    Acetylcholine primes vasodilation of both local and regional arterioles and arteries.

  63. 63.

    Subtype PKG1 is the predominant vascular isoform.

  64. 64.

    A major subtype in smooth myocytes.

  65. 65.

    On the other hand, PKG activated by the NO-cGMP axis phosphorylates numerous ion carriers, thereby reducing the cytosolic Ca 2+ level as well as causing a membrane hyperpolarization, hence a relaxation of arterial smooth myocytes.

  66. 66.

    The hydrostatic pressure decreases with height at a rate of ∼ 100 Pa/cm for an arterial (p a) and venous (p v) pressure and ∼ 0.1 Pa/cm for an alveolar pressure (p A).

  67. 67.

    Four MLCK types exist: skeletal (skMLCK), cardiac (cMLCK), and smooth muscle (smMLCK) isoforms encoded by the MYLK2, MYLK3, and MYLK1 genes, respectively, as well as nonmuscle MLCK (nmMLCK) with 4 high-molecular-weight isoforms (MLCK1–MLCK4) that are splice variants translated from the MYLK1 gene. Isoforms MLCK1 and MLCK2 are the most highly expressed subtypes in the vascular endothelium.

  68. 68.

    Glycosaminoglycans are linear heteropolysaccharides, combination of which create different GAG types, such as heparan (50% of the total GAG pool at the endothelial surface), chondroitin, and dermatan sulfate, and hyaluronic acid or hyaluronan. Membrane-bound glypicans with their heparan sulfate chains localize to caveolae. Transmembrane syndecans cluster in the outer edge of caveolae. They connect to the cytoskeleton. Hyaluronan is a very long glycosaminoglycans that is not sulfated. It is not attached to a core protein. Transmembrane epican, or heparan sulfate proteoglycan, can contain chondroitin and heparan sulfate as well as oligosaccharides. It localizes to caveolae.

  69. 69.

    A glycoprotein has short oligosaccharide branched chains. Glycoproteins encompass many receptors on the cell surface, such as integrins, selectins, and members of the immunoglobulin superfamily.

  70. 70.

    After removal of the glycocalyx by heparinase, cultured endotheliocytes do not align in the streamwise direction and can proliferate after 1 d of experiencing flow.

  71. 71.

    The skin and skeletal muscles jointly contain around two-thirds of the extracellular fluid.

  72. 72.

    Chaperone HSP90 binds to both NOS3 and sGC and facilitates their interaction, stabilizing sGC and enhancing cGMP production.

  73. 73.

    Isoform VEGFa, or VEGF, is synthesized in almost all cells subjected to hypoxia or other stress types. These proteins signals upon binding to their cognate receptors, in particular VEGFR1 to VEGFR3, once they homo- and heterodimerize. They operate as a potent (but not very powerful) endothelial growth factor, a powerful vascular permeabilizing agent, and a potent vasodilator.

  74. 74.

    In cultured endothelial monolayers most often stimulated by thrombin as an acute inflammatory stimulus, paracellular gap formation is blocked upon inhibition of RoCK or MLCK, but not in situ. Thrombin launches an active cell RhoA-dependent contraction that creates large gap formation and, hence, an acute increase in endothelial barrier permeability. Some of the effects of thrombin on vascular permeability result from the release of other inflammatory mediators from mastocytes or neurons. Thrombin primes a contraction-dependent increase in permeability [150]. On the other hand, platelet-activating factor rises endothelial permeability in a cell contraction-independent manner in inflamed rat mesentery venules. In addition, thrombin activates platelets that contribute to elevated endothelial permeability.

  75. 75.

    A.k.a. synectin-binding RhoA exchange factor (Syx).

  76. 76.

    In Drosophila melanogaster, the Crumbs polarity complex includes: (1) type-1 transmembrane Crumbs (Crb) and (2) Stardust (Sdt), a scaffold protein of the MAGUK (membrane-associated guanylate kinase) family. In humans, it comprises: (1) Crumbs homologs (Crb1–Crb3) encoded by 3 genes and (2) members of the P55-like (P55 Stardust) MAGUK subfamily, or membrane protein, palmitoylated (MMP1–MMP7), among which MPP5, or protein associated with Lin7 PALS1, is most similar to Stardust; (3) protein (PALS1) associated with tight junctions (PATJ) and its related molecule multiPDZ domain-containing protein MuPP1; and (4) Lin7 homolog-C (Lin7a–Lin7c; Abnormal cell lineage Lin7 in Caenorhabditis elegans) encoded by 3 genes.

  77. 77.

    Macromolecular transport is not always coupled with water flows. Furthermore, capillaries without large pores exist.

  78. 78.

    The CSNK1D and CSNK1E genes encode casein kinases CK1δ and CK1ε, respectively.

  79. 79.

    The circadian clock in the suprachiasmatic nucleus (Bmal1-based oscillator) is entrained by light. Another circadian clock in the dorsomedial nucleus of the hypothalamus (also Bmal1-based oscillator) is primed by food [173].

  80. 80.

    Fibrinolytic activity falls during early morning hours.

  81. 81.

    Several proteins encoded by these genes tune lipogenesis and lipolysis, as well as lipid droplet stability (e.g., adiponutrin, 1-acylglycerol-3-phosphate O-acyltransferase, and diacylglycerol O-acyltransferase-2 that are involved in lipogenesis) on the one hand, and glycogenolysis and glycolysis (e.g., protein kinase-A, protein phosphatase-1, and phosphofructokinase) [179]. Moreover, the transcriptional activity of peroxisome proliferator-activated receptors PPARα (NR1c1) that activates genes for fatty acid oxidation is controlled by the circadian clock of the cardiomyocyte.

  82. 82.

    Metabolomics technology relies on method coupling (mass spectrometry, gas and liquid chromatography, and capillary electrophoresis. Hepatic lipase mRNA in the mouse liver has a peak expression slightly before that of lysophosphatidylcoline [171].

  83. 83.

    Image-guided radiofrequency ablation treats cancers particularly localized to the liver, kidney, and adrenal glands by heating. One or more radiofrequency needles are inserted into the tumor. Cryotherapy uses gas-refrigerated cryoprobes, which are inserted inside the tumor, initiating the formation of ice balls to destroy cancerous cells by freezing and thawing processes. One of the main difficulties is the determination of the optimal position of the probes and treatment duration for complete destruction of cancerous cells without damaging too many surrounding normal cells. Another kind of tumor therapy consists of thermal and mechanical exposure to high-frequency focused ultrasound (HIFU). Tumor antigens and other compounds released from destroyed cells can stimulate antitumoral immunity. The optimal exposure time is an important parameter to avoid damage of normal cells, especially walls of neighboring blood vessels.

  84. 84.

    Pennes underestimated the magnitudes of the conduction and convection terms in the energy balance, using inappropriate values of tissue thermal conductivity and tissue perfusion rate.

  85. 85.

    Receptor OR51e2 may be activated by several androgens.

  86. 86.

    Short-chain fatty acids are terminal products of fermentation by the gut microbiota that enter the blood circulation.

  87. 87.

    Receptor OR51e2 is unresponsive to other SCFAs. Renin release by juxtaglomerular apparatus cells depends on calcium-inhibitable adenylate cyclase AC5 and/or AC6 isoforms. On the other hand, AC3 produced in macula densa cells participates in renin secretion by juxtaglomerular apparatus cells as a paracrine factor.

  88. 88.

    Stretch-activated currents have been described in various mammalian cell types, such as vascular smooth myocytes, renal epithelicytes, somatosensory dorsal root ganglion neurons, and inner ear hair cells.

  89. 89.

    Polycystic kidney disease-2.

  90. 90.

    Previously called polycystin-1.

  91. 91.

    Carbon monoxide is a messenger and regulator of TREK1 as well as epithelial Na + (ENaC) channels, in addition to calcium-activated K + (BK), KV2.1, CaV1, and ligand-gated ionotropic P2X (e.g., P2X2 and P2X4).

  92. 92.

    Matricryptic sites are active sites, such as Arg–Gly–Asp (RGD) and Leu–Asp–Val (LDV), are hidden in the mature secreted form of matrix molecules. They become exposed upon conformational changes caused by oligomerization, adsorption, and mechanical stress. Matricryptic sites contribute in particular to acute changes in vascular permeability and fibrin–fibronectin polymerization in wound repair. Matricryptins are active fragments of matrix molecules with exposed active matricryptic sites. They can bind to specific integrins and regulate arteriolar tone using calcium and potassium channels.

  93. 93.

    Hormone-like substances that act locally and briefly.

  94. 94.

    The membrane is maintained in a relatively depolarized state, partially because of inhibition of K + channels.

  95. 95.

    Skin circulation is mostly regulated via the rostral ventromedial medulla and medullary raphe [221].

  96. 96.

    When it is not caused by vascular or renal disorders, hypertension can be due to a strong sympathetic tone.

  97. 97.

    The parabrachial nucleus is separated by the brachium conjunctivum into 2 main regions: the lateral and medial parabrachial nuclei. The lateral parabrachial nucleus is connected to the rostral ventral lateral medulla and nucleus of the solitary tract. The lateral parabrachial nucleus can be further subdivided to the dorsal (dPBN), ventral (vPBN), central (cPBN), and external lateral (elPBN) parabrachial nuclei.

  98. 98.

    In anesthetized cats, mean arterial pressure and renal sympathetic nerve activity rely on NO, especially that synthesized by NOS2 in the rostral ventrolateral medulla [224].

  99. 99.

    Two groups of parasympathetic vasodilatory fibers originate from the chorda tympani nerve, a branch of the facial nerve, and from the trigeminal portion of the distal lingual nerve (probably via the glossopharyngeal nerve) [225].

  100. 100.

    Formerly known as metastin, as it was originally identified as a human metastasis suppressor. Its alias is formed by 2 groups of letters “Ki” refering to the location of its discovery, Hershey, Pennsylvania, home of Hershey Chocolate Kiss and “SS” for suppressor sequence. Kisspeptin is encoded by the KISS1 gene. The gene product is a 145-amino acid precursor that is cleaved to 54-amino acid peptide, which can be further truncated to 14-, 13-, or 10-amino acid C-terminal fragments, the kisspeptins. Kisspeptin145 represents the precursor, kisspeptin54 (or kisspeptin \(_{(68--121)}\)) the peptide, and kisspeptin14 (or kisspeptin \(_{(108--121)}\)), kisspeptin13 (or kisspeptin \(_{(109--121)}\)), and kisspeptin10 (or kisspeptin \(_{(112--121)}\)) the C-terminal fragments. Kisspeptin signaling in the brain mediates the negative feedback action of sex steroids on gonadotropin secretion, generating the preovulatory GnRH–LH surge, triggering and guiding the tempo of sexual maturation at puberty, controlling seasonal reproduction, and restraining reproductive activity during lactation [226]. The KISS1 gene expression is regulated by estradiol (E2) in the hypothalamus. Kisspeptin-1 is also synthesized in the neocortex of fetal adrenal glands. It stimulates secretion of aldosterone [226]. It is also produced in pancreatic β cells, where it can stimulate insulin release (auto- and paracrine action). Kisspeptin54, -13, and -10 are potent vasoconstrictors. Kisspeptin-1 is a G-protein-coupled receptor ligand for GPR54 (or Kiss1R). The kisspeptin-Kiss1R complex initiates secretion of gonadotropin-releasing hormone (GnRH) at puberty. Synthesized in the brain, kisspeptin unleashes hormones that stimulate the production of estrogen or testosterone in ovaries and testes, starting the physical transformations of puberty. Menopause is characterized by ovarian follicle depletion, reduction of ovarian steroids, compensatory gonadotrophin hypersecretion, and hypertrophy of neurons expressing neurokinin-B (NKB), kisspeptin-1, and estrogen receptor-α within the hypothalamic infundibular (arcuate) nucleus.

  101. 101.

    Neurokinin-B is encoded by the TAC3 (tachykinin-3) gene. On the other hand, the other human tachykinin gene, the TAC1 gene, encodes neurokinin-A (or substance-K), neuropeptide-K (or neurokinin-K), neuropeptide-γ, and substance-P.

  102. 102.

    Dynorphin, an opioid peptide derived from the prodynorphin gene product, inhibits the reproductive axis. The dynorphin gene expression decreases in postmenopausal women. The secretion of luteinizing hormone can then rise [227].

  103. 103.

    Secretion of GnRH into portal capillaries stimulates luteinizing hormone (LH) secretion from the anterior hypophysis, which stimulates the secretion of 17β-estradiol from the ovary. The negative feedback primed by 17β-estradiol via NR3a1 reduces the plasma LH level and decreases neurokinin-B and kisspeptin synthesis in KND+ neurons.

  104. 104.

    Renal vasoconstriction reduces the blood supply, causing excessive renin secretion and inappropriate salt and water retention.

  105. 105.

    In 1898, R. Tigerstedt and P. Bergman discovered that a cortical extract of rabbit kidney causes vasoconstriction when injected intravenously [236]. They isolated the substance that was named renin.

  106. 106.

    The Na +–K + ATPase is a heteromeric enzyme that comprises a catalytic α and a glycosylated β subunit. The central isoform-specific region is targeted for protein kinase-C activation. This pump catalyzes the export of 3 Na + ions and import of 2 K + ions at the expense of 1 ATP molecule. α4-Isoform lodges exclusively in the sperm tail. In the heart, the cytosolic Ca 2+ concentration increases during contraction and decreases during relaxation via sarco(endo)plasmic reticulum Ca 2+ ATPase and plasmalemmal Ca 2+ ATPase and Na +–Ca 2+ exchanger. Tha latter uses the Na + gradient established by Na +–K + ATPase. Inhibition of Na +–K + ATPase raises cytosolic Na + concentration. Therefore, Na +–Ca 2+ exchanger augments cytosolic Ca 2+ concentration, thereby causing a positive inotropic effect. α2-Isozyme is a main regulator of calcium in the myocardium, its inhibition increasing calcium influx and contractibility [237]. α1-Isoform depresses cardiac contractility via excess extracellular K + level without apparent changes in intracellular calcium handling.

  107. 107.

    Somali waabaayo: arrow poison. Ouabain is also called G-strophanthin. It is found in ripe seeds of African plants Strophanthus gratus and the bark of Acokanthera ouabaio. It is a poisonous cardiac glycoside at high (micromolar to millimolar) concentrations. It is structurally related to digoxin, another lipophilic cardiac glycoside. It binds to and inhibits plasmalemmal Na +–K + ATPase (sodium pump). At low (nanomolar and subnanomolar) concentrations, at least in guinea pig ventriculomyocytes, this endogenous substance stimulates the Na +–K + ATPase (α1–α3-isoforms) [239].

  108. 108.

    Receptor AT1 is expressed by epithelialocytes throughout the nephron, in the glomerulus, and renal blood vessels. Once it is activated, it promotes sodium reabsorption by stimulating both sodium–proton antiporter and sodium–potassium ATPase on the apical (luminal) and basolateral plasma membrane, respectively, in the proximal tubule of the nephron. It stimulates epithelial sodium channels in the collecting ducts. Furthermore, activated vascular AT1 induces vasoconstriction, which subsequently reduces renal blood flow and sodium excretory capacity.

  109. 109.

    Respiratory sinus arrhythmia is the variation in heart rate occurring simultaneously with respiration. On ECG traces, it induces fluctuations of the R–R interval series.

  110. 110.

    Nerve fibers in adventitia act by electrochemical stimulation at neuromuscular junctions and biochemical processes (release of neurotransmitters) preferentially at external layers of the media.

  111. 111.

    Flowing vasoactive hormones act after transmural migration up to internal layers of the media.

  112. 112.

    Latin limbus: border, edge, fringe, hem, selvage.

  113. 113.

    The hypothalamic paraventricular nucleus receives direct noradrenergic, adrenergic, and peptidergic innervation from the nucleus of the solitary tract [250].

  114. 114.

    Postural hypotension is defined as at least a 2.66-kPa decrease in systolic blood pressure or 1.33-kPa decrease in diastolic blood pressure upon standing.

  115. 115.

    Nitrogenous wastes are excreted as ammonia, urea, or uric acid.

  116. 116.

    Protein Ser/Thr kinases of the WNK (with no lysine [Lys or K]) set are characterized by the absence of lysine usually found in the catalytic domain of all other protein serine/threonine kinases. Kinases WNK1 and WNK4 are expressed in the distal convoluted tubule, connecting tubule, and collecting duct of the nephron (Vol. 4 – Chap. 5. Cytoplasmic Protein Ser/Thr Kinases).

  117. 117.

    Angiotensin-2 also directly stimulates renal sodium reabsorption, independently of aldosterone.

  118. 118.

    Uncoupling protein-1 in mitochondria of brown adipose tissue produces heat by nonshivering thermogenesis, a primary process of heat generation in human infants.

  119. 119.

    Receptors V1 and V3 are also called V1Ra and V1Rb receptors, respectively.

  120. 120.

    Reflex control of the cardiovascular system mainly involves baroreceptors, afferents to the central nervous system, cardiovascular centers, and sympathetic and parasympathetic efferents to the heart and vasculature. The potentialization of baroreflexes is done via central action, activating V1-receptors in the area postrema, and sensitization of the arterial baroreceptors, as well as cardiac afferents.

  121. 121.

    Lack in vasopressin or in V2 receptor in the collecting ducts is responsible for central and nephrogenic diabetes insipidus, respectively.

  122. 122.

    A.k.a. NPRa and GCa.

  123. 123.

    A.k.a. NPRb and GCb.

References

Introduction

  1. Bachelard G (1938 [1969]) La psychanalyse du feu [The Psychoanalysis of Fire]. Gallimard, Paris

    Google Scholar 

Chap. 1. Anatomy of the Cardiovascular System

  1. Echtler K, Stark K, Lorenz M, Kerstan S, Walch A, Jennen L, Rudelius M, Seidl S, Kremmer E, Emambokus NR, von Bruehl ML, Frampton J, Isermann B, Genzel-Boroviczny O, Schreiber C, Mehilli J, Kastrati A, Schwaiger M, Shivdasani RA, Massberg S (2010) Platelets contribute to postnatal occlusion of the ductus arteriosus. Nature – Medicine 16:75–82

    Google Scholar 

  2. Hong Z, Kutty S, Toth PT, Marsboom G, Hammel JM, Chamberlain C, Ryan JJ, Zhang HJ, Sharp WW, Morrow E, Trivedi K, Weir EK, Archer SL (2013) Role of dynamin-related protein 1 (drp1)-mediated mitochondrial fission in oxygen sensing and constriction of the ductus arteriosus. Circulation Research 112:802–815

    Google Scholar 

  3. Gray H (1995) Gray’s anatomy: anatomy descriptive and surgical. Barnes and Noble, New York

    Google Scholar 

  4. Rouvire H, Delmas A (2002) Anatomie humaine descriptive, topographique et fonctionnelle [Descriptive, Topographical, and Functional Human Anatomy], Vols. I–IV. Masson, Paris

    Google Scholar 

  5. Iacobellis G, Corradi D, Sharma AM (2005) Epicardial adipose tissue: anatomic, biomolecular and clinical relationships with the heart. Nature – Clinical Practice Cardiovascular Medicine 2:536–543.

    Google Scholar 

  6. Badano LP, Agricola E, Perez de Isla L, Gianfagna P, Zamorano JL (2009) Evaluation of the tricuspid valve morphology and function by transthoracic real-time three-dimensional echocardiography. European Journal of Echocardiography 10:477–484

    Google Scholar 

  7. Kozlowski D, Owerczuk A, Piwko G, Kozlowska M, Bigus K, Grzybiak M (2002) The topography of the subthebesian fossa in relation to neighbouring structures within the right atrium. Folia Morphologica 62:65–70

    Google Scholar 

  8. Stradins P, Lacis R, Ozolanta I, Purina B, Ose V, Feldmane L, Kasyanov V (2004) Comparison of biomechanical and structural properties between human aortic and pulmonary valve. European Journal of Cardio-thoracic Surgery 26:634–639

    Google Scholar 

  9. Keith A, Flack M (1907) The form and nature of the muscular connections between the primary divisions of the vertebrate heart. Journal of Anatomy and Physiology 41:172–189

    Google Scholar 

  10. Anderson RH, Razavi R, Taylor AM (2004) Cardiac anatomy revisited. Journal of Anatomy 205:159–177

    Google Scholar 

  11. Anderson RH, Webb S, Brown NA (1999) Clinical anatomy of the atrial septum with reference to its developmental components. Clinical Anatomy 12:362–374

    Google Scholar 

  12. Staszewsky L, Latini R (2013) What is the atrium trying to tell us? European Heart Journal 34:255-257

    Google Scholar 

  13. Gupta S, Matulevicius SA, Ayers CR, Berry JD, Patel PC, Markham DW, Levine BD, Chin KM, de Lemos JA, Peshock RM, Drazner MH (2013) Left atrial maximal volume and left atrial emptying fraction as predictors of cardiovascular events in community-based or population studies. European Heart Journal 34:278–285

    Google Scholar 

  14. Swanson WM, Clark RE (1974) Dimensions and geometric relationships of the human aortic valve as a function of pressure. Circulation Research 35:871–882

    Google Scholar 

  15. Grande KJ, Kunzelman KS, Cochran RP, David TE, Verrier ED (1993) Porcine aortic leaflet arrangement may contribute to clinical xenograft failure. ASAIO Journal 39:918–922

    Google Scholar 

  16. Bäck M, Gasser TC, Michel JB, Caligiuri G (2013) Biomechanical factors in the biology of aortic wall and aortic valve diseases. Cardiovascular Research 99:232–241

    Google Scholar 

  17. Valsalva AM (1740) Opera. Venice

    Google Scholar 

  18. Bellhouse BJ (1969) Velocity and pressure distributions in the aortic valve. Journal of Fluid Mechanics 37:587–600

    ADS  Google Scholar 

  19. Jatene MB, Monteiro R, Guimaraes MH, Veronezi SC, Koike MK, Jatene FB, Jatene AD (1999) Aortic valve assessment. Anatomical study of 100 healthy human hearts. Arquivos Brasileiros de Cardiologia 73:81-86

    Google Scholar 

  20. Tank PW, Gross Anatomy, Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Sciences, http://anatomy.uams.edu/anatomyhtml/heart2.html

  21. Jiamsripong P, Honda T, Reuss CS, Hurst RT, Chaliki HP, Grill DE, Schneck SL, Tyler R, Khandheria BK, Lester SJ (2007) Three methods for evaluation of left atrial volume. European Journal of Echocardiography 9:351–355

    Google Scholar 

  22. Herregods MC, De Paep G, Bijnens B, Bogaert JG, Rademakers FE, Bosmans HT, Bellon EP, Marchal GJ, Baert AL, Van de Werf F, De Geest H (1994) Determination of left ventricular volume by two-dimensional echocardiography: comparison with magnetic resonance imaging. European Heart Journal 15:1070–1073

    Google Scholar 

  23. Armour JA (2008) Potential clinical relevance of the ’little brain’ on the mammalian heart. Experimental Physiology 93:165–176

    Google Scholar 

  24. Gray AL, Johnson TA, Ardell JL, Massari VJ (2004) Parasympathetic control of the heart. II. A novel interganglionic intrinsic cardiac circuit mediates neural control of heart rate. Journal of Applied Physiology 96:2273–2278

    Google Scholar 

  25. Waldmann M, Thompson GW, Kember GC, Ardell JL, Armour JA (2006) Stochastic behavior of atrial and ventricular intrinsic cardiac neurons. Journal of Applied Physiology 101:413–419

    Google Scholar 

  26. Sharma V (2009) Deterministic chaos and fractal complexity in the dynamics of cardiovascular behavior: perspectives on a new frontier. Open Cardiovascular Medicine Journal 3:110–123

    Google Scholar 

  27. Avnir D, Biham O, Lidnar D, Malcai O (1998) Is the geometry of nature fractal? Science 279:39–40

    ADS  MATH  Google Scholar 

  28. Kleiber M (1947) Body size and metabolic rate. Physiological Reviews 27:511–541

    Google Scholar 

  29. West GB, Brown JH, Enquist BJ (1997) A general model for the origin of allometric scaling laws in biology. Science 276:122–126

    Google Scholar 

  30. Sapoval B, Gobron T, Margolina A (1991) Vibrations of fractal drums. Physical Review Letters 67:2974–2977

    ADS  Google Scholar 

  31. D’Arcy Thompson W (1917) On Growth and Form. Cambridge University Press, Cambridge, UK

    Google Scholar 

  32. Van Vliet P, Wu SM, Zaffran S, Pucéat M (2012) Early cardiac development: a view from stem cells to embryos. Cardiovascular Research 96:352–362

    Google Scholar 

  33. Senyo SE, Steinhauser ML, Pizzimenti CL, Yang VK, Cai L, Wang M, Wu TD, Guerquin-Kern JL, Lechene CP, Lee RT (2013) Mammalian heart renewal by pre-existing cardiomyocytes. Nature 493:433–436

    ADS  Google Scholar 

  34. Mercola M (2012) Cardiovascular biology: A boost for heart regeneration. Nature 492: 360–362

    ADS  Google Scholar 

  35. Eulalio A, Mano M, Dal Ferro M, Zentilin L, Sinagra G, Zacchigna S, Giacca M (2012) Functional screening identifies miRNAs inducing cardiac regeneration. Nature 492:376–381

    ADS  Google Scholar 

  36. Chien KR, Domian IJ, Parker KK (2008) Cardiogenesis and the complex biology of regenerative cardiovascular medicine. Science 322:1494–1497

    ADS  Google Scholar 

  37. Smart N, Riley PR (2009) Derivation of epicardium-derived progenitor cells (EPDCs) from adult epicardium. Current Protocols in Stem Cell Biology 2:unit2c.2

    Google Scholar 

  38. Zhou B, Ma Q, Rajagopal S, Wu SM, Domian I, Rivera-Feliciano J, Jiang D, von Gise A, Ikeda S, Chien KR, Pu WT (2008) Epicardial progenitors contribute to the cardiomyocyte lineage in the developing heart. Nature 454:109–113

    ADS  Google Scholar 

  39. Wagner KD, Wagner N, Schedl A (2003) The complex life of WT1. Journal of Cell Science 116:1653–1658

    Google Scholar 

  40. Wagner KD, Wagner N, Bondke A, Nafz B, Flemming B, Theres H, Scholz H (2002) The Wilms’ tumor suppressor Wt1 is expressed in the coronary vasculature after myocardial infarction. FASEB Journal 16:1117–1119

    Google Scholar 

  41. Koninckx R, Daniëls A, Windmolders S, Mees U, Macianskiene R, Mubagwa K, Steels P, Jamaer L, Dubois J, Robic B, Hendrikx M, Rummens JL, Hensen K (2013) The cardiac atrial appendage stem cell: a new and promising candidate for myocardial repair. Cardiovascular Research 97:413–423

    Google Scholar 

  42. Nam YJ, Song K, Luo X, Daniel E, Lambeth K, West K, Hill JA, DiMaio JM, Baker LA, Bassel-Duby R, Olson EN (2013) Reprogramming of human fibroblasts toward a cardiac fate. Proceedings of the National Academy of Sciences of the United States of America 110:5588–5593

    ADS  Google Scholar 

  43. Mulligan-Kehoe MJ (2010) The vasa vasorum in diseased and nondiseased arteries. American Journal of Physiology – Heart and Circulatory Physiology 298:H295–H305

    Google Scholar 

  44. Chambers R, Zweifach BW (1994) Topography and function of the mesenteric capillary circulation. American Journal of Anatomy 75:175–205

    Google Scholar 

  45. Lee JS (2000) Biomechanics of the microcirculation, an integrative and therapeutic perspective. Annals of Biomedical Engineering 28:1–13

    ADS  Google Scholar 

  46. Hilgers RHP, Schiffers PMH, Aartsen WM, Fazzi GE, Smits JFM, De Mey JGR (2004) Tissue angiotensin-converting enzyme in imposed and physiological flow-related arterial remodeling in mice. Arteriosclerosis, Thrombosis, and Vascular Biology 24:892–897

    Google Scholar 

  47. Batra S, Rakusan K (1992) Capillary length, tortuosity, and spacing in rat myocardium during cardiac cycle. American Journal of Physiology – Heart and Circulatory Physiology 263:H1369–H1376

    Google Scholar 

  48. Hudlicka O, Tyler KR (1984) The effect of long-term high-frequency stimulation on capillary density and fibre types in rabbit fast muscles. Journal of Physiology 353:435–445

    Google Scholar 

  49. Krenz GS, Lin J, Dawson CA, Linehan JH (1994) Impact of parallel heterogeneity on a continuum model of the pulmonary arterial tree. Journal of Applied Physiology 77:660–670

    Google Scholar 

  50. Marxen M, Henkelman RM (2003) Branching tree model with fractal vascular resistance explains fractal perfusion heterogeneity. American Journal of Physiology – Heart and Circulatory Physiology 284:H1848–H1857

    Google Scholar 

  51. Liew G, Mitchell P, Rochtchina E, Wong TY, Hsu W, Lee ML, Wainwright A, Wang JJ (2003) Fractal analysis of retinal microvasculature and coronary heart disease mortality. European Heart Journal 32:422–429

    Google Scholar 

  52. Schelin AB, Károlyi G, de Moura AP, Booth NA, Grebogi C (2010) Fractal structures in stenoses and aneurysms in blood vessels. Philosophical Transactions of the Royal Society – London – A Mathematical, Physical, and Engineering sciences 368:5605–5617

    Google Scholar 

  53. Bassingthwaighte JB, King RB, Roger SA (1989) Fractal nature of regional myocardial blood flow heterogeneity. Circulation Research 65:578–590

    Google Scholar 

  54. Karch R, Neumann F, Podesser BK, Neumann M, Szawlowski P, Schreiner W (2003) Fractal properties of perfusion heterogeneity in optimized arterial trees: a model study. Journal of General Physiology 122:307–321

    Google Scholar 

  55. Kurz H, Sandau K (1998) Allometric scaling in biology. Science 281:751

    ADS  Google Scholar 

  56. Kurz H, Wilting J, Sandau K, Christ B (1998) Automated evaluation of angiogenic effects mediated by VEGF and PlGF homo- and heterodimers. Microvascular Research 55:92–102

    Google Scholar 

  57. Mori D, Yamaguchi T (2002) Computational fluid dynamics modeling and analysis of the effect of 3-D distortion of the human aortic arch. Computer Methods in Biomechanics and Biomedical Engineering 5:249–260

    Google Scholar 

  58. Ruddy JM, Jones JA, Spinale FG, Ikonomidis JS (2008) Regional heterogeneity within the aorta: relevance to aneurysm disease. Journal of Thoracic and Cardiovascular Surgery 136:1123–1130

    Google Scholar 

  59. Cebral JR (2005) www.scs.gmu.edu/∼jcebral/

  60. Bouthillier A, van Loveren HR, Keller JT (1996) Segments of the internal carotid artery: a new classification. Neurosurgery 38:425–432

    Google Scholar 

  61. Schaller B (2004) Physiology of cerebral venous blood flow: from experimental data in animals to normal function in humans. Brain Research Reviews 46:243–260

    Google Scholar 

  62. Harmon JV, Edwards WD (1987) Venous valves in subclavian and internal jugular veins. Frequency, position, and structure in 100 autopsy cases. American Journal of Cardiovascular Pathology 1:51–54

    Google Scholar 

  63. Henry JL, Calaresu FR (1974) Excitatory and inhibitory inputs from medullary nuclei projecting to spinal cardioacceleratory neurons in the cat. Experimental Brain Research 20:485–504

    Google Scholar 

  64. Hildebrandt JR (1974) Central connections of aortic depressor and carotid sinus nerves. Experimental Neurology 45:590–605

    Google Scholar 

  65. Gebber GL, Taylor DG, Weaver LC (1973) Electrophysiological studies on organization of central vasopressor pathways. American Journal of Physiology 224:470–481

    Google Scholar 

  66. Snyder DW, Gebber GL (1973) Relationships between medullary depressor region and central vasopressor pathways. American Journal of Physiology 225:1129–1137

    Google Scholar 

  67. Weaver LC, Gebber GL (1974) Electrophysiological analysis of neural events accompanying active dilatation. American Journal of Physiology 226:84–89

    Google Scholar 

  68. Abboud FM (2010) In search of autonomic balance: the good, the bad, and the ugly. American Journal of Physiology — Regulatory, Integrative and Comparative Physiology 298:R1449–R1467

    Google Scholar 

  69. Klabunde RE (2011) Cardiovascular Physiology Concepts, 2nd edition, Wolters Kluwer – Lippincott Williams and Wilkins, Philadelphia, Pennsylvania

    Google Scholar 

  70. Prabhakar NR, Peng YJ (2004) Peripheral chemoreceptors in health and disease. Journal of Applied Physiology 96:359–366

    Google Scholar 

  71. Schultz HD, Li YL (2007) Carotid body function in heart failure. Respiratory Physiology and Neurobiology 157:171–185

    Google Scholar 

  72. Eyzaguirre C (2007) Electric synapses in the carotid body–nerve complex. Respiratory Physiology and Neurobiology 157:116–122

    Google Scholar 

  73. De Castro F (1928) Sur la structure et l’innervation du sinus carotidien de l’homme et des mammifères. Nouveaux faits sur l’innervation et la fonction du glomus caroticum. [On the structure and innervation of carotid sinus in humans and mammals. New facts on innervation and function of the glomus caroticum.] Travaux du Laboratoire de Recherches en Biologie 25:331–380

    Google Scholar 

  74. Kummer W, Gibbins IL, Heym C (1989) Peptidergic innervation of arterial chemoreceptors. Archives of Histology and Cytology 52:361–364

    Google Scholar 

  75. Rey S, Del Rio R, Alcayaga J, Iturriaga R (2006) Endothelins in the cat petrosal ganglion and carotid body: effects and immunolocalization. Brain Research 1069:154–158

    Google Scholar 

  76. Prabhakar NR (2000) Oxygen sensing by the carotid body chemoreceptors. Journal of Applied Physiology 88:2287–2295

    Google Scholar 

  77. Schultz HD, Li YL, Ding Y (2007) Arterial chemoreceptors and sympathetic nerve activity: implications for hypertension and heart failure. Hypertension 50:6–13

    Google Scholar 

  78. Molenda O (1975) Morphology and topography of the carotid body and carotid sinus in sheep. Polskie Archiwum Weterynaryjne 18:343–364

    Google Scholar 

  79. Sadik AH, Al-Shaikhly AK, Khamas WA (1993) Anatomic location of the carotid body and carotid sinus in sheep and goats. Small Ruminant Research 12:371–377

    Google Scholar 

  80. Peng YJ, Nanduri J, Raghuraman G, Souvannakitti D, Gadalla MM, Kumar GK, Snyder SH, Prabhakar NR (2010) H2S mediates O2 sensing in the carotid body. Proceedings of the National Academy of Sciences of the United States of America 107:10719–10724

    ADS  Google Scholar 

  81. Doan TN, Stephans K, Ramirez AN, Glazebrook PA, Andresen MC, Kunze DL (2004) Differential distribution and function of hyperpolarization-activated channels in sensory neurons and mechanosensitive fibers. Journal of Neuroscience 24:3335–3343

    Google Scholar 

Chap.2. Anatomy of the Ventilatory Apparatus

  1. Ochs M, Nyengaard JR, Jung A, Knudsen L, Voigt M, Wahlers T, Richter J, Gundersen HJ (2004) The number of alveoli in the human lung. American Journal of Respiratory and Critical Care Medicine 169:120–124

    Google Scholar 

  2. Horsfield K (1978) Morphometry of the small pulmonary arteries in man. Circulation Research 42:593–597

    Google Scholar 

  3. Glenny RW (2011) Emergence of matched airway and vascular trees from fractal rules. Journal of Applied Physiology 110:1119–1129

    Google Scholar 

  4. Fetita C, Mancini S, Perchet D, Prêteux F, Thiriet M, Vial L (2005) An image-based computational model of oscillatory flow in the proximal part of tracheobronchial trees. Computer Methods in Biomechanics and Biomedical Engineering 8:279–293

    Google Scholar 

  5. Christophe JJ, Ishikawa T, Matsuki N, Imai Y, Takase K, Thiriet M, Yamaguchi T (2010) Patient-specific morphological and blood flow analysis of pulmonary artery in the case of severe deformations of the lung due to pneumothorax. Journal of Biomechanical Science and Engineering 5:485–498

    Google Scholar 

  6. Robinson RJ, Russo J, Doolittle RL (2009) 3D airway reconstruction using visible human data set and human casts with comparison to morphometric data. Anatomical Record – Advances in Integrative Anatomy and Evolutionary Biology 292:1028–1044

    Google Scholar 

  7. Guyton AC (1985) Anatomy and Physiology, Saunders College Publishing, New York

    Google Scholar 

  8. Golde AR (2006) Rhinoplastic techniques for the nasal valve for the patient with sleep apnea. Operative Techniques in Otolaryngology-Head and Neck Surgery 17:242–251

    Google Scholar 

  9. Haight JS, Cole P (1983) The site and function of the nasal valve. Laryngoscope 93:49–55

    Google Scholar 

  10. Martínez MM, Román LJ, C Villalobos (2004) Biofluid dynamics of the ear–nose–throat system. Congress on Biofluid Dynamics of Human Body Systems at University of Puerto Rico, Mayagëz

    Google Scholar 

  11. Bachmann W, Legler U (1972) Studies on the structure and function of the anterior section of the nose by means of luminal impressions. Acta Oto-Laryngologica 73:433–442

    Google Scholar 

  12. Ingels KJ, Meeuwsen F, van Strien HL, Graamans K, Huizing EH (1990) Ciliary beat frequency and the nasal cycle, European Archives of Otorhinolaryngology 248:123–126

    Google Scholar 

  13. Sappey MPC (1867–1874) Traité d’anatomie descriptive (Treatise of Descriptive Anatomy), Paris; and Sappey MPC (1879) Atlas d’Anatomie Descriptive (Atlas of Descriptive Anatomy), Paris (see also “The Larynx – Gray’s Anatomy of the Human Body” Yahoo – Education. education.yahoo.com/reference/gray/subjects/subject/236)

    Google Scholar 

  14. Begis D, Delpuech C, Le Tallec P, Loth L, Thiriet M, Vidrascu M (1988) A finite-element model of tracheal collapse. Journal of Applied Physiology 64:1359–1368

    Google Scholar 

  15. Thiriet M (1994) Etude des écoulements dans les voies aériennes proximales et les artères de gros calibre. Mémoire pour l’habilitation à diriger des recherches, UFR de physique, Université Paris VII. (Study of flows in proximal airways and large arteries. Thesis for Accreditation to Supervise Research, Paris Diderot University)

    Google Scholar 

  16. Thiriet M, Maarek JM, Chartrand DA, Delpuech C, Davis L, Hatzfeld C, Chang HK (1989) Transverse images of the human thoracic trachea during forced expiration. Journal of Applied Physiology 67:1032–1040

    Google Scholar 

  17. Rhodin J, Dalhamn T (1956) Electron microscopy of the tracheal ciliated mucosa in rat. Zeitschrift für Zellforschung und mikroskopische Anatomie 44:345–412

    Google Scholar 

  18. Reinhardt JM, Ding K, Cao K, Christensen GE, Hoffman EA, Bodas SV (2008) Registration-based estimates of local lung tissue expansion compared to xenon CT measures of specific ventilation. Medical Image Analysis 12:752–763

    Google Scholar 

  19. Ukil S, Reinhardt JM (2009) Anatomy-guided lung lobe segmentation in X-ray CT images. IEEE Transactions on Medical Imaging 28:202–214

    Google Scholar 

  20. Miserocchi G (1997) Physiology and pathophysiology of pleural fluid turnover. European Respiratory Journal 10:219–225

    Google Scholar 

  21. Vasilescu DM, Gao Z, Saha PK, Yin L, Wang G, Haefeli-Bleuer B, Ochs M, Weibel ER, Hoffman EA (2012) Assessment of morphometry of pulmonary acini in mouse lungs by nondestructive imaging using multiscale microcomputed tomography. Proceedings of the National Academy of Sciences of the United States of America 109:17105–17110

    ADS  Google Scholar 

  22. Bucher U, Reid L (1961) Development of the intrasegmental bronchial tree: the pattern of branching and development of cartilage at various stages of intra-uterine life. Thorax 16:207–218

    Google Scholar 

  23. Sera T, Uesugi K, Yagi N (2005) Localized morphometric deformations of small airways and alveoli in intact mouse lungs under quasi-static inflation. Respiratory Physiology and Neurobiology 147:51–63

    Google Scholar 

  24. Weibel ER (1963) Morphometry of the human lung, Academic Press, New York

    Google Scholar 

  25. Choi J, Tawhai MH, Hoffman EA, Lin CL (2009) On intra- and intersubject variabilities of airflow in the human lungs. Physics of Fluids 21:101901

    ADS  Google Scholar 

  26. Lin CL, Tawhai MH, McLennan G, Hoffman EA (2007) Characteristics of the turbulent laryngeal jet and its effect on airflow in the human intra-thoracic airways. Respiratory Physiology and Neurobiology 157:295–309

    Google Scholar 

  27. Mandelbrot BB (1982) The Fractal Geometry of Nature. Henry Holt and Company (Macmillan), New York

    Google Scholar 

  28. Weibel ER, Gomez DM (1962) Architecture of the human lung. Use of quantitative methods establishes fundamental relations between size and number of lung structures. Science 137:577–585

    Google Scholar 

  29. Nelson TR, West BJ, Goldberger AL (1990) The fractal lung: universal and species-related scaling patterns. Experientia (Cellular and Molecular Life Sciences) 46:251–254

    Google Scholar 

  30. Mauroy B, Filoche M, Weibel ER, Sapoval B (2004) An optimal bronchial tree may be dangerous. Nature 427:633-636

    ADS  Google Scholar 

  31. West BJ, Bhargava V, Goldberger AL (1986) Beyond the principle of similitude: renormalization in the bronchial tree. Journal of Applied Physiology 60:1089–1097

    Google Scholar 

  32. Imre A (1999) Ideas in theoretical biology – Comment about the fractality of the lung. Acta Biotheoretica 47:79–81

    Google Scholar 

  33. Kitaoka H, Takaki R (1999) Fractal analysis of the human fetal lung development. Forma 14:205–212

    Google Scholar 

  34. Hou C, Gheorghiu S, Coppens MO, Huxley VH, Pfeifer P (2005) Gas diffusion through the fractal landscape of the lung: how deep does oxygen enter the alveolar system? (p. 17–30) In: Losa GA, Merlini D, Nonnenmacher TF, Weibel ER (Eds). Fractals in Biology and Medicine, Vol. IV, Birkhäuser, Basel

    Google Scholar 

  35. Hou C, Gheorghiu S, Huxley VH, Pfeifer P (2010) Reverse engineering of oxygen transport in the lung: adaptation to changing demands and resources through space-filling networks. PLoS Computational Biology 6:e1000902

    Google Scholar 

  36. Basset F, Poirier J, Le Crom M, Turiaf J (1971) Ultrastructural study of the human bronchiolar epithelium. Zeitschrift für Zellforschung und mikroskopische Anatomie 116:425–442

    Google Scholar 

  37. Clara M (1937) Zur Histologie des Bronchialepithels Zeitschrift für mikroskopisch-anatomische Forschung 41:321–347

    Google Scholar 

  38. ten Have-Opbroek AA, Otto-Verberne CJ, Dubbeldam JA, Dykman JH (1991) The proximal border of the human respiratory unit, as shown by scanning and transmission electron microscopy and light microscopical cytochemistry. Anatomical Record 229:339–354

    Google Scholar 

  39. Metzger RJ, Krasnow MA (1999) Genetic control of branching morphogenesis. Science 284:1635–1639

    Google Scholar 

  40. Metzger RJ, Klein OD, Martin GR, Krasnow MA (2008) The branching programme of mouse lung development. Nature 453:745–750

    ADS  Google Scholar 

  41. Hilfer SR (1996) Morphogenesis of the lung: control of embryonic and fetal branching. Annual Review of Physiology 58:93–113

    Google Scholar 

  42. Jeffery PK (1998) The development of large and small airways. American Journal of Respiratory and Critical Care Medicine 157:S174–S180

    Google Scholar 

  43. Hirashima T, Iwasa Y, Morishita Y (2009) Mechanisms for split localization of Fgf10 expression in early lung development. Developmental Dynamics 238:2813–2822

    Google Scholar 

  44. Thurlbeck WM (1975) Postnatal growth and development of the lung. American Review of Respiratory Diseases 111:803–844

    Google Scholar 

  45. Hislop A, Muir DCF, Jacobsen M, Simon G, Reid L (1972) Postnatal growth and function of the pre-acinar airways. Thorax 27:265–274

    Google Scholar 

  46. Hislop AA, Haworth SG (1989) Airway size and structure in the normal fetal and infant lung and the effect of premature delivery and artificial ventilation. American Review of Respiratory Diseases 140:1717–1726

    Google Scholar 

  47. Horsefield K, Cordon WI, Kemp W, Phillips S (1987) Growth of bronchial tree in man. Thorax 42:383–388

    Google Scholar 

  48. Masters JR (1976) Epithelial-mesenchymal interaction during lung development: the effect of mesenchymal mass. Developmental Biology 51:98–108

    Google Scholar 

  49. Mollard R, Dziadek M (1998) A correlation between epithelial proliferation rates, basement membrane component localization patterns, and morphogenetic potential in the embryonic mouse lung. American Journal of Respiratory Cell and Molecular Biology 19:71–82

    Google Scholar 

  50. Lu P, Werb Z (2008) Patterning mechanisms of branched organs. Science 322:1506–1509

    ADS  Google Scholar 

  51. Bellusci S, Grindley J, Emoto H, Itoh N, Hogan BL (1997) Fibroblast growth factor 10 (FGF10) and branching morphogenesis in the embryonic mouse lung. Development 124:4867–4878

    Google Scholar 

  52. Zhou S, Degan S, Potts EN, Foster WM, Sunday ME (2009) NPAS3 is a trachealess homolog critical for lung development and homeostasis. Proceedings of the National Academy of Sciences of the United States of America 106:11691–11696

    ADS  Google Scholar 

  53. Serra R, Pelton RW, Moses HL (1994) TGF β1 inhibits branching morphogenesis and N-myc expression in lung bud organ cultures. Development 120:2153–2161

    Google Scholar 

  54. Mahlapuu M, Enerbäck S, Carlsson P (2001) Haploinsufficiency of the forkhead gene Foxf1, a target for sonic hedgehog signaling, causes lung and foregut malformations. Development 128:2397–2406

    Google Scholar 

  55. Li Y, Zhang H, Choi SC, Litingtung Y, Chiang C (2004) Sonic hedgehog signaling regulates Gli3 processing, mesenchymal proliferation, and differentiation during mouse lung organogenesis. Developmental Biology 270:214–231

    Google Scholar 

  56. Motoyama J, Liu J, Mo R, Ding Q, Post M, Hui CC (1998) Essential function of Gli2 and Gli3 in the formation of lung, trachea and oesophagus. Nature – Genetics 20:54–57

    Google Scholar 

  57. Kicheva A, Cohen M, Briscoe J (2012) Developmental pattern formation: insights from physics and biology. Science 338:210–212

    ADS  Google Scholar 

  58. Mollard R, Dziadek M (1997) Homeobox genes from clusters A and B demonstrate characteristics of temporal colinearity and differential restrictions in spatial expression domains in the branching mouse lung. International Journal of Developmental Biology 41:655–666

    Google Scholar 

  59. Gjorevski N, Nelson CM (2010) The mechanics of development: models and methods for tissue morphogenesis. Birth Defects Research. Part C, Embryo Today 90:193–202

    Google Scholar 

  60. Schittny JC, Miserocchi G, Sparrow MP (2000) Spontaneous peristaltic airway contractions propel lung liquid through the bronchial tree of intact and fetal lung explants. American Journal of Respiratory Cell and Molecular Biology 23:11–18

    Google Scholar 

  61. Hislop A, Fairweather DV, Blackwell RJ, Howard S (1984) The effect of amniocentesis and drainage of amniotic fluid on lung development in Macaca fascicularis. British Journal of Obstetrics and Gynaecology 91:835–842

    Google Scholar 

  62. Perlman M, Williams J, Hirsch M (1976) Neonatal pulmonary hypoplasia after prolonged leakage of amniotic fluid. Archives of Disease in Childhood 51:349–353

    Google Scholar 

  63. Moore KA, Polte T, Huang S, Shi B, Alsberg E, Sunday ME, Ingber DE (2005) Control of basement membrane remodeling and epithelial branching morphogenesis in embryonic lung by Rho and cytoskeletal tension. Developmental Dynamics 232:268–281

    Google Scholar 

  64. Turing AM (1952) The chemical basis of morphogenesis. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 237:37–72

    Google Scholar 

  65. Gierer A, Meinhardt H (1972) A theory of biological pattern formation. Kybernetik 12:30–39

    Google Scholar 

  66. Murray JD (2003) On the mechanochemical theory of biological pattern formation with application to vasculogenesis. Comptes Rendues Biologies 326:239–252

    Google Scholar 

  67. Elliott FM, Reid L (1965) Some new facts about the pulmonary artery and its branching pattern. Clinical Radiology 16:193–198

    Google Scholar 

  68. Pump KK (1972) Distribution of bronchial arteries in human lung. Chest 62:447–451

    Google Scholar 

  69. Hislop A, Reid L (1972) Intrapulmonary arterial development during fetal life: branching pattern and structure. Journal of Anatomy 113:35–48

    Google Scholar 

  70. Hislop A, Reid L (1973) Fetal and childhood development of the intrapulmonary veins in man: branching pattern and structure. Thorax 28:313–319

    Google Scholar 

  71. West JB (2008) Respiratory Physiology: The Essentials, Lippincott Williams and Wilkins, Baltimore, MD

    Google Scholar 

  72. Plank L, James J, Wagenvoort CA (1980) Caliber and elastin content of the pulmonary trunk. Archives of Pathology and Laboratory Medicine 104:238–241

    Google Scholar 

  73. Rhoades R, Bell DR (2009) Medical Physiology: Principles for Clinical Medicine, 3rd ed., Wolters Kluwer – Lippincott Williams and Wilkins, Philadelphia, Pennsylvania

    Google Scholar 

  74. Sant’Ambrogio G (1987) Nervous receptors of the tracheobronchial tree. Annual Review of Physiology 49:611–627

    Google Scholar 

  75. Kang S, Jang JH, Price MP, Gautam M, Benson CJ, Gong H, Welsh MJ, Brennan TJ (2012) Simultaneous disruption of mouse ASIC1a, ASIC2 and ASIC3 genes enhances cutaneous mechanosensitivity. PLoS ONE 7:e35225

    ADS  Google Scholar 

  76. Manzke T (2005) Expression and function of serotonin receptor isoforms in the respiratory system. PhD Thesis, Göttingen

    Google Scholar 

  77. Heistad DD, Abboud FM, Mark AL, Schmid PG (1974) Interaction of baroreceptor and chemoreceptor reflexes. Modulation of the chemoreceptor reflex by changes in baroreceptor activity. Journal of Clinical Investigation 53:1226–1236

    Google Scholar 

  78. Miura M, Reis DJ (1971) The paramedian reticular nucleus: a site of inhibitory interaction between projections from fastigial nucleus and carotid sinus nerve acting on blood pressure. Journal of Physiology 216:441–460

    Google Scholar 

  79. Miura M, Reis DJ (1972) The role of the solitary and paramedian reticular nuclei in mediating cardiovascular reflex responses from carotid baro- and chemoreceptors. Journal of Physiology 223:525–548

    Google Scholar 

  80. Van De Borne P, Mezzetti S, Montano N, Narkiewicz K, Degaute JP, Somers VK (2000) Hyperventilation alters arterial baroreflex control of heart rate and muscle sympathetic nerve activity. American Journal of Physiology – Heart and Circulatory Physiology 279:H536–H541

    Google Scholar 

  81. Somers VK, Mark AL, Zavala DC, Abboud FM (1989) Influence of ventilation and hypocapnia on sympathetic nerve responses to hypoxia in normal humans. Journal of Applied Physiology 67:2095–2100

    Google Scholar 

  82. Narkiewicz K, van de Borne P, Montano N, Hering D, Kara T, Somers VK (2006) Sympathetic neural outflow and chemoreflex sensitivity are related to spontaneous breathing rate in normal men. Hypertension 47:51–55

    Google Scholar 

  83. Schocken Roth (1977) Reduced β-adrenoceptor concentrations in ageing man. Nature 267:856–858

    ADS  Google Scholar 

  84. Barnes P, Jacobs M, Roberts JM (1984) Glucocorticoids preferentially increase fetal alveolar β-adrenoreceptors: autoradiographic evidence. Pediatric Research 18:1191–1194

    Google Scholar 

  85. Schell DN, Durham D, Murphree SS, Muntz KH, Shaul PW (1992) Ontogeny of β-adrenergic receptors in pulmonary arterial smooth muscle, bronchial smooth muscle and alveolar lining cells in the rat. American Journal of Respiratory Cell and Molecular Biology 7:317–324

    Google Scholar 

  86. Puler N, Bernard P, Carrara M, Bencini C, Pacifici GM (1988) Muscarinic cholinergic receptors in lung of developing rats. Developmental Pharmacology and Therapeutics 11:142–146

    Google Scholar 

  87. Sheppard MN, Marangos PJ, Bloom SR, Polak JM (1984) Neuron specific enolase: a marker for the early development of nerves and endocrine cells in the human lung. Life Sciences 34:264–271

    Google Scholar 

  88. Hislop AA, Wharton J, Allen KM, Polak JM, Haworth SG (1990) Immunohistochemical localization of peptide-containing nerves in the airways of normal young children. American Journal of Respiratory Cell and Molecular Biology 3:191–198

    Google Scholar 

  89. Sheppard MN, Polak JM, Allen JM, Bloom SR (1984) Neuropeptide tyrosine (NPY): a newly discovered peptide is present in the mammalian respiratory tract. Thorax 39:326–330

    Google Scholar 

  90. Abdel-Samad D, Perreault C, Ahmarani L, Avedanian L, Bkaily G, Magder S, D’Orlans-Juste P, Jacques D (2012) Differences in neuropeptide Y-induced secretion of endothelin-1 in left and right human endocardial endothelial cells. Neuropeptides pii: S0143-4179(12)00099-6

    Google Scholar 

  91. Allen KM, Wharton J, Polak JM, Haworth SG (1989) A study of nerves containing peptides in the pulmonary vasculature of healthy infants and children and of those with pulmonary hypertension. British Heart Journal 62:353–360

    Google Scholar 

  92. Sharma RK, Addis BJ, Jeffery PK (1995) The distribution and density of airway vasoactive intestinal polypeptide (VIP) binding sites in cystic fibrosis and asthma. Pulmonary Pharmacology 8:91–96

    Google Scholar 

  93. Klabunde RE (2004) Cardiovascular Physiology Concepts. Lippincott Williams and Wilkins, Philadelphia, Pennsylvania (cvphysiology.com)

    Google Scholar 

  94. Kraske S, Cunningham JT, Hajduczok G, Chapleau MW, Abboud FM, Wachtel RE (1998) Mechanosensitive ion channels in putative aortic baroreceptor neurons. American Journal of Physiology – Heart and Circulatory Physiology 275:1497–1501

    Google Scholar 

  95. Krauhs JM (1979) Structure of rat aortic baroreceptors and their relationship to connective tissue. Journal of Neurocytology 8:401–414

    Google Scholar 

Chap. 3. Physiology of the Cardiovascular Apparatus

  1. Bestel J, Clément F, Sorine M (2001) A biomechanical model of muscle contraction (p. 1159–1161). In Niessen WJ, Viergever MA (eds) Medical Image Computing and Computer-Assisted Intervention (MICCAI’01), Lecture Notes in Computer Science (LNCS), vol. 2208, Springer

    Google Scholar 

  2. Krejci P, Sainte-Marie J, Sorine M, Urquiza JM (2006) Solutions to muscle fiber equations and their long time behaviour. Nonlinear Analysis: Real World Applications 7:535558

    MathSciNet  Google Scholar 

  3. Sainte-Marie J, Chapelle D, Cimrman R, Sorine M (2006) Modeling and estimation of the cardiac electromechanical activity. Computers and Structures 84:1743–1759

    MathSciNet  Google Scholar 

  4. Fernández MA, Gerbeau JF, Grandmont C (2007) A projection semi-implicit scheme for the coupling of an elastic structure with an incompressible fluid. International Journal for Numerical Methods in Engineering 69:794821

    Google Scholar 

  5. Burman E, Fernández MA (2007) Stabilized explicit coupling for fluid–structure interaction using Nitsche’s method. Comptes Rendus de l’Académie des sciences, Paris, Ser. I (Mathematics) 345:467–472

    Google Scholar 

  6. Prassl AJ, Kickinger F, Ahammer H, Grau V, Schneider JE, Hofer E, Vigmond EJ, Trayanova NA, Plank G (2009) Automatically generated, anatomically accurate meshes for cardiac electrophysiology problems. IEEE Transactions on Biomedical Engineering 56:1318–1330

    Google Scholar 

  7. Diniz dos Santos N, Gerbeau JF, Bourgat JF (2008) A partitioned fluid–structure algorithm for elastic thin valves with contact. Computer Methods in Applied Mechanics and Engineering 197:1750–1761

    MathSciNet  ADS  MATH  Google Scholar 

  8. Deng W, Bukiya AN, Rodríguez-Menchaca AA, Zhang Z, Baumgarten CM, Logothetis DE, Levitan I, Rosenhouse-Dantsker A (2012) Hypercholesterolemia induces up-regulation of KACh cardiac currents via a mechanism independent of phosphatidylinositol 4,5-bisphosphate and Gβγ. Journal of Biological Chemistry 287:4925–4935

    Google Scholar 

  9. Moireau P, Chapelle D, Le Tallec P (2008) Joint state and parameter estimation for distributed mechanical systems. Computer Methods in Applied Mechanics and Engineering, 197:659677

    Google Scholar 

  10. Chapelle D, Moireau P, Le Tallec P (2009) Robust filtering for joint state-parameter estimation in distributed mechanical systems. Discrete and Continuous Dynamical Systems, Series A 23:65–84

    MathSciNet  MATH  Google Scholar 

  11. Poon CS, Merrill CK (1997) Decrease of cardiac chaos in congestive heart failure, Nature 389:492–495

    ADS  Google Scholar 

  12. Pironet A, Dauby PC, Paeme S, Kosta S, Chase JG, Desaive T (2013) Simulation of left atrial function using a multi-scale model of the cardiovascular system. PLoS One 8:e65146

    ADS  Google Scholar 

  13. Penney D (2003) Cardiac cycle, www.coheadquarters.com/PennLibr/MyPhysiology/

  14. Al-Rubaiee M, Gangula PR, Millis RM, Walker RK, Umoh NA, Cousins VM, Jeffress MA, Haddad GE (2013) Inotropic and lusitropic effects of calcitonin gene-related peptide in the heart. American Journal of Physiology – Heart and Circulatory Physiology 304:H1525–H1537

    Google Scholar 

  15. Robinson TF, Factor SM, Sonnenblick EH (1986) The heart as a suction pump. Scientific American 6:62-69

    Google Scholar 

  16. Pagel PS, Kehl F, Gare M, Hettrick DA, Kersten JR, Warltier DC (2003) Mechanical function of the left atrium: new insights based on analysis of pressure-volume relations and Doppler echocardiography. Anesthesiology 98:975–994

    Google Scholar 

  17. Malik ZA, Kott KS, Poe AJ, Kuo T, Chen L, Ferrara KW, Knowlton AA (2013) Cardiac myocyte exosomes: stability, HSP60, and proteomics. American Journal of Physiology – Heart and Circulatory Physiology 304:H954–H965

    Google Scholar 

  18. Zhang P, Su J, Mende U (2012) Cross talk between cardiac myocytes and fibroblasts: from multiscale investigative approaches to mechanisms and functional consequences. American Journal of Physiology – Heart and Circulatory Physiology 303:H1385–H1396

    Google Scholar 

  19. Sipido KR, Cheng H (2013) T-tubules and ryanodine receptor microdomains: on the road to translation. Cardiovascular Research 98:159–161

    Google Scholar 

  20. Zhang H, Gomez AM, Wang X, Yan Y, Zheng M, Cheng H (2013) ROS regulation of microdomain Ca 2+ signalling at the dyads. Cardiovascular Research 98:248–258

    Google Scholar 

  21. Kohl T, Lehnart SE (2013) Imaging T-tubules: dynamic membrane structures for deep functions. Cardiovascular Research 98:162–164

    Google Scholar 

  22. Guo A, Zhang C, Wei S, Chen B, Song LS (2013) Emerging mechanisms of T-tubule remodelling in heart failure. Cardiovascular Research 98:204–215

    Google Scholar 

  23. Shaw RM, Colecraft HM (2013) L-type calcium channel targeting and local signalling in cardiac myocytes. Cardiovascular Research 98:177–186

    Google Scholar 

  24. Scriven DR, Asghari P, Moore ED (2013) Microarchitecture of the dyad. Cardiovascular Research 98:169–176

    Google Scholar 

  25. Tanskanen AJ, Greenstein JL, Chen A, Sun SX, Winslow RL (2007) Protein geometry and placement in the cardiac dyad influence macroscopic properties of calcium-induced calcium release. Biophysical Journal 92:3379–3396

    ADS  Google Scholar 

  26. Maier SK, Westenbroek RE, Schenkman KA, Feigl EO, Scheuer T, Catterall WA (2002) An unexpected role for brain-type sodium channels in coupling of cell surface depolarization to contraction in the heart. Proceedings of the National Academy of Sciences of the United States of America 99:4073–4078

    ADS  Google Scholar 

  27. Zobel C, Cho HC, Nguyen TT, Pekhletski R, Diaz RJ, Wilson GJ, Backx PH (2003) Molecular dissection of the inward rectifier potassium current (IK1) in rabbit cardiomyocytes: evidence for heteromeric co-assembly of Kir2.1 and Kir2.2. Journal of Physiology 550:365–372

    Google Scholar 

  28. Liu GX, Derst C, Schlichthörl G, Heinen S, Seebohm G, Brüggemann A, Kummer W, Veh RW, Daut J, Preisig-Müller R (2001) Comparison of cloned Kir2 channels with native inward rectifier K + channels from guinea-pig cardiomyocytes. Journal of Physiology 532:115–126

    Google Scholar 

  29. Gorelik J, Wright PT, Lyon AR, Harding SE (2013) Spatial control of the 0̆3b2AR system in heart failure: the transverse tubule and beyond. Cardiovascular Research 98:216–224

    Google Scholar 

  30. Wu CY, Jia Z, Wang W, Ballou LM, Jiang YP, Chen B, Mathias RT, Cohen IS, Song LS, Entcheva E, Lin RZ (2011) PI3Ks maintain the structural integrity of T-tubules in cardiac myocytes. PLoS One 6:e24404

    ADS  Google Scholar 

  31. Chopra N, Knollmann BC (2013) Triadin regulates cardiac muscle couplon structure and microdomain Ca 2+ signalling: a path towards ventricular arrhythmias. Cardiovascular Research 98:187–191

    Google Scholar 

  32. Kohlhaas M, Maack C (2013) Calcium release microdomains and mitochondria. Cardiovascular Research 98: 259–268

    Google Scholar 

  33. Plovanich M, Bogorad RL, Sancak Y, Kamer KJ, Strittmatter L, Li AA, Girgis HS, Kuchimanchi S, De Groot J, Speciner L, Taneja N, Oshea J, Koteliansky V, Mootha VK (2013) MICU2, a paralog of MICU1, resides within the mitochondrial uniporter complex to regulate calcium handling. PLoS One 8:e55785

    ADS  Google Scholar 

  34. Mallilankaraman K, Cárdenas C, Doonan PJ, Chandramoorthy HC, Irrinki KM, Golenár T, Csordás G, Madireddi P, Yang J, Müller M, Miller R, Kolesar JE, Molgó J, Kaufman B, Hajnóczky G, Foskett JK, Madesh M (2012) MCUR1 is an essential component of mitochondrial Ca 2+ uptake that regulates cellular metabolism. Nature – Cell Biology 14:1336–1343

    Google Scholar 

  35. Domenech RJ, Sánchez G, Donoso P, Parra V, Macho P (2003) Effect of tachycardia on myocardial sarcoplasmic reticulum and Ca 2+ dynamics: a mechanism for preconditioning? Journal of Molecular and Cellular Cardiology 35:1429–1437

    Google Scholar 

  36. Sánchez G, Pedrozo Z, Domenech RJ, Hidalgo C, Donoso PJ (2005) Tachycardia increases NADPH oxidase activity and RyR2 S-glutathionylation in ventricular muscle. Journal of Molecular and Cellular Cardiology 39:982–991

    Google Scholar 

  37. Beigi F, Gonzalez DR, Minhas KM, Sun QA, Foster MW, Khan SA, Treuer AV, Dulce RA, Harrison RW, Saraiva RM, Premer C, Schulman IH, Stamler JS, Hare JM (2012) Dynamic denitrosylation via S-nitrosoglutathione reductase regulates cardiovascular function. Proceedings of the National Academy of Sciences of the United States of America 109:4314–4319

    Google Scholar 

  38. Lopaschuk GD, Ussher JR, Folmes CD, Jaswal JS, Stanley WC (2010) Myocardial fatty acid metabolism in health and disease. Physiological Reviews 90:207–258

    Google Scholar 

  39. Kahn BB, Alquier T, Carling D, Hardie DG (2005) AMP-activated protein kinase: ancient energy gauge provides clues to modern understanding of metabolism. Cell Metabolism 1: 15–25

    Google Scholar 

  40. Pawlikowska P, Orzechowski A (2007) Role of transmembrane GTPases in mitochondrial morphology and activity [Article in Polish]. Postepy Biochemii 53:53–59

    Google Scholar 

  41. Legros F, Lombès A, Frachon P, Rojo M (2002) Mitochondrial fusion in human cells is efficient, requires the inner membrane potential, and is mediated by mitofusins. Molecular Biology of the Cell 13:4343–4354

    Google Scholar 

  42. Shi Y, Dierckx A, Wanrooij PH, Wanrooij S, Larsson NG, Wilhelmsson LM, Falkenberg M, Gustafsson CM (2012) Mammalian transcription factor A is a core component of the mitochondrial transcription machinery. Proceedings of the National Academy of Sciences of the United States of America 109:16510–16515

    ADS  Google Scholar 

  43. Metodiev MD, Lesko N, Park CB, Cámara Y, Shi Y, Wibom R, Hultenby K, Gustafsson CM, Larsson NG (2009) Methylation of 12S rRNA is necessary for in vivo stability of the small subunit of the mammalian mitochondrial ribosome. Cell Metabolism 9:386–397

    Google Scholar 

  44. Spåhr H, Habermann B, Gustafsson CM, Larsson NG, Hallberg BM (2012) Structure of the human MTERF4-NSUN4 protein complex that regulates mitochondrial ribosome biogenesis. Proceedings of the National Academy of Sciences of the United States of America 109:15253–15258

    ADS  Google Scholar 

  45. Beck H, Flynn K, Lindenberg KS, Schwarz H, Bradke F, Di Giovanni S, Knöll B (2012) Serum Response Factor (SRF)-cofilin-actin signaling axis modulates mitochondrial dynamics. Proceedings of the National Academy of Sciences of the United States of America 109:E2523-E2532

    ADS  Google Scholar 

  46. Murphy MP (2012) Modulating mitochondrial intracellular location as a redox signal. Science Signaling 5:pe39

    Google Scholar 

  47. Carrer M, Liu N, Grueter CE, Williams AH, Frisard MI, Hulver MW, Bassel-Duby R, Olson EN (2012) Control of mitochondrial metabolism and systemic energy homeostasis by microRNAs 378 and 378. Proceedings of the National Academy of Sciences of the United States of America 109:15330–15335

    ADS  Google Scholar 

  48. Yu E, Mercer J, Bennett M (2012) Mitochondria in vascular disease. Cardiovascular Research 95:173–182

    Google Scholar 

  49. O’Rourke B (2007) Mitochondrial ion channels. Annual Review of Physiology 69:19–49

    Google Scholar 

  50. O’Rourke B, Cortassa S, Aon MA (2005) Mitochondrial ion channels: gatekeepers of life and death. Physiology 20:303–315

    Google Scholar 

  51. Zaobornyj T, Ghafourifar P (2012) Strategic localization of heart mitochondrial NOS: a review of the evidence. American Journal of Physiology – Heart and Circulatory Physiology 303:H1283–H1293

    Google Scholar 

  52. Virkki LV, Forster IC, Biber J, Murer H (2005) Substrate interactions in the human type IIa sodium-phosphate cotransporter (NaP i -IIa). American Journal of Physiology – Renal Physiology 288:F969–F981

    Google Scholar 

  53. Aprille JR (2003) Mechanism and regulation of the mitochondrial ATP-Mg/P i carrier. Journal of Bioenergetics and Biomembranes 25:473–481

    Google Scholar 

  54. Rich PR (2003) The molecular machinery of Keilin’s respiratory chain. Biochemical Society Transactions 31:1095–1105

    Google Scholar 

  55. Covian R, Balaban RS (2012) Cardiac mitochondrial matrix and respiratory complex protein phosphorylation. American Journal of Physiology – Heart and Circulatory Physiology 303:H940–H966

    Google Scholar 

  56. Illingworth J (Faculty of Biological Sciences, University of Leeds) Bioenergetics, www.bmb.leeds.ac.uk/illingworth/oxphos/index.htm

  57. Lu G, Sun H, Korge P, Koehler CM, Weiss JN, Wang Y (2009) Functional characterization of a mitochondrial Ser/Thr protein phosphatase in cell death regulation. Methods in Enzymology 457:255–273

    Google Scholar 

  58. Castro L, Demicheli V, Tórtora V, Radi R (2011) Mitochondrial protein tyrosine nitration. Free Radical Research 45:37–52

    Google Scholar 

  59. Wirstam M, Blomberg MRA, Siegbahn PEM (1999) Reaction mechanism of compound I formation in heme peroxidases: a density functional theory study. Journal of the American Chemical Society 121:10178–10185

    Google Scholar 

  60. Hurd TR, Costa NJ, Dahm CC, Beer SM, Brown SE, Filipovska A, Murphy MP (2005) Glutathionylation of mitochondrial proteins. Antioxidants and Redox Signaling 7:999–1010

    Google Scholar 

  61. Murphy E, Kohr M, Sun J, Nguyen T, Steenbergen C (2012) S-nitrosylation: a radical way to protect the heart. Journal of Molecular and Cellular Cardiology 52:568–577

    Google Scholar 

  62. Tarze A, Deniaud A, Le Bras M, Maillier E, Molle D, Larochette N, Zamzami N, Jan G, Kroemer G, Brenner C (2007) GAPDH, a novel regulator of the pro-apoptotic mitochondrial membrane permeabilization. Oncogene 26:2606–2620

    Google Scholar 

  63. Sirover MA (2005) New nuclear functions of the glycolytic protein, glyceraldehyde-3-phosphate dehydrogenase, in mammalian cells. Journal of Cellular Biochemistry 95:45–52

    Google Scholar 

  64. Jandu SK, Webb AK, Pak A, Sevinc B, Nyhan D, Belkin AM, Flavahan NA, Berkowitz DE, Santhanam L (2011) Nitric oxide regulates tissue transglutaminase localization and function in the vasculature. Amino Acids 0939-4451:1-9

    Google Scholar 

  65. Gundemir S, Johnson GVW (2009) Intracellular localization and conformational state of transglutaminase 2: implications for cell death. PLoS One 4:e6123

    ADS  Google Scholar 

  66. Kim Y, Park J, Kim S, Song S, Kwon SK, Lee SH, Kitada T, Kim JM, Chung J (2008) PINK1 controls mitochondrial localization of Parkin through direct phosphorylation. Biochemical and Biophysical Research Communications 377:975–980

    Google Scholar 

  67. Junn E, Jang WH, Zhao X, Jeong BS, Mouradian MM (2009) Mitochondrial localization of DJ-1 leads to enhanced neuroprotection. Journal of Neuroscience Research 87:123–129

    Google Scholar 

  68. Smirnova E, Griparic L, Shurland DL, van der Bliek AM (2001) Dynamin-related protein Drp1 is required for mitochondrial division in mammalian cells. Molecular Biology of the Cell 12:2245–2256

    Google Scholar 

  69. Schroeder MA, Ali MA, Hulikova A, Supuran CT, Clarke K, Vaughan-Jones RD, Tyler DJ, Swietach P (2013) Extramitochondrial domain rich in carbonic anhydrase activity improves myocardial energetics. Proceedings of the National Academy of Sciences of the United States of America 110:E958–E967

    ADS  Google Scholar 

  70. Des Rosiers C, Labarthe F, Lloyd SG, Chatham JC (2011) Cardiac anaplerosis in health and disease: food for thought. Cardiovascular Research 90:210–219

    Google Scholar 

  71. Cotter DG, Schugar RC, Crawford PA (2013) Ketone body metabolism and cardiovascular disease. American Journal of Physiology – Heart and Circulatory Physiology 304:H1060–H1076

    Google Scholar 

  72. Robinson AM, Williamson DH (1978) Utilization of D-3-hydroxy[3-14C]butyrate for lipogenesis in vivo in lactating rat mammary gland. Biochemical Journal 176:635–638

    Google Scholar 

  73. Wise A, Foord SM, Fraser NJ, Barnes AA, Elshourbagy N, Eilert M, Ignar DM, Murdock PR, Steplewski K, Green A, Brown AJ, Dowell SJ, Szekeres PG, Hassall DG, Marshall FH, Wilson S, Pike NB (2003) Molecular identification of high and low affinity receptors for nicotinic acid. Journal of Biological Chemistry 278:9869–9874

    Google Scholar 

  74. Tunaru S, Kero J, Schaub A, Wufka C, Blaukat A, Pfeffer K, Offermanns S (2003) PUMA-G and HM74 are receptors for nicotinic acid and mediate its anti-lipolytic effect. Nature – Medicine 9:352–355

    Google Scholar 

  75. Jeninga EH, Bugge A, Nielsen R, Kersten S, Hamers N, Dani C, Wabitsch M, Berger R, Stunnenberg HG, Mandrup S, Kalkhoven E (2009) Peroxisome proliferator-activated receptor γ regulates expression of the anti-lipolytic G-protein-coupled receptor 81 (GPR81/Gpr81). Journal of Biological Chemistry 284:26385–26393

    Google Scholar 

  76. Irukayama-Tomobe Y, Tanaka H, Yokomizo T, Hashidate-Yoshida T, Yanagisawa M, Sakurai T (2009) Aromatic D-amino acids act as chemoattractant factors for human leukocytes through a G protein-coupled receptor, GPR109B. Proceedings of the National Academy of Sciences of the United States of America 106:3930–3934

    ADS  Google Scholar 

  77. Yaniv Y, Spurgeon HA, Ziman BD, Lyashkov AE, Lakatta EG (2013) Mechanisms that match ATP supply to demand in cardiac pacemaker cells during high ATP demand. American Journal of Physiology – Heart and Circulatory Physiology 304:H1428–H1438

    Google Scholar 

  78. Traaseth N, Elfering S, Solien J, Haynes V, Giulivi C (2004) Role of calcium signaling in the activation of mitochondrial nitric oxide synthase and citric acid cycle. Biochimica et Biophysica Acta 1658:64–71

    Google Scholar 

  79. Takahashi E, Asano K (2002) Mitochondrial respiratory control can compensate for intracellular O2 gradients in cardiomyocytes at low PO2. American Journal of Physiology – Heart and Circulatory Physiology 283:H871–H878

    Google Scholar 

  80. Timmer SAJ, Knaapen P (2013) Coronary microvascular function, myocardial metabolism, and energetics in hypertrophic cardiomyopathy: insights from positron emission tomography. European Heart Journal – Cardiovascular Imaging 14:95–101

    Google Scholar 

  81. Chauhan VS, Tuvia S, Buhusi M, Bennett V, Grant AO (2000) Abnormal cardiac Na + channel properties and QT heart rate adaptation in neonatal ankyrinB knockout mice. Circulation Research 86:441–447

    Google Scholar 

  82. Mohler PJ, Schott JJ, Gramolini AO, Dilly KW, Guatimosim S, duBell WH, Song LS, Haurogne K, Kyndt F, Ali ME, Rogers TB, Lederer WJ, Escande D, Le Marec H, Bennett V (2003) Ankyrin-B mutation causes type 4 long-QT cardiac arrhythmia and sudden cardiac death. Nature 421:634–639

    ADS  Google Scholar 

  83. Bhasin N, Cunha SR, Mudannayake M, Gigena MS, Rogers TB, Mohler PJ (2007) Molecular basis for PP2A regulatory subunit B56α targeting in cardiomyocytes. American Journal of Physiology – Heart and Circulatory Physiology 293:H109–H119

    Google Scholar 

  84. Marx SO, Kurokawa J, Reiken S, Motoike H, D’Armiento J, Marks AR, Kass RS (2002) Requirement of a macromolecular signaling complex for β adrenergic receptor modulation of the KCNQ1–KCNE1 potassium channel. Science 295:496–499

    ADS  Google Scholar 

  85. Wehrens XHT, Lehnart SE, Marks AR (2005) Intracellular calcium release channels and cardiac disease. Annual Review of Physiology 67:69–98

    Google Scholar 

  86. Roberts BN, Yang PC, Behrens SB, Moreno JD, Clancy CE (2012) Computational approaches to understand cardiac electrophysiology and arrhythmias. American Journal of Physiology – Heart and Circulatory Physiology 303:H766–H783

    Google Scholar 

  87. Ha CH, Kim JY, Zhao J, Wang W, Jhun BS, Wong C, Jin ZG (2010) PKA phosphorylates histone deacetylase 5 and prevents its nuclear export, leading to the inhibition of gene transcription and cardiomyocyte hypertrophy. Proceedings of the National Academy of Sciences of the United States of America 107:15467–15472

    ADS  Google Scholar 

  88. Hallaq H, Yang Z, Viswanathan PC, Fukuda K, Shen W, Wang DW, Wells KS, Zhou J, Yi J, Murray KT (2006) Quantitation of protein kinase A-mediated trafficking of cardiac sodium channels in living cells. Cardiovascular Research 72:250–261

    Google Scholar 

  89. Rook MB, Evers MM, Vos MA, Bierhuizen MF (2012) Biology of cardiac sodium channel NaV1.5 expression. Cardiovascular Research 93:12–23

    Google Scholar 

  90. Nichols CB, Rossow CF, Navedo MF, Westenbroek RE, Catterall WA, Santana LF, McKnight GS (2010) Sympathetic stimulation of adult cardiomyocytes requires association of AKAP5 with a subpopulation of L-type calcium channels. Circulation Research 107:747–756

    Google Scholar 

  91. Taylor SS, Ilouz R, Zhang P, Kornev AP (2012) Assembly of allosteric macromolecular switches: lessons from PKA. Nature Reviews – Molecular Cell Biology 13:646–658

    Google Scholar 

  92. Aguiar CJ, Andrade VL, Gomes ER, Alves MN, Ladeira MS, Pinheiro AC, Gomes DA, Almeida AP, Goes AM, Resende RR, Guatimosim S, Leite MF (2009) Succinate modulates Ca 2+ transient and cardiomyocyte viability through PKA-dependent pathway. Cell Calcium 47:37–46

    Google Scholar 

  93. Houser SR (2009) Ca 2+ signaling domains responsible for cardiac hypertrophy and arrhythmias. Circulation Research 104:413–415

    Google Scholar 

  94. Chiang CS, Huang CH, Chieng H, Chang YT, Chang D, Chen JJ, Chen YC, Chen YH, Shin HS, Campbell KP, Chen CC (2009) The CaV3.2 T-type Ca 2+ channel is required for pressure overload-induced cardiac hypertrophy in mice. Circulation Research 104:522–530

    Google Scholar 

  95. Terentyev D, Belevych AE, Terentyeva R, Martin MM, Malana GE, Kuhn DE, Abdellatif M, Feldman DS, Elton TS, Györke S (2009) miR-1 overexpression enhances Ca 2+ release and promotes cardiac arrhythmogenesis by targeting PP2A regulatory subunit B56alpha and causing CaMKII-dependent hyperphosphorylation of RyR2. Circulation Research 104: 514–521

    Google Scholar 

  96. Carusi A, Burrage K, Rodrguez B (2012) Bridging experiments, models and simulations: an integrative approach to validation in computational cardiac electrophysiology. American Journal of Physiology – Heart and Circulatory Physiology 303:H144–H155

    Google Scholar 

  97. Quinn TA, Kohl P (2013) Combining wet and dry research: experience with model development for cardiac mechano-electric structure-function studies. Cardiovascular Research 97:601–611

    Google Scholar 

  98. Kraeutler MJ, Soltis AR, Saucerman JJ (2010) Modeling cardiac β-adrenergic signaling with normalized-Hill differential equations: comparison with a biochemical model. BMC Systems Biology 4:157

    Google Scholar 

  99. Grandi E, Puglisi JL, Wagner S, Maier LS, Severi S, Bers DM (2007) Simulation of Ca-calmodulin-dependent protein kinase II on rabbit ventricular myocyte ion currents and action potentials. Biophysical Journal 93:3835–3847

    ADS  Google Scholar 

  100. Hashambhoy YL, Greenstein JL, Winslow RL (2010) Role of CaMKII in RyR leak, EC coupling and action potential duration: a computational model. Journal of Molecular and Cellular Cardiology 49:617–624

    Google Scholar 

  101. Saucerman JJ, Zhang J, Martin JC, Peng LX, Stenbit AE, Tsien RY, McCulloch AD (2006) Systems analysis of PKA-mediated phosphorylation gradients in live cardiac myocytes. Proceedings of the National Academy of Sciences of the United States of America 103:12923–12928

    ADS  Google Scholar 

  102. Iancu RV, Jones SW, Harvey RD (2007) Compartmentation of cAMP signaling in cardiac myocytes: a computational study. Biophysical Journal 92:3317–3331

    ADS  Google Scholar 

  103. Himeno Y, Sarai N, Matsuoka S, Noma A (2008) Ionic mechanisms underlying the positive chronotropy induced by beta1-adrenergic stimulation in guinea pig sinoatrial node cells: A simulation study. Journal of Physiological Sciences 58:53–65

    Google Scholar 

  104. Soltis AR, Saucerman JJ (2010) Synergy between CaMKII substrates and β-adrenergic signaling in regulation of cardiac myocyte Ca 2+ handling. Biophysical Journal 99:2038–2047

    ADS  Google Scholar 

  105. Hodgkin AL and Huxley AF (1952) A quantitative description of membrane current and its application to conduction and excitation in nerve. Journal of Physiology 117:500–544

    Google Scholar 

  106. ten Tusscher KH, Noble D, Noble PJ, Panfilov AV (2004) A model for human ventricular tissue. American Journal of Physiology – Heart and Circulatory Physiology 286:H1573–H1589

    Google Scholar 

  107. Bernus O, Wilders R, Zemlin CW, Verschelde H, Panfilov AV (2002) A computationally efficient electrophysiological model of human ventricular cells. American Journal of Physiology – Heart and Circulatory Physiology 282:H2296–H2308

    Google Scholar 

  108. Beeler GW, Reuter H (1977) Reconstruction of the action potential of ventricular myocardial fibres. Journal of Physiology 268:177-210

    Google Scholar 

  109. Mitchell CC, Schaeffer DG (2003) A two-current model for the dynamics of cardiac membrane. Bulletin of Mathematical Biology 65:767–793

    Google Scholar 

  110. Aliev RR, Panfilov AV (1996) A simple two-variable model of cardiac excitation. Chaos Solitons Fractals 7:293–301

    ADS  Google Scholar 

  111. Fenton F, Karma A (1998) Vortex dynamics in three-dimensional continuous myocardium with fiber rotation: Filament instability and fibrillation. Chaos 8:20-47

    ADS  MATH  Google Scholar 

  112. Luo CH, Rudy Y (1991) A model of the ventricular cardiac action-potential: depolarization, repolarization, and their interaction. Circulation Research 68:1501–1526

    Google Scholar 

  113. Djabella K, Sorine M. (2006) A reduced differential model for cardiac action potentials. SIAM Conference on the Life Sciences, Raleigh, USA

    Google Scholar 

  114. Tolkacheva EG, Schaeffer DG, Gauthier DJ, Mitchell CC (2002) Analysis of the Fenton-Karma model through an approximation by a one-dimensional map. Chaos 12:1034–1042

    MathSciNet  ADS  MATH  Google Scholar 

  115. Boulakia M, Cazeau S, Fernndez MA, Gerbeau JF, Zemzemi N (2010) Mathematical modeling of electrocardiograms: a numerical study. Annals of Biomedical Engineering 38:1071–1097

    Google Scholar 

  116. Jiao Q, Bai Y, Akaike T, Takeshima H, Ishikawa Y, Minamisawa S (2009) Sarcalumenin is essential for maintaining cardiac function during endurance exercise training. American Journal of Physiology – Heart and Circulatory Physiology 297:H576–H582

    Google Scholar 

  117. Guyton AC, Hall JE (2006) Textbook of medical physiology (7th Edition) Elsevier – Saunders, Philadelphia, Pennsylvania

    Google Scholar 

  118. Milnor WR (1982) Haemodynamics. Williams and Wilkins, Baltimore, MD

    Google Scholar 

  119. Silbernagl S, Despopoulos A (2001) Atlas de poche de physiologie [Pocket Atlas of Physiology]. Flammarion, Paris

    Google Scholar 

  120. Davies JI, Struthers AD (2003) Pulse wave analysis and pulse wave velocity: a critical review of their strengths and weaknesses. Journal of Hypertension 21:463–472

    Google Scholar 

  121. Meaney, E, Alva F, Moguel R, Meaney A, Alva J, Webel R (2000) Formula and nomogram for the sphygmomanometric calculation of the mean arterial pressure. Heart 84:64

    Google Scholar 

  122. Learoyd BM, Taylor MG (1996) Alterations with age in the viscoelastic properties of human arterial walls. Circulation Research 18:278–292

    Google Scholar 

  123. Mills CJ, Gabe IT, Gault JH, Mason DT, Ross J Jr, Braunwald E, Shillingford JP (1970) Pressure-flow relationships and vascular impedance in man. Cardiovascular Research 4: 405–417

    Google Scholar 

  124. Anliker M et al (1977) Non-invasive measurement of blood flow, In: Hwang NHC, Normann NA (eds) Cardiovascular flow dynamics and measurements. University Park Press, Baltimore

    Google Scholar 

  125. Bergfeld GR, Forrester T (1992) Release of ATP from human erythrocytes in response to a brief period of hypoxia and hypercapnia. Cardiovascular Research 26:40–47

    Google Scholar 

  126. McCullough WT, Collins DM, Ellsworth ML (1997) Arteriolar responses to extracellular ATP in striated muscle. American Journal of Physiology – Heart and Circulatory Physiology 272:H1886–H1891

    Google Scholar 

  127. Arciero JC, Carlson BE, Secomb TW (2008) Theoretical model of metabolic blood flow regulation: roles of ATP release by red blood cells and conducted responses. American Journal of Physiology – Heart and Circulatory Physiology 295:H1562–H1571

    Google Scholar 

  128. Kalmanson D, Veyrat C (1978) Clinical aspects of venous return: a velocimetric approach to a new system dynamics concept. In: Baan J, Noordegraaf A, Raines J (eds) Cardiovascular System Dynamics. MIT Press, Cambridge

    Google Scholar 

  129. Moreno AH (1978) Dynamics of pressure in the central veins. In: Baan J, Noordegraaf A, Raines J (eds) Cardiovascular System Dynamics. MIT Press, Cambridge

    Google Scholar 

  130. Hoffman JI, Spaan JA (1990) Pressure-flow relations in coronary circulation. Physiological Reviews 70:331–390

    Google Scholar 

  131. Shukla P, Sun C, O’Rourke ST (2012) Melatonin inhibits nitric oxide signaling by increasing PDE5 phosphorylation in coronary arteries. American Journal of Physiology – Heart and Circulatory Physiology 303:H1418–H1425

    Google Scholar 

  132. Scaramucci J (1695) De motu cordis, theorema sexton. Theoremata familiaria viros eruditos consulentia de variis physico medicis lucubrationibus iucta leges mecanicas. Urbino, Italy: Apud Joannem Baptistam Bustum, 70–81

    Google Scholar 

  133. Lenègre J, Blondeau M; Bourdarias JP, Gerbaux A, Himbert J, Maurice P (1973) Cœur et Circulation [Heart and Circulation]. In Vallery-Radot P, Hamburger J, Lhermitte F (eds) Pathologie Mdicale. [Medical Pathology] (Vol.3), Flammarion Mdecine Sciences, Paris

    Google Scholar 

  134. Mori H, Tanaka E, Hyodo K, Mohammed MU, Sekka T, Ito K, Shinozaki Y, Tanaka A, Nakazawa H, Abe S, Handa S, Kubota M, Tanioka K, Umetani K, Ando M (1999) Synchrotron microangiography reveals configurational changes and to-and-fro flow in intramyocardial vessels. American Journal of Physiology. Heart Circulation Physiology 276:H429–H437

    Google Scholar 

  135. Carlson BE, Arciero JC, Secomb TW (2008) Theoretical model of blood flow autoregulation: roles of myogenic, shear-dependent, and metabolic responses. American Journal of Physiology – Heart and Circulatory Physiology 295:H1572–H1579

    Google Scholar 

  136. Olsson RA (1981) Local factors regulating cardiac and skeletal muscle blood flow. Annual Review of Physiology 43:385–395

    Google Scholar 

  137. Momen A, Mascarenhas V, Gahremanpour A, Gao Z, Moradkhan R, Kunselman A, Boehmer JP, Sinoway LI, Leuenberger UA (2009) Coronary blood flow responses to physiological stress in humans. American Journal of Physiology – Heart and Circulatory Physiology 296:H854–H861

    Google Scholar 

  138. Caesar K, Offenhauser N, Lauritzen M (2008) Gamma-aminobutyric acid modulates local brain oxygen consumption and blood flow in rat cerebellar cortex. Journal of Cerebral Blood Flow and Metabolism 28:906–915

    Google Scholar 

  139. Stefanovic B, Hutchinson E, Yakovleva V, Schram V, Russell JT, Belluscio L, Koretsky AP, Silva AC (2008) Functional reactivity of cerebral capillaries. Journal of Cerebral Blood Flow and Metabolism 28:961–972

    Google Scholar 

  140. Sirotin YB, Das A (2009) Anticipatory haemodynamic signals in sensory cortex not predicted by local neuronal activity. Nature 457:475–479

    ADS  Google Scholar 

  141. van Beek AHEA, Claassen JAHR, Rikkert MGMO, Jansen RWMM (2008) Cerebral autoregulation: an overview of current concepts and methodology with special focus on the elderly. Journal of Cerebral Blood Flow and Metabolism 28:1071–1085

    Google Scholar 

  142. Tzeng YC, Ainslie PN, Cooke WH, Peebles KC, Willie CK, Macrae BA, Smirl JD, Horsman HM, Rickards CA (2012) Assessment of cerebral autoregulation: the quandary of quantification. American Journal of Physiology – Heart and Circulatory Physiology 303:H658–H671

    Google Scholar 

  143. Fonck E, Feigl GG, Fasel J, Sage D, Unser M, Rüfenacht DA, Stergiopulos N (2009) Effect of aging on elastin functionality in human cerebral arteries. Stroke 40:2552–2556

    Google Scholar 

  144. West JB (1974) Respiratory Physiology. Williams and Wilkins, Baltimore, MD

    Google Scholar 

  145. Wagner WW, Latham LP (1975) Pulmonary capillary recruitment during airway hypoxia in the dog. Journal of Applied Physiology 39:900–905

    Google Scholar 

  146. Hanson WL, Emhardt JD, Bartek JP, Latham LP, Checkley LL, Capen RL, Wagner WW (1989) Site of recruitment in the pulmonary microcirculation. Journal of Applied Physiology 66:2079–2083

    Google Scholar 

  147. Dawson CA, Rickaby DA, Linehan JH (1986) Location and mechanisms of pulmonary vascular volume changes. Journal of Applied Physiology 60:402–409

    Google Scholar 

  148. Barman SA, Taylor AE (1990) Effect of pulmonary venous pressure elevation on vascular resistance and compliance. American Journal of Physiology – Heart and Circulatory Physiology 258:H1164–H1170

    Google Scholar 

  149. Ryan JW, Ryan US, Schultz DR, Whitaker C, Chung A (1975) Subcellular localization of pulmonary antiotensin-converting enzyme (kininase II). Biochemical Journal 146:497–499

    Google Scholar 

  150. Curry FRE, Adamson RH (2010) Vascular permeability modulation at the cell, microvessel, or whole organ level: towards closing gaps in our knowledge. Cardiovascular Research 87:218–229

    Google Scholar 

  151. Perktold K, Prosi M, Zunino P (2009) Mathematical models of mass transfer in the vascular walls (Chap. 7). In Formaggia L, Quarteroni A, Veneziani A (eds.) Cardiovascular Mathematics: Modeling and Simulation of the Circulatory System, Springer, Milano

    Google Scholar 

  152. Shen Q, Rigor RR, Pivetti CD, Wu MH, Yuan SY (2010) Myosin light chain kinase in microvascular endothelial barrier function. Cardiovascular Research 87:272–280

    Google Scholar 

  153. Curry FRE, Noll T (2010) Spotlight on microvascular permeability. Cardiovascular Research 87:195–197

    Google Scholar 

  154. VanTeeffelen JWGE, Brands J, Vink H (2010) Agonist-induced impairment of glycocalyx exclusion properties: contribution to coronary effects of adenosine. Cardiovascular Research 87:311–319

    Google Scholar 

  155. Spindler V, Schlegel1 N, Waschke1 J (2010) Role of GTPases in control of microvascular permeability. Cardiovascular Research 87:243–253

    Google Scholar 

  156. Durán WN, Breslin JW, Sánchez FA (2010) The NO cascade, eNOS location, and microvascular permeability. Cardiovascular Research 87:254–261

    Google Scholar 

  157. Bates DO (2010) Vascular endothelial growth factors and vascular permeability. Cardiovascular Research 87:262–271

    Google Scholar 

  158. Zhou X, He P (2010) Endothelial [Ca2+]i and caveolin-1 antagonistically regulate eNOS activity and microvessel permeability in rat venules. Cardiovascular Research 87:340–347

    Google Scholar 

  159. Rabiet M-J, Plantier J-L, Rival Y, Genoux Y, Lampugnani MG, Dejana E (1996) Thrombin-induced increase in endothelial permeability is associated with changes in cell-to-cell junction organization. Arteriosclerosis, Thrombosis, and Vascular Biology 16:488–496

    Google Scholar 

  160. Sun C, Wu MH, Guo M, Day ML, Lee ES, Yuan SY (2010) ADAM15 regulates endothelial permeability and neutrophil migration via Src/ERK1/2 signalling. Cardiovascular Research 87:348–355

    Google Scholar 

  161. He P (2010) Leucocyte/endothelium interactions and microvessel permeability: coupled or uncoupled? Cardiovascular Research 87:281–290

    Google Scholar 

  162. Ngok SP, Geyer R, Liu M, Kourtidis A, Agrawal S, Wu C, Seerapu HR, Lewis-Tuffin LJ, Moodie KL, Huveldt D, Marx R, Baraban JM, Storz P, Horowitz A, Anastasiadis PZ (2012) VEGF and Angiopoietin-1 exert opposing effects on cell junctions by regulating the Rho GEF Syx. Journal of Cell Biology 199:1103–1115

    Google Scholar 

  163. Michel CC, Curry FE (1999) Microvascular permeability. Physiological Reviews 79:703–761

    Google Scholar 

  164. Weinbaum S, Curry FE (1995) Modelling the structural pathways for transcapillary exchange. Symposia of the Society for Experimental Biology 49:323–345

    Google Scholar 

  165. Agre P, Brown D, Nielsen S (1995) Aquaporin water channels: unanswered questions and unresolved controversies. Current Opinion in Cell Biology 7:472–483

    Google Scholar 

  166. Tarbell JM, Demaio L, Zaw MM (1999) Effect of pressure on hydraulic conductivity of endothelial monolayers: role of endothelial cleft shear stress. Journal of Applied Physiology 87:261–268

    Google Scholar 

  167. Chen SC, Liu KM, Wagner RC (1998) Three-dimensional analysis of vacuoles and surface invaginations of capillary endothelia in the eel rete mirabile. Anatomical Record 252:546–553

    Google Scholar 

  168. Tarbell JM (2010) Shear stress and the endothelial transport barrier. Cardiovascular Research 87:320–330

    Google Scholar 

  169. Reed RK, Rubin K (2010) Transcapillary exchange: role and importance of the interstitial fluid pressure and the extracellular matrix. Cardiovascular Research 87:211–217

    Google Scholar 

  170. Levick JR, Michel CC (2010) Microvascular fluid exchange and the revised Starling principle. Cardiovascular Research 87:198–210

    Google Scholar 

  171. Minami Y, Kasukawa T, Kakazu Y, Iigo M, Sugimoto M, Ikeda S, Yasui A, van der Horst GT, Soga T, Ueda HR (2009) Measurement of internal body time by blood metabolomics. Proceedings of the National Academy of Sciences of the United States of America 106:9890–9895

    ADS  Google Scholar 

  172. Curtis AM, Cheng Y, Kapoor S, Reilly D, Price TS, FitzGerald GA (2007) Circadian variation of blood pressure and the vascular response to asynchronous stress. Proceedings of the National Academy of Sciences of the United States of America 104:3450–3455

    ADS  Google Scholar 

  173. Fuller PM, Lu J, Saper CB (2008) Differential rescue of light- and food-entrainable circadian rhythms. Science 320:1074–1077

    ADS  Google Scholar 

  174. Davidson AJ, London B, Block GD, Menaker M (2005) Cardiovascular tissues contain independent circadian clocks. Clinical and Experimental Hypertension 27:307–311

    Google Scholar 

  175. McNamara P, Seo SP, Rudic RD, Sehgal A, Chakravarti D, FitzGerald GA (2001) Regulation of CLOCK and MOP4 by nuclear hormone receptors in the vasculature: a humoral mechanism to reset a peripheral clock. Cell 105:877–889

    Google Scholar 

  176. Damiola F, Le Minh N, Preitner N, Kornmann B, Fleury-Olela F, Schibler U (2000) Restricted feeding uncouples circadian oscillators in peripheral tissues from the central pacemaker in the suprachiasmatic nucleus. Genes and Development 14:2950–2961

    Google Scholar 

  177. Balsalobre A, Brown SA, Marcacci L, Tronche F, Kellendonk C, Reichardt HM, Schutz G, Schibler U (2000) Resetting of circadian time in peripheral tissues by glucocorticoid signaling. Science 289:2344–2347

    ADS  Google Scholar 

  178. Lemmer B (1992) Cardiovascular chronobiology and chronopharmacology. In: Touitou Y, Haus E (eds) Biologic Rhythms in Clinical and Laboratory Medicine, 418–427. Springer-Verlag, Berlin.

    Google Scholar 

  179. Bray MS, Young ME (2008) Diurnal variations in myocardial metabolism. Cardiovascular Research 79:228–237

    Google Scholar 

  180. Martino TA, Oudit GY, Herzenberg AM, Tata N, Koletar MM, Kabir GM, Belsham DD, Backx PH, Ralph MR, Sole MJ (2008) Circadian rhythm disorganization produces profound cardiovascular and renal disease in hamsters. American Journal of Physiology – Regulatory, Integrative and Comparative Physiology 294:R1675–1683

    Google Scholar 

  181. Ivanov PC, Hu K, Hilton MF, Shea SA, Stanley HE (2007) Endogenous circadian rhythm in human motor activity uncoupled from circadian influences on cardiac dynamics. Proceedings of the National Academy of Sciences of the United States of America 104:20702–20707

    ADS  Google Scholar 

  182. Pennes HH (1948) Analysis of tissue and arterial blood temperatures in the resting human forearm. Journal of Applied Physiology 1:93–122

    Google Scholar 

  183. Valvano JW, Bioheat transfer. users.ece.utexas.edu/ ∼ valvano/research/jwv.pdf

    Google Scholar 

  184. Werner J, Brinck H (2001) A three-dimensional vascular model and its application to the determination of the spatial variations in the arterial, venous, and tissue temperature distribution, In: Leondes C (ed) Biofluid Methods in Vascular and Pulmonary Systems. CRC Press, Boca Raton, FL

    Google Scholar 

  185. Wissler EH (1998) Pennes’ 1948 paper revisited. Journal of Applied Physiology 85:35–41

    Google Scholar 

  186. Arkin H, Xu LX, Holmes KR (1994) Recent developments in modeling heat transfer in blood perfused tissues. IEEE Transactions on Biomedical Engineering 41:97–107

    Google Scholar 

  187. Tedgui A, Lvy B (1994) Biologie de la paroi artrielle [Biology of the Arterial Wall]. Masson, Paris

    Google Scholar 

  188. Dongaonkar RM, Nguyen TL, Quick CM, Hardy J, Laine GA, Wilson E, Stewart RH (2013) Adaptation of mesenteric lymphatic vessels to prolonged changes in transmural pressure. American Journal of Physiology – Heart and Circulatory Physiology 305:H203–H210

    Google Scholar 

  189. Bayliss W (1902) On the local reactions of the arterial wall to changes of internal pressure. Journal of Physiology 28:220–231

    Google Scholar 

  190. Davis MJ (2012) Perspective: physiological role(s) of the vascular myogenic response. Microcirculation 19:99-114

    Google Scholar 

  191. Lidington D, Schubert R, Bolz SS (2013) Capitalizing on diversity: an integrative approach towards the multiplicity of cellular mechanisms underlying myogenic responsiveness. Cardiovascular Research 97:404–412

    Google Scholar 

  192. Storch U, Schnitzler MM, Gudermann T (2012) G protein-mediated stretch reception. American Journal of Physiology – Heart and Circulatory Physiology 302:H1241–H1249

    Google Scholar 

  193. Pluznick JL, Protzko RJ, Gevorgyan H, Peterlin Z, Sipos A, Han J, Brunet I, Wan LX, Rey F, Wang T, Firestein SJ, Yanagisawa M, Gordon JI, Eichmann A, Peti-Peterdi J, Caplan MJ (2013) Olfactory receptor responding to gut microbiota-derived signals plays a role in renin secretion and blood pressure regulation. Proceedings of the National Academy of Sciences of the United States of America 110:4410–4415

    ADS  Google Scholar 

  194. Inoue R, Jian Z, Kawarabayashi Y (2009) Mechanosensitive TRP channels in cardiovascular pathophysiology. Pharmacology and Therapeutics 123:371–385

    Google Scholar 

  195. Yin J, Kuebler WM (2010) Mechanotransduction by TRP channels: general concepts and specific role in the vasculature. Cell Biochemistry and Biophysics 56:1–18

    Google Scholar 

  196. Baumgarten CM (2007) Origin of Mechanotransduction: Stretch-Activated Ion Channels (Chap. 2) In Weckstrom M, Tavi P (eds.) Cardiac Mechanotransduction. Landes Bioscience, Austin, Texas, and Springer, New York

    Google Scholar 

  197. Coste B, Xiao B, Santos JS, Syeda R, Grandl J, Spencer KS, Kim SE, Schmidt M, Mathur J, Dubin AE, Montal M, Patapoutian A (2012) Piezo proteins are pore-forming subunits of mechanically activated channels. Nature 483:176–181

    ADS  Google Scholar 

  198. Hill MA, Trippe KM, Li QX, Meininger GA (1992) Arteriolar arcades and pressure distribution in cremaster muscle microcirculation. Microvascular Research 44:117–124

    Google Scholar 

  199. Chlopicki S, Nilsson H, Mulvany MJ (2001) Initial and sustained phases of myogenic response of rat mesenteric small arteries. American Journal of Physiology – Heart and Circulatory Physiology 281:H2176–H2183

    Google Scholar 

  200. Zou H, Ratz PH, Hill MA (2000) Temporal aspects of Ca 2+ and myosin phosphorylation during myogenic and norepinephrine-induced arteriolar constriction. Journal of Vascular Research 37:556–567

    Google Scholar 

  201. Bolz SS, Vogel L, Sollinger D, Derwand R, Boer C, Pitson SM, Spiegel S, and Pohl U (2003) Sphingosine kinase modulates microvascular tone and myogenic responses through activation of RhoA/Rho kinase. Circulation 108:342–347

    Google Scholar 

  202. Yeon DS, Kim JS, Ahn DS, Kwon SC, Kang BS, Morgan KG, Lee YH (2002) Role of protein kinase C- or RhoA-induced Ca 2+ sensitization in stretch-induced myogenic tone. Cardiovascular Research 53:431–438

    Google Scholar 

  203. Frisbee JC, Roman RJ, Krishna UM, Falck JR, Lombard JH (2001) 20-HETE modulates myogenic response of skeletal muscle resistance arteries from hypertensive Dahl-SS rats. American Journal of Physiology – Heart and Circulatory Physiology 280:H1066–H1074

    Google Scholar 

  204. Obara K, Koide M, Nakayama K (2002) 20-Hydroxyeicosatetraenoic acid potentiates stretch-induced contraction of canine basilar artery via PKC alpha-mediated inhibition of KCa channel. British Journal of Pharmacology 137:1362–1370

    Google Scholar 

  205. Martinez-Lemus LA, Wu X, Wilson E, Hill MA, Davis GE, Davis MJ, Meininger GA (2003) Integrins as unique receptors for vascular control. Journal of Vascular Research 40:211–233

    Google Scholar 

  206. Sun Z, Martinez-Lemus LA, Trache A, Trzeciakowski JP, Davis GE, Pohl U, Meininger GA (2005) Mechanical properties of the interaction between fibronectin and α5β1-integrin on vascular smooth muscle cells studied using atomic force microscopy. American Journal of Physiology – Heart and Circulatory Physiology 289:H2526–H2535

    Google Scholar 

  207. Martinez-Lemus LA, Crow T, Davis MJ, Meininger GA (2005) αVβ3- and α5β1-integrin blockade inhibits myogenic constriction of skeletal muscle resistance arterioles. American Journal of Physiology – Heart and Circulatory Physiology 289:H322–H329

    Google Scholar 

  208. Hong Z, Sun Z, Li Z, Mesquitta WT, Trzeciakowski JP, Meininger GA (2012) Coordination of fibronectin adhesion with contraction and relaxation in microvascular smooth muscle. Cardiovascular Research 96:73–80

    Google Scholar 

  209. Schmid-Schönbein GW (2012) The integrin–cortex complex under control of GPCRs. Cardiovascular Research 96:7–8

    Google Scholar 

  210. Nelson MT, Cheng H, Rubart M, Santana LF, Bonev AD, Knot HJ, Lederer WJ (1995) Relaxation of arterial smooth muscle by calcium sparks. Science 270:633–637

    ADS  Google Scholar 

  211. Bagher P, Beleznai T, Kansui Y, Mitchell R, Garland CJ, Dora KA (2012) Low intravascular pressure activates endothelial cell TRPV4 channels, local Ca 2+ events, and IKCa channels, reducing arteriolar tone. Proceedings of the National Academy of Sciences of the United States of America 109:18174–18179

    ADS  Google Scholar 

  212. Harder DR, Roman RJ, Gebremedhin D, Birks EK, Lange AR (1998) A common pathway for regulation of nutritive blood flow to the brain: arterial muscle membrane potential and cytochrome P450 metabolites. Acta Physiologica Scandinavica 164:527–532

    Google Scholar 

  213. Fischell TA, Bausback KN, McDonald TV (1990) Evidence for altered epicardial coronary artery autoregulation as a cause of distal coronary vasoconstriction after successful percutaneous transluminal coronary angioplasty. Journal of Clinical Investigation 86:575–584

    Google Scholar 

  214. Davis MJ, Hill MA (1999) Signaling mechanisms underlying the vascular myogenic response. Physiological Reviews 79:387–423

    Google Scholar 

  215. Mederos y Schnitzler M, Storch U, Meibers S, Nurwakagari P, Breit A, Essin K, Gollasch M, Gudermann T (2008) Gq-coupled receptors as mechanosensors mediating myogenic vasoconstriction. EMBO Journal 27:3092–3103

    Google Scholar 

  216. Zou Y, Akazawa H, Qin Y, Sano M, Takano H, Minamino T, Makita N, Iwanaga K, Zhu W, Kudoh S, Toko H, Tamura K, Kihara M, Nagai T, Fukamizu A, Umemura S, Iiri T, Fujita T, Komuro I (2004) Mechanical stress activates angiotensin II type 1 receptor without the involvement of angiotensin II. Nature – Cell Biology 6:499–506

    Google Scholar 

  217. Hofmann T, Obukhov AG, Schaefer M, Harteneck C, Gudermann T, Schultz G (1999) Direct activation of human TRPC6 and TRPC3 channels by diacylglycerol. Nature 397:259–263

    ADS  Google Scholar 

  218. Nilius B, Owsianik G, Voets T, Peters JA (2007) Transient receptor potential cation channels in disease. Physiological Reviews 87:165–217

    Google Scholar 

  219. Sriram K, Salazar Vázquez BY, Tsai AG, Cabrales P, Intaglietta M, Tartakovsky DM (2012) Autoregulation and mechanotransduction control the arteriolar response to small changes in hematocrit. American Journal of Physiology – Heart and Circulatory Physiology 303:H1096–H1106

    Google Scholar 

  220. Chu C, Thai K, Park KW, Wang P, Makwana O, Lovett DH, Simpson PC, Baker AJ (2013) Intraventricular and interventricular cellular heterogeneity of inotropic responses to α1-adrenergic stimulation. American Journal of Physiology – Heart and Circulatory Physiology 304:H946–H953

    Google Scholar 

  221. Guyenet PG (2006) The sympathetic control of blood pressure. Nature Reviews – Neuroscience 7:335–346

    Google Scholar 

  222. Pyke KE, Poitras V, Tschakovsky ME (2008) Brachial artery flow-mediated dilation during handgrip exercise: evidence for endothelial transduction of the mean shear stimulus. American Journal of Physiology – Heart and Circulatory Physiology 294:H2669–H2679

    Google Scholar 

  223. Green DJ, Bilsborough W, Naylor LH, Reed C, Wright J, O’Driscoll G, Walsh JH (2005) Comparison of forearm blood flow responses to incremental handgrip and cycle ergometer exercise: relative contribution of nitric oxide. Journal of Physiology 562:617–628

    Google Scholar 

  224. Guo ZL, Tjen-A-Looi SC, Fu LW, Longhurst JC (2009) Nitric oxide in rostral ventrolateral medulla regulates cardiac-sympathetic reflexes: role of synthase isoforms. American Journal of Physiology – Heart and Circulatory Physiology 297:H1478–H1486

    Google Scholar 

  225. Izumi H, Karita K (1994) The parasympathetic vasodilator fibers in the trigeminal portion of the distal lingual nerve in the cat tongue. American Journal of Physiology 266:R1517–R1522

    Google Scholar 

  226. Oakley AE, Clifton DK, Steiner RA (2009) Kisspeptin signaling in the brain. Endocrine Reviews 30:713–743

    Google Scholar 

  227. Rometo AM, Rance NE (2008) Changes in prodynorphin gene expression and neuronal morphology in the hypothalamus of postmenopausal women. Journal of Neuroendocrinology 20:1376–1381

    Google Scholar 

  228. Mittelman-Smith MA, Williams H, Krajewski-Hall SJ, McMullen NT, Rance NE (2012) Role for kisspeptin/neurokinin B/dynorphin (KNDy) neurons in cutaneous vasodilatation and the estrogen modulation of body temperature. Proceedings of the National Academy of Sciences of the United States of America 109:19846–19851

    ADS  Google Scholar 

  229. Ieda M, Kanazawa H, Kimura K, Hattori F, Ieda Y, Taniguchi M, Lee JK, Matsumura K, Tomita Y, Miyoshi S, Shimoda K, Makino S, Sano M, Kodama I, Ogawa S, Fukuda K (2007) Sema3a maintains normal heart rhythm through sympathetic innervation patterning. Nature – Medicine 13:604–612

    Google Scholar 

  230. Fu LW, Guo ZL, Longhurst JC (2012) Ionotropic glutamate receptors in the external lateral parabrachial nucleus participate in processing cardiac sympathoexcitatory reflexes. American Journal of Physiology – Heart and Circulatory Physiology 302:H1444–H1453

    Google Scholar 

  231. Koba S, Gao Z, Xing J, Sinoway LI, Li J (2006) Sympathetic responses to exercise in myocardial infarction rats: a role of central command. American Journal of Physiology – Heart and Circulatory Physiology 291, H2735-H2742

    Google Scholar 

  232. Sin PY, Galletly DC, Tzeng YC (2010) Influence of breathing frequency on the pattern of respiratory sinus arrhythmia and blood pressure: old questions revisited. American Journal of Physiology – Heart and Circulatory Physiology 298:H1588–H1599

    Google Scholar 

  233. Blain G, Meste O, Blain A, Bermon S (2009) Time-frequency analysis of heart rate variability reveals cardiolocomotor coupling during dynamic cycling exercise in humans. American Journal of Physiology-Heart and Circulatory Physiology 296:H1651-H1659

    Google Scholar 

  234. Aletti F, Bassani T, Lucini D, Pagani M, Baselli G (2009) Multivariate decomposition of arterial blood pressure variability for the assessment of arterial control of circulation. IEEE Transactions on Biomedical Engineering 56:1781–1790

    Google Scholar 

  235. Kamiya A, Kawada T, Mizuno M, Shimizu S, Sugimachi M (2010) Parallel resetting of arterial baroreflex control of renal and cardiac sympathetic nerve activities during upright tilt in rabbits. American Journal of Physiology – Heart and Circulatory Physiology 298:H1966–H1975

    Google Scholar 

  236. Tigerstedt R, Bergman P (1898) Niere und Kreislauf [Kidney and circulation]. Skandinavisches Archiv für Physiologie 8:223–271

    Google Scholar 

  237. James PF, Grupp IL, Grupp G, Woo AL, Askew GR, Croyle ML, Walsh RA, Lingrel JB (1999) Identification of a specific role for the Na,K-ATPase α2 isoform as a regulator of calcium in the heart. Molecular Cell 3:555–563

    Google Scholar 

  238. Blaustein MP, Leenen FH, Chen L, Golovina VA, Hamlyn JM, Pallone TL, Van Huysse JW, Zhang J, Wier WG (2012) How NaCl raises blood pressure: a new paradigm for the pathogenesis of salt-dependent hypertension. American Journal of Physiology – Heart and Circulatory Physiology 302:H1031–H1049

    Google Scholar 

  239. Gao J, Wymore RS, Wang Y, Gaudette GR, Krukenkamp IB, Cohen IS, Mathias RT (2002) Isoform-specific stimulation of cardiac Na/K pumps by nanomolar concentrations of glycosides. Journal of General Physiology 119:297–312

    Google Scholar 

  240. Crowley SD, Gurley SB, Herrera MJ, Ruiz P, Griffiths R, Kumar AP, Kim HS, Smithies O, Le TH, Coffman TM (2006) Angiotensin II causes hypertension and cardiac hypertrophy through its receptors in the kidney. Proceedings of the National Academy of Sciences of the United States of America 103:17985–17990

    ADS  Google Scholar 

  241. Machnik A, Neuhofer W, Jantsch J, Dahlmann A, Tammela T, Machura K, Park JK, Beck FX, Müller DN, Derer W, Goss J, Ziomber A, Dietsch P, Wagner H, van Rooijen N, Kurtz A, Hilgers KF, Alitalo K, Eckardt KU, Luft FC, Kerjaschki D, Titze J (2009) Macrophages regulate salt-dependent volume and blood pressure by a vascular endothelial growth factor-C-dependent buffering mechanism. Nature – Medicine 15:545–552

    Google Scholar 

  242. Smith OA, Astley CA, Spelman FA, Golanov EV, Bowden DM, Chesney MA, Chalyan V (2000) Cardiovascular responses in anticipation of changes in posture and locomotion. Brain Research Bulletin 53:69–76

    Google Scholar 

  243. Taylor JA, Eckberg DL (1996) Fundamental relations between short-term RR interval and arterial pressure oscillations in humans. Circulation 93:1527–1532

    Google Scholar 

  244. Zhang R, Khoo MSC, Wu Y, Yang Y, Grueter CE, Ni G, Price EE, Thiel W, Guatimosim S, Song LS, Madu EC, Shah AN, Vishnivetskaya TA, Atkinson JB, Gurevich VV, Salama G, Lederer WJ, Colbran RJ, Anderson ME (2005) Calmodulin kinase II inhibition protects against structural heart disease. Nature – Medicine 11:409–417

    Google Scholar 

  245. Goyal RK (1989) Muscarinic receptor subtypes: physiology and clinical implications. New England Journal of Medicine 321:1022–1029

    Google Scholar 

  246. Lymperopoulos A, Rengo G, Funakoshi H, Eckhart AE, Koch WJ (2007) Adrenal GRK2 upregulation mediates sympathetic overdrive in heart failure. Nature – Medicine 13:315–323

    Google Scholar 

  247. Monti A, Mdigue C, Sorine M (2002) Short-term modelling of the controlled cardiovascular system. ESAIM: Proceedings 12:115–128

    MATH  Google Scholar 

  248. Hammer PE, Saul JP (2005) Resonance in a mathematical model of baroreflex control: arterial blood pressure waves accompanying postural stress. American Journal of Physiology – Regulatory, Integrative and Comparative Physiology 288:R1637–R1648.

    Google Scholar 

  249. Degtyarenko AM, Kaufman MP (2005) MLR-induced inhibition of barosensory cells in the NTS. American Journal of Physiology – Heart and Circulatory Physiology 289:H2575–H2584

    Google Scholar 

  250. Ulrich-Lai1 YM, Herman JP (2009) Neural regulation of endocrine and autonomic stress responses. Nature Reviews – Neuroscience 10:397–409

    Google Scholar 

  251. Joëls M, Baram TZ (2009) The neuro-symphony of stress. Nature Reviews – Neuroscience 10:459–466

    Google Scholar 

  252. Watts SW, Morrison SF, Davis RP, Barman SM (2012) Serotonin and blood pressure regulation. Pharmacological Reviews 64:359–388

    Google Scholar 

  253. Ramage AG, Villalón CM (2008) 5-hydroxytryptamine and cardiovascular regulation. Trends in Pharmacological Sciences 29:472–481

    Google Scholar 

  254. Kurbel S, Dodig K, Radic R (2002) The osmotic gradient in kidney medulla: a retold story. Advances in Physiology Education 26:278–281

    Google Scholar 

  255. Lombes M, Farman N, Oblin ME, Baulieu EE, Bonvalet JP, Erlanger BF, Gasc J (1990) Immunohistochemical localization of renal mineralocorticoid receptor by using an anti-idiotypic antibody that is an internal image of aldosterone. Proceedings of the National Academy of Sciences of the United States of America 87:1086–1088

    ADS  Google Scholar 

  256. Sasano H, Fukushima K, Sasaki I, Matsuno S, Nagura H, Krozowski ZS (1992) Immunolocalization of mineralocorticoid receptor in human kidney, pancreas, salivary, mammary and sweat glands: a light and electron microscopic immunohistochemical study. Journal of Endocrinology 132:305–310

    Google Scholar 

  257. Cantin M, Genest J (1986) Le cœur est une glande endocrine [The heart is an endocrine gland]. Pour la Science 102:43–49

    Google Scholar 

  258. Kondoh G, Tojo H, Nakatani N, N Komazawa, Murata C, Yamagata K, Maeda Y, Kinoshita T, Okabe M, Taguchi R, Takeda J (2005) Angiotensin-converting enzyme is a GPI-anchored protein releasing factor crucial for fertilization. Nature – Medicine 11:160–166

    Google Scholar 

  259. Lalioti MD, Zhang J, Volkman HM, Kahle KT, Hoffmann KE, Toka HR, Nelson-Williams C, Ellison DE, Flavell R, Booth CJ, Lu Y, Geller DS, Lifton RP (2006) Wnk4 controls blood pressure and potassium homeostasis via regulation of mass and activity of the distal convoluted tubule. Nature – Genetics 38:1124–1132

    Google Scholar 

  260. Coffman TM (2006) A WNK in the kidney controls blood pressure. Nature – Genetics 38:1105–1106

    Google Scholar 

  261. Jentsch TJ, Hbner CA, Fuhrmann JC (2004) Ion channels: Function unravelled by dysfunction. Nature – Cell Biology 6:1039–1047 (2004)

    Google Scholar 

  262. Oberleithner H, Riethmller C, Schillers H, MacGregor GH, de Wardener HE, Hausberg M (2007) Plasma sodium stiffens vascular endothelium and reduces nitric oxide release. Proceedings of the National Academy of Sciences of the United States of America 104:16281–16286

    ADS  Google Scholar 

  263. de Kloet AD, Krause EG, Scott KA, Foster MT, Herman JP, Sakai RR, Seeley RJ, Woods SC (2011) Central angiotensin II has catabolic action at white and brown adipose tissue. American Journal of Physiology – Endocrinology and Metabolism 301:E1081–E1091

    Google Scholar 

  264. Yoshida T, Semprun-Prieto L, Wainford RD, Sukhanov S, Kapusta DR, Delafontaine P (2012) Angiotensin II reduces food intake by altering orexigenic neuropeptide expression in the mouse hypothalamus. Endocrinology 153:1411–1420

    Google Scholar 

  265. Grobe JL, Grobe CL, Beltz TG, Westphal SG, Morgan DA, Xu D, de Lange WJ, Li H, Sakai K, Thedens DR, Cassis LA, Rahmouni K, Mark AL, Johnson AK, Sigmund CD (2010) The brain renin-angiotensin system controls divergent efferent mechanisms to regulate fluid and energy balance. Cell Metabolism 12:431–442

    Google Scholar 

  266. Hilzendeger AM, Morgan DA, Brooks L, Dellsperger D, Liu X, Grobe JL, Rahmouni K, Sigmund CD, Mark AL (2012) A brain leptin–renin–angiotensin system interaction in the regulation of sympathetic nerve activity. American Journal of Physiology – Heart and Circulatory Physiology 303:H197–H206

    Google Scholar 

  267. Bełtowski J (2012) Leptin and the regulation of endothelial function in physiological and pathological conditions. Clinical and Experimental Pharmacology and Physiology 39: 168–178

    Google Scholar 

  268. Benkhoff S, Loot AE, Pierson I, Sturza A, Kohlstedt K, Fleming I, Shimokawa H, Grisk O, Brandes RP, Schröder K (2012) Leptin potentiates endothelium-dependent relaxation by inducing endothelial expression of neuronal NO synthase. Arteriosclerosis, Thrombosis, and Vascular Biology 32:1605–1612

    Google Scholar 

  269. Abboud FM, Floras JS, Aylward PE, Guo GB, Gupta BN, Schmid PG. Role of vasopressin in cardiovascular and blood pressure regulation. Blood Vessels 27:106–115

    Google Scholar 

  270. Koshimizu TA, Nasa Y, Tanoue A, Oikawa R, Kawahara Y, Kiyono Y, Adachi T, Tanaka T, Kuwaki T, Mori T, Takeo S, Okamura H, Tsujimoto G (2006) V1a vasopressin receptors maintain normal blood pressure by regulating circulating blood volume and baroreflex sensitivity. Proceedings of the National Academy of Sciences of the United States of America 103:7807–7812

    ADS  Google Scholar 

  271. Chassin C, Hornef MW, Bens M, Lotz M, Goujon JM, Vimont S, Arlet G, Hertig A, Rondeau E, Vandewalle A (2007) Hormonal control of the renal immune response and antibacterial host defense by arginine vasopressin. Journal of Experimental Medicine 204:2837–2852

    Google Scholar 

  272. Knepper MA, Star RA (2008) Vasopressin: friend or foe? Nature – Medicine 14:14–16

    Google Scholar 

  273. de Bold AJ (1985) Atrial natriuretic factor: a hormone produced by the heart. Science 230:767–770

    ADS  Google Scholar 

  274. Tsujita Y, Muraski J, Shiraishi I, Kato T, Kajstura J, Anversa P, Sussman MA (2006) Nuclear targeting of Akt antagonizes aspects of cardiomyocyte hypertrophy. Proceedings of the National Academy of Sciences of the United States of America 103:11946-11951

    ADS  Google Scholar 

  275. Suga SI, Itoh H, Komatsu Y, Ishida H, Igaki T, Yamashita J, Doi K, Chun TH, Yoshimasa T, Tanaka I, Nakao K (1998) Regulation of endothelial production of C-type natriuretic peptide by interaction between endothelial cells and macrophages. Endocrinology 139:1920–1926

    Google Scholar 

  276. Vesely BA, Eichelbaum EJ, Alli AA, Sun Y, Gower WR, Vesely DL (2006) Urodilatin and four cardiac hormones decrease human renal carcinoma cell numbers. European Journal of Clinical Investigation 36:810–819

    Google Scholar 

  277. Callaghan B, Hunne B, Hirayama H, Sartor DM, Nguyen TV, Abogadie FC, Ferens D, McIntyre P, Ban K, Baell J, Furness JB, Brock JA (2012) Sites of action of ghrelin receptor ligands in cardiovascular control. American Journal of Physiology – Heart and Circulatory Physiology 303:H1011–H1021

    Google Scholar 

  278. Hökfelt T, Lundberg JM, Schultzberg M, Johansson O, Skirboll L, Anggård A, Fredholm B, Hamberger B, Pernow B, Rehfeld J, Goldstein M (1980) Cellular localization of peptides in neural structures. Proceedings of the Royal Society of London. Series B, Biological Sciences 210:63–77

    Google Scholar 

  279. Sartor DM, Verberne AJ (2008) Abdominal vagal signalling: a novel role for cholecystokinin in circulatory control? Brain Research Reviews 59:140–154

    Google Scholar 

  280. Mahapatra NR (2008) Catestatin is a novel endogenous peptide that regulates cardiac function and blood pressure. Cardiovascular Research 80:330–338

    Google Scholar 

Chap. 4. Physiology of the Ventilation

  1. Bernard C (1966) Introduction à l’étude de médecine expérimentale [Introduction to the Study of Experimental Medicine]. Garnier – Flammarion, Paris

    Google Scholar 

  2. Dejours P (1981) Principles of Comparative Respiratory Physiology, Elsevier and North-Holland Biomedical Press, Amsterdam and New York

    Google Scholar 

  3. Atkins PW, de Paula J (2002) Physical Chemistry (7th Edition). Freeman WH, New York

    Google Scholar 

  4. Thiriet M, Douguet D, Bonnet JC, Canonne C, Hatzfeld C (1979) Influence du mélange He–O2 sur la mixique dans les bronchopneumopathies obstructives chroniques [Influence of a He–O2 mixture on gas mixing in chronic obstructive lung diseases]. Bulletin Européen de Physiopathologie Respiratoire 15:1053–1068

    Google Scholar 

  5. Cantor CR, Schimmel PR (1980) Biophysical Chemistry, Part 2: Techniques for the Study of Biological Structure and Function. Freeman WH, New York

    Google Scholar 

  6. Anonymous authors (2000-2013) Diffusion Time Calculator(www.physiologyweb.com)

  7. Keener JP (2013) Mathematical Biology (www.math.utah.edu/keener/classes/math5120)

  8. Mircea D, Panaitescu M (2013) Green Pack Online: Environmental Components – Air composition. The Regional Environmental Center for Central and Eastern Europe www.greenpackonline.org/english/environmental-components.php?id=01-01

  9. Holt PG, Strickland DH, Wikström ME, Jahnse FL (2008) Regulation of immunological homeostasis in the respiratory tract. Nature Reviews – Immunology 8:142-152

    Google Scholar 

  10. Salathe M (2007) Regulation of mammalian ciliary beating. Annual Review of Physiology 69:401–422

    Google Scholar 

  11. Ingber DE (2006) Cellular mechanotransduction: putting all the pieces together again. FASEB Journal 20:811–827

    Google Scholar 

  12. Wright JL, Thurlbeck WM (2005) Quantitative Anatomy of the Lung. In: Churg AM, Myers JL, Tazelaar HD, Wright JL (eds), Thurlbeck’s Pathology of the Lung, third edition, Thieme, New York

    Google Scholar 

  13. Hart MC, Orzalesi MM, Cook CD (1963) Relation between anatomic respiratory dead space and body size and lung volume. Journal of Applied Physiology 18:519–522

    Google Scholar 

  14. Rafferty GF, Gardner WN (1996) Control of the respiratory cycle in conscious humans. Journal of Applied Physiology 81:1744–1753

    Google Scholar 

  15. Rafferty GF, Gardner WN (1995) Interaction between expiratory time and inspiration in conscious humans. Biological Psychology 41:96–97

    Google Scholar 

  16. Israël-Asselain R, Pocidalo JJ (1971) Respiration et maladies respiratoires. [Respiration and respiratory diseases]. In Vallery-Radot P, Hamburger J, Lhermitte F (eds.) Pathologie Mdicale. [Medical Pathology] (Vol.2), Flammarion Médecine Sciences, Paris

    Google Scholar 

  17. Fenn WO, Rahn H, and Otis AB (1946) A theoretical study of the composition of the alveolar air at altitude. American Journal of Physiology 146:637-653

    Google Scholar 

  18. Riley RL, Cournand A (1949) ”Ideal” alveolar air and the analysis of ventilation-perfusion relationships in the lungs. Journal of Applied Physiology 1:825–847

    Google Scholar 

  19. West JB, Dollery CT (1960) Distribution of blood flow and ventilation-perfusion ratio in the lung, measured with radioactive carbon dioxide. Journal of Applied Physiology 15:405–410

    Google Scholar 

  20. West JB (1970) Ventilation/Blood Flow and Gas Exchange. Blackwell, Oxford

    Google Scholar 

  21. Bates DV, Christie RV (1964) Respiratory Function in Disease, WB Saunders, Philadelphia

    Google Scholar 

  22. Brudin LH, Rhodes CG, Valind SO, Jones T, Hughes JM (1994) Interrelationships between regional blood flow, blood volume, and ventilation in supine humans. Journal of Applied Physiology 76:1205–1210

    Google Scholar 

  23. Wasserman DH, Whipp BJ (1983) Coupling of ventilation to pulmonary gas exchange during nonsteady-state work in men. Journal of Applied Physiology 54:587-593

    Google Scholar 

  24. Haouzi P (2006) Theories on the nature of the coupling between ventilation and gas exchange during exercise. Respiratory Physiology and Neurobiology 151:267–279

    Google Scholar 

  25. Altman PL, Dittmer DS [eds.] (1971) Biological Handbooks: Respiration and Circulation, Federation of American Societies for Experimental Biology, Bethesda, MD

    Google Scholar 

  26. Driehuys B, Cofer GP, Pollaro J, Mackel JB, Hedlund LW, Johnson GA (2006) Imaging alveolar-capillary gas transfer using hyperpolarized 129Xe MRI. Proceedings of the National Academy of Sciences of the United States of America 103:18278–18283

    ADS  Google Scholar 

  27. Kruhoffer P (1954) Lung diffusion coefficient for CO in normal human subjects by means of C14O. Acta Physiollogica Scandinavica 32:106–123.

    Google Scholar 

  28. Roughton FJW, Forster RE (1957) Relative importance of diffusion and chemical reaction in determining rate of exchange of gases in the human lung. Journal of Applied Physiology 11:290–302

    Google Scholar 

  29. Tartullier M, Ritz B, Ferrini M (1982) Physiologie de la Circulation Pulmonaire [Pulmonary Circulation Physiology]. In Denolin H (ed.) Physio-Pathologie Cardio-Pulmonaire [Cardiopulmonary Pathophysiology], SIMEP, Villeurbanne, France

    Google Scholar 

  30. Hartridge H, Roughton FJW (1923) Measurement of the rates of oxidation and reduction of haemoglobin. Nature 111:325–326

    ADS  Google Scholar 

  31. Hartridge H, Roughton FJW (1923) Method of measuring the velocity of very rapid chemical reactions. Proceedings of the Royal Society London Series A 104:376–394

    ADS  Google Scholar 

  32. Millikan GAA (1933) A simple photoelectric calorimeter. Journal of Physiology, London 79:158–179

    Google Scholar 

  33. Even P (1983) La respiration (p. 1087–1358). In Physiologie humaine, Meyer P (ed), Flammarion Médecine–Sciences, Paris

    Google Scholar 

  34. Yuan G, Peng YJ, Reddy VD, Makarenko VV, Nanduri J, Khan SA, Garcia JA, Kumar GK, Semenza GL, Prabhakar NR (2013) Mutual antagonism between hypoxia-inducible factors 1α and 2α regulates oxygen sensing and cardio-respiratory homeostasis. Proceedings of the National Academy of Sciences of the United States of America 110:E1788–E1796

    ADS  Google Scholar 

  35. Henderson LJ (1908) Concerning the relationship between the strength of acids and their capacity to preserve neutrality. American Journal of Physiology 21:173–179

    Google Scholar 

  36. Paton JFR, Abdala APL, Koizumi H, Smith JC, St-John WM (2006) Respiratory rhythm generation during gasping depends on persistent sodium current. Nature – Neuroscience 9:311–313

    Google Scholar 

  37. Feldman JL, Del Negro CA (2006) Looking for inspiration: new perspectives on respiratory rhythm. Nature Reviews – Neuroscience 7:232–241

    Google Scholar 

  38. Feldman JL, Kam K, Janczewski WA (2009) Practice makes perfect, even for breathing. Nature – Neuroscience 12:961 - 963

    Google Scholar 

  39. Tan W, Janczewski WA, Yang P, Shao XS, Callaway EM, Feldman JL (2008) Silencing preBötzinger complex somatostatin-expressing neurons induces persistent apnea in awake rat. Nature – Neuroscience 11:538–540

    Google Scholar 

  40. Bouvier J, Thoby-Brisson M, Renier N, Dubreuil V, Ericson J, Champagnat J, Pierani A, Chdotal A, Fortin G (2010) Hindbrain interneurons and axon guidance signaling critical for breathing. Nature – Neuroscience 13:1066–1074

    Google Scholar 

  41. Thoby-Brisson M, Karlén M, Wu N, Charnay P, Champagnat J, Fortin G (2009) Genetic identification of an embryonic parafacial oscillator coupling to the preBötzinger complex. Nature – Neuroscience 12:1028–1035

    Google Scholar 

  42. Gibson GG, Skett P (2001) Introduction to Drug Metabolism, Nelson Thornes Publishers, Cheltenham, UK

    Google Scholar 

  43. Capron M, Capron A, Goetzl EJ, Austen KF (1981) Tetrapeptides of the eosinophil chemotactic factor of anaphylaxis (ECF-A) enhance eosinophil Fc receptor. Nature 289:71–73

    ADS  Google Scholar 

  44. Sirois P, Borgeat P (1982) Leukotrienes: a new approach to the biochemistry of hypersensitivity. Survey of Immunologic Research l:279–285

    Google Scholar 

  45. Morris HR, Taylor GW, Jones CM, Scully N, Piper PJ, Tippins JR, Samhoun MN (1981) Structure elucidation and biosynthesis of slow reacting substances and slow reacting substance of anaphylaxis from guinea pig and human lungs. Progress in Lipid Research 20:719–725

    Google Scholar 

  46. Piper PJ (1978) Slow reacting substance of anaphylaxis. Annals of the Royal College of Surgeons of England 60:201–204

    Google Scholar 

  47. Gao X, Vockley CM, Pauli F, Newberry KM, Xue Y, Randell SH, Reddy TE, Hogan BL (2013) Evidence for multiple roles for grainyheadlike 2 in the establishment and maintenance of human mucociliary airway epithelium. Proceedings of the National Academy of Sciences of the United States of America 110:9356–9361

    ADS  Google Scholar 

  48. Guttinger M, Sutti F, Panigada M, Porcellini S, Merati B, Mariani M, Teesalu T, Consalez GG, Grassi F (1998) Epithelial V-like antigen (EVA), a novel member of the immunoglobulin superfamily, expressed in embryonic epithelia with a potential role as homotypic adhesion molecule in thymus histogenesis. Journal of Cell Biology 141:1061–1071

    Google Scholar 

  49. Wojcik E, Carrithers LM, Carrithers MD (2011) Characterization of epithelial V-like antigen in human choroid plexus epithelial cells: potential role in CNS immune surveillance. Neuroscience Letters 495:115–120

    Google Scholar 

  50. Yang CF, Hwu WL, Yang LC, Chung WH, Chien YH, Hung CF, Chen HC, Tsai PJ, Fann CS, Liao F, Chen YT (2008) A promoter sequence variant of ZNF750 is linked with familial psoriasis. Journal of Investigative Dermatology 128:1662–1668

    Google Scholar 

  51. Chung C, Kim T, Kim M, Kim M, Song H, Kim TS, Seo E, Lee SH, Kim H, Kim SK, Yoo G, Lee DH, Hwang DS, Kinashi T, Kim JM, Lim DS (2013) Hippo-Foxa2 signaling pathway plays a role in peripheral lung maturation and surfactant homeostasis. Proceedings of the National Academy of Sciences of the United States of America 110:7732–7737

    ADS  Google Scholar 

Chap. 5. Medical Images and Physiological Signals

  1. Bachelard G (1934) Le nouvel esprit scientifique [The New Scientific Spirit]. Presses Universitaires de France, Paris

    Google Scholar 

  2. Cebral JR, Löhner R (2001) From medical images to anatomically accurate finite element grids. International Journal for Numerical Methods in Engineering 51:985–1008

    ADS  MATH  Google Scholar 

  3. Thiriet M, Brugières P, Bittoun J, Gaston A (2001) Computational flow models in cerebral congenital aneurisms I: Steady flow. Revue Mcanique et Industries 2:107–118

    Google Scholar 

  4. Salmon S, Thiriet M, Gerbeau J-F (2003) Medical image-based computational model of pulsatile flow in saccular aneurisms. Mathematical Modelling and Numerical Analysis 37:663–679

    MathSciNet  MATH  Google Scholar 

  5. Milner JS, Moore JA, Rutt BK, Steinman DA (1998) Hemodynamics of human carotid artery bifurcations: computational studies with models reconstructed from magnetic resonance imaging of normal subjects. Journal of Vascular Surgery 1998:143–156

    Google Scholar 

  6. Moore JA, Rutt BK, Karlik SJ, Yin K, Ethier CR (1999) Computational blood flow modeling based on in vivo measurements. Annals of Biomedical Engineering 27:627–640

    Google Scholar 

  7. Ladak HM, Milner JS, Steinman, DA (2000) Rapid 3D segmentation of the carotid bifurcation from serial MR images. Journal of Biomechanical Engineering 122:96–99

    Google Scholar 

  8. Papaharilaou Y, Doorly DJ, Sherwin SJ, Peiró J, Griffith C, Chesire N, Zervas V, Anderson J, Sanghera B, Watkins N, Caro CG (2002) Combined MRI and computational fluid dynamics detailed investigation of flow in idealised and realistic arterial bypass graft models. Biorheology 39:525–532

    Google Scholar 

  9. Gill JD, Ladak HM, Steinman DA, Fenster A (2000) Accuracy and variability assessment of a semiautomatic technique for segmentation of the carotid arteries from 3D ultrasound images. Medical Physics 27:1333–1342

    ADS  Google Scholar 

  10. de Feyter PJ (2012) CT functional imaging using intracoronary gradient analysis: an indispensable boost for CT coronary angiography. European Heart Journal – Cardiovasc Imaging 13:971–972

    Google Scholar 

  11. Choi JH, Koo BK, Yoon YE, Min JK, Song YB, Hahn JY, Choi SH, Gwon HC, Choe YH (2012) Diagnostic performance of intracoronary gradient-based methods by coronary computed tomography angiography for the evaluation of physiologically significant coronary artery stenoses: a validation study with fractional flow reserve. European Heart Journal – Cardiovasc Imaging 13:1001–1007

    Google Scholar 

  12. Thiriet M, Maarek JM, Chartrand DA, Delpuech C, Davis L, Hatzfeld C, Chang HK (1989) Transverse images of the human thoracic trachea during forced expiration. Journal of Applied Physiology 67:1032–1040

    Google Scholar 

  13. Bachelard G (1940) La philosophie du non: essai d’une philosophie du nouvel esprit scientifique [The Philosophy of No: a Philosophy of the New Scientific Mind]. Presses Universitaires de France, Paris

    Google Scholar 

  14. Bittoun J (1998) Basic principles of magnetic resonance imaging. In: Cerdan S, Haase A, Terrier F (eds.) Spectroscopy and Clinical MRI. Springer, New York

    Google Scholar 

  15. Singer JR (1959) Blood flow rates by nuclear magnetic resonance measurements. Science 130:1652–1653

    ADS  Google Scholar 

  16. McCready VR, Leach M, Ell PJ (1987) Functional Studies Using NMR. Springer, New York

    Google Scholar 

  17. Zerhouni EA, Parish DM, Rogers WJ, Yang A, Shapiro EP (1988) Human heart: tagging with MR imaging – a method for noninvasive assessment of myocardial motion. Radiology 169:59–63

    Google Scholar 

  18. Axel L, Dougherty L (1989) Heart wall motion: improved method of spatial modulation of magnetization for MR imaging. Radiology, 172:349–350

    Google Scholar 

  19. Mosher TJ, Smith MB (1990) A DANTE tagging sequence for the evaluation of translational sample motion. Magnetic Resonance in Medicine 15:334–339

    Google Scholar 

  20. Fischer SE, McKinnon GC, Maier SE, Boesiger P (1993) Improved myocardial tagging contrast. Magnetic Resonance in Medicine 30:191–200

    Google Scholar 

  21. McVeigh ER (1996) MRI of myocardial function: motion tracking techniques. Magnetic Resonance Imaging 14:137-150

    Google Scholar 

  22. Basser PJ, Mattiello J, LeBihan D (1994) MR diffusion tensor spectroscopy and imaging. Biophysical Journal 66:259–267

    ADS  Google Scholar 

  23. Hsu EW, Muzikant AL, Matulevicius SA, Penland RC, Henriquez CS (1998) Magnetic resonance myocardial fiber-orientation mapping with direct histological correlation. American Journal of Physiology – Heart and Circulatory Physiology 274:H1627–H1634

    Google Scholar 

  24. Scollan DF, Holmes A, Winslow R, Forder J (1998) Histological validation of reconstructed myocardial microstructure obtained from diffusion tensor magnetic resonance imaging. American Journal of Physiology – Heart and Circulatory Physiology 275 44:H2308–H2318

    Google Scholar 

  25. Helm PA, Tseng HJ, Younes L, McVeigh ER, Winslow RL (2005) Ex vivo 3D diffusion tensor imaging and quantification of cardiac laminar structure. Magnetic Resonance in Medicine 54:850-859

    Google Scholar 

  26. Winslow RL, Scollan DF, Holmes A, Yung CK, Zhang J, Jafri MS (2000) Electrophysiological modeling of cardiac ventricular function: from cell to organ. Annual Review of Biomedical Engineering 2:119–155

    Google Scholar 

  27. Papademetris X, Sinusas AJ, Dione DP, Constable RT, Duncan JS (2002) Estimation of 3-D left ventricular deformation from medical images using biomechanical models. IEEE Transactions on Medical Imaging 21:786–800

    Google Scholar 

  28. Sinusas AJ, Papademetris X, Constable RT, Dione DP, Slade MD, Shi P, Duncan JS (2001) Quantification of 3-D regional myocardial deformation: shape-based analysis of magnetic resonance images. American Journal of Physiology – Heart and Circulatory Physiology 281:698-714

    Google Scholar 

  29. Declerck J, Ayache N, McVeigh ER (1999) Use of a 4D planispheric transformation for the tracking and the analysis of LV motion with tagged MR images. In: Chen C-T, Clough AV (eds.) Medical Imaging 1999: Physiology and Function from Multidimensional Images. SPIE, Bellingham

    Google Scholar 

  30. Kozerke S, Scheidegger MB, Pedersen EM, Boesiger P (1999) Heart motion adapted cine phase-contrast flow measurements through the aortic valve. Magnetic Resonance in Medicine 42:970–978

    Google Scholar 

  31. Gleich B, Weizenecker J (2005) Tomographic imaging using the nonlinear response of magnetic particles. Nature 435:1214–1217

    ADS  Google Scholar 

  32. Ratnayaka K, Faranesh AZ, Hansen MS, Stine AM, Halabi M, Barbash IM, Schenke WH, Wright VJ, Grant LP, Kellman P, Kocaturk O, Lederman RJ (2013) Real-time MRI-guided right heart catheterization in adults using passive catheters. European Heart Journal 34: 380–389

    Google Scholar 

  33. Zimmerman JE, Theine P, Harding JT (1970) Design and operation of stable rf-biased superconducting point-contact quantum devices, and a note on the properties of perfectly clean metal contacts. Journal of Applied Physics 41:1572–1580

    ADS  Google Scholar 

  34. Cohen D, Edelsack EA, Zimmerman JE (1970) Magnetocardiograms taken inside a shielded room with a superconducting point-contact magnetometer. Applied Physics Letters 16: 278–280

    ADS  Google Scholar 

  35. Groeger S, Bison G, Knowles PE, Wynands R, Weis A (2006) Laser-pumped cesium magnetometers for high-resolution medical and fundamental research. Sensors and Actuators – A:Physical 129:1–5

    Google Scholar 

  36. Koch H (2004) Recent advances in magnetocardiography. Journal of Electrocardiology 37:117-122

    Google Scholar 

  37. Valsangiacomo Buechel ER, Mertens LL (2012) Imaging the right heart: the use of integrated multimodality imaging. European Heart Journal 33:949–960

    Google Scholar 

  38. Schaar JA, de Korte CL, Mastik F, Baldewsing R, Regar E, de Feyter P, Slager CJ, van der Steen AF, Serruys PW (2003) Intravascular palpography for high-risk vulnerable plaque assessment. Herz 28:488–495

    Google Scholar 

  39. Kanai H, Hasegawa H, Chubachi N, Koiwa Y, Tanaka M (1997) Noninvasive evaluation of local myocardial thickening and its color-coded imaging. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 44:752–768

    Google Scholar 

  40. Argyle RA, Ray SG (2009) Stress and strain: double trouble or useful tool? European Journal of Echocardiography 10:716–722

    Google Scholar 

  41. Leong-Poi H (2009) Molecular imaging using contrast-enhanced ultrasound: evaluation of angiogenesis and cell therapy. Cardiovascular Research 84:190–200

    Google Scholar 

  42. Todaro MC, Choudhuri I, Belohlavek M, Jahangir A, Carerj S, Oreto L, Khandheria BK (2012) New echocardiographic techniques for evaluation of left atrial mechanics. European Heart Journal – Cardiovascular Imaging 13:973–984

    Google Scholar 

  43. Ammar KA, Umland MM, Kramer C, Sulemanjee N, Jan MF, Khandheria BK, Seward JB, Paterick TE (2012) The ABCs of left ventricular assist device echocardiography: a systematic approach. European Heart Journal – Cardiovascular Imaging 13:885–899

    Google Scholar 

  44. Gutiérrez-Chico1 JL, Alegra-Barrero E, Teijeiro-Mestre R, Chan PH, Tsujioka H, de Silva R, Viceconte N, Lindsay A, Patterson T, Foin N, Akasaka T, di Mario C (2012) Optical coherence tomography: from research to practice. European Heart Journal – Cardiovascular Imaging 13:370–384

    Google Scholar 

  45. Prati F, Guagliumi G, Mintz GS, Costa M, Regar E, Akasaka T, Barlis P, Tearney GJ, Jang IK, Arbustini E, Bezerra HG, Ozaki Y, Bruining N, Dudek D, Radu M, Erglis A, Motreff P, Alfonso F, Toutouzas K, Gonzalo N, Tamburino C, Adriaenssens T, Pinto F, Serruys PW, Di Mario C; for the Expert’s OCT Review Document (2012) Expert review document part 2: methodology, terminology and clinical applications of optical coherence tomography for the assessment of interventional procedures. European Heart Journal 33:2513–2520.

    Google Scholar 

  46. Laughner JI, Zhang S, Li H, Shao CC, Efimov IR (2012) Mapping cardiac surface mechanics with structured light imaging. American Journal of Physiology – Heart and Circulatory Physiology 303:H712–H720

    Google Scholar 

  47. Thiberville L, Salaün M, Lachkar S, Dominique S, Moreno-Swirc S, Vever-Bizet C, Bourg-Heckly G (2009) Human in vivo fluorescence microimaging of the alveolar ducts and sacs during bronchoscopy. European Respiratory Journal 33:974–985

    Google Scholar 

  48. Moore JA, Steinman DA, Ethier CR (1998) Computational blood flow modelling: errors associated with reconstructing finite element models from magnetic resonance images. Journal of Biomechanics 31:179–184

    Google Scholar 

  49. Boissonnat J-D (1988) Shape reconstruction from planar cross-sections. Computer Vision, Graphics, and Image Processing 44:1–29

    Google Scholar 

  50. Boissonnat J-D, Chaine R, Frey P, Malandain G, Salmon S, Saltel E, Thiriet M (2005) From arteriographies to computational flow in saccular aneurisms: the INRIA experience. Medical Image Analysis 9:133–143

    Google Scholar 

  51. Boissonnat, J-D, Cazals F (2002) Smooth surface reconstruction via natural neighbour interpolation of distance functions. Computational Geometry 22:185–203

    MathSciNet  MATH  Google Scholar 

  52. Osher S, Sethian JA (1988) Fronts propagating with curvature-dependent speed: algorithms based on Hamilton–Jacobi formulations. Journal of Computational Physics 79:12–49

    MathSciNet  ADS  MATH  Google Scholar 

  53. Sethian, JA (1996) Level Set Methods: Evolving Interfaces in Geometry, Fluid Mechanics, Computer Vision, and Materials Science. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  54. Lorensen, WE, Cline HE (1987) Marching cubes: a high resolution 3D surface construction algorithm. Computer Graphics 21:163–169

    Google Scholar 

  55. Delingette H, Hbert M, Ikeuchi K (1992) Shape representation and image segmentation using deformable surfaces. Image and Vision Computing 10:132–144

    Google Scholar 

  56. Taylor CA, Hughes TJR, Zarins CK (1998) Finite element modeling of blood flow in arteries. Computer Methods in Applied Mechanics and Engineering 158:155–196

    MathSciNet  ADS  MATH  Google Scholar 

  57. Peiró J, Giordana S, Griffith C, Sherwin SJ (2002) High-order algorithms for vascular flow modelling. International Journal for Numerical Methods in Fluids 40:137–151

    MathSciNet  ADS  MATH  Google Scholar 

  58. Sherwin SJ, Peiró J (2002) Mesh generation in curvilinear domains using high-order elements. International Journal for Numerical Methods in Engineering 53:207–223

    ADS  MATH  Google Scholar 

  59. Giachetti A, Tuveri M, Zanetti G (2003) Reconstruction and web distribution of measurable arterial models. Medical Image Analysis 7:79–93

    Google Scholar 

  60. Cohen LD (1991) On active contour models and balloons. Computer Vision, Graphics, and Image Processing 53:211–218

    MATH  Google Scholar 

  61. Xu C, Prince JL (1998) Snakes, shapes and gradient vector flow. IEEE Transactions on Image Processing 7:359–369

    MathSciNet  ADS  MATH  Google Scholar 

  62. McInerney T, Terzopoulos D (1995) Topologically adaptable snakes. In: Proceedings of the fifth international conference on computer vision. IEEE

    Google Scholar 

  63. Krissian K, Malandain G, Ayache N (1998) Model based multiscale detection and reconstruction of 3D vessels. INRIA Research Report RR-3442

    Google Scholar 

  64. Fetita C, Prteux F, Beigelman-Aubry C, Grenier P (2004) Pulmonary airways: 3D reconstruction from multi-slice CT and clinical investigation, IEEE Transactions on Medical Imaging 23:1353–1364

    Google Scholar 

  65. Perchet D, Fetita CI, Vial L, Prteux F, Sbirlea-Apiou G, Thiriet M (2004) Virtual investigation of pulmonary airways in volumetric computed tomography, Computer Animation and Virtual Worlds 15:361–376

    Google Scholar 

  66. George P-L, Hecht H, Saltel E (1990) Fully automatic mesh generator for 3D domains of any shape. Impact of Computing in Science and Engineering 2:187–218

    MATH  Google Scholar 

  67. George P-L (1990) Gnration automatique de maillages [Automatic Mesh Generation]. Masson, Paris

    Google Scholar 

  68. George P-L, Borouchaki H (1997) Triangulation de Delaunay et maillage [Delaunay Triangulation and Mesh]. Hermès, Paris

    Google Scholar 

  69. Frey PJ, George P-L (1999) Maillages [Meshes]. Hermès, Paris

    Google Scholar 

  70. George P-L, Hecht F (1999), Nonisotropic grid. In: Thompson JF, Soni BK, Weatherill NP (eds.) Handbook of Grid Generation. CRC Press, Boca Raton, FL

    Google Scholar 

  71. Mohammadi B, George P-L, Hecht F, Saltel, E (2000) 3D Mesh adaptation by metric control for CFD. Revue europenne des lments finis 9:439–449

    MATH  Google Scholar 

  72. Habashi WG, Dompierre J, Bourgault Y, Fortin M, Vallet M-G (1998) Certifiable computational fluid mechanics through mesh optimization. AIAA Journal 36:703–711

    ADS  Google Scholar 

  73. Fortin, M (2000) Anisotropic mesh adaptation through hierarchical error estimators. In: Minev, P, Yanping L (eds.) Scientific Computing and Applications. Nova Science, Commack, NY

    Google Scholar 

  74. Dompierre J, Vellet M-G, Bourgault Y, Fortin M, Habashi WG (2002) Anisotropic mesh adaptation: towards user-independent, mesh-independent and solver-independent CFD III: Unstructured meshes. International Journal for Numerical Methods in Fluids 39:675–702

    MathSciNet  ADS  MATH  Google Scholar 

  75. Fortin A, Bertrand F, Fortin M, Boulanger-Nadeau PE, El Maliki A, Najeh N (2004) Adaptive remeshing strategy for shear-thinning fluid flow simulations. Computers and Chemical Engineering 28:2363–2375

    Google Scholar 

  76. Cebral JR, Lohner R (2001) From medical images to anatomically accurate finite element grids. International Journal for Numerical Methods in Engineering 51:985–1008

    ADS  MATH  Google Scholar 

  77. Taubin G (1995) Curve and surface smoothing without shrinkage. In: Proceedings of the Fifth International Conference on Computer Vision. IEEE

    Google Scholar 

  78. Frey PJ, Borouchaki H (1998) Geometric surface mesh optimization. Computing and Visualization in Science 1:113–121

    MATH  Google Scholar 

  79. Thiriet M, Graham JMR, Issa RI (1992) A pulsatile developing flow in a bend. Journal de Physique III 2:995–1013

    ADS  Google Scholar 

  80. Frey PJ, Borouchaki H (2003) Surface meshing using a geometric error estimate. International Journal for Numerical Methods in Engineering 58:227–245

    ADS  MATH  Google Scholar 

  81. Belhamadia Y, Fortin A, Chamberland E (2004) Anisotropic mesh adaptation for the solution of the Stefan problem. Journal of Computational Physics 194:233–255

    MathSciNet  ADS  MATH  Google Scholar 

  82. Belhamadia Y, Fortin A, Chamberland E (2004) Three-dimensional anisotropic mesh adaptation for phase change problems, Journal of Computational Physics 201:753–770

    MathSciNet  ADS  MATH  Google Scholar 

  83. McGraw-Hill Encyclopedia of Science and Technology (1960) McGraw-Hill, New York

    Google Scholar 

  84. Conrad WA, McQueen DM, Yellin EL (1980) Steady pressure flow relations in compressed arteries: Possible origin of Korotkoff sounds. Medical and Biological Engineering and Computing 18:419–426

    Google Scholar 

  85. Risacher F (1995) tude de la propagation de l’onde de pouls par plthysmographie d’impdance lectrique [Study of the propagation of pulse waves by electric impedance plethysmography]. PhD Thesis, University Claude Bernard, Lyon

    Google Scholar 

  86. O’Rourke MF, Avolio AP, Kelly RP (1992) The Arterial Pulse. Lea & Febiger, Baltimore, MD

    Google Scholar 

  87. Penaz J (1992) Criteria for set point estimation in the volume clamp method of blood pressure measurement. Physiological Research 41:5–10

    Google Scholar 

  88. Williams B, Lacy PS (2010) Central haemodynamics and clinical outcomes: going beyond brachial blood pressure? European Heart Journal 31:1819–1822

    Google Scholar 

  89. Vlachopoulos C, Aznaouridis K, O’Rourke MF, Safar ME, Baou K, Stefanadis C (2010) Prediction of cardiovascular events and all-cause mortality with central haemodynamics: a systematic review and meta-analysis. European Heart Journal 31:1865–1871

    Google Scholar 

  90. Omboni S, Parati G, Frattola A, Mutti E, Di Rienzo M, Castiglioni P, Mancia G (1993) Spectral and sequence analysis of finger blood pressure variability. Comparison with analysis of intra-arterial recordings. Hypertension 22:26–33

    Google Scholar 

  91. Novak V, Novak P, Schondorf R (1994) Accuracy of beat-to-beat noninvasive measurement of finger arterial pressure using the Finapres: a spectral analysis approach. Journal of Clinical Monitoring 10:118–126

    Google Scholar 

  92. Imholz BP, Wieling W, van Montfrans GA, Wesseling KH (1998) Fifteen years experience with finger arterial pressure monitoring: assessment of the technology. Cardiovascular Research 38:605–616

    Google Scholar 

  93. Coron J-M, Crpeau E (2003) Exact boundary controllability of a nonlinear KdV equation with critical lengths. INRIA Research Report RR-5000

    Google Scholar 

  94. Whitman GB (1999) Linear and Nonlinear Waves. Wiley-Interscience, New York

    Google Scholar 

  95. Crpeau E, Sorine M (2005) personal communication

    Google Scholar 

  96. Tasu J-P, Mousseaux E, Colin P, Slama MS, Jolivet O, Bittoun J (2002) Estimation of left ventricle performance through temporal pressure variations measured by MR velocity and acceleration mappings. Journal of Magnetic Resonance Imaging 16:246–252

    Google Scholar 

  97. Laleg TM, Crépeau E, Papelier Y, Sorine M (2007) Arterial blood pressure analysis based on scattering transform. 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC), Lyon, France

    Google Scholar 

  98. Kitney RI, Giddens DP (1983) Analysis of blood velocity waveforms by phase shift averaging and autoregressive spectral estimation. Journal of Biomechanical Engineering 105:398–401

    Google Scholar 

  99. Thiriet M, Cybulski G, Darrow RD, Doorly DJ, Dumoulin C, Tarnawski M, Caro CG (1997) Apports et limitations de la vlocimtrie par rsonance magntique nuclaire en biomcanique. Mesures dans un embranchement plan symtrique [Contributions and limitations of the nuclear magnetic resonance velocimetry in biomechanics. Measures in a two plane symmetrical bifurcation]. Journal de Physique III 7:771–787

    ADS  Google Scholar 

  100. Durand E, Guillot G, Darrasse L, Tastevin G, Nacher PJ, Vignaud A, Vattolo D, Bittoun J (2002) CPMG measurements and ultrafast imaging in human lungs with hyperpolarized helium-3 at low field (0.1 T). Magnetic Resonance in Medicine 47:75–81

    Google Scholar 

  101. de Rochefort L., Vial L., Fodil R., Maître X., Louis B., Isabey D., Caillibotte G., Thiriet M., Bittoun J., Durand E., Sbirlea-Apiou G. (2007) In vitro validation of CFD simulation in human proximal airways reconstructed from medical images with hyperpolarized helium-3 MRI phase contrast velocimetry. Journal of Applied Physiology: Respiratory, Environmental and Exercise Physiology 102:2012–2023

    Google Scholar 

  102. Dumoulin CL, Hart HR Jr (1986) Magnetic resonance angiography. Radiology 161 717–720

    Google Scholar 

  103. Dumoulin CL, Souza SP, Hart HR (1987) Rapid scan magnetic resonance angiography. Magnetic Resonance in Medicine 5:238–245

    Google Scholar 

  104. Dumoulin CL, Souza SP, Walker MF, Yoshitome E (1988) Time-resolved magnetic resonance angiography. Magnetic Resonance in Medicine 6:275–286

    Google Scholar 

  105. Dumoulin CL, Souza SP, Walker MF, Wagle W (1989) Three-dimensional phase contrast angiography. Magnetic Resonance in Medicine 9:139–149

    Google Scholar 

  106. Dumoulin CL, Doorly DJ, Caro CG (1993) Quantitative measurement of velocity at multiple positions using comb excitation and Fourier velocity encoding. Magnetic Resonance in Medicine 29:44–52

    Google Scholar 

  107. Bittoun J, Jolivet O, Herment A, Itti E, Durand E, Mousseaux E, Tasu J-P (2000) Multidimensional MR mapping of multiple components of velocity and acceleration by Fourier phase encoding with a small number of encoding steps. Magnetic Resonance in Medicine 44:723–730

    Google Scholar 

  108. Durand E, Jolivet O, Itti E, Tasu J-P, Bittoun J (2001) Precision of magnetic resonance velocity and acceleration measurements: theoreticals issues and phantom experiments. Magnetic Resonance in Medicine 13:445–451

    Google Scholar 

  109. Liebman FM, Pearl J, Bagnol S (1962) The electrical conductance properties of blood in motion. Physics in Medicine and Biology 7:177–194

    ADS  Google Scholar 

  110. Geddes LA, Sadler C (1973) The specific resistance of blood at body temperature. Medical and Biological Engineering 11:336–339

    Google Scholar 

  111. Brody DA (1956) A theoretical analysis of intracavitary blood mass influence on the heart-lead relationship. Circulation Research 4:731–738

    Google Scholar 

  112. Gulrajani RM, Roberge FA, Mailloux GE (1989) The forward problem of electrocardiography. In Comprehensive Electrocardiology: Theory and Practice in Health and Disease. Macfarlane PW, Lawrie TDV (eds.), 237–288, Pergamon Press, New York

    Google Scholar 

  113. Einthoven W (1895) Uber die Form des menschlichen Electrokardiograms [On the shape of the electrocardiogram in men]. Pflügers Archiv fur die gesamte Physiologie des Menschen und der Tiere 60:101-123

    Google Scholar 

  114. Einthoven W (1908) Weiteres über das Elektrokardiogram [More on the electrocardiogram]. Pflügers Archiv fur die gesamte Physiologie des Menschen und der Tiere 122:517–548

    Google Scholar 

  115. Einthoven W, Fahr G, de Waart A (1913) Uber die Richtung und die Manifeste Grösse der Potentialschwankungen im mennschlichen Herzen und über den Einfluss der Herzlage auf die Form des Elektrokardiogramms [On the direction and manifest size of the variations of potential in the human heart and on the influence of the heart position in the shape of the electrocardiogram]. Pflügers Archiv fur die gesamte Physiologie des Menschen und der Tiere 150:275-315

    Google Scholar 

  116. Goldberger E (1942) The aVL, aVR, and aVF leads. A simplification of standard lead electrocardiography. American Heart Journal 24:378–396

    Google Scholar 

  117. Einthoven W, Fahr G, de Waart A (1950) On the direction and manifest size of the variations of potential in the human heart and on the influence of the position of the heart on the form of the electrocardiogram. American Heart Journal 40:163–211

    Google Scholar 

  118. Baumert M, Lambert GW, Dawood T, Lambert EA, Esler MD, McGrane M, Barton D, Nalivaiko E (2008) QT interval variability and cardiac norepinephrine spillover in patients with depression and panic disorder. American Journal of Physiology – Heart and Circulatory Physiology 295:H962–H968

    Google Scholar 

  119. Boulakia M, Fernández MA, Gerbeau JF, Zenzemi N (2007) Numerical simulation of ECG. Functional Imaging and Modeling of the Heart: FIMH07, Springer, NY

    Google Scholar 

  120. Frank E (1956) An accurate, clinically practical system for spatial vectorcardiography. Circulation 13: 737–749

    Google Scholar 

  121. Nousiainen J, Oja S, Malmivuo J (1994) Normal vector magnetocardiogram. I. Correlation with the normal vector ECG. Journal of Electrocardiology 27:221–231

    Google Scholar 

  122. Nousiainen J, Oja S, Malmivuo J (1994) Normal vector magnetocardiogram. II. Effect of constitutional variables. Journal of Electrocardiology 27:233–241

    Google Scholar 

  123. Baule GM, McFee R (1963) Detection of the magnetic field of the heart. American Heart Journal 66:95–96

    Google Scholar 

  124. van Oosterom A, Oostendorp TF, Huiskamp GJ, ter Brake HJ (1990) The magnetocardiogram as derived from electrocardiographic data. Circulation Research 67:1503–1509

    Google Scholar 

  125. Penney BC (1986) Theory and cardiac applications of electrical impedance measurements. CRC Critical Reviews in Biomedical Engineering 13:227-281

    Google Scholar 

  126. Cybulski G (2005) Dynamic impedance cardiography – the system and its applications. Polish Journal of Medical Physics and Engineering 11:127–209

    Google Scholar 

  127. Mead J, Whittenberger JL (1953) Physical properties of human lungs measured during spontaneous respiration. Journal of Applied Physiology 5:779–796

    Google Scholar 

  128. DuBois AB, Botelho SY, Comroe JH (1956) A new method for measuring airway resistance in man using a body plethysmograph: values in normal subjects and in patients with respiratory disease. Journal of Clinical Investigation 35:327–335

    Google Scholar 

  129. Jaeger MJ, Otis AB (1964) Measurement of airway resistance with a volume displacement body plethysmograph. Journal of Applied Physiology 19:813–819

    Google Scholar 

  130. Rice DA (1980) Sound speed in the upper airways. Journal of Applied Physiology 49: 326–336

    Google Scholar 

  131. Rice DA (1983) Sound speed in pulmonary parenchyma. Journal of Applied Physiology 54:304–308

    Google Scholar 

  132. Scherer PW, Shendalman LH, Greene NM, Bouhuys A (1975) Measurement of axial diffusivities in a model of the bronchial airways. Journal of Applied Physiology 38:719–723

    Google Scholar 

  133. Ultman JS, Blatman HS (1977) Longitudinal mixing in pulmonary airways. Analysis of inert gas dispersion in symmetric tube network models. Respiration physiology 30:349–367

    Google Scholar 

  134. Grubb BR, Mills CD (1981) Blood oxygen content in microliter samples using an easy-to-build galvanic oxygen cell. Journal of Applied Physiology 50:456-464

    Google Scholar 

  135. Krogh A, Krogh M (1909) Rate of diffusion into lungs of man. Skandinavisches Archiv für Physiologie 23:236–247

    Google Scholar 

  136. Krogh A (1909) On the mechanism of gas exchange in the lungs. Skandinavisches Archiv für Physiologie 23:248–278

    Google Scholar 

  137. Krogh M (1915) The diffusion of gases through the lungs of man. Journal of Physiology, London 49:271–296

    Google Scholar 

  138. Forster RE, Fowler WS, Bates DV (1954) The absorption of carbon monoxide by the lungs during breathholding. Journal of Clinical Investigation 33:1135–1145

    Google Scholar 

  139. Roughton FJW, Forster RE (1957) Relative importance of diffusion and chemical reaction in determining rate of exchange of gases in the human lung. Journal of Applied Physiology 11:290–302

    Google Scholar 

  140. Burrows B, Kasik JE, Niden AH, Barclay WR (1961) Clinical usefulness of the single-breath pulmonucy diffusing capacity test. American Review of Respiratory Diseases 84:789–806

    Google Scholar 

  141. Hughes JMB, Bates DV (2003) Historical review: the carbon monoxide diffusing capacity and its membrane and red cell components. Respiratory Physiology and Neurobiology 138:115–142

    Google Scholar 

  142. Widdicombe J (1997) Airway and alveolar permeability and surface liquid thickness: theory. Journal of Applied Physiology 82:3–12

    Google Scholar 

Conclusion

  1. Kobori H, Nangaku M, Navar LG, Nishiyama A (2007) The intrarenal renin-angiotensin system: from physiology to the pathobiology of hypertension and kidney disease. Pharmacological Reviews 59:251–287

    Google Scholar 

  2. Fitzsimons JT (1998) Angiotensin, thirst, and sodium appetite. Physiological Reviews 78:583–686

    Google Scholar 

  3. Beuschlein F (2013) Regulation of aldosterone secretion: from physiology to disease. European Journal of Endocrinology 168:R85–R93

    Google Scholar 

Appendices

  1. Hoffmann R, Valencia A (2004) A gene network for navigating the literature. Nature – Genetics 36:664 (Information Hyperlinked over Proteins. www.ihop-net.org)

  2. BioGRID: General Repository for Interaction Datasets; database of physical and genetic interactions for model organisms (www.thebiogrid.org)

  3. GeneCards human gene database. Crown Human Genome Center, Department of Molecular Genetics, the Weizmann Institute of Science (www.genecards.org)

  4. Universal Protein Resource (UniProt) Consortium (European Bioinformatics Institute, Swiss Institute of Bioinformatics, and Protein Information Resource. www.uniprot.org)

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Thiriet, M. (2014). Cardiovascular Physiology. In: Anatomy and Physiology of the Circulatory and Ventilatory Systems. Biomathematical and Biomechanical Modeling of the Circulatory and Ventilatory Systems, vol 6. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-9469-0_3

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