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Advancements of Mass Spectrometry in Biomedical Research pp 55–98Cite as

Proteome Imaging: From Classic to Modern Mass Spectrometry-Based Molecular Histology

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Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1140))

Abstract

In order to overcome the limitations of classic imaging in Histology during the actually era of multiomics, the multi-color “molecular microscope” by its emerging “molecular pictures” offers quantitative and spatial information about thousands of molecular profiles without labeling of potential targets. Healthy and diseased human tissues, as well as those of diverse invertebrate and vertebrate animal models, including genetically engineered species and cultured cells, can be easily analyzed by histology-directed MALDI imaging mass spectrometry. The aims of this review are to discuss a range of proteomic information emerging from MALDI mass spectrometry imaging comparative to classic histology, histochemistry and immunohistochemistry, with applications in biology and medicine, concerning the detection and distribution of structural proteins and biological active molecules, such as antimicrobial peptides and proteins, allergens, neurotransmitters and hormones, enzymes, growth factors, toxins and others. The molecular imaging is very well suited for discovery and validation of candidate protein biomarkers in neuroproteomics, oncoproteomics, aging and age-related diseases, parasitoproteomics, forensic, and ecotoxicology. Additionally, in situ proteome imaging may help to elucidate the physiological and pathological mechanisms involved in developmental biology, reproductive research, amyloidogenesis, tumorigenesis, wound healing, neural network regeneration, matrix mineralization, apoptosis and oxidative stress, pain tolerance, cell cycle and transformation under oncogenic stress, tumor heterogeneity, behavior and aggressiveness, drugs bioaccumulation and biotransformation, organism’s reaction against environmental penetrating xenobiotics, immune signaling, assessment of integrity and functionality of tissue barriers, behavioral biology, and molecular origins of diseases. MALDI MSI is certainly a valuable tool for personalized medicine and “Eco-Evo-Devo” integrative biology in the current context of global environmental challenges.

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Abbreviations

2-D/3-D MSI:

Two-dimensional/three-dimensional mass spectrometry images

ABC:

Avidin-biotin complex

ABPP:

Activity-based protein profiling

AD:

Alzheimer’s disease

AFAI-MSI:

Air flow-assisted ionization mass spectrometry imaging

APCI:

Atmospheric pressure chemical ionization

APPI:

Atmospheric pressure photo-ionization

BALF:

Bronchoalveolar lavage fluid

BBB:

Blood-brain barrier

CAFs:

Cancer associated fibroblasts

CHCA:

α-Cyano-4-hydroxycinnamic acid

CLS/CLSM:

Confocal laser scanning microscopy

COMP:

Cartilage oligomeric matrix glycoprotein

CSP:

Characteristic spectral patterns

DESI/ESI:

Desorption electrospray ionization/electrospray ionization

DHB:

2,5-Dihydroxybenzoic acid

DIC:

Differential interference contrast

DIOS:

Desorption/ionization on silicon

EBC:

Exhaled breath condensate

ESI:

Electrospray ionization

FAIMS:

High field asymmetric waveform ion mobility spectrometry

FF:

Fresh-frozen

FFPE:

Formalin-fixed, paraffin-embedded

FISH:

Fluorescence in situ hybridization

FITC:

Fluorescein isothiocyanate

FLIM:

Fluorescence lifetime imaging

FRET:

Fluorescence resonance energy transfer

FT-ICR:

Fourier transform ion cyclotron resonance

GBL:

Gamma-butyrolactone

GC:

Gas chromatography

GC-MS:

Gas chromatography-mass spectrometry

GFAP:

Glial fibrillary acidic protein

GFP:

Green fluorescent protein

GHB:

Gamma-hydroxybutyric acid

GHB-Gluc:

Gamma-hydroxybutyric acid glucuronide

H&E:

Hematoxylin and eosin

HC:

Histochemistry

HCA:

Hierarchical clustering analysis

HCCA:

Alpha-cyano-4-hydroxycinnamic acid

HNP:

Human neutrophil peptide

HPLC:

High-performance/pressure liquid chromatography

HPLC/ESI-MS:

High-performance liquid chromatography/electrospray ionization-mass spectrometry

HPLC/ESI-MS/MS:

High-performance liquid chromatography/electrospray ionization-tandem mass spectrometry

HPLC/TOF-MS:

High-performance liquid chromatography/time-of-flight mass spectrometry

HPLC-MS:

High-performance liquid chromatography mass spectrometry

HPLC-MS/MS:

High-performance liquid chromatography tandem mass spectrometry

HRP:

Horseradish peroxidase

HTT:

Hyalinizing trabecular tumor

ICC:

Immunocytochemistry

IHC:

Immunohistochemistry

IMS:

Ion mobility spectrometry

IR-MALDESI QMSI:

Infrared matrix-assisted laser desorption electrospray ionization quantitative mass spectrometry imaging

ITO:

Indium tin oxide glass microscope slide

LAESI:

Laser ablation electrospray ionization mass spectrometry

LA-ICP-MSI:

Laser ablation inductively coupled plasma mass spectrometry imaging

LAMMA:

Laser microprobe mass analysis

LC:

Liquid chromatography

LCM:

Laser-capture microdissection

LC-MS:

Liquid chromatography-mass spectrometry

LC-MS/MS:

Liquid chromatography-tandem mass spectrometry

LESA:

Liquid extraction surface analysis

LMJ-SSP:

Liquid microjunction surface sampling

LSEs:

Living skin equivalents

m/z :

Mass/charge

MALD-ESI:

Matrix-assisted laser desorption electrospray ionization

MALDI:

Matrix-assisted laser desorption/ionization

MALDI-FTICR-MS:

Matrix-assisted laser desorption/ionization–Fourier transform ion cyclotron resonance–mass spectrometry

MALDI-FTICR-MSI:

Matrix-assisted laser desorption/ionization–Fourier transform ion cyclotron resonance–mass spectrometry imaging

MALDI-IMS-MSI:

Matrix-assisted laser desorption/ionization-ion mobility separation-mass spectrometry imaging

MALDI-MS:

Matrix-assisted laser desorption/ionization mass spectrometry

MALDI-MSI:

Matrix-assisted laser desorption/ionization mass spectrometry imaging

MALDI-TOF-MS:

Matrix-assisted laser desorption/ionization–time-of-flight–mass spectrometry

MALDI-TOF-MSI:

Matrix-assisted laser desorption/ionization–time-of-flight–mass spectrometry imaging

mMALDI MSI:

Multigrid MALDI MSI

MRI:

Magnetic resonance imaging

MS:

Mass spectrometry

MS/MS:

Tandem mass spectrometry

MSI:

Mass spectrometry imaging

MudPIT:

Multidimensional protein identification technology

MyHC:

Myosin heavy chain

NALDI:

Nano-assisted laser desorption ionization

NIMS:

Nanostructure-initiator mass spectrometry

NSOM:

Near-field scanning optical microscopy

PCA:

Principal component analysis

PET:

Positron emission tomography

PPI:

Protein-protein interactions

PTC:

Papillary thyroid carcinoma

QMSI:

Quantitative mass spectrometry imaging

REIMS:

Rapid evaporative ionization mass spectrometry

ROIs:

Regions of interests

SA:

Sinapinic acid

SALDI:

Surface-assisted laser desorption/ionization

SDCM:

Spinning disk confocal microscopy

SELDI:

Surface-enhanced laser desorption/ionization

SELDI-MS:

Surface-enhanced laser desorption/ionization-mass spectrometry

SEM:

Scanning electron microscopy

SIMS:

Secondary ion mass spectrometry

SMALDI:

Scanning microprobe MALDI

SPR:

Surface plasmon resonance

Tag-Mass MSI:

Targeted mass spectrometric imaging

TEM:

Transmission electron microscopy

TIRF:

Total internal reflection fluorescence

TMAs:

Tissue microarrays

TOF:

Time-of-flight

t-SNE:

t-Distributed stochastic neighbor embedding

UHPLC:

Ultra-high-performance liquid chromatography

UHPLC-MS/MS:

Ultra-high-performance liquid chromatography tandem mass spectrometry

References

  1. Ur Rehman, H., Azam, N., Yao, J., & Benso, A. (2017). A three-way approach for protein function classification. PLoS One, 12(2), e0171702.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. Milo, R. (2013). What is the total number of protein molecules per cell volume? A call to rethink some published values. BioEssays, 35(12), 1050–1055.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Lukeš, T., Glatzová, D., Kvíčalová, Z., Levet, F., Benda, A., Letschert, S., et al. (2017). Quantifying protein densities on cell membranes using super-resolution optical fluctuation imaging. Nature Communications, 8(1), 1731.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Li, J., Akbani, R., Zhao, W., Lu, Y., Weinstein, J. N., Mills, G. B., et al. (2017). Explore, visualize, and analyze functional Cancer proteomic data using the cancer proteome atlas. Cancer Research, 77(21), e51–e54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Shruthi, B. S., Vinodhkumar, P., & Selvamani. (2016). Proteomics: A new perspective for cancer. Advanced Biomedical Research, 5, 67.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Manzoni, C., Kia, D. A., Vandrovcova, J., Hardy, J., Wood, N. W., Lewis, P. A., et al. (2018). Genome, transcriptome and proteome: The rise of omics data and their integration in biomedical sciences. Briefings in Bioinformatics, 19(2), 286–302.

    Article  CAS  PubMed  Google Scholar 

  7. Harper, J. W., & Bennett, E. J. (2016). Proteome complexity and the forces that drive proteome imbalance. Nature, 537(7620), 328–338.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Amaral, A., Castillo, J., Ramalho-Santos, J., & Oliva, R. (2014). The combined human sperm proteome: Cellular pathways and implications for basic and clinical science. Human Reproduction Update, 20(1), 40–62.

    Article  CAS  PubMed  Google Scholar 

  9. Bryk, A. H., & Wiśniewski, J. R. (2017). Quantitative analysis of human red blood cell proteome. Journal of Proteome Research, 16(8), 2752–2761.

    Article  CAS  PubMed  Google Scholar 

  10. Tomazella, G. G., da Silva, I., Laure, H. J., Rosa, J. C., Chammas, R., Wiker, H. G., et al. (2009). Proteomic analysis of total cellular proteins of human neutrophils. Proteome Science, 7(1), 32.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Slany, A., Paulitschke, V., Haudek-Prinz, V., Meshcheryakova, A., & Gerner, C. (2014). Determination of cell type-specific proteome signatures of primary human leukocytes, endothelial cells, keratinocytes, hepatocytes, fibroblasts and melanocytes by comparative proteome profiling. Electrophoresis, 35(10), 1428–1438.

    Article  CAS  PubMed  Google Scholar 

  12. Uhlén, M., Fagerberg, L., Hallström, B. M., Lindskog, C., Oksvold, P., Mardinoglu, A., et al. (2015). Tissue-based map of the human proteome. Science, 347(6220), 1260419.

    Article  PubMed  CAS  Google Scholar 

  13. Barbosa, E. B., Vidotto, A., Polachini, G. M., Henrique, T., de Marqui, A. B. T., & Helena Tajara, E. (2012). Proteomics: Methodologies and applications to the study of human diseases. Revista da Associação Médica Brasileira (English Edition), 58(3), 366–375.

    Article  Google Scholar 

  14. Sallam, R. M. (2015). Proteomics in cancer biomarkers discovery: Challenges and applications. Disease Markers, 2015, 12.

    Article  CAS  Google Scholar 

  15. Jimenez, C. R., Zhang, H., Kinsinger, C. R., & Nice, E. C. (2018). The cancer proteomic landscape and the HUPO Cancer proteome project. Clinical Proteomics, 15, 4.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Lundström, S. L., Zhang, B., Rutishauser, D., Aarsland, D., & Zubarev, R. A. (2017). SpotLight proteomics: Uncovering the hidden blood proteome improves diagnostic power of proteomics. Scientific Reports, 7, 41929.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Anderson, N. L., Polanski, M., Pieper, R., Gatlin, T., Tirumalai, R. S., Conrads, T. P., et al. (2004). The human plasma proteome. A nonredundant list developed by combination of four separate sources. Molecular and Cellular Proteomics, 3(4), 311–326.

    Article  CAS  PubMed  Google Scholar 

  18. Geyer, P. E., Kulak, N. A., Pichler, G., Holdt, L. M., Teupser, D., & Mann, M. (2016). Plasma proteome profiling to assess human health and disease. Cell Systems, 2(3), 185–195.

    Article  CAS  PubMed  Google Scholar 

  19. Castagnola, M., Cabras, T., Iavarone, F., Fanali, C., Nemolato, S., Peluso, G., et al. (2012). The human salivary proteome: A critical overview of the results obtained by different proteomic platforms. Expert Review of Proteomics, 9(1), 33–46.

    Article  CAS  PubMed  Google Scholar 

  20. Sivadasan, P., Kumar Gupta, M., Sathe, G. J., Balakrishnan, L., Palit, P., Gowda, H., et al. (2015). Data from human salivary proteome - A resource of potential biomarkers for oral cancer. Data in Brief, 4, 374–378.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Wormwood, K. L., Aslebagh, R., Channaveerappa, D., Dupree, E. J., Borland, M. M., Ryan, J. P., et al. (2015). Salivary proteomics and biomarkers in neurology and psychiatry. Proteomics. Clinical Applications, 9(9–10), 899–906.

    Article  CAS  PubMed  Google Scholar 

  22. Ngounou Wetie, A. G., Wormwood, K. L., Russell, S., Ryan, J. P., Darie, C. C., & Woods, A. G. (2015). A pilot proteomic analysis of salivary biomarkers in autism Spectrum disorder. Autism Research, 8(3), 338–350.

    Article  PubMed  Google Scholar 

  23. Grassl, N., Kulak, N. A., Pichler, G., Geyer, P. E., Jung, J., Schubert, S., et al. (2016). Ultra-deep and quantitative saliva proteome reveals dynamics of the oral microbiome. Genome Medicine, 8(1), 44.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Castagnola, M., Scarano, E., Passali, G. C., Messana, I., Cabras, T., Iavarone, F., et al. (2017). Salivary biomarkers and proteomics: Future diagnostic and clinical utilitiesBiomarkers e proteomica salivari: Prospettive future cliniche e diagnostiche. Acta Otorhinolaryngologica Italica: organo ufficiale della Societa italiana di otorinolaringologia e chirurgia cervico-facciale, 37(2), 94–101.

    Article  CAS  Google Scholar 

  25. Iadarola, P., & Viglio, S. (2017). Spit it out! How could the sputum proteome aid clinical research into pulmonary diseases? Expert Review of Proteomics, 14(5), 391–393.

    Article  CAS  PubMed  Google Scholar 

  26. Burg, D., Schofield, J. P. R., Brandsma, J., Staykova, D., Folisi, C., Bansal, A., et al. (2018). Large-scale label-free quantitative mapping of the sputum proteome. Journal of Proteome Research, 17(6), 2072–2091.

    Article  CAS  PubMed  Google Scholar 

  27. Zhou, L., Zhao, S. Z., Koh, S. K., Chen, L., Vaz, C., Tanavde, V., et al. (2012). In-depth analysis of the human tear proteome. Journal of Proteomics, 75(13), 3877–3885.

    Article  CAS  PubMed  Google Scholar 

  28. Tang, Q., Zhang, C., Wu, X., Duan, W., Weng, W., Feng, J., et al. (2018). Comprehensive proteomic profiling of patients’ tears identifies potential biomarkers for the traumatic vegetative state. Neuroscience Bulletin, 34, 1–13.

    Article  CAS  Google Scholar 

  29. Beasley-Green, A. (2016). Urine proteomics in the era of mass spectrometry. International Neurourology Journal, 20(Suppl 2), S70–S75.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Zhao, M., Li, M., Yang, Y., Guo, Z., Sun, Y., Shao, C., et al. (2017). A comprehensive analysis and annotation of human normal urinary proteome. Scientific Reports, 7(1), 3024.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Csősz, É., Emri, G., Kalló, G., Tsaprailis, G., & Tőzsér, J. (2015). Highly abundant defense proteins in human sweat as revealed by targeted proteomics and label-free quantification mass spectrometry. Journal of the European Academy of Dermatology and Venereology, 29(10), 2024–2031.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Yu, Y., Prassas, I., Muytjens, C. M. J., & Diamandis, E. P. (2017). Proteomic and peptidomic analysis of human sweat with emphasis on proteolysis. Journal of Proteomics, 155, 40–48.

    Article  CAS  PubMed  Google Scholar 

  33. Aslebagh, R., Channaveerappa, D., Arcaro, K. F., & Darie, C. C. (2018). Proteomics analysis of human breast milk to assess breast cancer risk. Electrophoresis, 39(4), 653–665.

    Article  CAS  PubMed  Google Scholar 

  34. Barbhuiya, M. A., Sahasrabuddhe, N. A., Pinto, S. M., Muthusamy, B., Singh, T. D., Nanjappa, V., et al. (2011). Comprehensive proteomic analysis of human bile. Proteomics, 11(23), 4443–4453.

    Article  CAS  PubMed  Google Scholar 

  35. Schutzer, S. E., Liu, T., Natelson, B. H., Angel, T. E., Schepmoes, A. A., Purvine, S. O., et al. (2010). Establishing the proteome of normal human cerebrospinal fluid. PLoS One, 5(6), e10980.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Bhattacharjee, M., Balakrishnan, L., Renuse, S., Advani, J., Goel, R., Sathe, G., et al. (2016). Synovial fluid proteome in rheumatoid arthritis. Clinical Proteomics, 13, 12–12.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Maud, L., Caroline, M.-D., Florence, C., Alexandra, K., Christophe, B., Yves, V., et al. (2018). Proteomic characterization of human exhaled breath condensate. Journal of Breath Research, 12(2), 021001.

    Article  CAS  Google Scholar 

  38. Hmmier, A., O’Brien, M. E., Lynch, V., Clynes, M., Morgan, R., & Dowling, P. (2017). Proteomic analysis of bronchoalveolar lavage fluid (BALF) from lung cancer patients using label-free mass spectrometry. BBA Clinical, 7, 97–104.

    Google Scholar 

  39. Brunoro, G. V. F., Carvalho, P. C., da Silva Ferreira, A. T., Perales, J., Valente, R. H., de Moura Gallo, C. V., et al. (2015). Proteomic profiling of nipple aspirate fluid (NAF): Exploring the complementarity of different peptide fractionation strategies. Journal of Proteomics, 117, 86–94.

    Article  CAS  PubMed  Google Scholar 

  40. Liu, X., Song, Y., Guo, Z., Sun, W., & Liu, J. (2018). A comprehensive profile and inter-individual variations analysis of the human normal amniotic fluid proteome. Journal of Proteomics, 192, 1–9.

    Article  PubMed  CAS  Google Scholar 

  41. Borgdorff, H., Gautam, R., Armstrong, S. D., Xia, D., Ndayisaba, G. F., van Teijlingen, N. H., et al. (2015). Cervicovaginal microbiome dysbiosis is associated with proteome changes related to alterations of the cervicovaginal mucosal barrier. Mucosal Immunology, 9, 621.

    Article  PubMed  CAS  Google Scholar 

  42. Shen, X., Liu, X., Zhu, P., Zhang, Y., Wang, J., Wang, Y., et al. (2017). Proteomic analysis of human follicular fluid associated with successful in vitro fertilization. Reproductive Biology and Endocrinology, 15(1), 58.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Dutta, S., Chanda, A., Kalita, B., Islam, T., Patra, A., & Mukherjee, A. K. (2017). Proteomic analysis to unravel the complex venom proteome of eastern India Naja naja: Correlation of venom composition with its biochemical and pharmacological properties. Journal of Proteomics, 156, 29–39.

    Article  CAS  PubMed  Google Scholar 

  44. Brinkman, D. L., Jia, X., Potriquet, J., Kumar, D., Dash, D., Kvaskoff, D., et al. (2015). Transcriptome and venom proteome of the box jellyfish Chironex fleckeri. BMC Genomics, 16(1), 407–407.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. Adeola, H. A., Wyk, J. C., Arowolo, A., Ngwanya, R. M., Mkentane, K., & Khumalo, N. P. (2018). Emerging diagnostic and therapeutic potentials of human hair proteomics. Proteomics. Clinical Applications, 12(2), 1700048.

    Article  CAS  Google Scholar 

  46. Adav, S. S., Subbaiaih, R. S., Kerk, S. K., Lee, A. Y., Lai, H. Y., Ng, K. W., et al. (2018). Studies on the proteome of human hair - Identification of histones and Deamidated keratins. Scientific Reports, 8(1), 1599.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. Rice, R. H., Xia, Y., Alvarado, R. J., & Phinney, B. S. (2010). Proteomic analysis of human nail plate. Journal of Proteome Research, 9(12), 6752–6758.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Sawafuji, R., Cappellini, E., Nagaoka, T., Fotakis, A. K., Jersie-Christensen, R. R., Olsen, J. V., et al. (2017). Proteomic profiling of archaeological human bone. Royal Society Open Science, 4(6), 161004.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Jin, P., Wang, K., Huang, C., & Nice, E. C. (2017). Mining the fecal proteome: From biomarkers to personalised medicine. Expert Review of Proteomics, 14(5), 445–459.

    Article  CAS  PubMed  Google Scholar 

  50. Huynh, C., Brunelle, E., Halámková, L., Agudelo, J., & Halámek, J. (2015). Forensic identification of gender from fingerprints. Analytical Chemistry, 87(22), 11531–11536.

    Article  CAS  PubMed  Google Scholar 

  51. Han, X., Aslanian, A., & Yates, J. R. (2008). Mass spectrometry for proteomics. Current Opinion in Chemical Biology, 12(5), 483–490.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Raza, K. (2017). Protein features identification for machine learning-based prediction of protein-protein interactions. bioRxiv. https://doi.org/10.1101/137257

  53. Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., et al. (2000). Gene ontology: Tool for the unification of biology. The gene ontology consortium. Nature Genetics, 25(1), 25–29.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Horgan, R. P., & Kenny, L. C. (2011). ‘Omic’ technologies: Genomics, transcriptomics, proteomics and metabolomics. The Obstetrician & Gynaecologist, 13(3), 189–195.

    Article  Google Scholar 

  55. Tsai, K.-C., Jian, J.-W., Yang, E.-W., Hsu, P.-C., Peng, H.-P., Chen, C.-T., et al. (2012). Prediction of carbohydrate binding sites on protein surfaces with 3-dimensional probability density distributions of interacting atoms. PLoS One, 7(7), e40846.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Ngounou Wetie, A. G., Sokolowska, I., Woods, A. G., Roy, U., Deinhardt, K., & Darie, C. C. (2014). Protein–protein interactions: Switch from classical methods to proteomics and bioinformatics-based approaches. Cellular and Molecular Life Sciences, 71(2), 205–228.

    Article  CAS  PubMed  Google Scholar 

  57. Luck, K., Sheynkman, G. M., Zhang, I., & Vidal, M. (2017). Proteome-scale human Interactomics. Trends in Biochemical Sciences, 42(5), 342–354.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Gilany, K., Lakpour, N., Vafakhah, M., & Sadeghi, M. R. (2011). The profile of human sperm proteome; A mini-review. Journal of Reproduction & Infertility, 12(3), 193–199.

    CAS  Google Scholar 

  59. Santos, A. L., & Lindner, A. B. (2017). Protein posttranslational modifications: Roles in aging and age-related disease. Oxidative Medicine and Cellular Longevity, 2017, 5716409.

    PubMed  PubMed Central  Google Scholar 

  60. Ponomarenko, E. A., Poverennaya, E. V., Ilgisonis, E. V., Pyatnitskiy, M. A., Kopylov, A. T., Zgoda, V. G., et al. (2016). The size of the human proteome: The width and depth. International Journal of Analytical Chemistry, 2016, 7436849.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Theillet, F.-X., Binolfi, A., Frembgen-Kesner, T., Hingorani, K., Sarkar, M., Kyne, C., et al. (2014). Physicochemical properties of cells and their effects on intrinsically disordered proteins (IDPs). Chemical Reviews, 114(13), 6661–6714.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Christians, U., Klawitter, J., Klepacki, J., & Klawitter, J. (2017). Chapter Four - The role of proteomics in the study of kidney diseases and in the development of diagnostic tools. In C. L. Edelstein (Ed.), Biomarkers of kidney disease (2nd ed., pp. 119–223). Boston: Academic Press.

    Chapter  Google Scholar 

  63. Kim, M.-S., Pinto, S. M., Getnet, D., Nirujogi, R. S., Manda, S. S., Chaerkady, R., et al. (2014). A draft map of the human proteome. Nature, 509, 575.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Wilhelm, M., Schlegl, J., Hahne, H., Gholami, A. M., Lieberenz, M., Savitski, M. M., et al. (2014). Mass-spectrometry-based draft of the human proteome. Nature, 509, 582.

    Article  CAS  PubMed  Google Scholar 

  65. Longuespée, R., Casadonte, R., Kriegsmann, M., Pottier, C., Picard de Muller, G., Delvenne, P., et al. (2016). MALDI mass spectrometry imaging: A cutting-edge tool for fundamental and clinical histopathology. Proteomics. Clinical Applications, 10(7), 701–719.

    Article  PubMed  CAS  Google Scholar 

  66. Wang Kevin, C., & Chang Howard, Y. (2018). Epigenomics. Circulation Research, 122(9), 1191–1199.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Crecelius, A. C., Schubert, U. S., & von Eggeling, F. (2015). MALDI mass spectrometric imaging meets “omics”: Recent advances in the fruitful marriage. Analyst, 140(17), 5806–5820.

    Article  CAS  PubMed  Google Scholar 

  68. Thomas, T., Gilbert, J., & Meyer, F. (2012). Metagenomics - a guide from sampling to data analysis. Microbial Informatics and Experimentation, 2(1), 3–3.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Roux, S., Brum, J. R., Dutilh, B. E., Sunagawa, S., Duhaime, M. B., Loy, A., et al. (2016). Ecogenomics and potential biogeochemical impacts of globally abundant ocean viruses. Nature, 537, 689.

    Article  CAS  PubMed  Google Scholar 

  70. Braicu, C., Mehterov, N., Vladimirov, B., Sarafian, V., Nabavi, S., Atanasov, A., et al. (2017). Nutrigenomics in cancer: Revisiting the effects of natural compounds. Seminars in Cancer Biology, 46, 84–106.

    Article  CAS  PubMed  Google Scholar 

  71. Lavertu, A., McInnes, G., Daneshjou, R., Whirl-Carrillo, M., Klein, T. E., & Altman, R. B. (2018). Pharmacogenomics and big genomic data: From lab to clinic and back again. Human Molecular Genetics, 27(R1), R72–R78.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Chan, C. X., & Ragan, M. A. (2013). Next-generation phylogenomics. Biology Direct, 8(1), 3.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Hathout, Y. (2007). Approaches to the study of the cell secretome. Expert Review of Proteomics, 4(2), 239–248.

    Article  CAS  PubMed  Google Scholar 

  74. Romanova, E. V., & Sweedler, J. V. (2015). Peptidomics for the discovery and characterization of neuropeptides and hormones. Trends in Pharmacological Sciences, 36(9), 579–586.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Liu, Y., & Chance, M. R. (2014). Integrating phosphoproteomics in systems biology. Computational and Structural Biotechnology Journal, 10(17), 90–97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Hogrebe, A., von Stechow, L., Bekker-Jensen, D. B., Weinert, B. T., Kelstrup, C. D., & Olsen, J. V. (2018). Benchmarking common quantification strategies for large-scale phosphoproteomics. Nature Communications, 9(1), 1045.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  77. de Oliveira, D. N., de Bona Sartor, S., Ferreira, M. S., & Catharino, R. R. (2013). Cosmetic analysis using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). Materials (Basel Switzerland), 6(3), 1000–1010.

    Article  CAS  Google Scholar 

  78. Becker, J. S. (2013). Imaging of metals in biological tissue by laser ablation inductively coupled plasma mass spectrometry (LA–ICP–MS): state of the art and future developments. Journal of Mass Spectrometry, 48(2), i.

    Article  Google Scholar 

  79. Wolinsky, H. (2010). History in a single hair. EMBO Reports, 11(6), 427–430.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Altuntaş, E., & Schubert, U. S. (2014). “Polymeromics”: Mass spectrometry based strategies in polymer science toward complete sequencing approaches: A review. Analytica Chimica Acta, 808, 56–69.

    Article  PubMed  CAS  Google Scholar 

  81. Houle, D., Govindaraju, D. R., & Omholt, S. (2010). Phenomics: The next challenge. Nature Reviews Genetics, 11, 855.

    Article  CAS  PubMed  Google Scholar 

  82. Fornito, A., & Bullmore, E. T. (2015). Connectomics: A new paradigm for understanding brain disease. European Neuropsychopharmacology, 25(5), 733–748.

    Article  CAS  PubMed  Google Scholar 

  83. Shachuan, F., Zhou, L., Huang, C., Xie, K., & Nice, E. (2015). Interactomics: Toward protein function and regulation. Expert Review of Proteomics, 12(1), 37–60.

    Article  CAS  Google Scholar 

  84. Nalisnik, M., Amgad, M., Lee, S., Halani, S. H., Velazquez Vega, J. E., Brat, D. J., et al. (2017). Interactive phenotyping of large-scale histology imaging data with HistomicsML. Scientific Reports, 7(1), 14588.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  85. Dong, Y., Li, B., & Aharoni, A. (2016). More than Pictures: When MS imaging meets histology. Trends in Plant Science, 21(8), 686–698.

    Article  CAS  PubMed  Google Scholar 

  86. Gustafsson, J. O. R., Oehler, M. K., Ruszkiewicz, A., McColl, S. R., & Hoffmann, P. (2011). MALDI imaging mass spectrometry (MALDI-IMS)—Application of spatial proteomics for ovarian Cancer classification and diagnosis. International Journal of Molecular Sciences, 12(1), 773–794.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Pelaia, G., Terracciano, R., Vatrella, A., Gallelli, L., Busceti, M. T., Calabrese, C., et al. (2014). Application of proteomics and peptidomics to COPD. BioMed Research International, 2014, 764581.

    Article  PubMed  PubMed Central  Google Scholar 

  88. Roberts, A. M., Ward, C. C., & Nomura, D. K. (2017). Activity-based protein profiling for mapping and pharmacologically interrogating proteome-wide ligandable hotspots. Current Opinion in Biotechnology, 43, 25–33.

    Article  CAS  PubMed  Google Scholar 

  89. Joshi, S., Tiwari, A. K., Mondal, B., & Sharma, A. (2011). Oncoproteomics. Clinica Chimica Acta, 412(3), 217–226.

    Article  CAS  Google Scholar 

  90. Abu-Asab, M., Chaouchi, M., & Amri, H. (2006). Phyloproteomics: What phylogenetic analysis reveals about serum proteomics. Cancer Research, 66(8 Suppl), 672.

    Google Scholar 

  91. Nesvizhskii, A. I. (2014). Proteogenomics: Concepts, applications and computational strategies. Nature Methods, 11, 1114.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Barbieri, R., Guryev, V., Brandsma, C.-A., Suits, F., Bischoff, R., & Horvatovich, P. (2016). Proteogenomics: Key driver for clinical discovery and personalized medicine. In Proteogenomics (pp. 21–47). Cham: Springer.

    Chapter  Google Scholar 

  93. Wilmes, P., Heintz-Buschart, A., & Bond, P. L. (2015). A decade of metaproteomics: Where we stand and what the future holds. Proteomics, 15(20), 3409–3417.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Casanovas, A., Sprenger, R. R., Tarasov, K., Ruckerbauer, D. E., Hannibal-Bach, H. K., Zanghellini, J., et al. (2015). Quantitative analysis of proteome and Lipidome dynamics reveals functional regulation of global lipid metabolism. Chemistry & Biology, 22(3), 412–425.

    Article  CAS  Google Scholar 

  95. Jain, K. (2004). Role of pharmacoproteomics in the development of personalized medicine. Pharmacogenomics, 5(3), 331–336.

    Article  CAS  PubMed  Google Scholar 

  96. Cleland, T., & Schroeter, E. (2018). A comparison of common mass spectrometry approaches for paleoproteomics. Journal of Proteome Research, 17, 936–945.

    Article  CAS  PubMed  Google Scholar 

  97. Heeren, R. M. A. (2005). Proteome imaging: A closer look at life’s organization. Proteomics, 5(17), 4316–4326.

    Article  CAS  PubMed  Google Scholar 

  98. Schwamborn, K. (2017). Chapter One - The importance of histology and pathology in mass spectrometry imaging. In R. R. Drake & L. A. McDonnell (Eds.), Advances in cancer research (pp. 1–26). Boston: Academic Press.

    Google Scholar 

  99. Lowe, J. S., & Anderson, P. G. (2015). Chapter 1 - Histology. In J. S. Lowe & P. G. Anderson (Eds.), Stevens & Lowe’s Human histology (4th ed., pp. 1–10). Philadelphia: Mosby.

    Google Scholar 

  100. Alturkistani, H. A., Tashkandi, F. M., & Mohammedsaleh, Z. M. (2016). Histological stains: A literature review and case study. Global Journal of Health Science, 8(3), 72–79.

    Article  Google Scholar 

  101. Müllauer, L. (2017). Milestones in pathology-From histology to molecular biology. Memo, 10(1), 42–45.

    Article  PubMed  PubMed Central  Google Scholar 

  102. Pellicciari, C. (2015). Histochemistry in biology and medicine: A message from the citing journals. European Journal of Histochemistry, 59(4), 2610.

    Article  PubMed  PubMed Central  Google Scholar 

  103. Dubbink, H. J., Deans, Z. C., Tops, B. B. J., van Kemenade, F. J., Koljenović, S., van Krieken, H. J. M., et al. (2014). Next generation diagnostic molecular pathology: Critical appraisal of quality assurance in Europe. Molecular Oncology, 8(4), 830–839.

    Article  PubMed  PubMed Central  Google Scholar 

  104. Kurreck, A., Vandergrift, L. A., Fuss, T. L., Habbel, P., Agar, N. Y. R., & Cheng, L. L. (2017). Prostate cancer diagnosis and characterization with mass spectrometry imaging. Prostate Cancer and Prostatic Diseases. https://doi.org/10.1038/s41391-017-0011-z

    Article  PubMed  PubMed Central  Google Scholar 

  105. Shariatgorji, M., Svenningsson, P., & Andrén, P. E. (2014). Mass spectrometry imaging, an emerging Technology in Neuropsychopharmacology. Neuropsychopharmacology, 39(1), 34–49.

    Article  CAS  PubMed  Google Scholar 

  106. Gessel, M. M., Norris, J. L., & Caprioli, R. M. (2014). MALDI imaging mass spectrometry: Spatial molecular analysis to enable a new age of discovery. Journal of Proteomics, 107, 71–82.

    Article  CAS  PubMed  Google Scholar 

  107. Norris, J. L., & Caprioli, R. M. (2013). Analysis of tissue specimens by matrix-assisted laser desorption/ionization imaging mass spectrometry in biological and clinical research. Chemical Reviews, 113(4), 2309–2342.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Rémi, L., Maximilien, F., Charles, P., Florence, Q.-C., Marie-Alice, M., Dominique, B., et al. (2014). Tissue proteomics for the next decade? Towards a molecular dimension in histology. OMICS: A Journal of Integrative Biology, 18(9), 539–552.

    Article  CAS  Google Scholar 

  109. Prentice, B. M., Caprioli, R. M., & Vuiblet, V. (2017). Label-free molecular imaging of the kidney. Kidney International, 92(3), 580–598.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Grüner, B. M., Hahne, H., Mazur, P. K., Trajkovic-Arsic, M., Maier, S., Esposito, I., et al. (2012). MALDI imaging mass spectrometry for in situ proteomic analysis of preneoplastic lesions in pancreatic cancer. PLoS One, 7(6), e39424.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  111. Li, C., Li, Z., Tuo, Y., Ma, D., Shi, Y., Zhang, Q., et al. (2017). MALDI-TOF MS as a novel tool for the estimation of postmortem interval in liver tissue samples. Scientific Reports, 7, 4887.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  112. Longuespée, R., Casadonte, R., Schwamborn, K., Reuss, D., Kazdal, D., Kriegsmann, K., et al. (2018). Proteomics in pathology. Proteomics, 18(2), 1700361.

    Article  CAS  Google Scholar 

  113. Jin, P., Lan, J., Wang, K., Baker, M. S., Huang, C., & Nice, E. C. (2018). Pathology, proteomics and the pathway to personalised medicine. Expert Review of Proteomics, 15(3), 231–243.

    Article  CAS  PubMed  Google Scholar 

  114. Jones, E. A., Schmitz, N., Waaijer, C. J. F., Frese, C. K., van Remoortere, A., van Zeijl, R. J. M., et al. (2013). Imaging mass spectrometry-based molecular histology differentiates microscopically identical and heterogeneous tumors. Journal of Proteome Research, 12(4), 1847–1855.

    Article  CAS  PubMed  Google Scholar 

  115. Chaurand, P., Sanders, M. E., Jensen, R. A., & Caprioli, R. M. (2004). Proteomics in diagnostic pathology: Profiling and imaging proteins directly in tissue sections. The American Journal of Pathology, 165(4), 1057–1068.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Koga, D., Kusumi, S., Shodo, R., Dan, Y., & Ushiki, T. (2015). High-resolution imaging by scanning electron microscopy of semithin sections in correlation with light microscopy. Microscopy, 64(6), 387–394.

    Article  CAS  PubMed  Google Scholar 

  117. Kiernan, J. A. (2008). Histological and histochemical methods: Theory and practice. Banbury: Scion.

    Google Scholar 

  118. Bolt, M. (2017). Glass: The eye of science. International Journal of Applied Glass Science, 8(1), 4–22.

    Article  Google Scholar 

  119. Li, Y., Li, N., Yu, X., Huang, K., Zheng, T., Cheng, X., et al. (2018). Hematoxylin and eosin staining of intact tissues via delipidation and ultrasound. Scientific Reports, 8(1), 12259.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  120. Rae Buchberger, A., DeLaney, K., Johnson, J., & Li, L. (2018). Mass spectrometry imaging: A review of emerging advancements and future insights. Analytical Chemistry, 90(1), 240–265.

    Article  CAS  Google Scholar 

  121. Iseki, Y., Shibutani, M., Maeda, K., Nagahara, H., Fukuoka, T., Matsutani, S., et al. (2018). A new method for evaluating tumor-infiltrating lymphocytes (TILs) in colorectal cancer using hematoxylin and eosin (H-E)-stained tumor sections. PLoS One, 13(4), e0192744.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  122. Lahiani, A., Klaiman, E., & Grimm, O. (2018). Enabling histopathological annotations on immunofluorescent images through virtualization of hematoxylin and eosin. Journal of Pathology Informatics, 9(1), 1.

    Article  PubMed  PubMed Central  Google Scholar 

  123. Rao, R. S., Patil, S., Majumdar, B., & Oswal, R. G. (2015). Comparison of special stains for keratin with routine hematoxylin and eosin stain. Journal of International Oral Health, 7(3), 1–5.

    PubMed  PubMed Central  Google Scholar 

  124. Oostendorp, C., Uijtdewilligen, P. J. E., Versteeg, E. M., Hafmans, T. G., van den Bogaard, E. H., de Jonge, P. K. J. D., et al. (2016). Visualisation of newly synthesised collagen in vitro and in vivo. Scientific Reports, 6, 18780.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Osman, O. S., Selway, J. L., Harikumar, P. E., Stocker, C. J., Wargent, E. T., Cawthorne, M. A., et al. (2013). A novel method to assess collagen architecture in skin. BMC Bioinformatics, 14, 260.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  126. Bird, B., & Rowlette, J. (2017). A protocol for rapid, label-free histochemical imaging of fibrotic liver. Analyst, 142(8), 1179–1184.

    Article  CAS  PubMed  Google Scholar 

  127. de Jong, S., van Veen, T. A. B., de Bakker, J. M. T., & van Rijen, H. V. M. (2012). Monitoring cardiac fibrosis: A technical challenge. Netherlands Heart Journal, 20(1), 44–48.

    Article  PubMed  Google Scholar 

  128. Marcos-Garcés, V., Molina Aguilar, P., Bea Serrano, C., García Bustos, V., Benavent Seguí, J., Ferrández Izquierdo, A., et al. (2014). Age-related dermal collagen changes during development, maturation and ageing - A morphometric and comparative study. Journal of Anatomy, 225(1), 98–108.

    Article  PubMed  PubMed Central  Google Scholar 

  129. Krishna, M. (2013). Role of special stains in diagnostic liver pathology. Clinical Liver Disease, 2(S1), S8–S10.

    Article  PubMed  PubMed Central  Google Scholar 

  130. Chen, Y., Yu, Q., & Xu, C.-B. (2017). A convenient method for quantifying collagen fibers in atherosclerotic lesions by ImageJ software (Vol. 10, pp. 14927–14935).

    Google Scholar 

  131. Harvey, A., Cole, L. M., Day, R., Bartlett, M., Warwick, J., Bojar, R., et al. (2016). MALDI-MSI for the analysis of a 3D tissue-engineered psoriatic skin model. Proteomics, 16(11–12), 1718–1725.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Segnani, C., Ippolito, C., Antonioli, L., Pellegrini, C., Blandizzi, C., Dolfi, A., et al. (2015). Histochemical detection of collagen fibers by sirius red/fast green is more sensitive than van Gieson or sirius red alone in normal and inflamed rat colon. PLoS One, 10(12), e0144630.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  133. Bhutda, S., Surve, M. V., Anil, A., Kamath, K. G., Singh, N., Modi, D., et al. (2017). Histochemical staining of collagen and identification of its subtypes by picrosirius red dye in mouse reproductive tissues. Bio-protocol, 7(21), e2592.

    Article  PubMed  PubMed Central  Google Scholar 

  134. Winkler, M., Shoa, G., Tran, S. T., Xie, Y., Thomasy, S., Raghunathan, V. K., et al. (2015). A comparative study of vertebrate corneal structure: The evolution of a refractive Lens. Investigative Ophthalmology & Visual Science, 56(4), 2764–2772.

    Article  CAS  Google Scholar 

  135. Neagu, A.-N., & Petraru, O. M. (2015). “Aquatic” vs. “terrestrial” eye design. A functional ecomorphological approach. Analele Stiintifice Universitatii Al. I. Cuza Iasi Seria Biologie Animala, LXI, 101–115.

    Google Scholar 

  136. Ryu, S., Pepper, R. E., Nagai, M., & France, D. C. (2016). Vorticella: A protozoan for bio-inspired engineering. Micromachines, 8(1), 4.

    Article  PubMed Central  Google Scholar 

  137. Wassarman, P. M. (2008). Zona pellucida glycoproteins. The Journal of Biological Chemistry, 283(36), 24285–24289.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Adisa, A., Udeabor, S., Kubesch, A., Barbeck, M., & Ghanaati, S. (2016). The utility of azan trichrome staining in Ameloblastoma. Nigerian Postgraduate Medical Journal, 23(1), 44–46.

    Article  Google Scholar 

  139. Spicer, S., & Lillie, R. D. (1961). Histochemical identification of basic proteins with Biebrich Scarlet at alkaline pH. Stain Technology, 36, 365–370.

    Article  CAS  Google Scholar 

  140. Rajamohamedsait, H. B., & Sigurdsson, E. M. (2012). Histological staining of amyloid and pre-amyloid peptides and proteins in mouse tissue. Methods in Molecular Biology (Clifton, N.J.), 849, 411–424.

    Article  CAS  Google Scholar 

  141. Liebmann, T., Renier, N., Bettayeb, K., Greengard, P., Tessier-Lavigne, M., & Flajolet, M. (2016). Three-dimensional study of Alzheimer’s disease hallmarks using the iDISCO clearing method. Cell Reports, 16(4), 1138–1152.

    Article  CAS  PubMed  Google Scholar 

  142. Baumann, B., Woehrer, A., Ricken, G., Augustin, M., Mitter, C., Pircher, M., et al. (2017). Visualization of neuritic plaques in Alzheimer’s disease by polarization-sensitive optical coherence microscopy. Scientific Reports, 7, 43477.

    Article  PubMed  PubMed Central  Google Scholar 

  143. Wu, C., Scott, J., & Shea, J.-E. (2012). Binding of Congo red to amyloid protofibrils of the Alzheimer Aβ(9-40) peptide probed by molecular dynamics simulations. Biophysical Journal, 103(3), 550–557.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. Luna, J., Peralta-Ramirez, J., & Mena, R. (2008). P4-156: Thiazin red is a sensitive and accurate marker for the fast diagnosis of Alzheimer’s disease in nonfixed brain tissue in touch imprints preparations. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 4(4), T716.

    Google Scholar 

  145. Ly, P. T. T., Cai, F., & Song, W. (2011). Detection of neuritic plaques in Alzheimer’s disease mouse model. Journal of Visualized Experiments : JoVE, (53), 2831.

    Google Scholar 

  146. Chan, K. J. (2014). The wonderful colors of the hematoxylin-eosin stain in diagnostic surgical pathology. International Journal of Surgical Pathology, 22, 12–32.

    Article  PubMed  Google Scholar 

  147. Azevedo Tosta, T. A., Neves, L. A., & do Nascimento, M. Z. (2017). Segmentation methods of H&E-stained histological images of lymphoma: A review. Informatics in Medicine Unlocked, 9, 35–43.

    Article  Google Scholar 

  148. Kuru, K. (2014). Optimization and enhancement of H&E stained microscopical images by applying bilinear interpolation method on lab color mode. Theoretical Biology & Medical Modelling, 11, 9.

    Article  Google Scholar 

  149. Kherlopian, A. R., Song, T., Duan, Q., Neimark, M. A., Po, M. J., Gohagan, J. K., et al. (2008). A review of imaging techniques for systems biology. BMC Systems Biology, 2, 74.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  150. Garini, Y., Vermolen, B. J., & Young, I. T. (2005). From micro to nano: Recent advances in high-resolution microscopy. Current Opinion in Biotechnology, 16(1), 3–12.

    Article  CAS  PubMed  Google Scholar 

  151. Shoemaker, S. C., & Ando, N. (2018). X-rays in the cryo-electron microscopy era: Structural biology’s dynamic future. Biochemistry, 57(3), 277–285.

    Article  CAS  PubMed  Google Scholar 

  152. Centonze Frohlich, V. (2008). Phase contrast and differential interference contrast (DIC) microscopy. Journal of Visualized Experiments : JoVE, (17), 844.

    Google Scholar 

  153. Liu, Y., Gonen, S., Gonen, T., & Yeates, T. O. (2018). Near-atomic cryo-EM imaging of a small protein displayed on a designed scaffolding system. Proceedings of the National Academy of Sciences of the United States of America, 115(13), 3362–3367.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Monroe, E. B., Annangudi, S. P., Hatcher, N. G., Gutstein, H. B., Rubakhin, S. S., & Sweedler, J. V. (2008). SIMS and MALDI MS imaging of the spinal cord. Proteomics, 8(18), 3746–3754.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  155. Dilillo, M., Pellegrini, D., Ait-Belkacem, R., de Graaf, E. L., Caleo, M., & McDonnell, L. A. (2017). Mass spectrometry imaging, laser capture microdissection, and LC-MS/MS of the same tissue section. Journal of Proteome Research, 16(8), 2993–3001.

    Article  CAS  PubMed  Google Scholar 

  156. Taverna, D., Boraldi, F., De Santis, G., Caprioli, R. M., & Quaglino, D. (2015). Histology-directed and imaging mass spectrometry: An emerging technology in ectopic calcification. Bone, 74, 83–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Enthaler, B., Trusch, M., Fischer, M., Rapp, C., Pruns, J. K., & Vietzke, J.-P. (2013). MALDI imaging in human skin tissue sections: Focus on various matrices and enzymes. Analytical and Bioanalytical Chemistry, 405(4), 1159–1170.

    Article  CAS  PubMed  Google Scholar 

  158. Walch, A., Rauser, S., Deininger, S.-O., & Höfler, H. (2008). MALDI imaging mass spectrometry for direct tissue analysis: A new frontier for molecular histology. Histochemistry and Cell Biology, 130(3), 421–434.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  159. Franck, J., Arafah, K., Elayed, M., Bonnel, D., Vergara, D., Jacquet, A., et al. (2009). MALDI imaging mass spectrometry: State of the art technology in clinical proteomics. Molecular & Cellular Proteomics, 8(9), 2023–2033.

    Article  CAS  Google Scholar 

  160. Lazova, R., Seeley, E. H., Kutzner, H., Scolyer, R. A., Scott, G., Cerroni, L., et al. (2016). Imaging mass spectrometry assists in the classification of diagnostically challenging atypical Spitzoid neoplasms. Journal of the American Academy of Dermatology, 75(6), 1176–1186.e4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  161. He, L., Long, L. R., Antani, S., & Thoma, G. R. (2012). Histology image analysis for carcinoma detection and grading. Computer Methods and Programs in Biomedicine, 107(3), 538–556.

    Article  PubMed  PubMed Central  Google Scholar 

  162. Acar, E., Plopper, G. E., & Yener, B. (2012). Coupled analysis of in vitro and histology tissue samples to quantify structure-function relationship. PLoS One, 7(3), e32227.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  163. Lavis, L. D. (2011). Histochemistry: Live and in color. Journal of Histochemistry and Cytochemistry, 59(2), 139–145.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Rizzo, M. A., Davidson, M. W., & Piston, D. W. (2009). Fluorescent protein tracking and detection: Fluorescent protein structure and color variants. Cold Spring Harbor Protocols, 2009(12), pdb.top63.

    Article  PubMed  Google Scholar 

  165. Lev, R., & Gerard, A. (1967). The histochemical demonstration of protein in epithelial mucins. Journal of the Royal Microscopical Society, 87(3–4), 361–373.

    Article  CAS  PubMed  Google Scholar 

  166. Fujino, Y., Minamizaki, T., Yoshioka, H., Okada, M., & Yoshiko, Y. (2016). Imaging and mapping of mouse bone using MALDI-imaging mass spectrometry. Bone Reports, 5, 280–285.

    Article  PubMed  PubMed Central  Google Scholar 

  167. Žnidaršič, N., Mrak, P., Rajh, E., Soderžnik, K. Ž., Čeh, M., & Štrus, J. (2018). Cuticle matrix imaging by histochemistry, fluorescence, and electron microscopy. Resolution and Discovery, 3(1), 5–12.

    Article  Google Scholar 

  168. Halabi, C. M., & Mecham, R. P. (2018). Chapter 12 - Elastin purification and solubilization. In R. P. Mecham (Ed.), Methods in cell biology (pp. 207–222). Boston: Academic Press.

    Google Scholar 

  169. Percival, K. R., & Radi, Z. A. (2016). A modified Verhoeff-Van Gieson elastin histochemical stain to enable pulmonary arterial hypertension model characterization. European Journal of Histochemistry : EJH, 60(1), 2588.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  170. Bloemberg, D., & Quadrilatero, J. (2012). Rapid determination of myosin heavy chain expression in rat, mouse, and human skeletal muscle using multicolor immunofluorescence analysis. PLoS One, 7(4), e35273.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  171. Gkantidis, N., Blumer, S., Katsaros, C., Graf, D., & Chiquet, M. (2012). Site-specific expression of Gelatinolytic activity during morphogenesis of the secondary palate in the mouse embryo. PLoS One, 7(10), e47762.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  172. de Souza Guerra, C., Carla Lara Pereira, Y., Issa, J., Galisteu Luiz, K., Del Bel Guimaraes, E. A., Gerlach, R. F., et al. (2014). Histological, histochemical, and protein changes after induced malocclusion by occlusion alteration of Wistar rats. BioMed Research International, 2014, 10.

    Article  Google Scholar 

  173. Babii, C., Bahrin, L. G., Neagu, A.-N., Gostin, I., Mihasan, M., Birsa, L. M., et al. (2016). Antibacterial activity and proposed action mechanism of a new class of synthetic tricyclic flavonoids. Journal of Applied Microbiology, 120(3), 630–637.

    Article  CAS  PubMed  Google Scholar 

  174. Babii, C., Mihalache, G., Bahrin, L. G., Neagu, A.-N., Gostin, I., Mihai, C. T., et al. (2018). A novel synthetic flavonoid with potent antibacterial properties: In vitro activity and proposed mode of action. PLoS One, 13(4), e0194898.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  175. Boyd, V., Cholewa, O. M., & Papas, K. K. (2008). Limitations in the use of fluorescein diacetate/Propidium iodide (FDA/PI) and cell permeable nucleic acid stains for viability measurements of isolated islets of Langerhans. Current Trends in Biotechnology and Pharmacy, 2(2), 66–84.

    PubMed  PubMed Central  Google Scholar 

  176. Oyejide, L., Mendes, O. R., & Mikaelian, I. (2013). Chapter 10 - Molecular pathology: Applications in nonclinical drug development. In A. S. Faqi (Ed.), A comprehensive guide to toxicology in preclinical drug development (pp. 237–276). Boston: Academic Press.

    Chapter  Google Scholar 

  177. Chen, X., Velliste, M., & Murphy, R. F. (2006). Automated interpretation of subcellular patterns in fluorescence microscope images for location proteomics. Cytometry. Part A : The Journal Of The International Society For Analytical Cytology, 69(7), 631–640.

    Article  CAS  Google Scholar 

  178. Kamiyama, D., Sekine, S., Barsi-Rhyne, B., Hu, J., Chen, B., Gilbert, L. A., et al. (2016). Versatile protein tagging in cells with split fluorescent protein. Nature Communications, 7, 11046.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  179. Ghisaidoobe, A. B. T., & Chung, S. J. (2014). Intrinsic tryptophan fluorescence in the detection and analysis of proteins: A focus on Förster resonance energy transfer techniques. International Journal of Molecular Sciences, 15(12), 22518–22538.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  180. Niyangoda, C., Miti, T., Breydo, L., Uversky, V., & Muschol, M. (2017). Carbonyl-based blue autofluorescence of proteins and amino acids. PLoS One, 12(5), e0176983.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  181. Deeb, S., Nesr, K. H., Mahdy, E., Badawey, M., & Badei, M. (2008). Autofluorescence of routinely hematoxylin and eosin-stained sections without exogenous markers. African Journal of Biotechnology, 7.

    Google Scholar 

  182. Croce, A. C., & Bottiroli, G. (2014). Autofluorescence spectroscopy and imaging: A tool for biomedical research and diagnosis. European Journal of Histochemistry : EJH, 58(4), 2461.

    CAS  PubMed  PubMed Central  Google Scholar 

  183. Duraiyan, J., Govindarajan, R., Kaliyappan, K., & Palanisamy, M. (2012). Applications of immunohistochemistry. Journal of Pharmacy & Bioallied Sciences, 4(Suppl 2), S307–S309.

    Google Scholar 

  184. Robertson, D., Savage, K., Reis-Filho, J. S., & Isacke, C. M. (2008). Multiple immunofluorescence labelling of formalin-fixed paraffin-embedded (FFPE) tissue. BMC Cell Biology, 9, 13.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  185. Duncan, S. M., & Seigel, G. M. (2016). High-contrast enzymatic immunohistochemistry of pigmented tissues. Journal of Biological Methods, 3(3), e47.

    Article  PubMed  PubMed Central  Google Scholar 

  186. Lai, H. M., Ng, W.-L., Gentleman, S. M., & Wu, W. (2017). Chemical probes for visualizing intact animal and human brain tissue. Cell Chemical Biology, 24(6), 659–672.

    Article  CAS  PubMed  Google Scholar 

  187. Paulson, J. B., Ramsden, M., Forster, C., Sherman, M. A., McGowan, E., & Ashe, K. H. (2008). Amyloid plaque and neurofibrillary tangle pathology in a regulatable mouse model of Alzheimer’s disease. The American Journal of Pathology, 173(3), 762–772.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  188. Jarero-Basulto, J. J., Luna-Muñoz, J., Mena, R., Kristofikova, Z., Ripova, D., Perry, G., et al. (2013). Proteolytic cleavage of polymeric tau protein by caspase-3: Implications for Alzheimer disease. Journal of Neuropathology & Experimental Neurology, 72(12), 1145–1161.

    Article  CAS  Google Scholar 

  189. Morawski, M., Kirilina, E., Scherf, N., Jäger, C., Reimann, K., Trampel, R., et al. (2017). Developing 3D microscopy with CLARITY on human brain tissue: Towards a tool for informing and validating MRI-based histology. NeuroImage, 182, 417–428.

    Article  PubMed  Google Scholar 

  190. Hynes, R. O., & Zhao, Q. (2000). The evolution of cell adhesion. The Journal of Cell Biology, 150(2), F89–F96.

    Article  CAS  PubMed  Google Scholar 

  191. Heintz, T. G., Eva, R., & Fawcett, J. W. (2016). Regional regulation of Purkinje cell dendritic spines by Integrins and Eph/Ephrins. PLoS One, 11(8), e0158558.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  192. Shahrabi-Farahani, S., Wang, L., Zwaans, B. M. M., Santana, J. M., Shimizu, A., Takashima, S., et al. (2014). Neuropilin 1 expression correlates with differentiation status of epidermal cells and cutaneous squamous cell carcinomas. Laboratory Investigation, 94(7), 752–765.

    Article  CAS  PubMed  Google Scholar 

  193. Taverna, D., Nanney, L. B., Pollins, A. C., Sindona, G., & Caprioli, R. (2011). Spatial mapping by imaging mass spectrometry offers advancements for rapid definition of human skin proteomic signatures. Experimental Dermatology, 20(8), 642–647.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  194. Angel, P. M., Comte-Walters, S., Ball, L. E., Talbot, K., Mehta, A., Brockbank, K. G. M., et al. (2018). Mapping extracellular matrix proteins in formalin-fixed, paraffin-embedded tissues by MALDI imaging mass spectrometry. Journal of Proteome Research, 17(1), 635–646.

    Article  CAS  PubMed  Google Scholar 

  195. Yamamoto, T., Hasegawa, T., Yamamoto, T., Hongo, H., & Amizuka, N. (2016). Histology of human cementum: Its structure, function, and development. Japanese Dental Science Review, 52(3), 63–74.

    Article  Google Scholar 

  196. Senbanjo, L. T., & Chellaiah, M. A. (2017). CD44: A multifunctional cell surface adhesion receptor is a regulator of progression and metastasis of cancer cells. Frontiers in Cell and Developmental Biology, 5, 18.

    Article  PubMed  PubMed Central  Google Scholar 

  197. Forest, F., Thuret, G., Gain, P., Dumollard, J.-M., Peoc’h, M., Perrache, C., et al. (2015). Optimization of immunostaining on flat-mounted human corneas. Molecular Vision, 21, 1345–1356.

    CAS  PubMed  PubMed Central  Google Scholar 

  198. He, Z., Campolmi, N., Ha Thi, B.-M., Dumollard, J.-M., Peoc’h, M., Garraud, O., et al. (2011). Optimization of immunolocalization of cell cycle proteins in human corneal endothelial cells. Molecular Vision, 17, 3494–3511.

    CAS  PubMed  PubMed Central  Google Scholar 

  199. He, Z., Forest, F., Gain, P., Rageade, D., Bernard, A., Acquart, S., et al. (2016). 3D map of the human corneal endothelial cell. Scientific Reports, 6, 29047.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  200. Ren, S., Liu, T., Jia, C., Qi, X., & Wang, Y. (2010). Physiological expression of lens α-, β-, and γ-crystallins in murine and human corneas. Molecular vision (Vol. 16, pp. 2745–2752).

    Google Scholar 

  201. Chucair-Elliott, A. J., Zheng, M., & Carr, D. J. J. (2015). Degeneration and regeneration of corneal nerves in response to HSV-1 infection. Investigative Ophthalmology & Visual Science, 56(2), 1097–1107.

    Article  CAS  Google Scholar 

  202. Wilsbacher, L. D., & Coughlin, S. R. (2015). Analysis of cardiomyocyte development using immunofluorescence in embryonic mouse heart. Journal of Visualized Experiments : JoVE, (97), 52644.

    Google Scholar 

  203. Sitaram, P., Hainline, S. G., & Lee, L. A. (2014). Cytological analysis of spermatogenesis: Live and fixed preparations of Drosophila testes. Journal of Visualized Experiments : JoVE, (83), e51058.

    Google Scholar 

  204. Montgomery, S. C., & Cox, B. C. (2016). Whole mount dissection and immunofluorescence of the adult mouse cochlea. Journal of Visualized Experiments : JoVE, (107), 53561.

    Google Scholar 

  205. Pellicciari, C. (2016). Is there still room for novelty, in histochemical papers? European Journal of Histochemistry : EJH, 60(4), 2758.

    PubMed  PubMed Central  Google Scholar 

  206. Siegerist, F., Endlich, K., & Endlich, N. (2018). Novel microscopic techniques for podocyte research. Frontiers in Endocrinology, 9, 379.

    Article  PubMed  PubMed Central  Google Scholar 

  207. Fritzky, L., & Lagunoff, D. (2013). Advanced methods in fluorescence microscopy. Analytical Cellular Pathology (Amsterdam), 36(1–2), 5–17.

    Article  CAS  Google Scholar 

  208. Wallrabe, H., & Periasamy, A. (2005). Imaging protein molecules using FRET and FLIM microscopy. Current Opinion in Biotechnology, 16(1), 19–27.

    Article  CAS  PubMed  Google Scholar 

  209. Kollmannsperger, A., Sharei, A., Raulf, A., Heilemann, M., Langer, R., Jensen, K. F., et al. (2016). Live-cell protein labelling with nanometre precision by cell squeezing. Nature Communications, 7, 10372.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  210. Stehbens, S., Pemble, H., Murrow, L., & Wittmann, T. (2012). Imaging intracellular protein dynamics by spinning disk confocal microscopy. Methods in Enzymology, 504, 293–313.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  211. Chozinski, T. J., Gagnon, L. A., & Vaughan, J. C. (2014). Twinkle, twinkle little star: Photoswitchable fluorophores for super-resolution imaging. FEBS Letters, 588(19), 3603–3612.

    Article  CAS  PubMed  Google Scholar 

  212. Sydor, A. M., Czymmek, K. J., Puchner, E. M., & Mennella, V. (2015). Super-resolution microscopy: From single molecules to supramolecular assemblies. Trends in Cell Biology, 25(12), 730–748.

    Article  CAS  PubMed  Google Scholar 

  213. Cox, S. (2015). Super-resolution imaging in live cells. Developmental Biology, 401(1), 175–181.

    Article  CAS  PubMed  Google Scholar 

  214. Galbraith, C. G., & Galbraith, J. A. (2011). Super-resolution microscopy at a glance. Journal of Cell Science, 124(Pt 10), 1607–1611.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  215. Hell, S. W., & Wichmann, J. (1994). Breaking the diffraction resolution limit by stimulated emission: Stimulated-emission-depletion fluorescence microscopy. Optics Letters, 19(11), 780–782.

    Article  CAS  PubMed  Google Scholar 

  216. Bianchini, P., Peres, C., Oneto, M., Galiani, S., Vicidomini, G., & Diaspro, A. (2015). STED nanoscopy: A glimpse into the future. Cell and Tissue Research, 360(1), 143–150.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  217. Kempf, C., Staudt, T., Bingen, P., Horstmann, H., Engelhardt, J., Hell, S. W., et al. (2013). Tissue multicolor STED nanoscopy of presynaptic proteins in the calyx of held. PLoS One, 8(4), e62893.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  218. Huang, B., Jones, S. A., Brandenburg, B., & Zhuang, X. (2008). Whole-cell 3D STORM reveals interactions between cellular structures with nanometer-scale resolution. Nature Methods, 5(12), 1047–1052.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  219. Bates, M., Jones, S. A., & Zhuang, X. (2013). Stochastic optical reconstruction microscopy (STORM): A method for superresolution fluorescence imaging. Cold Spring Harbor Protocols, 2013(6), pdb.top075143.

    Article  PubMed  Google Scholar 

  220. Zhang, J., Carver, C. M., Choveau, F. S., & Shapiro, M. S. (2016). Clustering and functional coupling of diverse ion channels and signaling proteins revealed by super-resolution STORM microscopy in neurons. Neuron, 92(2), 461–478.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  221. Ke, M.-T., Nakai, Y., Fujimoto, S., Takayama, R., Yoshida, S., Kitajima, T. S., et al. (2016). Super-resolution mapping of neuronal circuitry with an index-optimized clearing agent. Cell Reports, 14(11), 2718–2732.

    Article  CAS  PubMed  Google Scholar 

  222. Loussert Fonta, C., Leis, A., Mathisen, C., Bouvier, D. S., Blanchard, W., Volterra, A., et al. (2015). Analysis of acute brain slices by electron microscopy: A correlative light–electron microscopy workflow based on Tokuyasu cryo-sectioning. Journal of Structural Biology, 189(1), 53–61.

    Article  PubMed  Google Scholar 

  223. Nickerson, A., Huang, T., Lin, L.-J., & Nan, X. (2014). Photoactivated localization microscopy with bimolecular fluorescence complementation (BiFC-PALM) for nanoscale imaging of protein-protein interactions in cells. PLoS One, 9(6), e100589.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  224. Moore, T. I., Aaron, J., Chew, T.-L., & Springer, T. A. (2018). Measuring integrin conformational change on the cell surface with super-resolution microscopy. Cell Reports, 22(7), 1903–1912.

    Article  CAS  PubMed  Google Scholar 

  225. Schnorrenberg, S., Grotjohann, T., Vorbrüggen, G., Herzig, A., Hell, S. W., & Jakobs, S. (2016). In vivo super-resolution RESOLFT microscopy of Drosophila melanogaster. eLife, 5, e15567.

    Article  PubMed  PubMed Central  Google Scholar 

  226. Lavoie-Cardinal, F., Jensen, N. A., Westphal, V., Stiel, A. C., Chmyrov, A., Bierwagen, J., et al. (2014). Two-color RESOLFT Nanoscopy with Green and red fluorescent photochromic proteins. Chemphyschem, 15(4), 655–663.

    Article  CAS  PubMed  Google Scholar 

  227. Godin, A. G., Lounis, B., & Cognet, L. (2014). Super-resolution microscopy approaches for live cell imaging. Biophysical Journal, 107(8), 1777–1784.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  228. Nahidiazar, L., Agronskaia, A. V., Broertjes, J., van den Broek, B., & Jalink, K. (2016). Optimizing imaging conditions for demanding multi-color super resolution localization microscopy. PLoS One, 11(7), e0158884.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  229. Choquet, D. (2014). The 2014 Nobel prize in chemistry: A large-scale prize for achievements on the nanoscale. Neuron, 84(6), 1116–1119.

    Article  CAS  PubMed  Google Scholar 

  230. Stahley, S. N., Warren, M. F., Feldman, R. J., Swerlick, R. A., Mattheyses, A. L., & Kowalczyk, A. P. (2016). Super-resolution microscopy reveals altered desmosomal protein organization in tissue from patients with Pemphigus Vulgaris. The Journal of Investigative Dermatology, 136(1), 59–66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  231. Stahley, S. N., Bartle, E. I., Atkinson, C. E., Kowalczyk, A. P., & Mattheyses, A. L. (2016). Molecular organization of the desmosome as revealed by direct stochastic optical reconstruction microscopy. Journal of Cell Science, 129(15), 2897–2904.

    CAS  PubMed  PubMed Central  Google Scholar 

  232. Shelden, E. A., Colburn, Z. T., & Jones, J. C. R. (2016). Focusing super resolution on the cytoskeleton. F1000Research, 5, F1000 Faculty Rev-998.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  233. Nahidiazar, L., Kreft, M., van den Broek, B., Secades, P., Manders, E. M. M., Sonnenberg, A., et al. (2015). The molecular architecture of hemidesmosomes, as revealed with super-resolution microscopy. Journal of Cell Science, 128(20), 3714–3719.

    CAS  PubMed  Google Scholar 

  234. Grebe, S. K. G., & Singh, R. J. (2011). LC-MS/MS in the clinical laboratory – Where to from Here? The Clinical Biochemist Reviews, 32(1), 5–31.

    PubMed  PubMed Central  Google Scholar 

  235. Addie, R. D., Balluff, B., Bovée, J. V. M. G., Morreau, H., & McDonnell, L. A. (2015). Current state and future challenges of mass spectrometry imaging for clinical research. Analytical Chemistry, 87(13), 6426–6433.

    Article  CAS  PubMed  Google Scholar 

  236. Caprioli, R. M., Farmer, T. B., & Gile, J. (1997). Molecular imaging of biological samples: Localization of peptides and proteins using MALDI-TOF MS. Analytical Chemistry, 69(23), 4751–4760.

    Article  CAS  PubMed  Google Scholar 

  237. Schwamborn, K., & Caprioli, R. M. (2010). MALDI imaging mass spectrometry – Painting molecular pictures. Molecular Oncology, 4(6), 529–538.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  238. Maier, S. K., Hahne, H., Gholami, A. M., Balluff, B., Meding, S., Schoene, C., et al. (2013). Comprehensive identification of proteins from MALDI imaging. Molecular & Cellular Proteomics, 12(10), 2901–2910.

    Article  CAS  Google Scholar 

  239. Mourino-Alvarez, L., Iloro, I., de la Cuesta, F., Azkargorta, M., Sastre-Oliva, T., Escobes, I., et al. (2016). MALDI-imaging mass spectrometry: A step forward in the anatomopathological characterization of stenotic aortic valve tissue. Scientific Reports, 6, 27106.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  240. Yajima, Y., Hiratsuka, T., Kakimoto, Y., Ogawa, S., Shima, K., Yamazaki, Y., et al. (2018). Region of interest analysis using mass spectrometry imaging of mitochondrial and sarcomeric proteins in acute cardiac infarction tissue. Scientific Reports, 8(1), 7493.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  241. Heijs, B., Tolner, E. A., Bovée, J. V. M. G., van den Maagdenberg, A. M. J. M., & McDonnell, L. A. (2015). Brain region-specific dynamics of on-tissue protein digestion using MALDI mass spectrometry imaging. Journal of Proteome Research, 14(12), 5348–5354.

    Article  CAS  PubMed  Google Scholar 

  242. Wisztorski, M., Croix, D., Macagno, E., Fournier, I., & Salzet, M. (2008). Molecular MALDI imaging: An emerging technology for neuroscience studies. Developmental Neurobiology, 68(6), 845–858.

    Article  CAS  PubMed  Google Scholar 

  243. Toss, A., De Matteis, E., Rossi, E., Casa, L. D., Iannone, A., Federico, M., et al. (2013). Ovarian cancer: Can proteomics give new insights for therapy and diagnosis? International Journal of Molecular Sciences, 14(4), 8271–8290.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  244. Chughtai, K., & Heeren, R. M. A. (2010). Mass spectrometric imaging for biomedical tissue analysis. Chemical Reviews, 110(5), 3237–3277.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  245. Arentz, G., Mittal, P., Zhang, C., Ho, Y. Y., Briggs, M., Winderbaum, L., et al. (2017). Chapter Two - Applications of mass spectrometry imaging to cancer. In R. R. Drake & L. A. McDonnell (Eds.), Advances in cancer research (pp. 27–66). Boston: Academic Press.

    Google Scholar 

  246. Seeley, E. H., & Caprioli, R. M. (2012). 3D imaging by mass spectrometry: A new frontier. Analytical Chemistry, 84(5), 2105–2110.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  247. Spraggins, J. M., Rizzo, D. G., Moore, J. L., Noto, M. J., Skaar, E. P., & Caprioli, R. M. (2016). Next-generation technologies for spatial proteomics: Integrating ultra-high speed MALDI-TOF and high mass resolution MALDI FTICR imaging mass spectrometry for protein analysis. Proteomics, 16(11–12), 1678–1689.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  248. Angel, P. M., Baldwin, H. S., Gottlieb, D., Su, Y. R., Mayer, J. E., Bichell, D., et al. (2017). Advances in MALDI imaging mass spectrometry of proteins in cardiac tissue, including the heart valve. Biochimica et Biophysica Acta, 1865(7), 927–935.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  249. Grassl, J., Taylor, N. L., & Millar, A. (2011). Matrix-assisted laser desorption/ionisation mass spectrometry imaging and its development for plant protein imaging. Plant Methods, 7(1), 21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  250. Francese, S., Bradshaw, R., Flinders, B., Mitchell, C., Bleay, S., Cicero, L., et al. (2013). Curcumin: A multipurpose matrix for MALDI mass spectrometry imaging applications. Analytical Chemistry, 85(10), 5240–5248.

    Article  CAS  PubMed  Google Scholar 

  251. Baker, T. C., Han, J., & Borchers, C. H. (2017). Recent advancements in matrix-assisted laser desorption/ionization mass spectrometry imaging. Current Opinion in Biotechnology, 43, 62–69.

    Article  CAS  PubMed  Google Scholar 

  252. Schubert, K. O., Weiland, F., Baune, B. T., & Hoffmann, P. (2016). The use of MALDI-MSI in the investigation of psychiatric and neurodegenerative disorders: A review. Proteomics, 16(11–12), 1747–1758.

    Article  CAS  PubMed  Google Scholar 

  253. Franck, J., Longuespée, R., Wisztorski, M., Van Remoortere, A., Van Zeijl, R., Deelder, A., et al. (2010). MALDI mass spectrometry imaging of proteins exceeding 30,000 daltons. Medical Science Monitor, 16, BR293–BR299.

    CAS  PubMed  Google Scholar 

  254. van Remoortere, A., van Zeijl, R. J. M., van den Oever, N., Franck, J., Longuespée, R., Wisztorski, M., et al. (2010). MALDI imaging and profiling MS of higher mass proteins from tissue. Journal of the American Society for Mass Spectrometry, 21(11), 1922–1929.

    Article  PubMed  CAS  Google Scholar 

  255. Anderson, D. M. G., Floyd, K. A., Barnes, S., Clark, J. M., Clark, J. I., McHaourab, H., et al. (2015). A method to prevent protein delocalization in imaging mass spectrometry of non-adherent tissues: Application to small vertebrate lens imaging. Analytical and Bioanalytical Chemistry, 407(8), 2311–2320.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  256. Fico, D., Margapoti, E., Pennetta, A., & De Benedetto, G. E. (2018). An enhanced GC/MS procedure for the identification of proteins in paint microsamples. Journal of Analytical Methods in Chemistry, 2018, 8.

    Article  CAS  Google Scholar 

  257. Pitt, J. J. (2009). Principles and applications of liquid chromatography-mass spectrometry in clinical biochemistry. The Clinical Biochemist Reviews, 30(1), 19–34.

    PubMed  PubMed Central  Google Scholar 

  258. Pirman, D. A., Reich, R. F., Kiss, A., Heeren, R. M. A., & Yost, R. A. (2013). Quantitative MALDI tandem mass spectrometric imaging of cocaine from brain tissue with a deuterated internal standard. Analytical Chemistry, 85(2), 1081–1089.

    Article  CAS  PubMed  Google Scholar 

  259. Wilson, I. D. (2011). High-performance liquid chromatography-mass spectrometry (HPLC-MS)-based drug metabolite profiling. In T. O. Metz (Ed.), Metabolic profiling: Methods and protocols (pp. 173–190). Totowa: Humana Press.

    Chapter  Google Scholar 

  260. Li, M., Hou, X.-F., Zhang, J., Wang, S.-C., Fu, Q., & He, L.-C. (2011). Applications of HPLC/MS in the analysis of traditional Chinese medicines. Journal of Pharmaceutical Analysis, 1(2), 81–91.

    Article  CAS  PubMed  Google Scholar 

  261. Busardò, F. P., Kyriakou, C., Marchei, E., Pacifici, R., Pedersen, D. S., & Pichini, S. (2017). Ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC–MS/MS) for determination of GHB, precursors and metabolites in different specimens: Application to clinical and forensic cases. Journal of Pharmaceutical and Biomedical Analysis, 137, 123–131.

    Article  PubMed  CAS  Google Scholar 

  262. Lachat, L., & Glauser, G. (2018). Development and validation of an ultra-sensitive UHPLC–MS/MS method for neonicotinoid analysis in Milk. Journal of Agricultural and Food Chemistry, 66(32), 8639–8646.

    Article  CAS  PubMed  Google Scholar 

  263. Liu, C. (2011). The application of SELDI-TOF-MS in clinical diagnosis of cancers. Journal of Biomedicine and Biotechnology, 2011, 6.

    Google Scholar 

  264. Vorderwülbecke, S., Cleverley, S., Weinberger, S. R., & Wiesner, A. (2005). Protein quantification by the SELDI-TOF-MS–based ProteinChip® system. Nature Methods, 2, 393.

    Article  CAS  Google Scholar 

  265. Ryan, D. J., Nei, D., Prentice, B. M., Rose, K. L., Caprioli, R. M., & Spraggins, J. M. (2018). Protein identification in imaging mass spectrometry through spatially targeted liquid micro-extractions. Rapid Communications in Mass Spectrometry, 32(5), 442–450.

    Article  CAS  PubMed  Google Scholar 

  266. Barry, J. A., Groseclose, M. R., Robichaud, G., Castellino, S., & Muddiman, D. C. (2015). Assessing drug and metabolite detection in liver tissue by UV-MALDI and IR-MALDESI mass spectrometry imaging coupled to FT-ICR MS. International Journal of Mass Spectrometry, 377, 448–455.

    Article  CAS  PubMed  Google Scholar 

  267. Guinan, T., Kirkbride, P., Pigou, P. E., Ronci, M., Kobus, H., & Voelcker, N. H. (2015). Surface-assisted laser desorption ionization mass spectrometry techniques for application in forensics. Mass Spectrometry Reviews, 34(6), 627–640.

    Article  CAS  PubMed  Google Scholar 

  268. Lewis, W. G., Shen, Z., Finn, M. G., & Siuzdak, G. (2003). Desorption/ionization on silicon (DIOS) mass spectrometry: Background and applications. International Journal of Mass Spectrometry, 226(1), 107–116.

    Article  CAS  Google Scholar 

  269. Moening, T. N., Brown, V. L., & He, L. (2015). Nanostructure-initiator mass spectrometry (NIMS) for molecular mapping of animal tissues. In L. He (Ed.), Mass spectrometry imaging of small molecules (pp. 151–157). New York: Springer.

    Google Scholar 

  270. Yanes, O., Woo, H.-K., Northen, T. R., Oppenheimer, S. R., Shriver, L., Apon, J., et al. (2009). Nanostructure initiator mass spectrometry: Tissue imaging and direct biofluid analysis. Analytical Chemistry, 81(8), 2969–2975.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  271. Cobice, D. F., Goodwin, R. J. A., Andren, P. E., Nilsson, A., Mackay, C. L., & Andrew, R. (2015). Future technology insight: Mass spectrometry imaging as a tool in drug research and development. British Journal of Pharmacology, 172(13), 3266–3283.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  272. Garza, K. Y., Feider, C. L., Klein, D. R., Rosenberg, J. A., Brodbelt, J. S., & Eberlin, L. S. (2018). Desorption electrospray ionization mass spectrometry imaging of proteins directly from biological tissue sections. Analytical Chemistry, 90(13), 7785–7789.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  273. Schulz, S., Becker, M., Groseclose, M. R., Schadt, S., & Hopf, C. (2019). Advanced MALDI mass spectrometry imaging in pharmaceutical research and drug development. Current Opinion in Biotechnology, 55, 51–59.

    Article  CAS  PubMed  Google Scholar 

  274. Dilillo, M., Ait-Belkacem, R., Esteve, C., Pellegrini, D., Nicolardi, S., Costa, M., et al. (2017). Ultra-high mass resolution MALDI imaging mass spectrometry of proteins and metabolites in a mouse model of glioblastoma. Scientific Reports, 7(1), 603.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  275. Stauber, J., El Ayed, M., Wisztorski, M., Salzet, M., & Fournier, I. (2010). Specific MALDI-MSI: TAG-MASS. Methods in Molecular Biology, 656, 339–361.

    Article  CAS  PubMed  Google Scholar 

  276. Debois, D., Bertrand, V., Quinton, L., De Pauw-Gillet, M.-C., & De Pauw, E. (2010). MALDI-in source decay applied to mass spectrometry imaging: A new tool for protein identification. Analytical Chemistry, 82(10), 4036–4045.

    Article  CAS  PubMed  Google Scholar 

  277. Cooper, H. J. (2016). To what extent is FAIMS beneficial in the analysis of proteins? Journal of the American Society for Mass Spectrometry, 27, 566–577.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  278. Griffiths, R. L., Creese, A. J., Race, A. M., Bunch, J., & Cooper, H. J. (2016). LESA FAIMS mass spectrometry for the spatial profiling of proteins from tissue. Analytical Chemistry, 88(13), 6758–6766.

    Article  CAS  PubMed  Google Scholar 

  279. Bouslimani, A., Porto, C., Rath, C. M., Wang, M., Guo, Y., Gonzalez, A., et al. (2015). Molecular cartography of the human skin surface in 3D. Proceedings of the National Academy of Sciences, 112(17), E2120.

    Article  CAS  Google Scholar 

  280. Soufi, Y., & Soufi, B. (2016). Mass spectrometry-based bacterial proteomics: Focus on dermatologic microbial pathogens. Frontiers in Microbiology, 7, 181.

    Article  PubMed  PubMed Central  Google Scholar 

  281. Dunham, S. J. B., Ellis, J. F., Li, B., & Sweedler, J. V. (2017). Mass spectrometry imaging of complex microbial communities. Accounts of Chemical Research, 50(1), 96–104.

    Article  CAS  PubMed  Google Scholar 

  282. Propheter, D. C., & Hooper, L. V. (2015). Bacteria come into focus: New tools for visualizing the microbiota. Cell Host & Microbe, 18(4), 392–394.

    Article  CAS  Google Scholar 

  283. de Macedo, C. S., Anderson, D. M., & Schey, K. L. (2017). MALDI (matrix assisted laser desorption ionization) imaging mass spectrometry (IMS) of skin: Aspects of sample preparation. Talanta, 174, 325–335.

    Article  PubMed  CAS  Google Scholar 

  284. Brunetti, A. E., Marani, M. M., Soldi, R. A., Mendonça, J. N., Faivovich, J., Cabrera, G. M., et al. (2018). Cleavage of peptides from amphibian skin revealed by combining analysis of gland secretion and in situ MALDI imaging mass spectrometry. ACS omega, 3(5), 5426–5434.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  285. Margaux, F., Pascale, R., Marcela, S., Emmanuelle, L.-W., & Armelle, C.-D. (2017). Omics for precious rare biosamples: Characterization of ancient human hair by a proteomic approach. OMICS: A Journal of Integrative Biology, 21(7), 361–370.

    Article  CAS  Google Scholar 

  286. Kempson, I. M., & Lombi, E. (2011). Hair analysis as a biomonitor for toxicology, disease and health status. Chemical Society Reviews, 40(7), 3915–3940.

    Article  CAS  PubMed  Google Scholar 

  287. Wilson, A. S., & Tobin, D. J. (2010). Hair after death. In R. M. Trüeb & D. J. Tobin (Eds.), Aging hair (pp. 249–261). Heidelberg: Springer.

    Chapter  Google Scholar 

  288. Poetzsch, M., Steuer, A. E., Roemmelt, A. T., Baumgartner, M. R., & Kraemer, T. (2014). Single hair analysis of small molecules using MALDI-triple quadrupole MS imaging and LC-MS/MS: Investigations on opportunities and pitfalls. Analytical Chemistry, 86(23), 11758–11765.

    Article  CAS  PubMed  Google Scholar 

  289. Flinders, B., Cuypers, E., Zeijlemaker, H., Tytgat, J., & Heeren, R. M. A. (2015). Preparation of longitudinal sections of hair samples for the analysis of cocaine by MALDI-MS/MS and TOF-SIMS imaging. Drug Testing and Analysis, 7(10), 859–865.

    Article  CAS  PubMed  Google Scholar 

  290. Flinders, B., Beasley, E., Verlaan, R. M., Cuypers, E., Francese, S., Bassindale, T., et al. (2017). Optimization of sample preparation and instrumental parameters for the rapid analysis of drugs of abuse in hair samples by MALDI-MS/MS imaging. Journal of the American Society for Mass Spectrometry, 28(11), 2462–2468.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  291. Martin-Lorenzo, M., Alvarez-Llamas, G., McDonnell, L. A., & Vivanco, F. (2016). Molecular histology of arteries: Mass spectrometry imaging as a novel ex vivo tool to investigate atherosclerosis. Expert Review of Proteomics, 13(1), 69–81.

    Article  CAS  PubMed  Google Scholar 

  292. Martin-Lorenzo, M., Balluff, B., Maroto, A. S., Carreira, R. J., van Zeijl, R. J. M., Gonzalez-Calero, L., et al. (2015). Lipid and protein maps defining arterial layers in atherosclerotic aorta. Data in Brief, 4, 328–331.

    Article  PubMed  PubMed Central  Google Scholar 

  293. Martin-Lorenzo, M., Balluff, B., Maroto, A. S., Carreira, R. J., van Zeijl, R. J. M., Gonzalez-Calero, L., et al. (2015). Molecular anatomy of ascending aorta in atherosclerosis by MS imaging: Specific lipid and protein patterns reflect pathology. Journal of Proteomics, 126, 245–251.

    Article  CAS  PubMed  Google Scholar 

  294. Martin-Lorenzo, M., Balluff, B., Sanz-Maroto, A., van Zeijl, R. J. M., Vivanco, F., Alvarez-Llamas, G., et al. (2014). 30μm spatial resolution protein MALDI MSI: In-depth comparison of five sample preparation protocols applied to human healthy and atherosclerotic arteries. Journal of Proteomics, 108, 465–468.

    Article  CAS  PubMed  Google Scholar 

  295. Kong, S., Zhang, Y. H., & Zhang, W. (2018). Regulation of intestinal epithelial cells properties and functions by amino acids. BioMed Research International, 2018, 10.

    Google Scholar 

  296. Nilsson, A., Peric, A., Strimfors, M., Goodwin, R. J. A., Hayes, M. A., Andrén, P. E., et al. (2017). Mass spectrometry imaging proves differential absorption profiles of well-characterised permeability markers along the crypt-villus axis. Scientific Reports, 7(1), 6352.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  297. Andley, U. P. (2008). The lens epithelium: Focus on the expression and function of the alpha-crystallin chaperones. The International Journal of Biochemistry & Cell Biology, 40(3), 317–323.

    Article  CAS  Google Scholar 

  298. Ronci, M., Sharma, S., Chataway, T., Burdon, K. P., Martin, S., Craig, J. E., et al. (2011). MALDI-MS-imaging of whole human Lens capsule. Journal of Proteome Research, 10(8), 3522–3529.

    Article  CAS  PubMed  Google Scholar 

  299. Han, J., & Schey, K. L. (2006). MALDI tissue imaging of ocular lens α-Crystallin. Investigative Ophthalmology & Visual Science, 47(7), 2990–2996.

    Article  Google Scholar 

  300. Grey, A. C. (2016). MALDI imaging of the eye: Mapping lipid, protein and metabolite distributions in aging and ocular disease. International Journal of Mass Spectrometry, 401, 31–38.

    Article  CAS  Google Scholar 

  301. Grey, A. C., & Schey, K. L. (2009). Age-related changes in the spatial distribution of human lens alpha-crystallin products by MALDI imaging mass spectrometry. Investigative Ophthalmology & Visual Science, 50(9), 4319–4329.

    Article  Google Scholar 

  302. Stella, D. R., Floyd, K. A., Grey, A. C., Renfrow, M. B., Schey, K. L., & Barnes, S. (2010). Tissue localization and solubilities of αA-crystallin and its numerous C-terminal truncation products in pre- and postcataractous ICR/f rat lenses. Investigative Ophthalmology & Visual Science, 51(10), 5153–5161.

    Article  Google Scholar 

  303. Nye-Wood, M. G., Spraggins, J. M., Caprioli, R. M., Schey, K. L., Donaldson, P. J., & Grey, A. C. (2017). Spatial distributions of glutathione and its endogenous conjugates in normal bovine lens and a model of lens aging. Experimental Eye Research, 154, 70–78.

    Article  CAS  PubMed  Google Scholar 

  304. Grey, A. C., Chaurand, P., Caprioli, R. M., & Schey, K. L. (2009). MALDI imaging mass spectrometry of integral membrane proteins from ocular Lens and retinal tissue. Journal of Proteome Research, 8(7), 3278–3283.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  305. Jiao, J., Miao, A., Zhang, Y., Fan, Q., Lu, Y., & Lu, H. (2015). Imaging phosphorylated peptide distribution in human lens by MALDI MS. Analyst, 140(12), 4284–4290.

    Article  CAS  PubMed  Google Scholar 

  306. Mukherjee, P., & Mani, S. (2013). Methodologies to decipher the cell secretome. Biochimica et Biophysica Acta, 1834(11), 2226–2232.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  307. Yadav, N., Khurana, S. M., & Yadav, D. (2015). Plant secretomics: Unique initiatives. PlantOmics, 2015, 357–384.

    Google Scholar 

  308. Green-Mitchell, S. M., Cazares, L. H., Semmes, O. J., Nadler, J. L., & Nyalwidhe, J. O. (2011). On-tissue identification of insulin: In situ reduction coupled with mass spectrometry imaging. Proteomics. Clinical Applications, 5(7–8), 448–453.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  309. Schulz, S., Römpp, A., Kummer, W., & Spengler, B. (2011). AP-MALDI imaging of neuropeptides in mouse pituitary gland with 5 μm spatial resolution and high mass accuracy. International Journal of Mass Spectrometry, 305, 228–237.

    Article  CAS  Google Scholar 

  310. Oliva, R., Martínez-Heredia, J., & Estanyol, J. M. (2008). Proteomics in the study of the sperm cell composition, differentiation and function. Systems Biology in Reproductive Medicine, 54(1), 23–36.

    Article  CAS  PubMed  Google Scholar 

  311. Lagarrigue, M., Lavigne, R., Guével, B., Com, E., Chaurand, P., & Pineau, C. (2012). Matrix-assisted laser desorption/ionization imaging mass spectrometry: A promising technique for reproductive research. Biology of Reproduction, 86(3), 74, 1-11-74, 1-11.

    Article  PubMed  CAS  Google Scholar 

  312. Lagarrigue, M., Becker, M., Lavigne, R., Deininger, S.-O., Walch, A., Aubry, F., et al. (2011). Revisiting rat spermatogenesis with MALDI imaging at 20-microm resolution. Molecular & Cellular Proteomics : MCP, 10(3), M110.005991.

    Article  CAS  Google Scholar 

  313. Mondon, P., Hillion, M., Peschard, O., Andre, N., Marchand, T., Doridot, E., et al. (2015). Evaluation of dermal extracellular matrix and epidermal–dermal junction modifications using matrix-assisted laser desorption/ionization mass spectrometric imaging, in vivo reflectance confocal microscopy, echography, and histology: Effect of age and peptide applications. Journal of Cosmetic Dermatology, 14(2), 152–160.

    Article  PubMed  Google Scholar 

  314. Stefanov, I., & Simeonov, R. (2018). Histochemical and morphometric studies of connective tissue fibres in canine paranal sinus. Bulgarian Journal of Veterinary Medicine, 14(3), 171–178.

    Google Scholar 

  315. Gelse, K., Pöschl, E., & Aigner, T. (2003). Collagens—Structure, function, and biosynthesis. Advanced Drug Delivery Reviews, 55(12), 1531–1546.

    Article  CAS  PubMed  Google Scholar 

  316. Holzlechner, M., Strasser, K., Zareva, E., Steinhäuser, L., Birnleitner, H., Beer, A., et al. (2017). In situ characterization of tissue-resident immune cells by MALDI mass spectrometry imaging. Journal of Proteome Research, 16(1), 65–76.

    Article  CAS  PubMed  Google Scholar 

  317. Cillero-Pastor, B., Eijkel, G. B., Kiss, A., Blanco, F. J., & Heeren, R. M. A. (2013). Matrix-assisted laser desorption ionization–imaging mass spectrometry: A new methodology to study human osteoarthritic cartilage. Arthritis and Rheumatism, 65(3), 710–720.

    Article  CAS  PubMed  Google Scholar 

  318. Rocha, B., Cillero-Pastor, B., Blanco, F. J., & Ruiz-Romero, C. (2017). MALDI mass spectrometry imaging in rheumatic diseases. Biochimica et Biophysica Acta (BBA). Proteins and Proteomics, 1865(7), 784–794.

    Article  CAS  Google Scholar 

  319. Briggs, M. T., Kuliwaba, J. S., Muratovic, D., Everest-Dass, A. V., Packer, N. H., Findlay, D. M., et al. (2016). MALDI mass spectrometry imaging of N-glycans on tibial cartilage and subchondral bone proteins in knee osteoarthritis. Proteomics, 16(11–12), 1736–1741.

    Article  CAS  PubMed  Google Scholar 

  320. Peffers, M. J., Cillero-Pastor, B., Eijkel, G. B., Clegg, P. D., & Heeren, R. M. A. (2014). Matrix assisted laser desorption ionization mass spectrometry imaging identifies markers of ageing and osteoarthritic cartilage. Arthritis Research & Therapy, 16(3), R110.

    Article  CAS  Google Scholar 

  321. Centeno, D., Vénien, A., Pujos-Guillot, E., Astruc, T., Chambon, C., & Théron, L. (2017). Myofiber metabolic type determination by mass spectrometry imaging. Journal of Mass Spectrometry, 52(8), 493–496.

    Article  CAS  PubMed  Google Scholar 

  322. Klein, O., Strohschein, K., Nebrich, G., Oetjen, J., Trede, D., Thiele, H., et al. (2014). MALDI imaging mass spectrometry: Discrimination of pathophysiological regions in traumatized skeletal muscle by characteristic peptide signatures. Proteomics, 14(20), 2249–2260.

    Article  CAS  PubMed  Google Scholar 

  323. Shintani-Domoto, Y., Hayasaka, T., Maeda, D., Masaki, N., Ito, T. K., Sakuma, K., et al. (2017). Different desmin peptides are distinctly deposited in cytoplasmic aggregations and cytoplasm of desmin-related cardiomyopathy patients. Biochimica et Biophysica Acta (BBA). Proteins and Proteomics, 1865(7), 828–836.

    Article  CAS  Google Scholar 

  324. Noronha, A. M., Linden, C., & Sharma, P. (2016). Developments in cardiovascular proteomics. Journal of Proteomics & Bioinformatics, 9, 144–150.

    Article  CAS  Google Scholar 

  325. Kakimoto, Y., Ito, S., Abiru, H., Kotani, H., Ozeki, M., Tamaki, K., et al. (2013). Sorbin and SH3 domain-containing protein 2 is released from infarcted heart in the very early phase: Proteomic analysis of cardiac tissues from patients. Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, 2(6), e000565.

    Article  CAS  Google Scholar 

  326. Lefcoski, S., Kew, K., Reece, S., Torres, M. J., Parks, J., Reece, S., et al. (2018). Anatomical-molecular distribution of EphrinA1 in infarcted mouse heart using MALDI mass spectrometry imaging. Journal of the American Society for Mass Spectrometry, 29(3), 527–534.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  327. Bayés, A., & Grant, S. G. N. (2009). Neuroproteomics: Understanding the molecular organization and complexity of the brain. Nature Reviews Neuroscience, 10, 635.

    Article  PubMed  CAS  Google Scholar 

  328. Gemperline, E., Chen, B., & Li, L. (2014). Challenges and recent advances in mass spectrometric imaging of neurotransmitters. Bioanalysis, 6(4), 525–540.

    Article  CAS  PubMed  Google Scholar 

  329. Zimmerman, T., Rubakhin, S., & Sweedler, J. (2011). MALDI mass spectrometry imaging of neuronal cell cultures. Journal of the American Society for Mass Spectrometry, 22(5), 828–836.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  330. Ong, T.-H., Romanova, E. V., Roberts-Galbraith, R. H., Yang, N., Zimmerman, T. A., Collins, J. J., et al. (2016). Mass spectrometry imaging and identification of peptides associated with cephalic ganglia regeneration in Schmidtea mediterranea. Journal of Biological Chemistry, 291(15), 8109–8120.

    Article  CAS  Google Scholar 

  331. Chen, R., Ouyang, C., Xiao, M., & Li, L. (2014). In situ identification and mapping of neuropeptides from the stomatogastric nervous system of Cancer borealis. Rapid Communications in Mass Spectrometry, 28(22), 2437–2444.

    Article  CAS  PubMed  Google Scholar 

  332. Paine, M. R. L., Ellis, S. R., Maloney, D., Heeren, R. M. A., & Verhaert, P. D. E. M. (2018). Digestion-free analysis of peptides from 30-year-old formalin-fixed, paraffin-embedded tissue by mass spectrometry imaging. Analytical Chemistry, 90(15), 9272–9280.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  333. Ye, H., Hui, L., Kellersberger, K., & Li, L. (2013). Mapping of neuropeptides in the crustacean stomatogastric nervous system by imaging mass spectrometry. Journal of the American Society for Mass Spectrometry, 24(1), 134–147.

    Article  CAS  PubMed  Google Scholar 

  334. Crecelius, A. C., Cornett, D. S., Caprioli, R. M., Williams, B., Dawant, B. M., & Bodenheimer, B. (2005). Three-dimensional visualization of protein expression in mouse brain structures using imaging mass spectrometry. Journal of the American Society for Mass Spectrometry, 16(7), 1093–1099.

    Article  CAS  PubMed  Google Scholar 

  335. Schober, Y., Schramm, T., Spengler, B., & Römpp, A. (2011). Protein identification by accurate mass matrix-assisted laser desorption/ionization imaging of tryptic peptides. Rapid Communications in Mass Spectrometry, 25(17), 2475–2483.

    Article  CAS  PubMed  Google Scholar 

  336. Tucker, K. R., Serebryannyy, L. A., Zimmerman, T. A., Rubakhin, S. S., & Sweedler, J. V. (2011). The modified-bead stretched sample method: Development and application to MALDI-MS imaging of protein localization in the spinal cord. Chemical Science, 2(4), 785–795.

    Article  CAS  PubMed  Google Scholar 

  337. Sui, P., Watanabe, H., Artemenko, K., Sun, W., Bakalkin, G., Andersson, M., et al. (2017). Neuropeptide imaging in rat spinal cord with MALDI-TOF MS: Method development for the application in pain-related disease studies. European Journal of Mass Spectrometry, 23, 105–115.

    Article  CAS  PubMed  Google Scholar 

  338. Rubakhin, S. S., Ulanov, A., & Sweedler, J. V. (2015). Mass spectrometry imaging and GC-MS profiling of the mammalian peripheral sensory-motor circuit. Journal of the American Society for Mass Spectrometry, 26(6), 958–966.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  339. González de San Román, E., Bidmon, H.-J., Malisic, M., Susnea, I., Küppers, A., Hübbers, R., et al. (2018). Molecular composition of the human primary visual cortex profiled by multimodal mass spectrometry imaging. Brain Structure & Function, 223(6), 2767–2783.

    Article  CAS  Google Scholar 

  340. Liu, X., Ide, J. L., Norton, I., Marchionni, M. A., Ebling, M. C., Wang, L. Y., et al. (2013). Molecular imaging of drug transit through the blood-brain barrier with MALDI mass spectrometry imaging. Scientific Reports, 3, 2859.

    Article  PubMed  PubMed Central  Google Scholar 

  341. Wang, J. S. H., Freitas-Andrade, M., Bechberger, J. F., Naus, C. C., Yeung, K. K.-C., & Whitehead, S. N. (2018). Matrix-assisted laser desorption/ionization imaging mass spectrometry of intraperitoneally injected danegaptide (ZP1609) for treatment of stroke-reperfusion injury in mice. Rapid Communications in Mass Spectrometry, 32(12), 951–958.

    Article  PubMed  CAS  Google Scholar 

  342. Delcourt, V., Franck, J., Quanico, J., Gimeno, J.-P., Wisztorski, M., Raffo-Romero, A., et al. (2018). Spatially-resolved top-down proteomics bridged to MALDI MS imaging reveals the molecular Physiome of brain regions. Molecular & Cellular Proteomics, 17(2), 357–372.

    Article  CAS  Google Scholar 

  343. Majava, V., Polverini, E., Mazzini, A., Nanekar, R., Knoll, W., Peters, J., et al. (2010). Structural and functional characterization of human peripheral nervous system myelin protein P2. PLoS One, 5(4), e10300.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  344. Iloro, I., Fernández-Irigoyen, J., Escobes, I., Azkargorta, M., Santamaría, E., & Elortza, F. (2017). Methods for human olfactory bulb tissue studies using peptide/protein MALDI-TOF imaging mass spectrometry (MALDI-IMS). In E. Santamaría & J. Fernández-Irigoyen (Eds.), Current proteomic approaches applied to brain function (pp. 91–106). New York: Springer.

    Chapter  Google Scholar 

  345. Ye, H., Mandal, R., Catherman, A., Thomas, P. M., Kelleher, N. L., Ikonomidou, C., et al. (2014). Top-down proteomics with mass spectrometry imaging: A pilot study towards discovery of biomarkers for neurodevelopmental disorders. PLoS One, 9(4), e92831.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  346. Hanrieder, J., Ekegren, T., Andersson, M., & Bergquist, J. (2013). MALDI imaging of post-mortem human spinal cord in amyotrophic lateral sclerosis. Journal of Neurochemistry, 124(5), 695–707.

    Article  CAS  PubMed  Google Scholar 

  347. Winter, M., Tholey, A., Kristen, A., & Röcken, C. (2017). MALDI mass spectrometry imaging: A novel tool for the identification and classification of amyloidosis. Proteomics, 17(22), 1700236.

    Article  PubMed Central  CAS  Google Scholar 

  348. Kakuda, N., Miyasaka, T., Iwasaki, N., Nirasawa, T., Wada-Kakuda, S., Takahashi-Fujigasaki, J., et al. (2017). Distinct deposition of amyloid-β species in brains with Alzheimer’s disease pathology visualized with MALDI imaging mass spectrometry. Acta Neuropathologica Communications, 5, 73.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  349. Ho Kim, J., Franck, J., Kang, T., Heinsen, H., Ravid, R., Ferrer, I., et al. (2015). Proteome-wide characterization of signalling interactions in the hippocampal CA4/DG subfield of patients with Alzheimer’s disease. Scientific Reports, 5, 11138.

    Article  PubMed  PubMed Central  Google Scholar 

  350. Casaletto, K. B., Elahi, F. M., Bettcher, B. M., Neuhaus, J., Bendlin, B. B., Asthana, S., et al. (2017). Neurogranin, a synaptic protein, is associated with memory independent of Alzheimer biomarkers. Neurology, 89(17), 1782–1788.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  351. Esteve, C., Jones, E. A., Kell, D. B., Boutin, H., & McDonnell, L. A. (2017). Mass spectrometry imaging shows major derangements in neurogranin and in purine metabolism in the triple-knockout 3×Tg Alzheimer mouse model. Biochimica et Biophysica Acta (BBA). Proteins and Proteomics, 1865(7), 747–754.

    Article  CAS  Google Scholar 

  352. Reglodi, D., Jungling, A., Longuespée, R., Kriegsmann, J., Casadonte, R., Kriegsmann, M., et al. (2018). Accelerated pre-senile systemic amyloidosis in PACAP knockout mice - A protective role of PACAP in age-related degenerative processes. The Journal of Pathology, 245(4), 478–490.

    Article  CAS  PubMed  Google Scholar 

  353. Maccarrone, G., Nischwitz, S., Deininger, S.-O., Hornung, J., König, F. B., Stadelmann, C., et al. (2017). MALDI imaging mass spectrometry analysis—A new approach for protein mapping in multiple sclerosis brain lesions. Journal of Chromatography B, 1047, 131–140.

    Article  CAS  Google Scholar 

  354. Llombart, V., Trejo, S. A., Bronsoms, S., Morancho, A., Feifei, M., Faura, J., et al. (2017). Profiling and identification of new proteins involved in brain ischemia using MALDI-imaging-mass-spectrometry. Journal of Proteomics, 152, 243–253.

    Article  CAS  PubMed  Google Scholar 

  355. Lalowski, M., Magni, F., Mainini, V., Monogioudi, E., Gotsopoulos, A., Soliymani, R., et al. (2013). Imaging mass spectrometry: A new tool for kidney disease investigations. Nephrology Dialysis Transplantation, 28(7), 1648–1656.

    Article  Google Scholar 

  356. Magni, F., Lalowski, M., Mainini, V., Marchetti-Deschmann, M., Chinello, C., Urbani, A., et al. (2012). Proteomics imaging and the kidney. Journal of Nephrology, 26, 430–436.

    Article  PubMed  CAS  Google Scholar 

  357. Grobe, N., Elased, K. M., Cool, D. R., & Morris, M. (2012). Mass spectrometry for the molecular imaging of angiotensin metabolism in kidney. American Journal of Physiology. Endocrinology and Metabolism, 302(8), E1016–E1024.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  358. Smith, A., L’Imperio, V., Sio, G., Ferrario, F., Scalia, C., Dell’Antonio, G., et al. (2016). α-1-Antitrypsin detected by MALDI imaging in the study of glomerulonephritis: Its relevance in chronic kidney disease progression. Proteomics, 16(11–12), 1759–1766.

    Article  CAS  PubMed  Google Scholar 

  359. Smith, A., L’Imperio, V., Ajello, E., Ferrario, F., Mosele, N., Stella, M., et al. (2017). The putative role of MALDI-MSI in the study of membranous nephropathy. Biochimica et Biophysica Acta (BBA). Proteins and Proteomics, 1865(7), 865–874.

    Article  CAS  Google Scholar 

  360. Casadonte, R., Kriegsmann, M., Deininger, S.-O., Amann, K., Paape, R., Belau, E., et al. (2015). Imaging mass spectrometry analysis of renal amyloidosis biopsies reveals protein co-localization with amyloid deposits. Analytical and Bioanalytical Chemistry, 407, 5323–5331.

    Article  CAS  PubMed  Google Scholar 

  361. Winter, M., Tholey, A., Krüger, S., Schmidt, H., & Röcken, C. (2015). MALDI-mass spectrometry imaging identifies vitronectin as a common constituent of amyloid deposits. The Journal of Histochemistry and Cytochemistry : Official Journal of the Histochemistry Society, 63(10), 772–779.

    Article  CAS  Google Scholar 

  362. Kriegsmann, J., Kriegsmann, M., & Casadonte, R. (2015). MALDI TOF imaging mass spectrometry in clinical pathology: A valuable tool for cancer diagnostics (review). International Journal of Oncology, 46(3), 893–906.

    Article  CAS  PubMed  Google Scholar 

  363. Le Rhun, E., Duhamel, M., Wisztorski, M., Gimeno, J.-P., Zairi, F., Escande, F., et al. (2017). Evaluation of non-supervised MALDI mass spectrometry imaging combined with microproteomics for glioma grade III classification. Biochimica et Biophysica Acta (BBA). Proteins and Proteomics, 1865(7), 875–890.

    Article  CAS  Google Scholar 

  364. Boskamp, T., Lachmund, D., Oetjen, J., Cordero Hernandez, Y., Trede, D., Maass, P., et al. (2017). A new classification method for MALDI imaging mass spectrometry data acquired on formalin-fixed paraffin-embedded tissue samples. Biochimica et Biophysica Acta (BBA). Proteins and Proteomics, 1865(7), 916–926.

    Article  CAS  Google Scholar 

  365. Rebours, V., Le Faouder, J., Laouirem, S., Mebarki, M., Albuquerque, M., Camadro, J.-M., et al. (2013). In situ proteomic analysis by MALDI imaging identifies Ubiquitin and Thymosin-β4 as markers of malignant intraductal pancreatic mucinous neoplasms. Pancreatology, 14, 117–124.

    Article  PubMed  CAS  Google Scholar 

  366. Djidja, M.-C., Claude, E., Snel, M. F., Scriven, P., Francese, S., Carolan, V., et al. (2009). MALDI-ion mobility separation-mass spectrometry imaging of glucose-regulated protein 78 kDa (Grp78) in human formalin-fixed, paraffin-embedded pancreatic adenocarcinoma tissue sections. Journal of Proteome Research, 8(10), 4876–4884.

    Article  CAS  PubMed  Google Scholar 

  367. Zhou, X., Liao, W.-J., Liao, J.-M., Liao, P., & Lu, H. (2015). Ribosomal proteins: Functions beyond the ribosome. Journal of Molecular Cell Biology, 7(2), 92–104.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  368. Mittal, P., Klingler-Hoffmann, M., Arentz, G., Winderbaum, L., Kaur, G., Anderson, L., et al. (2016). Annexin A2 and alpha actinin 4 expression correlates with metastatic potential of primary endometrial cancer. Biochimica et Biophysica Acta (BBA). Proteins and Proteomics, 1865, 846–857.

    Article  CAS  Google Scholar 

  369. Zhang, C., Arentz, G., Winderbaum, L., Lokman, N. A., Klingler-Hoffmann, M., Mittal, P., et al. (2016). MALDI mass spectrometry imaging reveals decreased CK5 levels in vulvar squamous cell carcinomas compared to the precursor lesion differentiated vulvar intraepithelial neoplasia. International Journal of Molecular Sciences, 17(7), 1088.

    Article  PubMed Central  CAS  Google Scholar 

  370. Delcourt, V., Franck, J., Leblanc, E., Narducci, F., Robin, Y.-M., Gimeno, J.-P., et al. (2017). Combined mass spectrometry imaging and top-down microproteomics reveals evidence of a hidden proteome in ovarian cancer. eBioMedicine, 21, 55–64.

    Article  PubMed  PubMed Central  Google Scholar 

  371. Lemaire, R., Ait Menguellet, S., Stauber, J., Marchaudon, V., Lucot, J.-P., Collinet, P., et al. (2007). Specific MALDI imaging and profiling for biomarker hunting and validation: Fragment of the 11S proteasome activator complex, Reg alpha fragment, is a new potential ovary cancer biomarker. Journal of Proteome Research, 6(11), 4127–4134.

    Article  CAS  PubMed  Google Scholar 

  372. Gagnon, H., Franck, J., Wisztorski, M., Day, R., Fournier, I., & Salzet, M. (2012). Targeted mass spectrometry imaging: Specific targeting mass spectrometry imaging technologies from history to perspective. Progress in Histochemistry and Cytochemistry, 47(3), 133–174.

    Article  PubMed  Google Scholar 

  373. Nazari, M., Bokhart, M. T., Loziuk, P. L., & Muddiman, D. C. (2018). Quantitative mass spectrometry imaging of glutathione in healthy and cancerous hen ovarian tissue sections by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI). Analyst, 143(3), 654–661.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  374. Rauser, S., Marquardt, C., Balluff, B., Deininger, S.-O., Albers, C., Belau, E., et al. (2010). Classification of HER2 receptor status in breast Cancer tissues by MALDI imaging mass spectrometry. Journal of Proteome Research, 9(4), 1854–1863.

    Article  CAS  PubMed  Google Scholar 

  375. Djidja, M.-C., Chang, J., Hadjiprocopis, A., Schmich, F., Sinclair, J., Mršnik, M., et al. (2014). Identification of hypoxia-regulated proteins using MALDI-mass spectrometry imaging combined with quantitative proteomics. Journal of Proteome Research, 13(5), 2297–2313.

    Article  CAS  PubMed  Google Scholar 

  376. Végvári, Á., Shavkunov, A. S., Fehniger, T. E., Grabau, D., Niméus, E., & Marko-Varga, G. (2016). Localization of tamoxifen in human breast cancer tumors by MALDI mass spectrometry imaging. Clinical and Translational Medicine, 5, 10.

    Article  PubMed  PubMed Central  Google Scholar 

  377. Dekker, T. J. A., Balluff, B. D., Jones, E. A., Schöne, C. D., Schmitt, M., Aubele, M., et al. (2014). Multicenter matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) identifies proteomic differences in breast-Cancer-associated stroma. Journal of Proteome Research, 13(11), 4730–4738.

    Article  CAS  PubMed  Google Scholar 

  378. Steurer, S., Borkowski, C., Odinga, S., Buchholz, M., Koop, C., Huland, H., et al. (2013). MALDI mass spectrometric imaging based identification of clinically relevant signals in prostate cancer using large-scale tissue microarrays. International Journal of Cancer, 133(4), 920–928.

    Article  CAS  PubMed  Google Scholar 

  379. Panderi, I., Yakirevich, E., Papagerakis, S., Noble, L., Lombardo, K., & Pantazatos, D. (2017). Differentiating tumor heterogeneity in formalin-fixed paraffin-embedded (FFPE) prostate adenocarcinoma tissues using principal component analysis of matrix-assisted laser desorption/ionization imaging mass spectral data. Rapid Communications in Mass Spectrometry, 31(2), 160–170.

    Article  CAS  PubMed  Google Scholar 

  380. Lazova, R., Yang, Z., El Habr, C., Lim, Y., Choate, K. A., Seeley, E. H., et al. (2017). Mass spectrometry imaging can distinguish on a proteomic level between proliferative nodules within a benign congenital nevus and malignant melanoma. The American Journal of Dermatopathology, 39(9), 689–695.

    Article  PubMed  PubMed Central  Google Scholar 

  381. Guran, R., Vanickova, L., Horak, V., Krizkova, S., Michalek, P., Heger, Z., et al. (2017). MALDI MSI of MeLiM melanoma: Searching for differences in protein profiles. PLoS One, 12(12), e0189305.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  382. Vanickova, L., Guran, R., Kollár, S., Emri, G., Krizkova, S., Do, T., et al. (2019). Mass spectrometric imaging of cysteine rich proteins in human skin. International Journal of Biological Macromolecules, 125, 270–277.

    Article  CAS  PubMed  Google Scholar 

  383. Hardesty, W. M., Kelley, M. C., Mi, D., Low, R. L., & Caprioli, R. M. (2011). Protein signatures for survival and recurrence in metastatic melanoma. Journal of Proteomics, 74(7), 1002–1014.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  384. Smith, A., Piga, I., Galli, M., Stella, M., Denti, V., Del Puppo, M., et al. (2017). Matrix-assisted laser desorption/ionisation mass spectrometry imaging in the study of gastric Cancer: A mini review. International Journal of Molecular Sciences, 18(12), 2588.

    Article  PubMed Central  CAS  Google Scholar 

  385. Balluff, B., Rauser, S., Meding, S., Elsner, M., Schöne, C., Feuchtinger, A., et al. (2011). MALDI imaging identifies prognostic seven-protein signature of novel tissue markers in intestinal-type gastric cancer. The American Journal of Pathology, 179(6), 2720–2729.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  386. Gemoll, T., Strohkamp, S., Schillo, K., Thorns, C., & Habermann, J. K. (2015). MALDI-imaging reveals thymosin beta-4 as an independent prognostic marker for colorectal cancer. Oncotarget, 6(41), 43869–43880.

    Article  PubMed  PubMed Central  Google Scholar 

  387. Steurer, S., Seddiqi, A. S., Singer, J. M., Bahar, A. S., Eichelberg, C., Rink, M., et al. (2014). MALDI imaging on tissue microarrays identifies molecular features associated with renal cell Cancer phenotype. Anticancer Research, 34(5), 2255–2261.

    PubMed  Google Scholar 

  388. Na, C. H., Hong, J. H., Kim, W. S., Shanta, S. R., Bang, J. Y., Park, D., et al. (2015). Identification of protein markers specific for papillary renal cell carcinoma using imaging mass spectrometry. Molecules and Cells, 38(7), 624–629.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  389. Calligaris, D., Feldman, D. R., Norton, I., Olubiyi, O., Changelian, A. N., Machaidze, R., et al. (2015). MALDI mass spectrometry imaging analysis of pituitary adenomas for near-real-time tumor delineation. Proceedings of the National Academy of Sciences, 112(32), 9978–9983.

    Article  CAS  Google Scholar 

  390. Powers, T. W., Jones, E. E., Betesh, L. R., Romano, P., Gao, P., Copland, J. A., et al. (2013). A MALDI imaging mass spectrometry workflow for spatial profiling analysis of N-linked glycan expression in tissues. Analytical Chemistry, 85(20), 9799–9806.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  391. Gustafsson, O. J. R., Briggs, M. T., Condina, M. R., Winderbaum, L. J., Pelzing, M., McColl, S. R., et al. (2015). MALDI imaging mass spectrometry of N-linked glycans on formalin-fixed paraffin-embedded murine kidney. Analytical and Bioanalytical Chemistry, 407(8), 2127–2139.

    Article  CAS  PubMed  Google Scholar 

  392. Min, K.-W., Bang, J.-Y., Kim, K. P., Kim, W.-S., Lee, S. H., Shanta, S. R., et al. (2014). Imaging mass spectrometry in papillary thyroid carcinoma for the identification and validation of biomarker proteins. Journal of Korean Medical Science, 29(7), 934–940.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  393. Pagni, F., Sio, G., Garancini, M., Scardilli, M., Chinello, C., Smith, A. J., et al. (2016). Proteomics in thyroid cytopathology: Relevance of MALDI-imaging in distinguishing malignant from benign lesions. Proteomics, 16(11–12), 1775–1784.

    Article  CAS  PubMed  Google Scholar 

  394. Pietrowska, M., Diehl, H. C., Mrukwa, G., Kalinowska-Herok, M., Gawin, M., Chekan, M., et al. (2017). Molecular profiles of thyroid cancer subtypes: Classification based on features of tissue revealed by mass spectrometry imaging. Biochimica et Biophysica Acta (BBA). Proteins and Proteomics, 1865(7), 837–845.

    Article  CAS  Google Scholar 

  395. Biron, D. G., Marché, L., Ponton, F., Loxdale, H. D., Galéotti, N., Renault, L., et al. (2005). Behavioural manipulation in a grasshopper harbouring hairworm: A proteomics approach. Proceedings of the Royal Society B: Biological Sciences, 272(1577), 2117–2126.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  396. Biron, D., Moura, H., Marche, L., Hughes, A., & Thomas, F. (2005). Towards a new conceptual approach to ‘parasitoproteomics’. Trends in Parasitology, 21, 162–168.

    Article  CAS  PubMed  Google Scholar 

  397. Biron, D. G., & Loxdale, H. D. (2013). Host–parasite molecular cross-talk during the manipulative process of a host by its parasite. The Journal of Experimental Biology, 216(1), 148–160.

    Article  PubMed  Google Scholar 

  398. Jaegger, C. F., Negrão, F., Assis, D. M., Belaz, K. R. A., Angolini, C. F. F., Fernandes, A. M. A. P., et al. (2017). MALDI MS imaging investigation of the host response to visceral leishmaniasis. Molecular BioSystems, 13(10), 1946–1953.

    Article  CAS  PubMed  Google Scholar 

  399. Negrão, F., Rocha, D. F. d. O., Jaeeger, C. F., Rocha, F. J. S., Eberlin, M. N., & Giorgio, S. (2017). Murine cutaneous leishmaniasis investigated by MALDI mass spectrometry imaging. Molecular BioSystems, 13(10), 2036–2043.

    Article  PubMed  Google Scholar 

  400. Pieri, M., Lombardi, A., Basilicata, P., Mamone, G., & Picariello, G. (2018). Proteomics in forensic sciences: Identification of the nature of the last meal at autopsy. Journal of Proteome Research, 17(7), 2412–2420.

    Article  CAS  PubMed  Google Scholar 

  401. Procopio, N., Williams, A., Chamberlain, A. T., & Buckley, M. (2018). Forensic proteomics for the evaluation of the post-mortem decay in bones. Journal of Proteomics, 177, 21–30.

    Article  CAS  PubMed  Google Scholar 

  402. Parker, G. J., Leppert, T., Anex, D. S., Hilmer, J. K., Matsunami, N., Baird, L., et al. (2016). Demonstration of protein-based human identification using the hair shaft proteome. PLoS One, 11(9), e0160653.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  403. Duriez, E., Armengaud, J., Fenaille, F., & Ezan, E. (2016). Mass spectrometry for the detection of bioterrorism agents: From environmental to clinical applications. Journal of Mass Spectrometry, 51(3), 183–199.

    Article  CAS  PubMed  Google Scholar 

  404. Åberg, A. T., Björnstad, K., & Hedeland, M. (2013). Mass spectrometric detection of protein-based toxins. Biosecurity and Bioterrorism: Biodefense Strategy, Practice, and Science, 11(S1), S215–S226.

    Article  Google Scholar 

  405. Mertz, L. (2017). New forensics methods looking more like CSI: Rapid DNA analysis, proteomics, and new technology increasingly impact forensics investigations. IEEE Pulse, 8(6), 40–45.

    Article  PubMed  Google Scholar 

  406. Deininger, L., Patel, E., Clench, M. R., Sears, V., Sammon, C., & Francese, S. (2016). Proteomics goes forensic: Detection and mapping of blood signatures in fingermarks. Proteomics, 16(11–12), 1707–1717.

    Article  CAS  PubMed  Google Scholar 

  407. Bradshaw, R., Denison, N., & Francese, S. (2017). Implementation of MALDI MS profiling and imaging methods for the analysis of real crime scene fingermarks. Analyst, 142(9), 1581–1590.

    Article  CAS  PubMed  Google Scholar 

  408. Guráň, R., Blažková, I., Kenšová, R., Richtera, L., Blažková, L., Zítka, O., et al. (2015). MALDI-TOF MSI and electrochemical detection of metallothionein in chicken liver after cadmium exposure. Journal of Metallomics and Nanotechnologies, 2(3), 43–49.

    Google Scholar 

  409. Lagarrigue, M., Caprioli, R. M., & Pineau, C. (2016). Potential of MALDI imaging for the toxicological evaluation of environmental pollutants. Journal of Proteomics, 144, 133–139.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  410. Yoshimura, Y., Goto-Inoue, N., Moriyama, T., & Zaima, N. (2016). Significant advancement of mass spectrometry imaging for food chemistry. Food Chemistry, 210, 200–211.

    Article  CAS  PubMed  Google Scholar 

  411. Francese, S., Lambardi, D., Mastrobuoni, G., la Marca, G., Moneti, G., & Turillazzi, S. (2009). Detection of honeybee venom in envenomed tissues by direct MALDI MSI. Journal of the American Society for Mass Spectrometry, 20(1), 112–123.

    Article  CAS  PubMed  Google Scholar 

  412. Maltseva, A. (2016). Application of MALDI-MSI for detection of antimicrobial peptides in tissues of the marine invertebrate Arenicola marina. Invertebrate Survival Journal, 13, 205–209.

    Google Scholar 

  413. Maltseva, A. L., Kotenko, O. N., Kokryakov, V. N., Starunov, V. V., & Krasnodembskaya, A. D. (2014). Expression pattern of arenicins-the antimicrobial peptides of polychaete Arenicola marina. Frontiers in Physiology, 5, 497.

    Article  PubMed  PubMed Central  Google Scholar 

  414. Baumann, T., Kämpfer, U., Schürch, S., Schaller, J., Largiader, C., Nentwig, W., et al. (2010). Ctenidins: Antimicrobial glycine-rich peptides from the hemocytes of the spider Cupiennius salei. Cellular and Molecular Life Sciences, 67, 2787–2798.

    Article  CAS  PubMed  Google Scholar 

  415. Kuhn-Nentwig, L., Kopp, L. S., Nentwig, W., Haenni, B., Streitberger, K., Schürch, S., et al. (2014). Functional differentiation of spider hemocytes by light and transmission electron microscopy, and MALDI-MS-imaging. Developmental & Comparative Immunology, 43(1), 59–67.

    Article  CAS  Google Scholar 

  416. Grey, A. C., & Schey, K. L. (2008). Distribution of bovine and rabbit lens alpha-crystallin products by MALDI imaging mass spectrometry. Molecular Vision, 14, 171–179.

    CAS  PubMed  PubMed Central  Google Scholar 

  417. Nicklay, J. J., Harris, G. A., Schey, K. L., & Caprioli, R. M. (2013). MALDI imaging and in situ identification of integral membrane proteins from rat brain tissue sections. Analytical Chemistry, 85(15), 7191–7196.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  418. Gregson, C. (2009). Optimization of MALDI tissue imaging and correlation with immunohistochemistry in rat kidney sections. Bioscience Horizons: The International Journal of Student Research, 2(2), 134–146.

    Article  CAS  Google Scholar 

  419. Piga, I., Heijs, B., Nicolardi, S., Giusti, L., Marselli, L., Marchetti, P., et al. (2017). Ultra-high resolution MALDI-FTICR-MSI analysis of intact proteins in mouse and human pancreas tissue. International Journal of Mass Spectrometry, 437, 10–16.

    Article  CAS  Google Scholar 

  420. DeKeyser, S. S., Kutz-Naber, K. K., Schmidt, J. J., Barrett-Wilt, G. A., & Li, L. (2007). Imaging mass spectrometry of neuropeptides in decapod crustacean neuronal tissues. Journal of Proteome Research, 6(5), 1782–1791.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  421. Cillero-Pastor, B., Eijkel, G., Blanco, F., & Heeren, R. (2014). Protein classification and distribution in osteoarthritic human synovial tissue by matrix-assisted laser desorption ionization mass spectrometry imaging. Analytical and Bioanalytical Chemistry, 407, 2213–2222.

    Article  PubMed  CAS  Google Scholar 

  422. Hanrieder, J., Ljungdahl, A., & Andersson, M. (2012). MALDI imaging mass spectrometry of neuropeptides in Parkinson’s disease. Journal of Visualized Experiments : JoVE, 60, 3445.

    Google Scholar 

  423. Mainini, V., Pagni, F., Ferrario, F., Pieruzzi, F., Grasso, M., Stella, A., et al. (2014). MALDI imaging mass spectrometry in glomerulonephritis: Feasibility study. Histopathology, 64(6), 901–906.

    Article  PubMed  Google Scholar 

  424. Anderson, D. M. G., Van de Plas, R., Rose, K. L., Hill, S., Schey, K. L., Solga, A. C., et al. (2016). 3-D imaging mass spectrometry of protein distributions in mouse Neurofibromatosis 1 (NF1)-associated optic glioma. Journal of Proteomics, 149, 77–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  425. Smith, A., Galli, M., Piga, I., Denti, V., Stella, M., Chinello, C., et al. (2019). Molecular signatures of medullary thyroid carcinoma by matrix-assisted laser desorption/ionisation mass spectrometry imaging. Journal of Proteomics, 191, 114–123.

    Article  CAS  PubMed  Google Scholar 

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  1. Laboratory of Animal Histology, Faculty of Biology, “Alexandru Ioan Cuza” University of Iasi, Iasi, Romania

    Anca-Narcisa Neagu

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  1. Biochemistry and Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson University, Potsdam, NY, USA

    Alisa G. Woods

  2. Biochemistry and Proteomics Group, Department of Chemistry and Biomolecular Science, Clarkson University, Potsdam, NY, USA

    Costel C. Darie

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Neagu, AN. (2019). Proteome Imaging: From Classic to Modern Mass Spectrometry-Based Molecular Histology. In: Woods, A., Darie, C. (eds) Advancements of Mass Spectrometry in Biomedical Research. Advances in Experimental Medicine and Biology, vol 1140. Springer, Cham. https://doi.org/10.1007/978-3-030-15950-4_4

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