請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/85808完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 黃念祖(Nien-Tsu Huang) | |
| dc.contributor.author | Ching-Hsu Yang | en |
| dc.contributor.author | 楊景旭 | zh_TW |
| dc.date.accessioned | 2023-03-19T23:25:01Z | - |
| dc.date.copyright | 2022-04-26 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-03-31 | |
| dc.identifier.citation | 1. Tuerk, C.; Gold, L. Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. science 1990, 249, 505-510. 2. Cai, S.; Yan, J.; Xiong, H.; Liu, Y.; Peng, D.; Liu, Z. Investigations on the interface of nucleic acid aptamers and binding targets. Analyst 2018, 143, 5317-5338, doi:10.1039/c8an01467a. 3. Sun, W.; Song, W.; Guo, X.; Wang, Z. Ultrasensitive detection of nucleic acids and proteins using quartz crystal microbalance and surface plasmon resonance sensors based on target-triggering multiple signal amplification strategy. Anal Chim Acta 2017, 978, 42-47, doi:10.1016/j.aca.2017.04.047. 4. Bi, S.; Yue, S.; Zhang, S. Hybridization chain reaction: a versatile molecular tool for biosensing, bioimaging, and biomedicine. Chem Soc Rev 2017, 46, 4281-4298, doi:10.1039/c7cs00055c. 5. Özay, B.; McCalla, S.E. A review of reaction enhancement strategies for isothermal nucleic acid amplification reactions. Sensors and Actuators Reports 2021, 3, 100033, doi:https://doi.org/10.1016/j.snr.2021.100033. 6. Dirks, R.M.; Pierce, N.A. Triggered amplification by hybridization chain reaction. Proc Natl Acad Sci U S A 2004, 101, 15275-15278, doi:10.1073/pnas.0407024101. 7. Zhao, M.; Zhuo, Y.; Chai, Y.; Xiang, Y.; Liao, N.; Gui, G.; Yuan, R. Dual signal amplification strategy for the fabrication of an ultrasensitive electrochemiluminescenct aptasensor. Analyst 2013, 138, 6639-6644, doi:10.1039/C3AN01567J. 8. Lu, J.; Wu, L.; Hu, Y.; Wang, S.; Guo, Z. Ultrasensitive Faraday cage-type electrochemiluminescence assay for femtomolar miRNA-141 via graphene oxide and hybridization chain reaction-assisted cascade amplification. Biosens Bioelectron 2018, 109, 13-19, doi:10.1016/j.bios.2018.02.062. 9. Yang, C.H.; Wu, T.H.; Chang, C.C.; Lo, H.Y.; Liu, H.W.; Huang, N.T.; Lin, C.W. Biosensing Amplification by Hybridization Chain Reaction on Phase-Sensitive Surface Plasmon Resonance. Biosensors (Basel) 2021, 11, doi:10.3390/bios11030075. 10. Wang, H.; Li, C.; Liu, X.; Zhou, X.; Wang, F. Construction of an enzyme-free concatenated DNA circuit for signal amplification and intracellular imaging. Chemical Science 2018, 9, 5842-5849, doi:10.1039/C8SC01981A. 11. Zhou, P.; Yang, X.-L.; Wang, X.-G.; Hu, B.; Zhang, L.; Zhang, W.; Si, H.-R.; Zhu, Y.; Li, B.; Huang, C.-L., et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature 2020, 579, 270-273, doi:10.1038/s41586-020-2012-7. 12. Hu, B.; Guo, H.; Zhou, P.; Shi, Z.L. Characteristics of SARS-CoV-2 and COVID-19. Nat Rev Microbiol 2021, 19, 141-154, doi:10.1038/s41579-020-00459-7. 13. Asselah, T.; Durantel, D.; Pasmant, E.; Lau, G.; Schinazi, R.F. COVID-19: Discovery, diagnostics and drug development. J Hepatol 2021, 74, 168-184, doi:10.1016/j.jhep.2020.09.031. 14. Ravi, N.; Cortade, D.L.; Ng, E.; Wang, S.X. Diagnostics for SARS-CoV-2 detection: A comprehensive review of the FDA-EUA COVID-19 testing landscape. Biosens Bioelectron 2020, 165, 112454, doi:10.1016/j.bios.2020.112454. 15. Dramé, M.; Tabue Teguo, M.; Proye, E.; Hequet, F.; Hentzien, M.; Kanagaratnam, L.; Godaert, L. Should RT-PCR be considered a gold standard in the diagnosis of COVID-19? J Med Virol 2020, 92, 2312-2313, doi:10.1002/jmv.25996. 16. Mathuria, J.P.; Yadav, R.; Rajkumar. Laboratory diagnosis of SARS-CoV-2 - A review of current methods. J Infect Public Health 2020, 13, 901-905, doi:10.1016/j.jiph.2020.06.005. 17. van Niel, G.; D'Angelo, G.; Raposo, G. Shedding light on the cell biology of extracellular vesicles. Nature Reviews Molecular Cell Biology 2018, 19, 213-228, doi:10.1038/nrm.2017.125. 18. Zhang, Y.; Bi, J.; Huang, J.; Tang, Y.; Du, S.; Li, P. Exosome: A Review of Its Classification, Isolation Techniques, Storage, Diagnostic and Targeted Therapy Applications. Int J Nanomedicine 2020, 15, 6917-6934, doi:10.2147/IJN.S264498. 19. Steeg, P.S. Targeting metastasis. Nat Rev Cancer 2016, 16, 201-218, doi:10.1038/nrc.2016.25. 20. Homola, J. Surface plasmon resonance sensors for detection of chemical and biological species. Chem Rev 2008, 108, 462-493, doi:10.1021/cr068107d. 21. He, L.; Musick, M.D.; Nicewarner, S.R.; Salinas, F.G.; Benkovic, S.J.; Natan, M.J.; Keating, C.D. Colloidal Au-Enhanced Surface Plasmon Resonance for Ultrasensitive Detection of DNA Hybridization. Journal of the American Chemical Society 2000, 122, 9071-9077, doi:10.1021/ja001215b. 22. Zhang, Z.; Cheng, Q.; Feng, P. Selective removal of DNA-labeled nanoparticles from planar substrates by DNA displacement reactions. Angew Chem Int Ed Engl 2009, 48, 118-122, doi:10.1002/anie.200803840. 23. Yi, X.; Hao, Y.; Xia, N.; Wang, J.; Quintero, M.; Li, D.; Zhou, F. Sensitive and continuous screening of inhibitors of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) at single SPR chips. Anal Chem 2013, 85, 3660-3666, doi:10.1021/ac303624z. 24. Bai, Y.; Feng, F.; Zhao, L.; Wang, C.; Wang, H.; Tian, M.; Qin, J.; Duan, Y.; He, X. Aptamer/thrombin/aptamer-AuNPs sandwich enhanced surface plasmon resonance sensor for the detection of subnanomolar thrombin. Biosens Bioelectron 2013, 47, 265-270, doi:10.1016/j.bios.2013.02.004. 25. Deng, S.; Wang, P.; Yu, X. Phase-Sensitive Surface Plasmon Resonance Sensors: Recent Progress and Future Prospects. Sensors (Basel) 2017, 17, doi:10.3390/s17122819. 26. Nelson, S.G.; Johnston, K.S.; Yee, S.S. High sensitivity surface plasmon resonace sensor based on phase detection. Sensors and Actuators B: Chemical 1996, 35, 187-191, doi:https://doi.org/10.1016/S0925-4005(97)80052-4. 27. Kabashin, A.V.; Patskovsky, S.; Grigorenko, A.N. Phase and amplitude sensitivities in surface plasmon resonance bio and chemical sensing. Opt. Express 2009, 17, 21191-21204, doi:10.1364/OE.17.021191. 28. Gorodkiewicz, E.; Lukaszewski, Z. Recent Progress in Surface Plasmon Resonance Biosensors (2016 to Mid-2018). Biosensors (Basel) 2018, 8, doi:10.3390/bios8040132. 29. Nguyen, H.H.; Park, J.; Kang, S.; Kim, M. Surface plasmon resonance: a versatile technique for biosensor applications. Sensors (Basel) 2015, 15, 10481-10510, doi:10.3390/s150510481. 30. Šípová, H.; Homola, J. Surface plasmon resonance sensing of nucleic acids: a review. Anal Chim Acta 2013, 773, 9-23, doi:10.1016/j.aca.2012.12.040. 31. Lorenzo-Gómez, R.; Fernández-Alonso, N.; Miranda-Castro, R.; de-los-Santos-Álvarez, N.; Lobo-Castañón, M.J. Unravelling the lipocalin 2 interaction with aptamers: May rolling circle amplification improve their functional affinity? Talanta 2019, 197, 406-412, doi:https://doi.org/10.1016/j.talanta.2019.01.057. 32. Fathi, F.; Rashidi, M.-R.; Omidi, Y. Ultra-sensitive detection by metal nanoparticles-mediated enhanced SPR biosensors. Talanta 2019, 192, 118-127, doi:https://doi.org/10.1016/j.talanta.2018.09.023. 33. Li, Q.; Wang, Q.; Yang, X.; Wang, K.; Zhang, H.; Nie, W. High sensitivity surface plasmon resonance biosensor for detection of microRNA and small molecule based on graphene oxide-gold nanoparticles composites. Talanta 2017, 174, 521-526, doi:10.1016/j.talanta.2017.06.048. 34. Gu, Y.; Song, J.; Li, M.X.; Zhang, T.T.; Zhao, W.; Xu, J.J.; Liu, M.; Chen, H.Y. Ultrasensitive MicroRNA Assay via Surface Plasmon Resonance Responses of Au@Ag Nanorods Etching. Anal Chem 2017, 89, 10585-10591, doi:10.1021/acs.analchem.7b02920. 35. Wang, C.; Liu, M.; Wang, Z.; Li, S.; Deng, Y.; He, N. Point-of-care diagnostics for infectious diseases: From methods to devices. Nano Today 2021, 37, 101092, doi:https://doi.org/10.1016/j.nantod.2021.101092. 36. Wood, R.W. On a Remarkable Case of Uneven Distribution of Light in a Diffraction Grating Spectrum. Proceedings of the Physical Society of London 1902, 18, 269-275, doi:10.1088/1478-7814/18/1/325. 37. Wood, R.W. XXVII. Diffraction gratings with controlled groove form and abnormal distribution of intensity. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science 1912, 23, 310-317, doi:10.1080/14786440208637224. 38. Al Mohtar, A.; Vaillant, J.; Sedaghat, Z.; Kazan, M.; Joly, L.; Stoeffler, C.; Cousin, J.; Khoury, A.; Bruyant, A. Generalized lock-in detection for interferometry: application to phase sensitive spectroscopy and near-field nanoscopy. Opt Express 2014, 22, 22232-22245, doi:10.1364/oe.22.022232. 39. Vaillant, J.; Bruyant, A. An unbalanced interferometer insensitive to wavelength drift. Sensors and Actuators A: Physical 2017, 268, 188-192, doi:https://doi.org/10.1016/j.sna.2017.10.022. 40. Adams, N.M.; Leelawong, M.; Benton, A.; Quinn, C.; Haselton, F.R.; Schmitz, J.E. COVID-19 diagnostics for resource-limited settings: Evaluation of 'unextracted' qRT-PCR. J Med Virol 2021, 93, 559-563, doi:10.1002/jmv.26328. 41. Chang, C.C.; Lin, S.; Lee, C.H.; Chuang, T.L.; Hsueh, P.R.; Lai, H.C.; Lin, C.W. Amplified surface plasmon resonance immunosensor for interferon-gamma based on a streptavidin-incorporated aptamer. Biosens Bioelectron 2012, 37, 68-74, doi:10.1016/j.bios.2012.04.038. 42. Macdonald, J.; Denoyer, D.; Henri, J.; Jamieson, A.; Burvenich, I.J.G.; Pouliot, N.; Shigdar, S. Bifunctional Aptamer-Doxorubicin Conjugate Crosses the Blood-Brain Barrier and Selectively Delivers Its Payload to EpCAM-Positive Tumor Cells. Nucleic Acid Ther 2020, 30, 117-128, doi:10.1089/nat.2019.0807. 43. Bing, T.; Liu, X.; Cheng, X.; Cao, Z.; Shangguan, D. Bifunctional combined aptamer for simultaneous separation and detection of thrombin. Biosens Bioelectron 2010, 25, 1487-1492, doi:10.1016/j.bios.2009.11.003. 44. Brustugun, O.T.; Møller, B.; Helland, A. Years of life lost as a measure of cancer burden on a national level. Br J Cancer 2014, 111, 1014-1020, doi:10.1038/bjc.2014.364. 45. Kuo, C.-N.; Liao, Y.-M.; Kuo, L.-N.; Tsai, H.-J.; Chang, W.-C.; Yen, Y. Cancers in Taiwan: Practical insight from epidemiology, treatments, biomarkers, and cost. Journal of the Formosan Medical Association 2020, 119, 1731-1741, doi:https://doi.org/10.1016/j.jfma.2019.08.023. 46. Qian, C.N.; Mei, Y.; Zhang, J. Cancer metastasis: issues and challenges. Chin J Cancer 2017, 36, 38, doi:10.1186/s40880-017-0206-7. 47. Elvin, P.; Garner, A.P. Tumour invasion and metastasis: challenges facing drug discovery. Curr Opin Pharmacol 2005, 5, 374-381, doi:10.1016/j.coph.2005.02.008. 48. Langley, R.R.; Fidler, I.J. The seed and soil hypothesis revisited--the role of tumor-stroma interactions in metastasis to different organs. International journal of cancer 2011, 128, 2527-2535, doi:10.1002/ijc.26031. 49. Hoshino, A.; Costa-Silva, B.; Shen, T.-L.; Rodrigues, G.; Hashimoto, A.; Tesic Mark, M.; Molina, H.; Kohsaka, S.; Di Giannatale, A.; Ceder, S., et al. Tumour exosome integrins determine organotropic metastasis. Nature 2015, 527, 329-335, doi:10.1038/nature15756. 50. Hoshino, A.; Costa-Silva, B.; Shen, T.L.; Rodrigues, G.; Hashimoto, A.; Tesic Mark, M.; Molina, H.; Kohsaka, S.; Di Giannatale, A.; Ceder, S., et al. Tumour exosome integrins determine organotropic metastasis. Nature 2015, 527, 329-335, doi:10.1038/nature15756. 51. Wortzel, I.; Dror, S.; Kenific, C.M.; Lyden, D. Exosome-Mediated Metastasis: Communication from a Distance. Dev Cell 2019, 49, 347-360, doi:10.1016/j.devcel.2019.04.011. 52. Mo, Z.; Cheong, J.Y.A.; Xiang, L.; Le, M.T.N.; Grimson, A.; Zhang, D.X. Extracellular vesicle-associated organotropic metastasis. Cell Prolif 2021, 54, e12948, doi:10.1111/cpr.12948. 53. Steinbichler, T.B.; Dudás, J.; Riechelmann, H.; Skvortsova, II. The role of exosomes in cancer metastasis. Semin Cancer Biol 2017, 44, 170-181, doi:10.1016/j.semcancer.2017.02.006. 54. Theodoraki, M.N.; Hong, C.S.; Donnenberg, V.S.; Donnenberg, A.D.; Whiteside, T.L. Evaluation of Exosome Proteins by on-Bead Flow Cytometry. Cytometry A 2021, 99, 372-381, doi:10.1002/cyto.a.24193. 55. van der Vlist, E.J.; Nolte-'t Hoen, E.N.; Stoorvogel, W.; Arkesteijn, G.J.; Wauben, M.H. Fluorescent labeling of nano-sized vesicles released by cells and subsequent quantitative and qualitative analysis by high-resolution flow cytometry. Nat Protoc 2012, 7, 1311-1326, doi:10.1038/nprot.2012.065. 56. Serrano-Pertierra, E.; Oliveira-Rodríguez, M.; Matos, M.; Gutiérrez, G.; Moyano, A.; Salvador, M.; Rivas, M.; Blanco-López, M.C. Extracellular Vesicles: Current Analytical Techniques for Detection and Quantification. Biomolecules 2020, 10, 824, doi:10.3390/biom10060824. 57. Wang, C.; Ding, Q.; Plant, P.; Basheer, M.; Yang, C.; Tawedrous, E.; Krizova, A.; Boulos, C.; Farag, M.; Cheng, Y., et al. Droplet digital PCR improves urinary exosomal miRNA detection compared to real-time PCR. Clin Biochem 2019, 67, 54-59, doi:10.1016/j.clinbiochem.2019.03.008. 58. Cho, S.M.; Shin, S.; Kim, Y.; Song, W.; Hong, S.G.; Jeong, S.H.; Kang, M.S.; Lee, K.A. A novel approach for tuberculosis diagnosis using exosomal DNA and droplet digital PCR. Clin Microbiol Infect 2020, 26, 942.e941-942.e945, doi:10.1016/j.cmi.2019.11.012. 59. Anderson, W.; Lane, R.; Korbie, D.; Trau, M. Observations of Tunable Resistive Pulse Sensing for Exosome Analysis: Improving System Sensitivity and Stability. Langmuir 2015, 31, 6577-6587, doi:10.1021/acs.langmuir.5b01402. 60. Yamauchi, M.; Shimizu, K.; Rahman, M.; Ishikawa, H.; Takase, H.; Ugawa, S.; Okada, A.; Inoshima, Y. Efficient method for isolation of exosomes from raw bovine milk. Drug Dev Ind Pharm 2019, 45, 359-364, doi:10.1080/03639045.2018.1539743. 61. Dou, D.; Ren, X.; Han, M.; Xu, X.; Ge, X.; Gu, Y.; Wang, X. Cancer-Associated Fibroblasts-Derived Exosomes Suppress Immune Cell Function in Breast Cancer via the miR-92/PD-L1 Pathway. Front Immunol 2020, 11, 2026, doi:10.3389/fimmu.2020.02026. 62. Liu, C.; Guo, J.; Tian, F.; Yang, N.; Yan, F.; Ding, Y.; Wei, J.; Hu, G.; Nie, G.; Sun, J. Field-Free Isolation of Exosomes from Extracellular Vesicles by Microfluidic Viscoelastic Flows. ACS Nano 2017, 11, 6968-6976, doi:10.1021/acsnano.7b02277. 63. Gaillard, M.; Thuaire, A.; Nonglaton, G.; Agache, V.; Roupioz, Y.; Raillon, C. Biosensing extracellular vesicles: contribution of biomolecules in affinity-based methods for detection and isolation. Analyst 2020, 145, 1997-2013, doi:10.1039/C9AN01949A. 64. Gurunathan, S.; Kang, M.H.; Jeyaraj, M.; Qasim, M.; Kim, J.H. Review of the Isolation, Characterization, Biological Function, and Multifarious Therapeutic Approaches of Exosomes. Cells 2019, 8, doi:10.3390/cells8040307. 65. Wang, W.M.; Wu, C.; Jin, H.Z. Exosomes in chronic inflammatory skin diseases and skin tumors. Exp Dermatol 2019, 28, 213-218, doi:10.1111/exd.13857. 66. Wang, J.; Ma, P.; Kim, D.H.; Liu, B.F.; Demirci, U. Towards Microfluidic-Based Exosome Isolation and Detection for Tumor Therapy. Nano Today 2021, 37, doi:10.1016/j.nantod.2020.101066. 67. Le, M.N.; Fan, Z.H. Exosome isolation using nanostructures and microfluidic devices. Biomed Mater 2021, 16, 022005, doi:10.1088/1748-605X/abde70. 68. Lin, B.; Lei, Y.; Wang, J.; Zhu, L.; Wu, Y.; Zhang, H.; Wu, L.; Zhang, P.; Yang, C. Microfluidic-Based Exosome Analysis for Liquid Biopsy. Small Methods 2021, 5, e2001131, doi:10.1002/smtd.202001131. 69. Zhang, H.; Freitas, D.; Kim, H.S.; Fabijanic, K.; Li, Z.; Chen, H.; Mark, M.T.; Molina, H.; Martin, A.B.; Bojmar, L., et al. Identification of distinct nanoparticles and subsets of extracellular vesicles by asymmetric flow field-flow fractionation. Nat Cell Biol 2018, 20, 332-343, doi:10.1038/s41556-018-0040-4. 70. Liu, F.; Vermesh, O.; Mani, V.; Ge, T.J.; Madsen, S.J.; Sabour, A.; Hsu, E.C.; Gowrishankar, G.; Kanada, M.; Jokerst, J.V., et al. The Exosome Total Isolation Chip. ACS Nano 2017, 11, 10712-10723, doi:10.1021/acsnano.7b04878. 71. Woo, H.-K.; Sunkara, V.; Park, J.; Kim, T.-H.; Han, J.-R.; Kim, C.-J.; Choi, H.-I.; Kim, Y.-K.; Cho, Y.-K. Exodisc for Rapid, Size-Selective, and Efficient Isolation and Analysis of Nanoscale Extracellular Vesicles from Biological Samples. ACS Nano 2017, 11, 1360-1370, doi:10.1021/acsnano.6b06131. 72. Yasui, T.; Yanagida, T.; Ito, S.; Konakade, Y.; Takeshita, D.; Naganawa, T.; Nagashima, K.; Shimada, T.; Kaji, N.; Nakamura, Y., et al. Unveiling massive numbers of cancer-related urinary-microRNA candidates via nanowires. Sci Adv 2017, 3, e1701133, doi:10.1126/sciadv.1701133. 73. Chen, Z.; Yang, Y.; Yamaguchi, H.; Hung, M.C.; Kameoka, J. Isolation of cancer-derived extracellular vesicle subpopulations by a size-selective microfluidic platform. Biomicrofluidics 2020, 14, 034113, doi:10.1063/5.0008438. 74. Costa-Silva, B.; Aiello, N.M.; Ocean, A.J.; Singh, S.; Zhang, H.; Thakur, Basant K.; Becker, A.; Hoshino, A.; Mark, M.T.; Molina, H., et al. Pancreatic cancer exosomes initiate pre-metastatic niche formation in the liver. Nature Cell Biology 2015, 17, 816-826, doi:10.1038/ncb3169. 75. Chen, C.; Ridzon, D.A.; Broomer, A.J.; Zhou, Z.; Lee, D.H.; Nguyen, J.T.; Barbisin, M.; Xu, N.L.; Mahuvakar, V.R.; Andersen, M.R., et al. Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res 2005, 33, e179, doi:10.1093/nar/gni178. 76. Spiga, F.M.; Bonyár, A.; Ring, B.; Onofri, M.; Vinelli, A.; Sántha, H.; Guiducci, C.; Zuccheri, G. Hybridization chain reaction performed on a metal surface as a means of signal amplification in SPR and electrochemical biosensors. Biosens Bioelectron 2014, 54, 102-108, doi:10.1016/j.bios.2013.10.036. 77. Gu, Y.; Song, J.; Li, M.-X.; Zhang, T.-T.; Zhao, W.; Xu, J.-J.; Liu, M.; Chen, H.-Y. Ultrasensitive MicroRNA Assay via Surface Plasmon Resonance Responses of Au@Ag Nanorods Etching. Analytical Chemistry 2017, 89, 10585-10591, doi:10.1021/acs.analchem.7b02920. 78. Berg, K.; Lange, T.; Mittelberger, F.; Schumacher, U.; Hahn, U. Selection and Characterization of an α6β4 Integrin blocking DNA Aptamer. Mol Ther Nucleic Acids 2016, 5, e294, doi:10.1038/mtna.2016.10. 79. Peterson, A.W.; Heaton, R.J.; Georgiadis, R.M. The effect of surface probe density on DNA hybridization. Nucleic Acids Res 2001, 29, 5163-5168, doi:10.1093/nar/29.24.5163. 80. Brogan, K.L.; Shin, J.H.; Schoenfisch, M.H. Influence of surfactants and antibody immobilization strategy on reducing nonspecific protein interactions for molecular recognition force microscopy. Langmuir 2004, 20, 9729-9735, doi:10.1021/la048437y. 81. Willms, E.; Cabañas, C.; Mäger, I.; Wood, M.J.A.; Vader, P. Extracellular Vesicle Heterogeneity: Subpopulations, Isolation Techniques, and Diverse Functions in Cancer Progression. Front Immunol 2018, 9, 738, doi:10.3389/fimmu.2018.00738. 82. Alberro, A.; Iparraguirre, L.; Fernandes, A.; Otaegui, D. Extracellular Vesicles in Blood: Sources, Effects, and Applications. International Journal of Molecular Sciences 2021, 22, 8163. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/85808 | - |
| dc.description.abstract | 在臨床生化檢測與分析化學領域中,表面電漿子共振生物感測器因具有即時性、免標識、非接觸式等優點,提供分子交互作用的定性與定量動態訊息,有許多成功的研究成果。然而,應用表面電漿子共振生物感測器來檢測樣品,特別是在復雜的生物樣品中,受到非特異性結合和信號差的限制。近年來,科學家研發多種用於支持更好檢測的擴增方法來克服這一缺陷。在生物樣品中,核酸,尤其是 DNA 適體,成為一種目標檢測工具。 雜交鏈式反應(Hybridization Chain Reaction,HCR)是一種只需三種DNA:線狀引子DNA、兩個環狀H1與H2的DNA鏈取代反應,是不需要酵素的等溫信號放大技術。在雜交鏈式反應中,引子引發兩種環狀DNA交替開環,自組裝,得到包含大量重覆單元的線性雙鏈DNA奈米結構,具有恆溫、免酵素、放大效率高等優點。結合相位式表面電漿子共振感測器和雜交鏈式反應的實驗中,在最佳鹽條件下,隨著 H1 和 H2 濃度的增加,HCR 信號增強,導致信號放大在 30 分鐘時達到檢測量的 6.5 倍。 我們使用雜交鏈式反應檢測嚴重急性呼吸道症候群冠狀病毒2型(Severe acute respiratory syndrome coronavirus 2,SARS-CoV-2)N1/N2/N3 基因座和人類核糖核酸酶 P的互補 DNA (cDNA),並開發雜交鏈式反應的演算法。該演算法有助於搜索具有低局部二級結構和高雜交性能的目標序列。雜交鏈式反應中 H1 和 H2的環域是此類反應中的可調片段,用作優化參數以提高鍊式反應的雜交效率。演算法衍生的雜交鏈式反應反應透過凝膠電泳驗證,反應都表現出分子質量 > 1.5k 鹼基對的雜交複合物。凝膠電泳的雜交效率趨勢與演算法的模擬結果很好地對應。 癌症轉移是一種發病率高和診斷難度較大的疾病。近年研究顯示,胞泌體在癌症轉移的過程扮演重要作用。我們開發靈敏的相位式表面電漿共振感測器系統,設計雙功能適體,結合 HCR 反應對胞泌體進行檢測,希望未來有機會透過這個檢測方式,更提早發現病人癌症轉移的問題。 相位式表面電漿共振子感測器以其高靈敏度聞名,較強度式表面電漿共振子感測器靈敏,對折射率之解析度至少高一個數量級。此技術有一個瓶頸,在固定角度設置下測量時,結果重現性低。這是一個尚未被充分討論的關鍵問題。一種可能的解決方案是通過簡單的非線性擬合,映射到折射率單位。然而,基本擬合函數不能很好地描繪非對稱相位曲線。另一方面,基於菲涅耳係數的多層反射率計算,可用於精確映射函數。然而,這種數值方法缺乏用於優化過程的明確數學公式。為此,我們為該問題提供一種方法,其中映射函數是從實驗數據的貝葉斯優化多層模型構建的。我們以量測轉移性癌症胞泌體的數據,使用多層模型作為優化試驗函數,透過分段多項式逼近的方法,提出了一種可視化方法來評估優化模型的擬合優度。 | zh_TW |
| dc.description.abstract | Surface Plasmon Resonance (SPR) is popularly used in biological and chemical sensing for the applications are extensive by the fascinating chemical, optical and catalytic properties. However, the application of SPR to detect trace targets, particularly in complex biological samples, is hampered by non-specific binding and poor signal. A variety of approaches for amplification to support better detection have been explored to overcome this deficiency. In biological samples, nucleic acids, especially DNA aptamers, are considered a versatile target detection tool. Hybridization chain reaction (HCR) is an enzyme-free DNA amplification method of high efficiency operated at room temperature in which two stable species of DNA hairpins coexist in the solution until the introduction of initiator DNA strand triggers a cascade of hybridization events. HCRs to detect Severe Acute Respiratory Syndrome Coronavirus 2 (SARS – CoV-2) nucleocapsid phosphoproteins gene loci and human RNase P are proposed to provide an isothermal amplification screening method. The proposed HCRs target the complementary DNA (cDNA) of SARS – CoV-2, with loci corresponding to the gold-standard polymerase chain reaction (PCR) loci. Four hybridization chain reactions are seen here, targeting N1 / N2 / N3 loci and human RNase P. The construction of the hybridization chain reaction is supported by an algorithm. The algorithm helps to search for target sequences with low local secondary structure and high hybridization performance. The loop domain of the H1 and H2 fuel pin molecules, which are tunable segments in such reactions, is used as an optimization parameter to increase the hybridization efficiency of the chain reaction. Algorithm-derived HCR reactions have been validated with gel electrophoresis. Both suggested reactions exhibit a hybridization complex with a molecular mass > 1.5k base pair, which is strong evidence of a chain reaction. The hybridization efficiency trend revealed by the gel electrophoresis corresponds well to the algorithm's simulated results. The HCR reactions and the corresponding algorithm serve as the basis for more SARS – CoV-2 sensing applications and promote improved screening strategies for the prevention of ongoing pandemics. Cancer metastasis is a difficult disease to cope with. The responsive methodology is important for accurate clinical use and remains unmet. Recent research has shown the significant role of exosomes in the growth of cancer metastases. Exosome-based liquid biopsy has therefore become the prevalent cancer diagnostic study. Our work has further extended to develop a sensitive phase-sensitive Surface Plasmon Resonance (pSPR) system for highly informative sensing of cancerous exosomes using bifunctional aptamers coupled with HCR amplification. The enhancement of more diverse recognition events can be accomplished by integrating HCR with aptamer stimuli tested by SPR. This feature enables DNA to serve as an amplifying transducer for biosensing applications. Our work established a pSPR system for highly informative sensing using HCR for amplification. High sensitivity is a characteristic of pSPR biosensors. One of these sensors' technical bottlenecks is that the phase sensorgram, when measured at a fixed angle set-up, might result in poor repeatability since the signal carries various data. As a result, maximizing sensitivity while maintaining acceptable reproducibility is an under-discussed critical topic. One such technique is to utilize sensor calibration data to transfer the phase sensorgram into refractive index units through a non-linear fit. The asymmetric phase curve, however, is poorly represented by fundamental fitting algorithms. An exact mapping function, on the other hand, may be achieved by using a multi-layer reflectivity calculation based on the Fresnel coefficient. This numerical method, on the other hand, lacks the clear mathematical formulation required for optimization. To that end, we propose a first technique for the problem, in which mapping functions are built from a Bayesian optimal multi-layer model of experimental data. Meta-modeling using segmented polynomial approximation overcomes the difficulty of employing a multi-layer model as an optimization trial function. The goodness-of-fit on the improved model is evaluated using a visualization technique. We show how the current study paves the way for improved plasmonic sensors by using metastatic cancer exosome sensing. | en |
| dc.description.provenance | Made available in DSpace on 2023-03-19T23:25:01Z (GMT). No. of bitstreams: 1 U0001-2303202220243300.pdf: 14401273 bytes, checksum: 3b97316e04faeaf59c0aa607f18f9316 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | 口試委員會審定書………………………………………………………………………………# 致謝………………………………………………………………………………………………i 中文摘要…………………………………………………………………………………………iii ABSTRACT……………………………………………………………………………………v CONTENTS……………………………………………………………………………………viii LIST OF TABLES………………………………………………………………………………x LIST OF FIGURES………………………………………………………………………………xi Chapter 1 Introduction……………………………………………………………………………1 Chapter 2 Hybridization Chain Reactions Targeting the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)…………………………………………………………………19 2.1 Background………………………………………………………………………………20 2.2 Methodology………………………………………………………………………………21 2.3 Results……………………………………………………………………………………21 2.4 Summary…………………………………………………………………………………28 Chapter 3 Biosensing Amplification by Hybridization Chain Reaction on Phase-Sensitive Surface Plasmon Resonance………………………………………………………………………………31 3.1 Background………………………………………………………………………………32 3.2 Materials and Methods……………………………………………………………………37 3.3 Results………………………………………………………………………………………43 3.4 Summary…………………………………………………………………………………48 Chapter 4 Multi-layer Reflectivity Calculation Based Meta-modeling of the Phase Mapping Function for Highly Reproducible Surface Plasmon Resonance Biosensing………………………………………………………………………………………51 4.1 Background………………………………………………………………………………52 4.2 Materials and Methods………………………………………………………………………55 4.3 Results………………………………………………………………………………………61 4.4 Summary…………………………………………………………………………………70 Chapter 5 Conclusions and Future Outlook………………………………………………72 References………………………………………………………………………………………76 Conferences and Publications………………………………………………………………88 | |
| dc.language.iso | zh-TW | |
| dc.subject | 演算法 | zh_TW |
| dc.subject | 雜交鏈式反應 | zh_TW |
| dc.subject | 雙功能適體 | zh_TW |
| dc.subject | 嚴重急性呼吸道症候群冠狀病毒2型 | zh_TW |
| dc.subject | 癌症轉移 | zh_TW |
| dc.subject | 胞泌體 | zh_TW |
| dc.subject | 相位式表面電漿共振感測器 | zh_TW |
| dc.subject | Cancer Metastasis | en |
| dc.subject | Algorithm | en |
| dc.subject | Phase-sensitive Surface Plasmon Resonance | en |
| dc.subject | Exosomes | en |
| dc.subject | Hybridization Chain Reaction | en |
| dc.subject | Bifunctional Aptamer | en |
| dc.subject | SARS – CoV-2 | en |
| dc.title | 雜交鍊式反應應用於相位表面電漿子共振感測器 | zh_TW |
| dc.title | The Utilization of Hybridization Chain Reaction on Phase-Sensitive Surface Plasmon Resonance | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 110-2 | |
| dc.description.degree | 博士 | |
| dc.contributor.author-orcid | 0000-0002-3086-6652 | |
| dc.contributor.advisor-orcid | 黃念祖(0000-0002-2569-805X) | |
| dc.contributor.coadvisor | 林啟萬(Chii-Wann Lin) | |
| dc.contributor.coadvisor-orcid | 林啟萬(0000-0002-8721-3441) | |
| dc.contributor.oralexamcommittee | 林致廷(Chih-Ting Lin),張家禎(Chia-Chen Chang),陳震宇(Chen-Yu Chen) | |
| dc.contributor.oralexamcommittee-orcid | 林致廷(0000-0002-4150-9693),張家禎(0000-0001-5466-4724),陳震宇(0000-0003-4519-8391) | |
| dc.subject.keyword | 雜交鏈式反應,雙功能適體,嚴重急性呼吸道症候群冠狀病毒2型,癌症轉移,胞泌體,相位式表面電漿共振感測器,演算法, | zh_TW |
| dc.subject.keyword | Hybridization Chain Reaction,Bifunctional Aptamer,SARS – CoV-2,Cancer Metastasis,Exosomes,Phase-sensitive Surface Plasmon Resonance,Algorithm, | en |
| dc.relation.page | 89 | |
| dc.identifier.doi | 10.6342/NTU202200658 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2022-03-31 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 生醫電子與資訊學研究所 | zh_TW |
| dc.date.embargo-lift | 2022-04-26 | - |
| 顯示於系所單位: | 生醫電子與資訊學研究所 | |
文件中的檔案:
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| U0001-2303202220243300.pdf | 14.06 MB | Adobe PDF | 檢視/開啟 |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。
