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Microfluidic Systems: Recent Advances in Chronic Disease Diagnosis and Their Therapeutic Management

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Abstract

Microfluidics has advanced the area of diagnostics during the past ten years by offering fresh approaches that weren’t achievable with traditional detection and treatment techniques. High-throughput operations can be carefully controlled by using microfluidics and are very cost-effective too. It has been accepted to be a quick and effective method for controlled medication delivery, biological sample preparation, and analysis. This new technology has made it possible to create a wide range of micro and nanocarriers for poorly soluble medications, which has many advantages over traditional drug delivery techniques. Furthermore, a targeted medication delivery system utilizing microfluidic technology can be developed to enhance the drug's local bioavailability. Over the years, extensive R&D in microfluidic technology has led to the creation of various advanced applications in both laboratory and consumer biotechnology. Miniaturized genetic and proteasome analyzers, cell culture and control platforms, biosensors, disease detection, optical imaging devices, diagnostic advanced drugs, drug delivery schemes, and innovative products are some of the advanced applications of the microfluidics system. Also, these are highly adaptable microfluidic tools for disease detection and organ modeling, as well as transduction devices used in biomedical applications to detect biological and chemical changes. Beyond the specialized difficulties in studying cell–cell interactions, microfluidics has several difficulties in biomedical applications, especially for diagnostic devices where minute interactions can lead to imprecise evaluations. Assay function can be significantly changed by the way plastics, adhesives, and other materials interact. Therefore, the foundation of microfluidic technology needs to be grounded in real-world uses that can be produced on a big scale and at a reasonable cost. Further, it is a very interdisciplinary field that requires the collaboration of professionals in fluidics, assay science, materials science, and instrumentation to provide devices with the proper and needed functionality. In this article, we have discussed the advanced disease diagnosis and their therapeutic management which will help to understand the current scenario in the field of microfluidics diagnosis and will fill knowledge about the ‘gap’ in the system.

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References

  1. Singh A, Agarwal R, Diaz-Ruiz CA, Willett NJ, Wang P, Lee LA, Wang Q, Guldberg RE, García AJ (2014) Nanoengineered particles for enhanced intra-articular retention and delivery of proteins. Adv Healthc Mater. https://doi.org/10.1002/adhm.201400051

    Article  PubMed  PubMed Central  Google Scholar 

  2. Duncanson WJ, Lin T, Abate AR, Seiffert S, Shah RK, Weitz DA (2012) Microfluidic synthesis of advanced microparticles for encapsulation and controlled release. Lab Chip 12:2135–2145

    Article  PubMed  CAS  Google Scholar 

  3. Prausnitz MR, Langer R (2008) Transdermal drug delivery. Nat Biotechnol 26:1261–1268

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Avesar J, Arye TB, Levenberg S (2014) Frontier microfluidic techniques for short and longterm single cell analysis. Lab Chip 14:2161–2167

    Article  PubMed  CAS  Google Scholar 

  5. Wu J, Kong T, Yeung KWK, Shum HC, Cheung KMC, Wang L, To MKT (2013) Fabrication and characterization of monodisperse PLGA–alginate core–shell microspheres with monodisperse size and homogeneous shells for controlled drug release. Acta Biomater 9:7410–7419

    Article  PubMed  CAS  Google Scholar 

  6. Kochhar JS, Goh WJ, Chan SY, Kang L (2013) A simple method of microneedle array fabrication for transdermal drug delivery. Drug Dev Ind Pharm 39:299–309

    Article  PubMed  CAS  Google Scholar 

  7. Kochhar JS, Anbalagan P, Shelar SB, Neo JK, Iliescu C, Kang L (2014) Direct microneedle array fabrication off a photomask to deliver collagen through skin. Pharm Res 31:1–11

    Article  Google Scholar 

  8. Jivani RR, Lakhtaria GJ, Patadiya DD, Patel LD, Jivani NP, Jhala BP (2013) Biomedical microelectromechanical systems (BioMEMS): revolution in drug delivery and analytical techniques. Saudi Pharm J 24:1–20

    Article  PubMed  PubMed Central  Google Scholar 

  9. Cui A, Li H, Wang D, Zhong J, Chen Y, Lu H (2020) Global, regional prevalence, incidence and risk factors of knee osteoarthritis in population-based studies. EClinicalMedicine 29:100587

    Article  PubMed  Google Scholar 

  10. Katz JN, Arant KR, Loeser RF (2021) Diagnosis and treatment of hip and knee osteoarthritis: a review. JAMA 325:568–578

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Zhao X, Liu S, Yildirimer L, Zhao H, Ding R, Wang H et al (2016) Injectable stem cell-laden photocrosslinkable microspheres fabricated using microfluidics for rapid generation of osteogenic tissue constructs. Adv Funct Mater 26:2809–2819

    Article  CAS  Google Scholar 

  12. Au M, Liu Z, Rong L, Zheng Y, Wen C (2020) Endothelin-1 induces chondrocyte senescence and cartilage damage via endothelin receptor type b in a post-traumatic osteoarthritis mouse model. Osteoarthr Cartil 28:1559–1571

    Article  CAS  Google Scholar 

  13. Chen X, Zhang YS, Zhang XP, Liu CS (2021) Organ-on-a-chip platforms for accelerating the evaluation of nanomedicine. Bioact Mater 6:1012–1027

    PubMed  CAS  Google Scholar 

  14. Vunjak-Novakovic G, Ronaldson-Bouchard K, Radisic M (2021) Organs-on-a-chip models for biological research. Cell 184:4597–4611

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Huh D, Matthews BD, Mammoto A, Montoya-Zavala M, Hsin HY, Ingber DE (2010) Reconstituting organ-level lung functions on a chip. Science 328:1662–1668

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Nunes SS, Miklas JW, Liu J, Aschar-Sobbi R, Xiao Y, Zhang B et al (2013) Biowire: a platform for maturation of human pluripotent stem cell– derived cardiomyocytes. Nat Methods 10:781–787

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Aleman J, Kilic T, Mille LS, Shin SR, Zhang YS (2021) Microfluidic integration of regeneratable electrochemical affinity-based biosensors for continual monitoring of organ-on-a-chip devices. Nat Protoc 16:2564–2593

    Article  PubMed  CAS  Google Scholar 

  18. Silva MO, Gregory JL, Ansari N, Stok KS (2020) Molecular signaling interactions and transport at the osteochondral interface: a review. Front Cell Dev Biol. https://doi.org/10.3389/fcell.2020.00750

    Article  PubMed  PubMed Central  Google Scholar 

  19. Shi X, Zhou J, Zhao Y, Li L, Wu H (2013) Gradient-regulated hydrogel for interface tissue engineering: steering simultaneous osteo/chondrogenesis of stem cells on a chip. Adv Healthc Mater 2:846–853

    Article  PubMed  CAS  Google Scholar 

  20. Prokai-Tatrai K, Prokai L (2003) Modifying peptide properties by prodrug design for enhanced transport into the CNS. Prog Drug Res 61:155–188. https://doi.org/10.1007/978-3-0348-8049-7_6

    Article  PubMed  CAS  Google Scholar 

  21. Huot P, Fox SH (2011) The serotonergic system in Parkinson’s disease. Prog Neurobiol 95:163–212. https://doi.org/10.1016/j.pneurobio.08.004

    Article  PubMed  CAS  Google Scholar 

  22. Perry M, Li Q, Kennedy RT (2009) Review of recent advances in analytical techniques for the determination of neurotransmitters. Anal Chim Acta 653:1–22

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Trouillon R, Svensson MI, Berglund EC, Cans AS, Ewing AG (2012) Highlights of selected recent electrochemical measurements in living systems. Electrochim Acta 84:84–95. https://doi.org/10.1016/j.electacta.2012.04.164

    Article  CAS  Google Scholar 

  24. Wang J, Ren L, Li L, Liu W, Zhou J, Yu W, Tong D, Chen S (2009) Microfluidics: a new cosset for neurobiology. Lab Chip 9:644–52. https://doi.org/10.1039/b813495b

    Article  PubMed  CAS  Google Scholar 

  25. Nandi P, Lunte SM (2009) Recent trends in microdialysis sampling integrated with conventional and microanalytical systems for monitoring biological events: a review. Anal Chim Acta 651:1–14. https://doi.org/10.1016/j.aca.2009.07.064

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Hanson JN, Motala MJ, Heien ML, Gillette M, Sweedler J, Nuzzo RG (2009) Textural guidance cues for controlling process outgrowth of mammalian neurons. Lab Chip 9:122–31. https://doi.org/10.1039/b803595d

    Article  PubMed  CAS  Google Scholar 

  27. Clark P, Britland S, Connolly P (1993) Growth cone guidance and neuron morphology on micropatterned laminin surfaces. J Cell Sci 105:203–212. https://doi.org/10.1242/jcs.105.1.203

    Article  PubMed  CAS  Google Scholar 

  28. Rogers JA, Nuzzo RG (2005) Recent progress in soft lithography. Mater Today 8:50–56

    Article  CAS  Google Scholar 

  29. Chauhan G, Madou MJ, Kalra S, Chopra V, Ghosh D, Martinez-Chapa SO (2020) Nanotechnology for COVID-19: therapeutics and vaccine research. ACS Nano 14:7760–7782. https://doi.org/10.1021/acsnano.0c04006

    Article  PubMed  CAS  Google Scholar 

  30. Liu Y, Workalemahu B, Jiang X (2017) The effects of physicochemical properties of nanomaterials on their cellular uptake in vitro and in vivo. Small 13:1701815. https://doi.org/10.1002/smll.201701815

    Article  CAS  Google Scholar 

  31. Mishra DK, Shandilya R, Mishra PK (2018) Lipid based nanocarriers: a translational perspective. Nanomed Nanotechnol, Biol Med 14:2023–2050. https://doi.org/10.1016/j.nano.2018.05.021

    Article  CAS  Google Scholar 

  32. Zhao Z, Cui H, Song W, Ru X, Zhou W, Yu X (2020) A simple magnetic nanoparticles-based viral RNA extraction method for efficient detection of SARS-CoV-2. bioRxiv. https://doi.org/10.1101/2020.02.22.961268

    Article  PubMed  PubMed Central  Google Scholar 

  33. Qiu G, Gai Z, Tao Y, Schmitt J, Kullak-Ublick GA, Wang J (2020) Dual-functional plasmonic photothermal biosensors for highly accurate severe acute respiratory syndrome coronavirus 2 detection. ACS nano 14:5268–5277

    Article  PubMed  CAS  Google Scholar 

  34. Shapiro RS (2021) COVID-19 vaccines and nanomedicine. Int J Dermatol. https://doi.org/10.1111/ijd.15673

    Article  PubMed  PubMed Central  Google Scholar 

  35. Varahachalam SP, Lahooti B, Chamaneh M, Bagchi S, Chhibber T, Morris K et al (2021) Nanomedicine for the SARS-CoV-2: state-of-the-art and future prospects. Int J Nanomedicine 16:539. https://doi.org/10.2147/ijn.s283686

    Article  PubMed  PubMed Central  Google Scholar 

  36. Li F, Qi J, Ren Z, Hu X, Chen Y, Li B, Fu X (2023) Tetrahedral DNA framework assisted rotational paper-based analytical device for differential detection of SARS-CoV-2 and influenza A H1N1 virus. Microchem J 185:108304

    Article  PubMed  CAS  Google Scholar 

  37. Alhadrami HA (2018) Biosensors classifications, medical applications, and future prospective. Biotechnol Appl Biochem 65:497–508

    Article  PubMed  CAS  Google Scholar 

  38. Alsabbagh K, Hornung T, Voigt A, Sadir S, Rajabi T, Lange K (2021) Microfluidic impedance biosensor chips using sensing layers based on DNA-based self-assembled monolayers for label-free detection of proteins. Biosensors 11:80

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Xing Y, Zhao L, Cheng Z, Lv C, Yu F, Yu F (2021) Microfluidics-based sensing of biospecies. ACS Appl Bio Mater 4:2160–2191

    Article  PubMed  CAS  Google Scholar 

  40. Welch NL, Zhu M, Hua C, Weller J, Mirhashemi ME, Nguyen TG et al (2022) Multiplexed CRISPR-based microfluidic platform for clinical testing of respiratory viruses and identification of SARS-CoV-2 variants. Nat Med 28(5):1083–1094. https://doi.org/10.1038/s41591-022-01734-1. (Erratum in: Nat Med. 2024; 30(1):307)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Sundar S, Khetrapal-Singh P, Frampton J, Trimble E, Rajaraman P, Mehrotra R, Hariprasad R, Maitra A, Gill P, Suri V, Srinivasan R, Singh G, Thakur JS, Dhillon P, Cazier JB (2018) Harnessing genomics to improve outcomes for women with cancer in India: key priorities for research. Lancet Oncol 19:e102–e112. https://doi.org/10.1016/S1470-2045(17)30726-X.Erratum.In:LancetOncol.2018Jun;19(6):e283

    Article  PubMed  Google Scholar 

  42. Robin P, Barnabei L, Marocco S, Pagnoncelli J, Nicolis D, Tarantelli C, Tavilla AC, Robortella R, Cascione L, Mayoraz L, Journot CM (2023) A DNA biosensors-based microfluidic platform for attomolar real-time detection of unamplified SARS-CoV-2 virus. Biosens Bioelectron: X 13:100302

    PubMed  CAS  Google Scholar 

  43. Fumet J-D, Truntzer C, Yarchoan M, Ghiringhelli F (2020) Tumour mutational burden as a biomarker for immunotherapy: current data and emerging concepts. Eur J Cancer 131:40–50

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. Suh RS, Zhu X, Phadke N et al (2006) IVF within microfluidic channels requires lower total numbers and lower concentrations of sperm. Hum Reprod 21:477–483

    Article  PubMed  Google Scholar 

  45. Swain J, Lai D, Takayama S et al (2013) Thinking big by thinking small: application of microfluidic technology to improve ART. Lab Chip 13:1213–1224

    Article  PubMed  CAS  Google Scholar 

  46. Han C, Zhang Q, Ma R et al (2010) Integration of single oocyte trapping, in vitro fertilization and embryo culture in a microwell-structured microfluidic device. Lab Chip 10:2848–2854

    Article  PubMed  CAS  Google Scholar 

  47. Farokhzad OC, Langer R (2009) Impact of nanotechnology on drug delivery. ACS Nano 3:16–20

    Article  PubMed  CAS  Google Scholar 

  48. Davis ME, Chen ZG, Shin DM (2008) Nanoparticle therapeutics: an emerging treatment modality for cancer. Nat Rev Drug Discov 7:771–782

    Article  PubMed  CAS  Google Scholar 

  49. Amiji MM, Vyas TK, Shah LK (2006) Role of nanotechnology in HIV/AIDS treatment: potential to overcome the viral reservoir challenge. Discov Med 6:157–162

    PubMed  Google Scholar 

  50. Pornillos O, Ganser-Pornillos BK, Kelly BN et al (2009) X-ray structures of the hexameric building block of the HIV capsid. Cell 137:1282–1292

    Article  PubMed  PubMed Central  Google Scholar 

  51. Parsa H, Wang BZ, Vunjak-Novakovic GA (2017) microfluidic platform for the high-throughput study of pathological cardiac hypertrophy. LChip 17:3264–3271

    CAS  Google Scholar 

  52. Shang L, Cheng Y, Zhao Y (2017) Emerging droplet microfluidics. Chem Rev 117:7964–8040

    Article  PubMed  CAS  Google Scholar 

  53. Demello AJ (2006) Control and detection of chemical reactions in microfluidic systems. Nature 442:394–402

    Article  PubMed  CAS  Google Scholar 

  54. Wang S et al (2020) Inner surface design of functional microchannels for microscale flow control. Small 16:1905318

    Article  CAS  Google Scholar 

  55. Huang G et al (2017) Functional and biomimetic materials for engineering of the three-dimensional cell microenvironment. Chem Rev 117:12764–12850

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Hong YJ, Jeong H, Cho KW, Lu N, Kim DH (2019) Wearable and implantable devices for cardiovascular healthcare: from monitoring to therapy based on flexible and stretchable electronics. Adv Funct Mater 29:1808247

    Article  Google Scholar 

  57. Klostranec JM, Xiang Q, Farcas GA, Lee JA, Rhee A, Lafferty EI, Perrault SD, Kain KC, Chan WC (2007) Convergence of quantum dot barcodes with microfluidics and signal processing for multiplexed high-throughput infectious disease diagnostics. Nano lett 7:2812–2818

    Article  PubMed  CAS  Google Scholar 

  58. Chen L, Fatima S, Peng J, Leng X (2009) SELDI protein chip technology for the detection of serum biomarkers for liver disease. Protein Pept Lett 16:467–472

    Article  PubMed  CAS  Google Scholar 

  59. Foudeh AM, Didar TF, Veres T, Tabrizian M (2012) Microfluidic designs and techniques using lab-on-a-chip devices for pathogen detection for point-of-care diagnostics. Lab Chip 12:3249–3266

    Article  PubMed  CAS  Google Scholar 

  60. Kodani M, Mixson-Hayden T, Drobeniuc J, Kamili S (2014) Rapid and sensitive approach to simultaneous detection of genomes of hepatitis A, B, C, D and E viruses. J Clin Virol 61:260–264

    Article  PubMed  CAS  Google Scholar 

  61. Chang HC, Chao YT, Yen JY, Yu YL, Lee CN, Ho BC, Liu KC, Fang J, Lin CW, Lee JH (2015) A turbidity test based centrifugal microfluidics diagnostic system for simultaneous detection of HBV, HCV, and CMV. Adv Mater Sci Eng 2015: 1–8

    Google Scholar 

  62. Duan L, Wang Y, Li S-S, Wan Z, Zhai J (2005) Rapid and simultaneous detection of human hepatitis B virus and hepatitis C virus antibodies based on a protein chip assay using nano-gold immunological amplification and silver staining method. BMC Infect Dis 5:53

    Article  PubMed  PubMed Central  Google Scholar 

  63. Alzheimer’s Association (2020) Available online: https://www.alz.org/alzheimers-dementia/what-isalzheimers (Accessed on 18 June 2020)

  64. Portet F, Ousset PJ, Visser PJ, Frisoni GB, Nobili F, Scheltens P, Vellas B, Touchon J (2006) MCI Working Group of the European Consortium on Alzheimer’s Disease (EADC). Mild cognitive impairment (MCI) in medical practice: a critical review of the concept and new diagnostic procedure. Report of the MCI working group of the European consortium on Alzheimer’s disease. J Neurol Neurosurg Psychiatry 77:714–718

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  65. Yeo LY, Chang HC, Chan PPY, Friend JR (2011) Microfluidic devices for bioapplications. Small 7:12–48

    Article  PubMed  CAS  Google Scholar 

  66. Lee S-A, Kang E, Ju J, Kim D-S, Lee S-H (2013) Spheroid-based three-dimensional liver-on-a-chip to investigate hepatocyte–hepatic stellate cell interactions and flow effects. Lab Chip 13:3529–3537

    Article  PubMed  CAS  Google Scholar 

  67. Duval K, Grover H, Han LH, Mou Y, Pegoraro AF, Fredberg J, Chen Z (2017) Modeling physiological events in 2D vs. 3D cell culture. Physiology 32:266–277

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  68. Yi YY, Park JS, Lim J, Lee CJ, Lee SH (2015) Central nervous system and its disease models on a chip. Trends Biotechnol 33:762–776

    Article  PubMed  CAS  Google Scholar 

  69. Lista S, O’Bryant SE, Blennow K, Dubois B, Hugon J, Zetterberg H, Hampel H (2015) Biomarkers in sporadic and familial Alzheimer’s disease. J Alzheimers Dis 47:291–317

    Article  PubMed  Google Scholar 

  70. Irizarry MC (2004) Biomarkers of Alzheimer disease in plasma. NeuroRx 1:226–234

    Article  PubMed  PubMed Central  Google Scholar 

  71. Lista S, O’Bryant SE, Blennow K, Dubois B, Hugon J, Zetterberg H, Hampel H, Shen Y (2015) Biomarkers in sporadic and familial Alzheimer’s disease. J Alzheimers Dis 47:291–317

    Article  PubMed  Google Scholar 

  72. Hampel H, O’Bryant SE, Molinuevo JL, Zetterberg H, Masters CL, Lista S, Kiddle SJ, Batrla R, Blennow K (2018) Blood-based biomarkers for Alzheimer disease: mapping the road to the clinic. Nat Rev Neurol 14:639–652

    Article  PubMed  PubMed Central  Google Scholar 

  73. Grundke-Iqbal I, Iqbal K, Tung Y-C, Quinlan M, Wisniewski HM, Binder LI (1986) Abnormal phosphorylation of the microtubule-associated protein tau (tau) in Alzheimer cytoskeletal pathology. Proc Natl Acad Sci USA 83:4913–4917

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  74. Fillit HM, Refolo LM (2002) Tau and Alzheimer’s disease. J Mol Neurosci 19:249–250

    Article  PubMed  CAS  Google Scholar 

  75. Overmyeapiola T, Lehtovirta M, Helisalmi S, Ramberg J, Alafuzoff I, Riekkinen PS, Soininen H (1997) The level of cerebrospinal fluid tau correlates with neurofibrillary tangles in Alzheimer’s disease. NeuroReport 8:3961–3963

    Article  Google Scholar 

  76. Vanmechelen E, Vanderstichele H, Davidsson P, Kerschaver EV, Perre BVD, Sjögren M, Andreasen N, Blennow K (2000) Quantification of tau phosphorylated at threonine 181 in human cerebrospinal fluid: a sandwich ELISA with a synthetic phosphopeptide for standardization. Neurosci. Lett 285:49–52

    Article  PubMed  CAS  Google Scholar 

  77. Petzold A (2005) Neurofilament phosphoforms: surrogate markers for axonal injury, degeneration and loss. J Neurol Sci 233:183–198

    Article  PubMed  CAS  Google Scholar 

  78. Bacioglu M, Maia L, Preische O, Schelle J, Jucker M (2016) Neurofilament light chain in blood and CSF as marker of disease progression in mouse models and in neurodegenerative diseases. Neuron 91:494–496

    Article  PubMed  CAS  Google Scholar 

  79. Preische O, Schultz SA, Apel A, Kuhle J, Kaeser SA, Barro C, Gräber S, Kuder-Buletta E, Lafougere C, Laske C et al (2019) Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer’s disease. Nat Med 25:277–283

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  80. Mestdagh P, Hartmann N, Baeriswyl L, Andreasen D, Bernard N, Chen C, Cheo D, D’Andrade P, DeMayo M, Dennis L et al (2014) Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study. Nat Methods 11:809–815

    Article  PubMed  CAS  Google Scholar 

  81. Boeri M, Verri C, Conte D, Roz L, Sozzi G (2011) MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer. Proc Natl Acad Sci USA 108:3713–3718

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  82. Hébert SS, Wang WX, Zhu Q, Nelson PT (2013) A study of small RNAs from cerebral neocortex of pathology-verified Alzheimer’s disease, dementia with lewy bodies, hippocampal sclerosis, frontotemporal lobar dementia, and non-demented human controls. J Alzheimers Dis 35:335–348

    Article  PubMed  PubMed Central  Google Scholar 

  83. Kenny AMH, Calero M, Rabano A, Madden SF, Adamson K, Forster R, Spain E, Prehn JH, Henshall DC, Medina M et al (2019) Elevated plasma microRNA-206 levels predict cognitive decline and progression to dementia from mild cognitive impairment. Biomolecules 9:734

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  84. Bianco F, Tonna N, Lovchik RD, Mastrangelo R, Morini R, Ruiz A, Delamarche E, Matteoli M (2012) Overflow microfluidic networks: application to the biochemical analysis of brain cell interactions in complex neuroinflammatory scenarios. Anal Chem 84:9833–9840

    Article  PubMed  CAS  Google Scholar 

  85. Urich E, Patsch C, Aigner S, Graf M, Iacone R, Freskgård P-O (2013) Multicellular self-assembled spheroidal model of the blood brain barrier. Sci Rep 3:1500

    Article  PubMed  PubMed Central  Google Scholar 

  86. Cho CF, Wolfe JM, Fadzen CM, Calligaris D, Hornburg K, Chiocca EA, Agar NYR, Pentelute BL, Lawler SE (2017) Blood-brain-barrier spheroids as an in vitro screening platform for brain-penetrating agents. Nat Commun 8:15623

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  87. Song HL, Shim S, Kim DH, Won SH, Joo S, Kim S, Jeon NL, Yoon SY (2014) β-Amyloid is transmitted via neuronal connections along axonal membranes. Ann Neurol 75:88–97

    Article  PubMed  CAS  Google Scholar 

  88. Lee JS, Ryu J, Park CB (2009) High-throughput analysis of Alzheimer’s beta-amyloid aggregation using a microfluidic self-assembly of monomers. Anal Chem 81:2751–2759

    Article  PubMed  CAS  Google Scholar 

  89. Lee JS, Park CB (2010) Microfluidic dissociation and clearance of Alzheimer’s beta-amyloid aggregates. Biomaterials 31:6789

    Article  PubMed  CAS  Google Scholar 

  90. Li W, Xu Z, Xu B, Chan CY, Lin X, Wang Y, Chen G, Wang Z, Yuan Q, Zhu G (2017) Investigation of the subcellular neurotoxicity of amyloid-β using a device integrating microfluidic perfusion and chemotactic guidance. Adv Healthc Mat 6:160895

    Google Scholar 

  91. Cho H, Hashimoto T, Wong E, Hori Y, Wood LB, Zhao L, Haigis KM, Hyman BT, Irimia D (2013) Microfluidic chemotaxis platform for differentiating the roles of soluble and bound amyloid-β on microglial accumulation. Sci Rep 3:1823

    Article  PubMed  PubMed Central  Google Scholar 

  92. Wu JW, Hussaini SA, Bastille IM, Rodriguez GA, Mrejeru A, Rilett K, Sanders DW, Cook C, Fu H, Boonen RACM (2016) Neuronal activity enhances tau propagation and tau pathology in vivo. Nat Neurosci 19:1085–1092

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  93. Claeysen S, BockaertJl GP (2015) Serotonin: a new hope in Alzheimer’s disease? ACS Chem Neurosci 6:940–943

    Article  PubMed  CAS  Google Scholar 

  94. LaFerla FM, Green KN, Oddo S (2007) Intracellular amyloid-β in Alzheimer’s disease. Nat Rev Neurosci 8:499–509

    Article  PubMed  CAS  Google Scholar 

  95. Béduer A, Joris P, Mosser S, Fraering PC, Renaud P (2015) Detection of Alzheimer’s disease amyloid-beta plaque deposition by deep brain impedance profiling. J Neural Eng 12:024001

    Article  PubMed  Google Scholar 

  96. Zhang X, Tian Y, Li Z, Tian X, Sun H, Liu H, Moore A, Ran C (2013) Design and synthesis of curcumin analogues for in vivo fluorescence imaging and inhibiting copper-induced cross-linking of amyloid beta species in Alzheimer’s disease. J Am Chem Soc 135:16397–409

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  97. Oh J, Yoo G, Chang YW, Kim HJ, Jose J, Kim E, Pyun JC, Yoo KH (2013) A carbon nanotube metal semiconductor field effect transistor-based biosensor for detection of amyloid-beta in human serum. Biosens Bioelectron 50:345–350

    Article  PubMed  CAS  Google Scholar 

  98. Georganopoulou DG, Chang L, Jwa-Min Nam C, Thaxton S, Mufson EJ, Klein WL, Mirkin CA (2005) Nanoparticle-based detection in cerebral spinal fluid of a soluble pathogenic biomarker for Alzheimer’s disease. Proc Nat Acad Sci 102:2273–2276. https://doi.org/10.1073/pnas.0409336102

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  99. Kaushik A, Yndart A, Jayant RD, Sagar V, Atluri V, Bhansali S, Nair M (2015) Electrochemical sensing method for point-of-care cortisol detection in human immunodeficiency virus-infected patients. Int J Nanomed 10:677

    Google Scholar 

  100. Vestergaard Md, Kerman K, Saito M, Nagatani N, Takamura Y, Tamiya EJ (2005) A rapid label-free electrochemical detection and kinetic study of Alzheimer’s amyloid beta aggregation. Am Chem Soc 127:11892–11893

    Article  CAS  Google Scholar 

  101. Oh J, Yoo G, Chang YW, Kim HJ, Jose J, Kim E, Pyun JC, Yoo KH (2013) A carbon nanotube metal semiconductor field effect transistor-based biosensor for detection of amyloid-beta in human serum. Biosens Bioelectron 50:345–350

    Article  PubMed  CAS  Google Scholar 

  102. Li J, Wu C, Chu PK, Gelinsky M (2020) 3d printing of hydrogels: Rational design strategies and emerging biomedical applications. Mater Sci Eng R Rep 140:100543

    Article  Google Scholar 

  103. Lewis JA (2006) Direct ink writing of 3d functional materials. Adv Func Mater 16:2193–2204

    Article  CAS  Google Scholar 

  104. Derby B (2010) Inkjet printing of functional and structural materials: fluid property requirements, feature stability, and resolution. Annu Rev Mater Res 40:395–414

    Article  CAS  Google Scholar 

  105. Tumbleston JR, Shirvanyants D, Ermoshkin N, Janusziewicz R, Johnson AR, Kelly D, Chen K, Pinschmidt R, Rolland JP, Ermoshkin A et al (2015) Continuous liquid interface production of 3d objects. Science 347:1349–1352

    Article  PubMed  CAS  Google Scholar 

  106. Jayamohan H, Sant HJ, Gale BK (2013) Applications of microfluidics for molecular diagnostics. Methods Mol Biol 949:305–334. https://doi.org/10.1007/978-1-62703-134-9_20.PMID:23329451

    Article  PubMed  CAS  Google Scholar 

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Acknowledgements

Authors are grateful to Dr. Shoor Vir Singh, Professor and Head, Department of Biotechnology at GLA University, Mathura for help and support during the present study.

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This review did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Saurabh G, AB contributed to the conceptualization, literature search, data collection, study design; Swadha G, AR contributed to critical review and preparation of the final version of the manuscript.

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Correspondence to Alok Bharadwaj or Amisha Rastogi.

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Pandey, S., Gupta, S., Bharadwaj, A. et al. Microfluidic Systems: Recent Advances in Chronic Disease Diagnosis and Their Therapeutic Management. Indian J Microbiol (2024). https://doi.org/10.1007/s12088-024-01296-5

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