布朗運動是一種自然現象，在過去的幾十年裡吸引了眾多研究人員並得到了廣泛的研究。特別是對於高靈敏度的蛋白質檢測，布朗運動檢測提供了可靠的技術。在這項研究中，雙性粒子在早期異常細胞激素分泌檢測中，展現了一種稱為旋轉布朗運動的自然現象，以及它在檢測微量生物分子中的潛在用途。通過用功能化的雙性粒子，目標細胞激素於旋轉擴散儀進行測量。根據斯托克斯-愛因斯坦-德拜關係，旋轉擴散對粒子體積變化高度敏感，可以通過閃爍信號進行量化。研究包括了了光源、穩定化和純化的前置時間以進行優化。可以在 300 秒內以 5 Hz 的綠光捕獲粒子圖像。在這樣的條件下，功能化的雙性粒子可達到 1 pg/mL 的檢測限。然而，由於粒徑、溫度和流體粘度之間的關係導致的分析不確定性通常會成為測量的障礙，為防止背景噪音成為在擴散測量中實現高精度檢測的關鍵。
因此，本研究首次提出一種基於粒子追蹤系統的自補償法，能夠去除溫度以及流體黏度變化的影響。本研究中平移布朗運動以粒子軌跡表示，而旋轉布朗運動以雙性粒子的閃爍信號表示。該演算法在溫度（10 °C 至 40 °C）和黏度（1 mPa.s 至 5 mPa.s）場中進行了模擬和實驗驗證。在生物感測器評估中，腫瘤壞死因子-α、干擾素−γ，被選為目標細胞激素。1 微米雙性粒子透過三明治免疫反應與 200 奈米螢光微珠結合，並利用旋轉擴散儀的量測，證實雙性粒子其旋轉擴散對於粒子體積的高敏感度，且可經由閃爍訊號進行量化。其自補償演算法以及交互相關法之檢測極限分別為 0.45pg/mL 以及 1 pg/mL.而自補償演算法受黏度以及溫度影響的不確定性較交互相關法分別低 164.14 以及 27.47 倍。結果表明自補償算法提供較低不確定性和高精度量測。本研究最終為未來需要超高穩定性和靈敏度的類似珠子免疫傳感提供了一種有前途的替代方案。

Brownian motion, which is a natural phenomenon, has attracted numerous researchers and received extensive studies over the past decades. Especially for the highly sensitive protein detection, Brownian motion detection provides a reliable technique. In this study, a natural phenomenon called rotational Brownian motion was characterized by Janus particles, and its potential use in the detection of trace biomolecules explored for early detection, such as abnormal cytokine secretion. Through the functionalization of the Janus particles with an antibody, the target cytokine, was measured in terms of rotational diffusion. Rotational diffusion is highly sensitive to the particle volume change according to the Stokes−Einstein−Debye relation and can be quantified by blinking signal. Accordingly, 1 μm half-gold and half-fluorescent microbeads were conjugated with 200 nm nanobeads through sandwiched immunocomplexes. The light source, lead time for stabilization, and
purification were investigated for optimization. Particle images can be captured with a green light at 5 Hz within 300 s. Under such conditions, the functionalized Janus particles eventually achieved a limit of detection of 1 pg/mL. However, the analysis uncertainty due to the coupling relationship between particle diameter, temperature, and fluid viscosity usually poses a barrier in measurement. Preventing random background noises becomes key to achieving high accuracy of detection in diffusometry.
Therefore, a simple self-compensated algorithm based on delicate removal of the temperature and fluid viscosity variations through particle tracking was firstly proposed in this study. To this end, translational Brownian motion was expressed in terms of particle trajectory while rotational Brownian motion was expressed in terms of blinking signal from Janus particles. The algorithm was verified simulatively and experimentally in controlled temperature (10 °C to 40 °C) and viscosity (1 mPa.s to 5 mPa.s) fields. In an evaluation of biosensing for a target protein, the target cytokine, that is, tumor necrosis factor-α and interferon-gamma, was measured in terms of rotational diffusion. According to StokesEinstein- Debye relation, rotational diffusion is highly sensitive to the particle volume change and can be quantified by blinking signal. Thereby, 1 μm half-gold and halffluorescence microbeads were conjugated with 200 nm nanobeads through sandwiched immunocomplexes. In an evaluation of biosensing for a target protein, IFN-, the limit of detection of the self-compensated diffusometry and cross-correlation diffusometry reached 0.45 pg/mL and 1 pg/mL, respectively. The uncertainty of viscosity and temperature of selfcompensated diffusometry were respectively 96 and 15 fold lower than the pure rotational Brownian motion counterpart. The result appeared to prove the low-uncertainty and highaccuracy biosensing capability resulting from the self-compensated algorithm. The research eventually provides a promising alternative to future similar bead-based immunosensing that requires ultra-high stability and sensitivity.

1. Alhajj, M. & Farhana, A. Enzyme-Linked Immunosorbent Assay. in StatPearls (StatPearls Publishing, 2021).
2. Homburger, H. & Singh, R. Assessment of proteins of the immune system. Clin. Immunol. 1419–1434 (2008) doi:10.1016/B978-0-323-04404-2.10096-X.
3. Simonian, M. H. Spectrophotometric Determination of Protein Concentration. Curr. Protoc. Cell Biol. 15, A.3B.1-A.3B.7 (2002).
4. Mahmood, T. & Yang, P.-C. Western blot: Technique, theory, and trouble shooting. North Am. J. Med. Sci. 4, 429–434 (2012).
5. Sethi, J. K. & Hotamisligil, G. S. Metabolic Messengers: tumour necrosis factor. Nat. Metab. 3, 1302–1312 (2021).
6. Gray, P. W. & Goeddel, D. V. Structure of the human immune interferon gene. Nature 298, 859–863 (1982).
7. Lassagne, H., Ressot, C., Mattei, M. G. & Gachon, A. M. F. Assignment of the Human Tear Lipocalin Gene (LCN1) to 9q34 by in Situ Hybridization. Genomics 18, 160–161 (1993).
8. di Giovine, F. S. & Duff, G. W. Interleukin 1: the first interleukin. Immunol. Today 11, 13–20 (1990).
9. Grotefend, S. et al. Protein quantitation using various modes of high-performance liquid chromatography. J. Pharm. Biomed. Anal. 71, 127–138 (2012).
10. Vestergaard, M. ’delanji, Kerman, K. & Tamiya, E. An Overview of Label-free Electrochemical Protein Sensors. Sensors 7, 3442–3458 (2007).
11. Han, X. X., Zhao, B. & Ozaki, Y. Surface-enhanced Raman scattering for protein detection. Anal. Bioanal. Chem. 394, 1719–1727 (2009).
12. Das, G. M., Managò, S., Mangini, M. & De Luca, A. C. Biosensing Using SERS Active Gold Nanostructures. Nanomater. Basel Switz. 11, 2679 (2021).
13. Wu, Y., Dang, H., Park, S.-G., Chen, L. & Choo, J. SERS-PCR assays of SARS-CoV-2 target genes using Au nanoparticles-internalized Au nanodimple substrates. Biosens. Bioelectron. 197, 113736 (2022).
14. Pérez-Fernández, B., Costa-García, A. & Muñiz, A. de la E.-. Electrochemical (Bio)Sensors for Pesticides Detection Using Screen-Printed Electrodes. Biosensors 10, (2020).
15. Vu, C.-A. & Chen, W.-Y. Field-Effect Transistor Biosensors for Biomedical Applications: Recent Advances and Future Prospects. Sensors 19, (2019).
16. Salehi, M. & Hamann-Steinmeier, A. Bioconjugation of SERS nanotags and increasing the reproducibility of results. BioNanoMaterials 18, (2017).
17. Yang, C. H., Chen, C. A. & Chen, C. F. Surface-modified cellulose paper and its application in infectious disease diagnosis. Sens. Actuators B-Chem. 265, 506–513 (2018).
18. Chaplin, B. P. Chapter 17 - Advantages, Disadvantages, and Future Challenges of the Use of Electrochemical Technologies for Water and Wastewater Treatment. in Electrochemical Water and Wastewater Treatment (eds. Martínez-Huitle, C. A., Rodrigo, M. A. & Scialdone, O.) 451–494 (Butterworth-Heinemann, 2018). doi:10.1016/B978-0-12-813160-2.00017-1.
19. Islam, S. et al. A smart nanosensor for the detection of human immunodeficiency virus and associated cardiovascular and arthritis diseases using functionalized graphene-based transistors. Biosens. Bioelectron. 126, 792–799 (2019).
20. Huergo, L. F. et al. Magnetic bead-based ELISA allow inexpensive, rapid and quantitative detection of human antibodies against SARS-CoV-2. medRxiv 2020.07.26.20162255 (2020) doi:10.1101/2020.07.26.20162255.
21. Wang, Y.-K. et al. An immunomagnetic-bead-based enzyme-linked immunosorbent assay for sensitive quantification of fumonisin B1. Food Control 40, 41–45 (2014).
22. Scholler, N. et al. Bead-based ELISA for validation of ovarian cancer early detection markers. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 12, 2117–2124 (2006).
23. Omar, N. A. S., Fen, Y. W., Abdullah, J., Chik, C. E. N. C. E. & Mahdi, M. A. Development of an optical sensor based on surface plasmon resonance phenomenon for diagnosis of dengue virus E-protein. Sens. Bio-Sens. Res. 20, 16–21 (2018).
24. Yang, C. H., Chen, C. A. & Chen, C. F. Surface-modified cellulose paper and its application in infectious disease diagnosis. Sens. Actuators B-Chem. 265, 506–513 (2018).
25. Wang, R. G., Zhang, W., Wang, P. L. & Su, X. O. A paper-based competitive lateral flow immunoassay for multi beta-agonist residues by using a single monoclonal antibody labelled with red fluorescent nanoparticles. Microchim. Acta 185, (2018).
26. Liana, D. D., Raguse, B., Gooding, J. J. & Chow, E. Recent advances in paper-based sensors. Sensors 12, 11505–11526 (2012).
27. González-Guerrero, A. B., Maldonado, J., Herranz, S. & Lechuga, L. M. Trends in photonic lab-on-chip interferometric biosensors for point-of-care diagnostics. Anal. Methods 8, 8380–8394 (2016).
28. Wu, J., Dong, M., Rigatto, C., Liu, Y. & Lin, F. Lab-on-chip technology for chronic disease diagnosis. Npj Digit. Med. 1, 7 (2018).
29. Patel, S., Nanda, R., Sahoo, S. & Mohapatra, E. Biosensors in Health Care: The Milestones Achieved in Their Development towards Lab-on-Chip-Analysis. Biochem. Res. Int. 2016, 3130469 (2016).
30. Chen, W.-L., Jayan, M., Kwon, J.-S. & Chuang, H.-S. Facile open-well immunofluorescence enhancement with coplanar-electrodes-enabled optoelectrokinetics and magnetic particles. Biosens. Bioelectron. 193, 113527 (2021).
31. Wang, J. C., Chi, S. W., Shieh, D. B. & Chuang, H. S. Development of a self-driving bioassay based on diffusion for simple detection of microorganisms. Sens. Actuators B-Chem. 278, 140–146 (2019).
32. Wang, J. C. et al. Culture-free detection of methicillin-resistant Staphylococcus aureus by using self-driving diffusometric DNA nanosensors. Biosens. Bioelectron. 148, (2020).
33. Wang, J. C., Chi, S. W., Yang, T. H. & Chuang, H. S. Label-Free Monitoring of Microorganisms and Their Responses to Antibiotics Based on Self-Powered Microbead Sensors. Acs Sens. 3, 2182–2190 (2018).
34. Lavalette, D., Tetreau, C., Tourbez, M. & Blouquit, Y. Microscopic viscosity and rotational diffusion of proteins in a macromolecular environment. Biophys. J. 76, 2744–2751 (1999).
35. Clayton, K. N., Berglund, G. D., Linnes, J. C., Kinzer-Ursem, T. L. & Wereley, S. T. DNA Microviscosity Characterization with Particle Diffusometry for Downstream DNA Detection Applications. Anal. Chem. 89, 13334–13341 (2017).
36. Chen, C. J., Chen, W. L., Phong, P. H. & Chuang, H. S. Investigation of Micro-volume Viscosity with Janus Microbeads Based on Rotational Brownian Motion. Sensors 19, (2019).
37. Chuang, H. S., Chen, Y. J. & Cheng, H. P. Enhanced diffusometric immunosensing with grafted gold nanoparticles for detection of diabetic retinopathy biomarker tumor necrosis factor-alpha. Biosens. Bioelectron. 101, 75–83 (2018).
38. Chen, W.-L. & Chuang, H.-S. Trace Biomolecule Detection with Functionalized Janus Particles by Rotational Diffusion. Anal. Chem. 92, (2020).
39. Fan, Y.-J., Deng, C.-Z., Chung, P.-S., Tian, W.-C. & Sheen, H.-J. A high sensitivity bead-based immunoassay with nanofluidic preconcentration for biomarker detection. Sens. Actuators B Chem. 272, 502–509 (2018).
40. Brown, R. XXVII. A brief account of microscopical observations made in the months of June, July and August 1827, on the particles contained in the pollen of plants; and on the general existence of active molecules in organic and inorganic bodies. Philos. Mag. 4, 161–173 (1828).
41. Einstein, A. Über die von der molekularkinetischen Theorie der Wärme geforderte Bewegung von in ruhenden Flüssigkeiten suspendierten Teilchen. Ann. Phys. 322, 549–560 (1905).
42. Knight, F. B. On the Random Walk and Brownian Motion. Trans. Am. Math. Soc. 103, 218–228 (1962).
43. Miller, C. C. The Stokes Einstein law for diffusion in solution. Proc. R. Soc. Lond. Ser. -Contain. Pap. Math. Phys. Character 106, 724–749 (1924).
44. Mayor, P., D’Anna, G., Barrat, A. & Loreto, V. Observing Brownian motion and measuring temperatures in vibration-fluidized granular matter. New J. Phys. 7, (2005).
45. Meng, X.-Y., Xu, Y., Zhang, H.-X., Mezei, M. & Cui, M. Predicting protein interactions by Brownian dynamics simulations. J. Biomed. Biotechnol. 2012, 121034–121034 (2012).
46. Cichocki, B., Ekiel-Jeżewska, M. L. & Wajnryb, E. Communication: Translational Brownian motion for particles of arbitrary shape. J. Chem. Phys. 136, 071102 (2012).
47. Kohler, L., Mader, M., Kern, C., Wegener, M. & Hunger, D. Tracking Brownian motion in three dimensions and characterization of individual nanoparticles using a fiber-based high-finesse microcavity. Nat. Commun. 12, 6385 (2021).
48. Chu, B. Laser Light Scattering. Annu. Rev. Phys. Chem. 21, 145–174 (1970).
49. Chamarthy, P. & Wereley, S. T. Micro-PIV-Based Diffusometry. in Encyclopedia of Microfluidics and Nanofluidics (ed. Li, D.) 1300–1305 (Springer US, 2008). doi:10.1007/978-0-387-48998-8_995.
50. Germain, D., Leocmach, M. & Gibaud, T. Differential dynamic microscopy to characterize Brownian motion and bacteria motility. Am. J. Phys. 84, 202–210 (2016).
51. Debye, P. Polar molecules. By P. Debye, Ph.D., Pp. 172. New York: Chemical Catalog Co., Inc., 1929. $ 3.50. J. Soc. Chem. Ind. 48, 1036–1037 (1929).
52. Wang, P. Y. & Mason, T. G. Dimer crystallization of chiral proteoids. Phys. Chem. Chem. Phys. 19, 7167–7175 (2017).
53. Hunter, G. L., Edmond, K. V., Elsesser, M. T. & Weeks, E. R. Tracking rotational diffusion of colloidal clusters. Opt. Express 19, 17189–17202 (2011).
54. Fujiwara, M., Shikano, Y., Tsukahara, R., Shikata, S. & Hashimoto, H. Observation of the linewidth broadening of single spins in diamond nanoparticles in aqueous fluid and its relation to the rotational Brownian motion. Sci. Rep. 8, (2018).
55. Wittmeier, A., Holterhoff, A. L., Johnson, J. & Gibbs, J. G. Rotational Analysis of Spherical, Optically Anisotropic Janus Particles by Dynamic Microscopy. Langmuir 31, 10402–10410 (2015).
56. Furry, W. H. Isotropic Rotational Brownian Motion. Phys. Rev. 107, 7–13 (1957).
57. Li, G. & Tang, J. X. Accumulation of Microswimmers near a Surface Mediated by Collision and Rotational Brownian Motion. Phys. Rev. Lett. 103, (2009).
58. McNaughton, B. H. et al. Experimental System for One-Dimensional Rotational Brownian Motion. J. Phys. Chem. B 115, 5212–5218 (2011).
59. Rings, D., Chakraborty, D. & Kroy, K. Rotational hot Brownian motion. New J. Phys. 14, 053012 (2012).
60. Kurzthaler, C. et al. Probing the Spatiotemporal Dynamics of Catalytic Janus Particles with Single-Particle Tracking and Differential Dynamic Microscopy. Phys. Rev. Lett. 121, 78001 (2018).
61. Walther, A. & Muller, A. H. E. Janus Particles: Synthesis, Self-Assembly, Physical Properties, and Applications. Chem. Rev. 113, 5194–5261 (2013).
62. Jiang, S. et al. Janus particle synthesis and assembly. Adv. Mater. 22, 1060–1071 (2010).
63. Johal, P. & Chaudhary, S. Electronic paper technology. Int J Adv Res Sci Eng 2, 106–110 (2013).
64. Howse, J. R. et al. Self-motile colloidal particles: from directed propulsion to random walk. Phys. Rev. Lett. 99, 048102 (2007).
65. Gangwal, S., Cayre, O. J., Bazant, M. Z. & Velev, O. D. Induced-charge electrophoresis of metallodielectric particles. Phys. Rev. Lett. 100, 058302 (2008).
66. Jiang, H.-R., Yoshinaga, N. & Sano, M. Active motion of a Janus particle by self-thermophoresis in a defocused laser beam. Phys. Rev. Lett. 105, 268302 (2010).
67. Paxton, W. F. et al. Catalytically induced electrokinetics for motors and micropumps. J. Am. Chem. Soc. 128, 14881–14888 (2006).
68. Xing, H. et al. DNA-directed assembly of asymmetric nanoclusters using Janus nanoparticles. ACS Nano 6, 802–809 (2012).
69. de Gennes, P.-G. Soft Matter (Nobel Lecture). Angew. Chem. Int. Ed. Engl. 31, 842–845 (1992).
70. Kim, S.-H., Kim, S.-H., Jeong, W. C. & Yang, S.-M. Low-Threshold Lasing in 3D Dye-Doped Photonic Crystals Derived from Colloidal Self-Assemblies. Chem. Mater. 21, 4993–4999 (2009).
71. Zhou, X., Du, Y. & Wang, X. Azo Polymer Janus Particles and Their Photoinduced, Symmetry-Breaking Deformation. ACS Macro Lett. 5, 234–237 (2016).
72. Howse, J. R. et al. Self-Motile Colloidal Particles: From Directed Propulsion to Random Walk. Phys Rev Lett 99, 048102 (2007).
73. Buttinoni, I., Volpe, G., Kümmel, F., Volpe, G. & Bechinger, C. Active Brownian motion tunable by light. J. Phys. Condens. Matter 24, 284129 (2012).
74. Paxton, W. F. et al. Catalytic Nanomotors:  Autonomous Movement of Striped Nanorods. J. Am. Chem. Soc. 126, 13424–13431 (2004).
75. Paxton, W. F. et al. Catalytically Induced Electrokinetics for Motors and Micropumps. J. Am. Chem. Soc. 128, 14881–14888 (2006).
76. Behrend, C. J., Anker, J. N., McNaughton, B. H. & Kopelman, R. Microrheology with modulated optical nanoprobes (MOONs). Proc. Fifth Int. Conf. Sci. Clin. Apllications Magn. Carr. 293, 663–670 (2005).
77. Behrend, C. J. et al. Metal-Capped Brownian and Magnetically Modulated Optical Nanoprobes (MOONs):  Micromechanics in Chemical and Biological Microenvironments. J. Phys. Chem. B 108, 10408–10414 (2004).
78. Casagrande, C. & Veyssie, M. Janus Beads - Realization and 1st Observation of Interfacial Properties. Comptes Rendus Acad. Sci. Ser. Ii 306, 1423–1425 (1988).
79. Zhang, J., Grzybowski, B. A. & Granick, S. Janus Particle Synthesis, Assembly, and Application. Langmuir 33, 6964–6977 (2017).
80. Jiang, S., Schultz, M. J., Chen, Q., Moore, J. S. & Granick, S. Solvent-free synthesis of Janus colloidal particles. Langmuir 24, 10073–10077 (2008).
81. Pawar, A. B. & Kretzschmar, I. Patchy particles by glancing angle deposition. Langmuir 24, 355–358 (2008).
82. Nakahama, K., Kawaguchi, H. & Fujimoto, K. A novel preparation of nonsymmetrical microspheres using the Langmuir- Blodgett technique. Langmuir 16, 7882–7886 (2000).
83. Bae, C., Moon, J., Shin, H., Kim, J. & Sung, M. M. Fabrication of monodisperse asymmetric colloidal clusters by using contact area lithography (CAL). J. Am. Chem. Soc. 129, 14232–14239 (2007).
84. Loget, G., Roche, J. & Kuhn, A. True bulk synthesis of Janus objects by bipolar electrochemistry. Adv. Mater. 24, 5111–5116 (2012).
85. Nie, Z., Li, W., Seo, M., Xu, S. & Kumacheva, E. Janus and ternary particles generated by microfluidic synthesis: design, synthesis, and self-assembly. J. Am. Chem. Soc. 128, 9408–9412 (2006).
86. Nisisako, T., Torii, T., Takahashi, T. & Takizawa, Y. Synthesis of monodisperse bicolored janus particles with electrical anisotropy using a microfluidic Co-Flow system. Adv. Mater. 18, 1152–1156 (2006).
87. Gröschel, A. H. et al. Facile, solution-based synthesis of soft, nanoscale Janus particles with tunable Janus balance. J. Am. Chem. Soc. 134, 13850–13860 (2012).
88. Takei, H. & Shimizu, N. Gradient sensitive microscopic probes prepared by gold evaporation and chemisorption on latex spheres. Langmuir 13, 1865–1868 (1997).
89. Love, J. C., Gates, B. D., Wolfe, D. B., Paul, K. E. & Whitesides, G. M. Fabrication and wetting properties of metallic half-shells with submicron diameters. Nano Lett. 2, 891–894 (2002).
90. Ogi, T., Modesto-Lopez, L. B., Iskandar, F. & Okuyama, K. Fabrication of a large area monolayer of silica particles on a sapphire substrate by a spin coating method. Colloids Surf. Physicochem. Eng. Asp. 297, 71–78 (2007).
91. Benjamin, P. & Weaver, C. The Adhesion of Evaporated Metal Films on Glass. Proc. R. Soc. Lond. Ser. Math. Phys. Sci. 261, 516–531 (1961).
92. Chen, S. B. & Ye, X. Faxen’s Laws of a Composite Sphere under Creeping Flow Conditions. J. Colloid Interface Sci. 221, 50–57 (2000).
93. Mathai, P. P., Berglund, A. J., Liddle, J. A. & Shapiro, B. A. Simultaneous positioning and orientation of a single nano-object by flow control: theory and simulations. New J. Phys. 13, 013027 (2011).
94. Buck, J. R., Daniel, M. M. & Singer, A. C. Computer Explorations in Signals and Systems Using MATLAB. (Prentice-Hall, Inc., 1997).
95. Stoica, P. & Moses, R. L. Spectral Analysis of Signals. Pearson Prentice Hall (2005).
96. Olsen, M. G. & Adrian, R. J. Out-of-focus effects on particle image visibility and correlation in microscopic particle image velocimetry. Exp. Fluids 29, S166–S174 (2000).
97. Huang, N. E. et al. The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series Analysis. Proc. Math. Phys. Eng. Sci. 454, 903–995 (1998).
98. Barnhart, B. L. The Hilbert-Huang transform: Theory, applications, development. in (2011).
99. Rilling, G., Flandrin, P. & Goncalves, P. On empirical mode decomposition and its algorithms. in IEEE-EURASIP workshop on nonlinear signal and image processing vol. 3 8–11 (NSIP-03, Grado (I), 2003).
100. Wang, G., Chen, X.-Y., Qiao, F.-L., Wu, Z. & Huang, N. E. On Intrinsic Mode Function. Adv. Adapt. Data Anal. 02, 277–293 (2010).
101. David, J. R. Delayed Hypersensitivity in Vitro - Its Mediation by Cell-Free Substances Formed by Lymphoid Cell-Antigen Interaction. Proc. Natl. Acad. Sci. U. S. A. 56, 72- (1966).
102. Cohen, S., Bigazzi, P. E. & Yoshida, T. Similarities of T-Cell Function in Cell-Mediated-Immunity and Antibody-Production. Cell. Immunol. 12, 150–159 (1974).
103. Boyle, J. J. Macrophage Activation in Atherosclerosis: Pathogenesis and Pharmacology of Plaque Rupture. Curr. Vasc. Pharmacol. 3, 63–68 (2005).
104. Poste, G. Bring on the biomarkers. Nature 469, 156–157 (2011).
105. Takemura, K. et al. Ultrasensitive detection of norovirus using a magnetofluoroimmunoassay based on synergic properties of gold/magnetic nanoparticle hybrid nanocomposites and quantum dots. Sens. Actuators B-Chem. 296, (2019).
106. Zhang, P. J., Yang, J. & Liu, D. B. Two-step signal amplification for high-sensitivity detection of biomarkers using gold nanoparticle-based conjugates. Electrophoresis 40, 2211–2217 (2019).
107. Gabbasov, R. et al. Study of Brownian motion of magnetic nanoparticles in viscous media by Mössbauer spectroscopy. J. Magn. Magn. Mater. 475, 146–151 (2019).
108. Ueda, H. et al. Open sandwich ELISA: A novel immunoassay based on the interchain interaction of antibody variable region. Nat. Biotechnol. 14, 1714–1718 (1996).
109. Cheng, H. P. & Chuang, H. S. Rapid and Sensitive Nano-Immunosensors for Botulinum. Acs Sens. 4, 1754–1760 (2019).
110. Park, Y. G. & Roh, Y. J. New Diagnostic and Therapeutic Approaches for Preventing the Progression of Diabetic Retinopathy. J. Diabetes Res. (2016) doi:Artn 1753584 10.1155/2016/1753584.
111. Stefansson, E. et al. Screening and prevention of diabetic blindness. Acta Ophthalmol. Scand. 78, 374–385 (2000).
112. Walther, A. & Muller, A. H. E. Janus Particles: Synthesis, Self-Assembly, Physical Properties, and Applications. Chem. Rev. 113, 5194–5261 (2013).
113. Keane, R. D. & Adrian, R. J. Theory of cross-correlation analysis of PIV images. Appl. Sci. Res. 49, 191–215 (1992).
114. Amendola, V., Pilot, R., Frasconi, M., Marago, O. M. & Iati, M. A. Surface plasmon resonance in gold nanoparticles: a review. J. Phys.-Condens. Matter 29, (2017).
115. Huang, X. H., Jain, P. K., El-Sayed, I. H. & El-Sayed, M. A. Plasmonic photothermal therapy (PPTT) using gold nanoparticles. Lasers Med. Sci. 23, 217–228 (2008).
116. Wang, X. et al. High-Motility Visible Light-Driven Ag/AgCl Janus Micromotors. Small 14, (2018).
117. Samy, R., Glawdel, T. & Ren, C. L. Method for Microfluidic Whole-Chip Temperature Measurement Using Thin-Film Poly(dimethylsiloxane)/Rhodamine B. Anal. Chem. 80, 369–375 (2008).
118. Shah, J. J., Gaitan, M. & Geist, J. Generalized Temperature Measurement Equations for Rhodamine B Dye Solution and Its Application to Microfluidics. Anal. Chem. 81, 8260–8263 (2009).
119. Costagliola, C. et al. TNF-Alpha Levels in Tears: A Novel Biomarker to Assess the Degree of Diabetic Retinopathy. Mediators Inflamm. 2013, 629529 (2013).
120. Teixeira, J., Bellissent-Funel, M.-C., Chen, S. H. & Dianoux, A. J. Experimental determination of the nature of diffusive motions of water molecules at low temperatures. Phys. Rev. A 31, 1913–1917 (1985).
121. Agmon, N. Tetrahedral Displacement: The Molecular Mechanism behind the Debye Relaxation in Water. J. Phys. Chem. 100, 1072–1080 (1996).
122. Laage, D. & Hynes, J. T. A Molecular Jump Mechanism of Water Reorientation. Science 311, 832 (2006).
123. Moilanen, D. E. et al. Water inertial reorientation: Hydrogen bond strength and the angular potential. Proc. Natl. Acad. Sci. 105, 5295 (2008).
124. Kawasaki, T. & Kim, K. Spurious violation of the Stokes–Einstein–Debye relation in supercooled water. Sci. Rep. 9, 8118 (2019).
125. Ishida, T., Maekawa, K. & Kishi, T. Enhanced modeling of moisture equilibrium and transport in cementitious materials under arbitrary temperature and relative humidity history. Cem. Concr. Res. 37, 565–578 (2007).
126. Squires, G. L. Practical Physics. (Cambridge University Press, 2001). doi:DOI: 10.1017/CBO9781139164498.
127. Davidson, G. A. A Modified Power Law Representation of the Pasquill-Gifford Dispersion Coefficients. J. Air Waste Manag. Assoc. 40, 1146–1147 (1990).
128. Woodard, R. Interpolation of Spatial Data: Some Theory for Kriging. Technometrics 42, 436–437 (2000).
129. Lu, G., Jiang, Z., Ye, L. & Huang, Y. Pulse Feature Extraction Based on Improved Gaussian Model. in 2014 International Conference on Medical Biometrics 90–94 (2014). doi:10.1109/ICMB.2014.23.
130. Volpe, G., Gigan, S. & Volpe, G. Simulation of the active Brownian motion of a microswimmer. Am. J. Phys. 82, 659–664 (2014).
131. Rosenblatt, M. Remarks on Some Nonparametric Estimates of a Density Function. Ann. Math. Stat. 27, 832–837 (1956).
132. Sheely, M. L. Glycerol Viscosity Tables. Ind. Eng. Chem. 24, 1060–1064 (1932).
133. Young, A. D. Boundary layers. (American Institute of Aeronautics and Astronautics, 1989).
134. Schroder, K., Hertzog, P. J., Ravasi, T. & Hume, D. A. Interferon-γ: an overview of signals, mechanisms and functions. J. Leukoc. Biol. 75, 163–189 (2004).