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Journal of Mechanical Science and Technology

, Volume 31, Issue 9, pp 4363–4369 | Cite as

Highly efficient in-line wet cyclone air sampler for airborne virus detection

  • Giwoon SungEmail author
  • Chisung Ahn
  • Atul Kulkarni
  • Weon Gyu Shin
  • Taesung KimEmail author
Article

Abstract

Early detection of highly pathogenic strains is particularly important from the point of view of controlling and minimizing the spread of the virus. Wherein, the sampling of infectious virus from air is a crucial step for effective pandemic disease diagnosis. However, most of the air samplers required long sampling time and real time virus analysis is not possible. Hence, the present work we report design and development of in-line virus detection system by adopting newly designed wet cyclone air sampler. An in line airborne virus detection system composed of preseparator and wet cyclone type impactor for air sampling, fluidics system, and virus sensing platform. All virus detection processes, such as sampling of air, hydration, delivery, and immunoassay were carried out on a single system without any preor post-sample treatment. Prior to virus detection, the collection efficiency @ 1000 L/min is tested with PSL particles and is observed that the air sampler efficiency for 1 μm AD is about 50 %, 1.5 μm AD is 78.3 %. And for the large size PSL the observed collection efficiency is about 100 %. Further, it is observed that, the developed system is capable of efficient collection of airborne viral pathogens such as H1N1 and H3N2.

Keywords

Influenza detection Airborne virus Lateral flow immunoassay reader Bio-aerosol Wet cyclone 

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References

  1. [1]
    J. Lum et al., Rapid detection of avian influenza H5N1 virus using impedance measurement of immuno-reaction coupled with RBC amplification, Biosensors & Bioelectronics, 38 (1) (2012) 67–73.CrossRefGoogle Scholar
  2. [2]
    Y. T. Kim et al., Integrated microdevice of reverse transcription-polymerase chain reaction with colorimetric immunochromatographic detection for rapid gene expression analysis of influenza A H1N1 virus, Biosensors & Bioelectronics, 33 (1) (2012) 88–94.CrossRefGoogle Scholar
  3. [3]
    F. Stripeli et al., Performance of rapid influenza testing in hospitalized children, European Journal of Clinical Microbiology & Infectious Diseases, 29 (6) (2010) 683–688.CrossRefGoogle Scholar
  4. [4]
    S. Marche and T. van den Berg, Evaluation of rapid antigen detection kits for the diagnosis of highly pathogenic avian influenza H5N1 infection, Avian Diseases, 54 (s1) (2010) 650–654.CrossRefGoogle Scholar
  5. [5]
    M. E. Alexander et al., Emergence of drug resistance: implications for antiviral control of pandemic influenza, Proceedings of the Royal Society B: Biological Sciences, 274 (2007) 1675–1684.CrossRefGoogle Scholar
  6. [6]
    D. Sykes, The development of a bioaerosol sampler for the detection of enzymes in industry, University of Teesside, UK (2005).Google Scholar
  7. [7]
    A. Hoisington et al., The impact of sampler selection on characterizing the indoor microbiome, Building and Environment, 80 (2014) 274–282.CrossRefGoogle Scholar
  8. [8]
    L. Wen-Hai and L. Chih-Shan, Influence of storage on the fungal concentration determination of impinger and filter samples, Am Indust. Hyg. Assoc. J., 64 (1) (2003) 102–107.CrossRefGoogle Scholar
  9. [9]
    V. Langer et al., Rapid quantification of bioaerosols containing L. pneumophila by Coriolis μ air sampler and chemiluminescence antibody microarrays, Journal of Aerosol Science, 48 (2012) 46–55.CrossRefGoogle Scholar
  10. [10]
    D. Saini et al., Sampling port for real-time analysis of bioaerosol in whole body exposure system for animal aerosol model development, Journal of Pharmacological and Toxicological Methods, 63 (2) (2011) 143–149.CrossRefGoogle Scholar
  11. [11]
    W. Peng et al., Reverse-flow centrifugal separators in parallel: performance and flow pattern, Am Inst. Chem. Engrs J., 53 (3) (2007) 589–597.CrossRefGoogle Scholar
  12. [12]
    T. Mothila and K. Pitchandi, Influence of inlet velocity of air and solid particle feed rate on holdup mass and heat transfer characteristics in cyclone heat exchanger, Journal of Mechanical Science and Technology, 29 (10) (2015) 4509–4518.CrossRefGoogle Scholar
  13. [13]
    R. S. Dungan, Use of a culture-independent approach to characterize aerosolized bacteria near an open-freestall dairy operation, Environment International, 41 (2012) 8–14.CrossRefGoogle Scholar
  14. [14]
    J. Macher et al., Field evaluation of a personal, bioaerosol cyclone sampler, Journal of Occupational and Environmental Hygiene, 5 (11) (2008) 724–734.CrossRefGoogle Scholar
  15. [15]
    A. D. Tolchinsky et al., Development of a personal bioaerosol sampler based on a conical cyclone with recirculating liquid film, Occupational and Environmental Hygiene, 7 (3) (2010) 156–162.CrossRefGoogle Scholar
  16. [16]
    R. Persoons et al., Critical working tasks and determinants of exposure to bioaerosols and MVOC at composting facilities, International Journal of Hygiene and Environmental Health, 213 (5) (2010) 338–347.CrossRefGoogle Scholar
  17. [17]
    B. K. Lavine et al., Prediction of mold contamination from microbial volatile organic compound profiles using head space gas chromatography/mass spectrometry, Microchemical Journal, 103 (2012) 37–41.CrossRefGoogle Scholar
  18. [18]
    C. W. Park et al., Effects of condensational growth on culturability of airborne bacteria: implications for sampling and control of bioaerosols, Journal of Aerosol Science, 42 (2011) 213–223.CrossRefGoogle Scholar
  19. [19]
    R. C. Spicer et al., Differences in detection frequency as a bioaerosol data criterion for evaluating suspect fungal contamination, Building and Environment, 45 (5) (2010) 1304–1311.CrossRefGoogle Scholar
  20. [20]
    S. Zhen et al., A comparison of the efficiencies of a portable BioStage impactor and a Reuter centrifugal sampler (RCS) High Flow for measuring airborne bacteria and fungi concentrations, Journal of Aerosol Science, 40 (6) (2009) 503–513.MathSciNetCrossRefGoogle Scholar
  21. [21]
    M. Son et al., Development of a novel aerosol impactor utilizing inward flow from a ring-shaped nozzle, Journal of Aerosol Science, 85 (2015) 1–9.CrossRefGoogle Scholar
  22. [22]
    B. Ngom et al., Development and application of lateral flow test strip technology for detection of infectious agents and chemical contaminants: a review, Analytical and Bioanalytical Chemistry, 397 (3) (2010) 1113–1135.CrossRefGoogle Scholar
  23. [23]
    A. R. McFarland et al., Wetted wall cyclones for bioaerosol sampling, Aerosol Science and Technology, 44 (4) (2010) 241–252.CrossRefGoogle Scholar
  24. [24]
    W. C. Hinds, Aerosol technology: Properties, behavior, and measurement of airborne particles, Wiley, New York and Chichester (1999) 190–195.Google Scholar
  25. [25]
    S. S. Hu and A. R. McFarland, Numerical performance simulation of a wetted wall bioaerosol sampling cyclone, Aerosol Science and Technology, 41 (2) (2007) 160–168.CrossRefGoogle Scholar
  26. [26]
    P. Skladal et al., Electrochemical immunosensor coupled to cyclone air sampler for detection of escherichia coli DH5 alpha in bioaerosols, Electroanalysis, 24 (3) (2012) 539–546.CrossRefGoogle Scholar
  27. [27]
    J. A. Hubbard et al., Liquid consumption of wetted wall bioaerosol sampling cyclones: Characterization and control, Aerosol Science and Technology, 45 (2) (2011) 172–182.CrossRefGoogle Scholar
  28. [28]
    J. M. Blatny et al., Tracking airborne Legionella and Legionella pneumophila at a biological treatment plant, Environmental Science & Technology, 42 (19) (2008) 7360–7367.CrossRefGoogle Scholar
  29. [29]
    S. Bamrungsap et al., Rapid and sensitive lateral flow immunoassay for influenza antigen using fluorescently-doped silica nanoparticles, Microchimica Acta, 181 (1) (2014) 223–230.CrossRefGoogle Scholar
  30. [30]
    N. Nagatani et al., Detection of influenza virus using a lateral flow immunoassay for amplified DNA by a microfluidic RT-PCR chip, Analyst, 137 (2012) 3422–3426.CrossRefGoogle Scholar
  31. [31]
    K. J. Jang et al., Optical reading system for quantitative analysis of lateral flow assay (LFA) based immunological diagnostic kits, Proceedings of the The Korean BioChip Society (2014) PIII-2-12.Google Scholar
  32. [32]
    F. Zhang et al., Lanthanide-labeled immunochromatographic strips for the rapid detection of Pantoea stewartii subsp stewartii, Biosensors & Bioelectronics, 51 (15) (2014) 29–35.CrossRefGoogle Scholar
  33. [33]
    W. Y. Zhang et al., Direct, analysis of trichloropyridinol in human saliva using an Au nanoparticles-based immunochromatographic test strip for biomonitoring of exposure to chlorpyrifos, Talanta, 114 (30) (2013) 261–267.CrossRefGoogle Scholar
  34. [34]
    W. Xu et al., Ru(phen)(3)(2+) doped silica nanoparticle based immunochromatographic strip for rapid quantitative detection of beta-agonist residues in swine urine, Talanta, 114 (30) (2013) 160–166.CrossRefGoogle Scholar
  35. [35]
    W. Wu et al., A lateral flow biosensor for the detection of human pluripotent stem cells, Analytical Biochemistry, 436 (2) (2013) 160–164.CrossRefGoogle Scholar

Copyright information

© The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.School of Mechanical EngineeringSungkyunkwan UniversitySuwonKorea
  2. 2.Department of Nuclear, Plasma, and Radiological EngineeringUniversity of Illinois at Urbana-ChampaignUrbanaUSA
  3. 3.Department of Mechanical EngineeringChungnam National UniversityDaejeonKorea
  4. 4.SKKU Advanced Institute of Nanotechnology (SAINT)Sungkyunkwan UniversitySuwonKorea

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