帳號:guest(18.223.172.180)          離開系統
字體大小: 字級放大   字級縮小   預設字形  

詳目顯示

以作者查詢圖書館館藏以作者查詢臺灣博碩士論文系統以作者查詢全國書目
作者(中文):俞凱強
作者(外文):Yu, Kai-Chiang
論文名稱(中文):皮膚分泌物採樣及線上質譜分析之機械化分析平台之開發
論文名稱(外文):Development of a Robotized System for Skin Excretion Sampling and On-Line Mass Spectrometric Analysis
指導教授(中文):帕偉鄂本
指導教授(外文):Urban, Pawel L.
口試委員(中文):曾建銘
庫碼
口試委員(外文):Tseng, Chien-Ming
Kumar, Vinoth
學位類別:碩士
校院名稱:國立清華大學
系所名稱:化學系
學號:108023570
出版年(民國):110
畢業學年度:109
語文別:英文
論文頁數:88
中文關鍵詞:自動化化學皮膚代謝物機械化採樣線上萃取質譜法
外文關鍵詞:automated chemistryskin excretionrobotic samplingon-line extractionmass spectrometry
相關次數:
  • 推薦推薦:0
  • 點閱點閱:280
  • 評分評分:*****
  • 下載下載:0
  • 收藏收藏:0
皮膚代謝物在臨床診斷中有著巨大的潛力。然而,皮膚的採樣和分析工作流程單調且耗時。此文中我們展示了基於水凝膠輔助採樣的皮膚代謝物採樣的自動販賣機式皮膚排泄物分析平台。此平台中,機器手臂操縱具有水凝膠的採樣探針並將之壓上受試者的前臂。由於水凝膠的高度親水性,皮膚釋放的水溶性代謝物會被水凝膠所收集。然後探針被放置在客製的開放採樣端口上,端口連接到串聯質譜儀的電噴灑離子源。水凝膠中的代謝物迅速透過端口中的溶劑接點被萃取並由質譜儀分析。目標分析物的離子電流會顯示在客制的圖形用戶界面上,其也可用於控制分析平台的關鍵組件。在使用者投入硬幣或插入健保卡、按下按鈕、並將手放至指定位置後,採樣和分析工作流程會自動啟動。為了使平台更加易用,系統會發出語音提示使用者目前系統的狀態。該平台由低成本的機械和電子模塊構成(包含機器手臂,單板電腦和兩個微控制器)。此系統對於瓊脂糖中的精氨酸,瓜氨酸和組氨酸的偵測極限分別為0.11,0.22和0.17 μM。此系統也成功串聯高解析度質譜儀來鑑定出所收集到的幾種低分子量代謝物。
Skin metabolites show huge potential for use in clinical diagnostics. However, skin sampling and analysis workflows are tedious and time-consuming. Here, we demonstrate a vending-machine-style skin excretion profiling platform based on hydrogel-assisted sampling of skin metabolites. In this platform, a sampling probe with hydrogel is held by a robotic arm. The robotic arm manoeuvres the probe to press it onto the forearm of human subject. Water-soluble metabolites—released by skin—are collected into the hydrogel due to its highly hydrophilic nature. The probe is then placed on a custom-made open port sampling interface coupled to an electrospray ion source of a tandem mass spectrometer. Metabolites in the hydrogel are immediately extracted by a solvent liquid junction in the interface, and analyzed by the mass spectrometer. The ion current of the target analyte is displayed on a customized graphical user interface, which can also be used to control the key components of the analytical platform. The automated sampling and analysis workflow starts after the user inserts coins or presents an insurance card, presses a button, and extends an arm on the sampling area. To make the platform user-friendly, voice messages are emitted to notify the users about the status of the system. The platform relies on low-cost mechanical and electronic modules (a robotic arm, a single-board computer, and two microcontroller boards). The limits of detection of arginine, citrulline, and histidine (in agarose) are 0.11, 0.22 and 0.17 μM, respectively. Various low-molecular-weight metabolites have been identified with a high-resolution mass spectrometer.
中文摘要 i
Abstract ii
謝誌 iii
Table of Contents iv
List of Tables v
List of Figures vi
List of Acronyms xi
Chapter 1: Introduction 1
1.1 Skin metabolites 1
1.1.1 Origin of skin metabolites 1
1.1.2 Chemicals present on skin 2
1.1.3 Sampling methods 3
1.2 Automation in chemistry 4
1.2.1 Robot 5
1.2.2 Microcontroller board 6
1.2.3 Single-board computer 7
1.3 Mass spectrometry 8
1.3.1 Ion sources 9
1.3.2 Mass analyzer 11
1.3.3 Tandem mass spectrometry 13
1.4 Goals of the study 15
Chapter 2: Vending-Machine-Style Skin Excretion Profiling: a Case of Robotization of Sampling and Analysis 17
2.1 Introduction 17
2.2 Experimental section 20
2.2.1 Preparation of hydrogel probes 20
2.2.2 Robotic arm for skin sampling 23
2.2.3 Open port sampling interface for mass spectrometry 25
2.2.4 System integration and electronic control 28
2.2.5 Mass spectrometry parameters 31
2.2.6 Data acquisition, transmission, and processing 31
2.2.7 Calculation of limit of detection and limit of quantitation 32
2.2.8 Chemicals 33
2.3 Results and discussions 33
2.3.1 Operation of the platform 33
2.3.2 Optimization of the platform 35
2.3.3 Characterization of the platform 39
2.3.4 Application of the platform in skin profiling 41
2.4 Conclusions 47
Chapter 3: Conclusions and Future Perspective 48
References 51
Appendix 1 64
Appendix 2 67

1. Slominski, A.; Wortsman, J.; Paus, R.; Elias, P. M.; Tobin, D. J.; Feingold, K. R. Skin as an Endocrine Organ: Implications for Its Function. Drug Discov. Today Dis. Mech. 2008, 5, e137-e144.
2. Suskind, R. R. Environment and the Skin. Environ. Health Perspect. 1977, 20, 27-37.
3. Losquadro, W. D. Anatomy of the Skin and the Pathogenesis of Nonmelanoma Skin Cancer. Facial Plast. Surg. Clin. North Am. 2017, 25, 283-289.
4. Del Rosso, J. Q.; Levin, J. The Clinical Relevance of Maintaining the Functional Integrity of the Stratum Corneum in Both Healthy and Disease-Affected Skin. J. Clin. Aesthet. Dermatol. 2011, 4, 22-42.
5. Cui, C.-Y.; Schlessinger, D. Eccrine Sweat Gland Development and Sweat Secretion. Exp. Dermatol. 2015, 24, 644-650.
6. Vig, K.; Chaudhari, A.; Tripathi, S.; Dixit, S.; Sahu, R.; Pillai, S.; Dennis, V. A.; Singh, S. R. Advances in Skin Regeneration Using Tissue Engineering. Int. J. Mol. Sci. 2017, 18, 789.
7. Hussain, J. N.; Mantri, N.; Cohen, M. M. Working up a Good Sweat — the Challenges of Standardising Sweat Collection for Metabolomics Analysis. Clin. Biochem. Rev. 2017, 38, 13-34.
8. Baker, L. B. Physiology of Sweat Gland Function: The Roles of Sweating and Sweat Composition in Human Health. Temperature (Austin) 2019, 6, 211-259.
9. Shirreffs, S. M.; Maughan, R. J. Whole Body Sweat Collection in Humans: An Improved Method with Preliminary Data on Electrolyte Content. J. Appl. Physiol. 1997, 82, 336-341.
10. Jadoon, S.; Karim, S.; Akram, M. R.; Kalsoom Khan, A.; Zia, M. A.; Siddiqi, A. R.; Murtaza, G. Recent Developments in Sweat Analysis and Its Applications. Int. J. Anal. Chem. 2015, 2015, 164974.
11. Wilke, K.; Martin, A.; Terstegen, L.; Biel, S. S. A Short History of Sweat Gland Biology. Int. J. Cosmet. Sci. 2007, 29, 169-179.
12. Stefaniak, A. B.; Harvey, C. J. Dissolution of Materials in Artificial Skin Surface Film Liquids. Toxicol. In Vitro 2006, 20, 1265-1283.
13. Dunstan, R. H.; Sparkes, D. L.; Dascombe, B. J.; Macdonald, M. M.; Evans, C. A.; Stevens, C. J.; Crompton, M. J.; Gottfries, J.; Franks, J.; Murphy, G.; et al. Sweat Facilitated Amino Acid Losses in Male Athletes During Exercise at 32-34°C. PLoS One 2016, 11, e0167844.
14. Picardo, M.; Ottaviani, M.; Camera, E.; Mastrofrancesco, A. Sebaceous Gland Lipids. Dermatoendocrinol. 2009, 1, 68-71.
15. Farrell, P. M.; Rosenstein, B. J.; White, T. B.; Accurso, F. J.; Castellani, C.; Cutting, G. R.; Durie, P. R.; LeGrys, V. A.; Massie, J.; Parad, R. B.; et al. Guidelines for Diagnosis of Cystic Fibrosis in Newborns through Older Adults: Cystic Fibrosis Foundation Consensus Report. J. Pediatr. 2008, 153, S4-S14.
16. Kintz, P.; Tracqui, A.; Mangin, P.; Edel, Y. Sweat Testing in Opioid Users with a Sweat Patch. J. Anal. Toxicol. 1996, 20, 393-397.
17. de la Torre, R.; Pichini, S. Usefulness of Sweat Testing for the Detection of Cannabis Smoke. Clin. Chem. 2004, 50, 1961-1962.
18. Elpa, D. P.; Chiu, H.-Y.; Wu, S.-P.; Urban, P. L. Skin Metabolomics. Trends Endocrinol. Metab. 2021, 32, 66-75.
19. Hammond, K. B.; Turcios, N. L.; Gibson, L. E. Clinical Evaluation of the Macroduct Sweat Collection System and Conductivity Analyzer in the Diagnosis of Cystic Fibrosis. The Journal of Pediatrics 1994, 124, 255-260.
20. Cizza, G.; Marques, A. H.; Eskandari, F.; Christie, I. C.; Torvik, S.; Silverman, M. N.; Phillips, T. M.; Sternberg, E. M. Elevated Neuroimmune Biomarkers in Sweat Patches and Plasma of Premenopausal Women with Major Depressive Disorder in Remission: The Power Study. Biol. Psychiatry 2008, 64, 907-911.
21. Calderón-Santiago, M.; Priego-Capote, F.; Turck, N.; Robin, X.; Jurado-Gámez, B.; Sanchez, J. C.; Luque de Castro, M. D. Human Sweat Metabolomics for Lung Cancer Screening. Anal. Bioanal. Chem. 2015, 407, 5381-5392.
22. Trivedi, D. K.; Sinclair, E.; Xu, Y.; Sarkar, D.; Walton-Doyle, C.; Liscio, C.; Banks, P.; Milne, J.; Silverdale, M.; Kunath, T.; et al. Discovery of Volatile Biomarkers of Parkinson’s Disease from Sebum. ACS Cent. Sci. 2019, 5, 599-606.
23. Dutkiewicz, E. P.; Hsieh, K.-T.; Wang, Y.-S.; Chiu, H.-Y.; Urban, P. L. Hydrogel Micropatch and Mass Spectrometry–Assisted Screening for Psoriasis-Related Skin Metabolites. Clin. Chem. 2016, 62, 1120-1128.
24. Smesny, S.; Schmelzer, C. E. H.; Hinder, A.; Köhler, A.; Schneider, C.; Rudzok, M.; Schmidt, U.; Milleit, B.; Milleit, C.; Nenadic, I.; et al. Skin Ceramide Alterations in First-Episode Schizophrenia Indicate Abnormal Sphingolipid Metabolism. Schizophr. Bull. 2012, 39, 933-941.
25. De Moraes, C. M.; Wanjiku, C.; Stanczyk, N. M.; Pulido, H.; Sims, J. W.; Betz, H. S.; Read, A. F.; Torto, B.; Mescher, M. C. Volatile Biomarkers of Symptomatic and Asymptomatic Malaria Infection in Humans. Proc. Natl. Acad. Sci. 2018, 115, 5780.
26. Nischal, U.; Nischal, K.; Khopkar, U. Techniques of Skin Biopsy and Practical Considerations. J. Cutan. Aesthet. Surg. 2008, 1, 107-111.
27. Lei, B. U. W.; Prow, T. W. A Review of Microsampling Techniques and Their Social Impact. Biomed. Microdevices 2019, 21, 81.
28. Wang, C. Y.; Maibach, H. I. Why Minimally Invasive Skin Sampling Techniques? A Bright Scientific Future. Cutan. Ocul. Toxicol. 2011, 30, 1-6.
29. ELITechGroup. Macroduct® Sweat Collection System. https://www.elitechgroup.com/product/macroduct-sweat-collection-system-2 (accessed Jan 04, 2021).
30. Kintz, P.; Cirimele, V.; Ludes, B. Detection of Cannabis in Oral Fluid (Saliva) and Forehead Wipes (Sweat) from Impaired Drivers. J. Anal. Toxicol. 2000, 24, 557-561.
31. Birkemeyer, C. S.; Thomsen, R.; Jänig, S.; Kücklich, M.; Slama, A.; Weiß, B. M.; Widdig, A. Sampling the Body Odor of Primates: Cotton Swabs Sample Semivolatiles Rather Than Volatiles. Chem. Senses 2016, 41, 525-535.
32. Dutkiewicz, E. P.; Lin, J.-D.; Tseng, T.-W.; Wang, Y.-S.; Urban, P. L. Hydrogel Micropatches for Sampling and Profiling Skin Metabolites. Anal. Chem. 2014, 86, 2337-2344.
33. Dutkiewicz, E. P.; Chiu, H.-Y.; Urban, P. L. Probing Skin for Metabolites and Topical Drugs with Hydrogel Micropatches. Anal. Chem. 2017, 89, 2664-2670.
34. Liao, P.-H.; Urban, P. L. Agarose-Based Gel-Phase Microextraction Technique for Quick Sampling of Polar Analytes Adsorbed on Surfaces. ACS Omega 2019, 4, 19063-19070.
35. Dutkiewicz, E. P.; Hsieh, K.-T.; Urban, P. L.; Chiu, H.-Y. Temporal Correlations of Skin and Blood Metabolites with Clinical Outcomes of Biologic Therapy in Psoriasis. J. Appl. Lab. Med. 2020, 5, 877-888.
36. Caló, E.; Khutoryanskiy, V. V. Biomedical Applications of Hydrogels: A Review of Patents and Commercial Products. Eur. Polym. J. 2015, 65, 252-267.
37. Groover, M. P. "Automation". Encyclopedia Britannica. https://www.britannica.com/technology/automation (accessed May 27, 2021).
38. Guarnieri, M. The Roots of Automation before Mechatronics [Historical]. IEEE Ind. Electron. Mag. 2010, 4, 42-43.
39. Moran, M. E. The Da Vinci Robot. J. Endourol. 2006, 20, 986-990.
40. Olsen, K. The First 110 Years of Laboratory Automation. J. Lab. Autom. 2012, 17, 469-480.
41. Boyd, J. Robotic Laboratory Automation. Science 2002, 295, 517.
42. Urban, P. L. Prototyping Instruments for the Chemical Laboratory Using Inexpensive Electronic Modules. Angew. Chem. Int. Ed. 2018, 57, 11074-11077.
43. Prabhu, G. R. D.; Urban, P. L. Elevating Chemistry Research with a Modern Electronics Toolkit. Chem. Rev. 2020, 120, 9482-9553.
44. Liscouski, J. G. Issues and Directions in Laboratory Automation. Anal. Chem. 1988, 60, 95A-99A.
45. Markin, R. S.; Whalen, S. A. Laboratory Automation: Trajectory, Technology, and Tactics. Clin. Chem. 2000, 46, 764-771.
46. May, M. A DIY Approach to Automating Your Lab. Nature 2019, 569, 587-588.
47. Wheeler, M. J. Overview on Robotics in the Laboratory. Ann. Clin. Biochem. 2007, 44, 209-218.
48. Holland, I.; Davies, J. A. Automation in the Life Science Research Laboratory. Front. Bioeng. Biotechnol. 2020, 8.
49. Online Etymology Dictionary Robot. https://www.etymonline.com/word/robot (accessed Jul 11, 2021).
50. Grau, A.; Indri, M.; Bello, L. L.; Sauter, T. Industrial Robotics in Factory Automation: From the Early Stage to the Internet of Things, In IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, 29 Oct.-1 Nov. 2017; 2017; pp 6159-6164.
51. Miller, L. S.; Bhullar, B. S.; Moore, V. S.; Scovell, L. J.; Lamm, J.; Sawhney, A.; Smith, L. A. A Robotic Immunoassay System for Detergent Enzymes. Chemometrics Intellig. Lab. Syst. 1994, 26, 79-87.
52. Pizzamiglio, M.; Marino, A.; Portera, G.; My, D.; Bellino, C.; Garofano, L. Robotic DNA Extraction System as a New Way to Process Sweat Traces Rapidly and Efficiently. Int. Congr. Ser. 2006, 1288, 598-600.
53. Lloyd, T. L.; Perschy, T. B.; Gooding, A. E.; Tomlinson, J. J. Robotic Solid Phase Extraction and High Performance Liquid Chromatographic Analysis of Ranitidine in Serum or Plasma. Biomed. Chromatogr. 1992, 6, 311-316.
54. Arthur, C. L.; Killam, L. M.; Buchholz, K. D.; Pawliszyn, J.; Berg, J. R. Automation and Optimization of Solid-Phase Microextraction. Anal. Chem. 1992, 64, 1960-1966.
55. Prabhu, G. R. D.; Urban, P. L. The Dawn of Unmanned Analytical Laboratories. TrAC, Trends Anal. Chem. 2017, 88, 41-52.
56. Alexovič, M.; Dotsikas, Y.; Bober, P.; Sabo, J. Achievements in Robotic Automation of Solvent Extraction and Related Approaches for Bioanalysis of Pharmaceuticals. J. Chromatogr. B 2018, 1092, 402-421.
57. Chiu, S.-H.; Urban, P. L. Robotics-Assisted Mass Spectrometry Assay Platform Enabled by Open-Source Electronics. Biosens. Bioelectron. 2015, 64, 260-268.
58. Chen, C.-L.; Chen, T.-R.; Chiu, S.-H.; Urban, P. L. Dual Robotic Arm “Production Line” Mass Spectrometry Assay Guided by Multiple Arduino-Type Microcontrollers. Sens. Actuator B-Chem. 2017, 239, 608-616.
59. Choi, B. J.; Jin, S. M.; Shin, S. H.; Koo, J. C.; Ryew, S. M.; Kim, J.; Son, W. H.; Ahn, K. T.; Chung, W.; Choi, H. R. Development of Flexible Biorobot Platform for Integrated Clinical Test. J. Assoc. Lab. Autom. 2008, 13, 90-96.
60. Li, A.; Paine, M. R. L.; Zambrzycki, S.; Stryffeler, R. B.; Wu, J.; Bouza, M.; Huckaby, J.; Chang, C.-Y.; Kumar, M.; Mukhija, P.; et al. Robotic Surface Analysis Mass Spectrometry (RoSA-MS) of Three-Dimensional Objects. Anal. Chem. 2018, 90, 3981-3986.
61. Burger, B.; Maffettone, P. M.; Gusev, V. V.; Aitchison, C. M.; Bai, Y.; Wang, X.; Li, X.; Alston, B. M.; Li, B.; Clowes, R.; et al. A Mobile Robotic Chemist. Nature 2020, 583, 237-241.
62. Yachie, N.; Consortium, R. B.; Takahashi, K.; Katayama, T.; Sakurada, T.; Kanda, G. N.; Takagi, E.; Hirose, T.; Katsura, T.; Moriya, T.; et al. Robotic Crowd Biology with Maholo Labdroids. Nat. Biotechnol. 2017, 35, 310-312.
63. Augarten, S., State of the Art: A Photographic History of the Integrated Circuit. Ticknor & Fields, 1983.
64. Keim, R. What Is a Microcontroller? The Defining Characteristics and Architecture of a Common Component. https://www.allaboutcircuits.com/technical-articles/what-is-a-microcontroller-introduction-component-characteristics-component/ (accessed Apr 06, 2021).
65. McRoberts, M., Beginning Arduino. Apress, 2010.
66. Kushner, D. The Making of Arduino. https://spectrum.ieee.org/geek-life/hands-on/the-making-of-arduino (accessed April 20, 2021).
67. Taneja, S. R.; Gupta, R. C.; Kumar, J.; Thariyan, K. K.; Verma, S. Design and Development of Microcontroller-Based Clinical Chemistry Analyser for Measurement of Various Blood Biochemistry Parameters. J. Auto. Meth. Manage. Chem. 2005, 2005, 240635.
68. D’Ambrosio, M. V.; Bakalar, M.; Bennuru, S.; Reber, C.; Skandarajah, A.; Nilsson, L.; Switz, N.; Kamgno, J.; Pion, S.; Boussinesq, M.; et al. Point-of-Care Quantification of Blood-Borne Filarial Parasites with a Mobile Phone Microscope. Sci. Transl. Med. 2015, 7, 286re4.
69. Grinias, J. P.; Whitfield, J. T.; Guetschow, E. D.; Kennedy, R. T. An Inexpensive, Open-Source Usb Arduino Data Acquisition Device for Chemical Instrumentation. J. Chem. Educ. 2016, 93, 1316-1319.
70. Panneer Selvam, A.; Muthukumar, S.; Kamakoti, V.; Prasad, S. A Wearable Biochemical Sensor for Monitoring Alcohol Consumption Lifestyle through Ethyl Glucuronide (EtG) Detection in Human Sweat. Sci. Rep. 2016, 6, 23111.
71. Mercer, C.; Leech, D. Cost-Effective Wireless Microcontroller for Internet Connectivity of Open-Source Chemical Devices. J. Chem. Educ. 2018, 95, 1221-1225.
72. Isikdag, U., Internet of Things: Single-Board Computers. In Enhanced Building Information Models: Using Iot Services and Integration Patterns, Isikdag, U., Ed. Springer International Publishing, 2015; pp 43-53.
73. Johnston, S. J.; Basford, P. J.; Perkins, C. S.; Herry, H.; Tso, F. P.; Pezaros, D.; Mullins, R. D.; Yoneki, E.; Cox, S. J.; Singer, J. Commodity Single Board Computer Clusters and Their Applications. Future Gener. Comput. Syst. 2018, 89, 201-212.
74. Bougot-Robin, K.; Paget, J.; Atkins, S. C.; Edel, J. B. Optimization and Design of an Absorbance Spectrometer Controlled Using a Raspberry Pi to Improve Analytical Skills. J. Chem. Educ. 2016, 93, 1232-1240.
75. Pan, J.-Z.; Yao, B.; Fang, Q. Hand-Held Photometer Based on Liquid-Core Waveguide Absorption Detection for Nanoliter-Scale Samples. Anal. Chem. 2010, 82, 3394-3398.
76. Shih, C.-P.; Yu, K.-C.; Ou, H.-T.; Urban, P. L. Portable Pen-Probe Analyzer Based on Ion Mobility Spectrometry for in Situ Analysis of Volatile Organic Compounds Emanating from Surfaces and Wireless Transmission of the Acquired Spectra. Anal. Chem. 2021, 93, 2424-2432.
77. Prabhu, G. R. D.; Witek, H. A.; Urban, P. L. Programmable Flow Rate Scanner for Evaluating Detector Sensitivity Regime. Sens. Actuator B-Chem. 2019, 282, 992-998.
78. Prabhu, G. R. D.; Ponnusamy, V. K.; Witek, H. A.; Urban, P. L. Sample Flow Rate Scan in Electrospray Ionization Mass Spectrometry Reveals Alterations in Protein Charge State Distribution. Anal. Chem. 2020, 92, 13042-13049.
79. Yang, T. H.; Yang, H. C.; Chang, C. H.; Prabhu, G. R. D.; Urban, P. L. Microanalysis Using Acoustically Actuated Droplets Pinned onto a Thread. IEEE Access 2019, 7, 154743-154749.
80. Soong, R.; Jenne, A.; Lysak, D. H.; Ghosh Biswas, R.; Adamo, A.; Kim, K. S.; Simpson, A. Titrate over the Internet: An Open-Source Remote-Control Titration Unit for All Students. J. Chem. Educ. 2021, 98, 1037-1042.
81. Herrero, P.; Delpino-Rius, A.; Ras-Mallorquí, M. R.; Arola, L.; Canela, N., Introduction to Mass Spectrometry Instrumentation and Methods Used in Chemical Biology. In Mass Spectrometry in Chemical Biology: Evolving Applications [Online] The Royal Society of Chemistry: London, 2018; pp. 17-56. http://dx.doi.org/10.1039/9781788010399-00017.
82. Thomson, J. J. Xl. Cathode Rays. Philos. Mag. Ser. 1897, 44, 293-316.
83. Thomson, J. J. Bakerian Lecture:— Rays of Positive Electricity. Proc. R. Soc. London, Ser. A 1913, 89, 1-20.
84. Aston, F. W. The Constitution of Atmospheric Neon. Philos. Mag. Ser. 1920, 39, 449-455.
85. Dong, Y.; Liu, J.; Guo, T., Introduction of Mass Spectrometry and Ambient Ionization Techniques. In Direct Analysis in Real Time Mass Spectrometry [Online] Wiley-VCH Verlag GmbH & Co. KGaA: Weinheim, 2018; pp. 1-42. https://onlinelibrary.wiley.com/doi/abs/10.1002/9783527803705.ch1.
86. Dempster, A. J. A New Method of Positive Ray Analysis. Phys. Rev. 1918, 11, 316-325.
87. Munson, M. S. B.; Field, F. H. Chemical Ionization Mass Spectrometry. I. General Introduction. J. Am. Chem. Soc. 1966, 88, 2621-2630.
88. Yamashita, M.; Fenn, J. B. Electrospray Ion Source. Another Variation on the Free-Jet Theme. J. Phys. Chem. 1984, 88, 4451-4459.
89. Taylor, G. I. Disintegration of Water Drops in an Electric Field. Proc. R. Soc. London, Ser. A 1964, 280, 383-397.
90. van den Broek, I.; Niessen, W. M. A.; van Dongen, W. D. Bioanalytical Lc–MS/MS of Protein-Based Biopharmaceuticals. J. Chromatogr. B 2013, 929, 161-179.
91. Bantscheff, M.; Lemeer, S.; Savitski, M. M.; Kuster, B. Quantitative Mass Spectrometry in Proteomics: Critical Review Update from 2007 to the Present. Anal. Bioanal. Chem. 2012, 404, 939-965.
92. Lu, W.; Bennett, B. D.; Rabinowitz, J. D. Analytical Strategies for Lc–MS-Based Targeted Metabolomics. J. Chromatogr. B 2008, 871, 236-242.
93. van der Veen, I.; de Boer, J. Phosphorus Flame Retardants: Properties, Production, Environmental Occurrence, Toxicity and Analysis. Chemosphere 2012, 88, 1119-1153.
94. de Hoffmann, E.; Stroobant, V., Mass Spectrometry: Principles and Applications. 3rd ed.; John Wiley & Sons, 2007.
95. Paul, W.; Steinwedel, H. Notizen: Ein Neues Massenspektrometer Ohne Magnetfeld. Z. Naturforsch. A 1953, 8, 448-450.
96. He, J.; Yu, Q.; Li, L.; Hang, W.; Huang, B. Characteristics and Comparison of Different Radiofrequency-Only Multipole Cooling Cells. Rapid Commun. Mass Spectrom. 2008, 22, 3327-3333.
97. Wolff, M. M.; Stephens, W. E. A Pulsed Mass Spectrometer with Time Dispersion. Rev. Sci. Instrum. 1953, 24, 616-617.
98. Wiley, W. C.; McLaren, I. H. Time‐of‐Flight Mass Spectrometer with Improved Resolution. Rev. Sci. Instrum. 1955, 26, 1150-1157.
99. Mamyrin, B. A.; Karataev, V. I.; Shmikk, D. V.; Zagulin, V. A. The Mass-Reflectron, a New Nonmagnetic Time-of-Flight Mass Spectrometer with High Resolution. Sov. Phys. JETP 1973, 37, 45.
100. Guru, A. Life Begins at 40 – a Brief History of Lc-MS/MS. https://analyteguru.com/life-begins-at-40-a-brief-history-of-lc-msms/ (accessed June 22, 2021).
101. Soler, C.; Hamilton, B.; Furey, A.; James, K. J.; Mañes, J.; Picó, Y. Comparison of Four Mass Analyzers for Determining Carbosulfan and Its Metabolites in Citrus by Liquid Chromatography/Mass Spectrometry. Rapid Commun. Mass Spectrom. 2006, 20, 2151-2164.
102. Lai-Cheong, J. E.; McGrath, J. A. Structure and Function of Skin, Hair and Nails. Medicine (Abingdon) 2017, 45, 347-351.
103. Robinson, S.; Robinson, A. H. Chemical Composition of Sweat. Physiol. Rev. 1954, 34, 202-220.
104. Hirokawa, T.; Okamoto, H.; Gosyo, Y.; Tsuda, T.; Timerbaev, A. R. Simultaneous Monitoring of Inorganic Cations, Amines and Amino Acids in Human Sweat by Capillary Electrophoresis. Anal. Chim. Acta 2007, 581, 83-88.
105. Lima, E. d. O.; de Macedo, C. S.; Esteves, C. Z.; de Oliveira, D. N.; Pessolani, M. C. V.; Nery, J. A. d. C.; Sarno, E. N.; Catharino, R. R. Skin Imprinting in Silica Plates: A Potential Diagnostic Methodology for Leprosy Using High-Resolution Mass Spectrometry. Anal. Chem. 2015, 87, 3585-3592.
106. Schazmann, B.; Morris, D.; Slater, C.; Beirne, S.; Fay, C.; Reuveny, R.; Moyna, N.; Diamond, D. A Wearable Electrochemical Sensor for the Real-Time Measurement of Sweat Sodium Concentration. Anal. Methods 2010, 2, 342-348.
107. Kim, J.; Jeerapan, I.; Sempionatto, J. R.; Barfidokht, A.; Mishra, R. K.; Campbell, A. S.; Hubble, L. J.; Wang, J. Wearable Bioelectronics: Enzyme-Based Body-Worn Electronic Devices. Acc. Chem. Res. 2018, 51, 2820-2828.
108. Delgado-Povedano, M. M.; Calderón-Santiago, M.; Luque de Castro, M. D.; Priego-Capote, F. Metabolomics Analysis of Human Sweat Collected after Moderate Exercise. Talanta 2018, 177, 47-65.
109. Schneider, S.; Ait-m-bark, Z.; Schummer, C.; Lemmer, P.; Yegles, M.; Appenzeller, B.; Wennig, R. Determination of Fentanyl in Sweat and Hair of a Patient Using Transdermal Patches. J. Anal. Toxicol. 2008, 32, 260-264.
110. Webb, B. W.; Flute, P. T.; Smith, M. J. The Electrolyte Content of the Sweat in Fibrocystic Disease of the Pancreas. Arch. Dis. Child. 1957, 32, 82-84.
111. Carter, E. P.; Barrett, A. D.; Heeley, A. F.; Kuzemko, J. A. Improved Sweat Test Method for the Diagnosis of Cystic Fibrosis. Arch. Dis. Child. 1984, 59, 919-922.
112. Hammond, K. B.; Turcios, N. L.; Gibson, L. E. Clinical Evaluation of the Macroduct Sweat Collection System and Conductivity Analyzer in the Diagnosis of Cystic Fibrosis. J. Pediatr. 1994, 124, 255-260.
113. PharmChem. Pharmchek® Sweat Patch. https://www.pharmchek.com/products/pharmchek-patch (accessed Jun 04, 2021).
114. Jenkins, A. J.; Caplan, Y. H., Drug Testing in Alternate Biological Specimens. Humana Press, 2008.
115. PharmChem. Pharmchek. https://www.pharmchek.com/ (accessed Jul 17, 2021).
116. Huestis, M. A.; Cone, E. J.; Wong, C. J.; Umbricht, A.; Preston, K. L. Monitoring Opiate Use in Substance Abuse Treatment Patients with Sweat and Urine Drug Testing. J. Anal. Toxicol. 2000, 24, 509-521.
117. Concheiro, M.; Shakleya, D. M.; Huestis, M. A. Simultaneous Analysis of Buprenorphine, Methadone, Cocaine, Opiates and Nicotine Metabolites in Sweat by Liquid Chromatography Tandem Mass Spectrometry. Anal. Bioanal. Chem. 2011, 400, 69-78.
118. Nagamine, K.; Mano, T.; Nomura, A.; Ichimura, Y.; Izawa, R.; Furusawa, H.; Matsui, H.; Kumaki, D.; Tokito, S. Noninvasive Sweat-Lactate Biosensor Emplsoying a Hydrogel-Based Touch Pad. Sci. Rep. 2019, 9, 10102.
119. Lin, S.; Wang, B.; Zhao, Y.; Shih, R.; Cheng, X.; Yu, W.; Hojaiji, H.; Lin, H.; Hoffman, C.; Ly, D.; et al. Natural Perspiration Sampling and in Situ Electrochemical Analysis with Hydrogel Micropatches for User-Identifiable and Wireless Chemo/Biosensing. ACS Sens. 2020, 5, 93-102.
120. Scarpa, E.; Mastronardi, V. M.; Guido, F.; Algieri, L.; Qualtieri, A.; Fiammengo, R.; Rizzi, F.; De Vittorio, M. Wearable Piezoelectric Mass Sensor Based on Ph Sensitive Hydrogels for Sweat Ph Monitoring. Sci. Rep. 2020, 10, 10854.
121. Yu, H.; Sun, J. Sweat Detection Theory and Fluid Driven Methods: A Review. Nanotechnol. Precis. Eng. 2020, 3, 126-140.
122. Salati, M. A.; Khazai, J.; Tahmuri, A. M.; Samadi, A.; Taghizadeh, A.; Taghizadeh, M.; Zarrintaj, P.; Ramsey, J. D.; Habibzadeh, S.; Seidi, F.; et al. Agarose-Based Biomaterials: Opportunities and Challenges in Cartilage Tissue Engineering. Polymers 2020, 12, 1150.
123. Tabor, D. P.; Roch, L. M.; Saikin, S. K.; Kreisbeck, C.; Sheberla, D.; Montoya, J. H.; Dwaraknath, S.; Aykol, M.; Ortiz, C.; Tribukait, H.; et al. Accelerating the Discovery of Materials for Clean Energy in the Era of Smart Automation. Nat. Rev. Mater. 2018, 3, 5-20.
124. Caramelli, D.; Salley, D.; Henson, A.; Camarasa, G. A.; Sharabi, S.; Keenan, G.; Cronin, L. Networking Chemical Robots for Reaction Multitasking. Nat. Commun. 2018, 9, 3406.
125. Steiner, S.; Wolf, J.; Glatzel, S.; Andreou, A.; Granda, J. M.; Keenan, G.; Hinkley, T.; Aragon-Camarasa, G.; Kitson, P. J.; Angelone, D.; et al. Organic Synthesis in a Modular Robotic System Driven by a Chemical Programming Language. Science 2019, 363, eaav2211.
126. Bailey, A. L.; Ledeboer, N.; Burnham, C.-A. D. Clinical Microbiology Is Growing Up: The Total Laboratory Automation Revolution. Clin. Chem. 2019, 65, 634-643.
127. Alexovič, M.; Urban, P. L.; Tabani, H.; Sabo, J. Recent Advances in Robotic Protein Sample Preparation for Clinical Analysis and Other Biomedical Applications. Clin. Chim. Acta 2020, 507, 104-116.
128. Abu Bakar, N. H.; Yu, K.-C.; Urban, P. L. Robotized Noncontact Open-Space Mapping of Volatile Organic Compounds Emanating from Solid Specimens. Anal. Chem. 2021, 93, 6889-6894.
129. Urban, P. L. Universal Electronics for Miniature and Automated Chemical Assays. Analyst 2015, 140, 963-975.
130. Prabhu, G. R. D.; Yang, T.-H.; Hsu, C.-Y.; Shih, C.-P.; Chang, C.-M.; Liao, P.-H.; Ni, H.-T.; Urban, P. L. Facilitating Chemical and Biochemical Experiments with Electronic Microcontrollers and Single-Board Computers. Nat. Protoc. 2020, 15, 925-990.
131. Van Berkel, G. J.; Sanchez, A. D.; Quirke, J. M. E. Thin-Layer Chromatography and Electrospray Mass Spectrometry Coupled Using a Surface Sampling Probe. Anal. Chem. 2002, 74, 6216-6223.
132. Van Berkel, G. J.; Kertesz, V. An Open Port Sampling Interface for Liquid Introduction Atmospheric Pressure Ionization Mass Spectrometry. Rapid Commun. Mass Spectrom. 2015, 29, 1749-1756.
133. Van Berkel, G. J.; Kertesz, V.; Orcutt, M.; Bentley, A.; Glick, J.; Flarakos, J. Combined Falling Drop/Open Port Sampling Interface System for Automated Flow Injection Mass Spectrometry. Anal. Chem. 2017, 89, 12578-12586.
134. Ovchinnikova, O. S.; Bhandari, D.; Lorenz, M.; Van Berkel, G. J. Transmission Geometry Laser Ablation into a Non-Contact Liquid Vortex Capture Probe for Mass Spectrometry Imaging. Rapid Commun. Mass Spectrom. 2014, 28, 1665-1673.
135. Gómez-Ríos, G. A.; Liu, C.; Tascon, M.; Reyes-Garcés, N.; Arnold, D. W.; Covey, T. R.; Pawliszyn, J. Open Port Probe Sampling Interface for the Direct Coupling of Biocompatible Solid-Phase Microextraction to Atmospheric Pressure Ionization Mass Spectrometry. Anal. Chem. 2017, 89, 3805-3809.
136. Liu, C.; Gómez-Ríos, G. A.; Schneider, B. B.; Le Blanc, J. C. Y.; Reyes-Garcés, N.; Arnold, D. W.; Covey, T. R.; Pawliszyn, J. Fast Quantitation of Opioid Isomers in Human Plasma by Differential Mobility Spectrometry/Mass Spectrometry Via Spme/Open-Port Probe Sampling Interface. Anal. Chim. Acta 2017, 991, 89-94.
137. UFACTORY. Uarm Swift & Uarm Swift Pro Specifications. https://cdn.sparkfun.com/assets/9/8/a/c/0/uArm-Swift-Specifications-en.pdf (accessed Jan 11, 2021).
138. Savitzky, A.; Golay, M. J. E. Smoothing and Differentiation of Data by Simplified Least Squares Procedures. Anal. Chem. 1964, 36, 1627-1639.
139. Casiez, G.; Roussel, N.; Vogel, D. 1 € Filter: A Simple Speed-Based Low-Pass Filter for Noisy Input in Interactive Systems, In Proceedings of the 2012 ACM annual conference on Human Factors in Computing Systems - CHI ’12, ACM Press: New York, New York, USA, 2012.
140. Chandran, S.; Singh, R. S. P. Comparison of Various International Guidelines for Analytical Method Validation. Pharmazie 2007, 62, 4-14.
141. Rousseau, L. Pcsclite Project. https://pcsclite.apdu.fr/ (accessed Jun 13, 2021).
142. Socha, E.; Koba, M.; Kośliński, P. Amino Acid Profiling as a Method of Discovering Biomarkers for Diagnosis of Neurodegenerative Diseases. Amino Acids 2019, 51, 367-371.
143. E.M.A. Method Validation. Guideline on Bioanalytical Method Validation;. 2009, (EMEA/CHMP/EWP/192217/2009 Rev. 1 Corr. 2).
144. Fatin-Rouge, N.; Milon, A.; Buffle, J.; Goulet, R. R.; Tessier, A. Diffusion and Partitioning of Solutes in Agarose Hydrogels:  The Relative Influence of Electrostatic and Specific Interactions. J. Phys. Chem. B 2003, 107, 12126-12137.
145. Islam, M. A. Einstein–Smoluchowski Diffusion Equation: A Discussion. Phys. Scr. 2004, 70, 120-125.
146. Holland, J.; Kingston, L.; McCarthy, C.; Armstrong, E.; O’Dwyer, P.; Merz, F.; McConnell, M. Service Robots in the Healthcare Sector. Robotics 2021, 10, 47.
147. Leipheimer, J. M.; Balter, M. L.; Chen, A. I.; Pantin, E. J.; Davidovich, A. E.; Labazzo, K. S.; Yarmush, M. L. First-in-Human Evaluation of a Hand-Held Automated Venipuncture Device for Rapid Venous Blood Draws. Technology (Singap. World Sci.) 2019, 7, 98-107.
148. Li, S.-Q.; Guo, W.-L.; Liu, H.; Wang, T.; Zhou, Y.-Y.; Yu, T.; Wang, C.-Y.; Yang, Y.-M.; Zhong, N.-S.; Zhang, N.-F.; et al. Clinical Application of an Intelligent Oropharyngeal Swab Robot: Implication for the Covid-19 Pandemic. Eur. Respir. J. 2020, 56, 2001912.
149. Balter, M. L.; Leipheimer, J. M.; Chen, A. I.; Shrirao, A.; Maguire, T. J.; Yarmush, M. L. Automated End-to-End Blood Testing at the Point-of-Care: Integration of Robotic Phlebotomy with Downstream Sample Processing. Technology (Singap. World Sci.) 2018, 6, 59-66.
150. Wang, Y.; Gu, M. The Concept of Spectral Accuracy for MS. Anal. Chem. 2010, 82, 7055-7062.
151. Röst, H. L.; Sachsenberg, T.; Aiche, S.; Bielow, C.; Weisser, H.; Aicheler, F.; Andreotti, S.; Ehrlich, H.-C.; Gutenbrunner, P.; Kenar, E.; et al. Openms: A Flexible Open-Source Software Platform for Mass Spectrometry Data Analysis. Nat. Methods 2016, 13, 741-748.
152. Calderón-Santiago, M.; Priego-Capote, F.; Jurado-Gámez, B.; Luque de Castro, M. D. Optimization Study for Metabolomics Analysis of Human Sweat by Liquid Chromatography–Tandem Mass Spectrometry in High Resolution Mode. J. Chromatogr. A 2014, 1333, 70-78.
153. Gallagher, M.; Wysocki, C. J.; Leyden, J. J.; Spielman, A. I.; Sun, X.; Preti, G. Analyses of Volatile Organic Compounds from Human Skin. Br. J. Dermatol. 2008, 159, 780-791.
154. Imani, S.; Bandodkar, A. J.; Mohan, A. M. V.; Kumar, R.; Yu, S.; Wang, J.; Mercier, P. P. A Wearable Chemical–Electrophysiological Hybrid Biosensing System for Real-Time Health and Fitness Monitoring. Nat. Commun. 2016, 7, 11650.
155. Emaminejad, S.; Gao, W.; Wu, E.; Davies, Z. A.; Yin Yin Nyein, H.; Challa, S.; Ryan, S. P.; Fahad, H. M.; Chen, K.; Shahpar, Z.; et al. Autonomous Sweat Extraction and Analysis Applied to Cystic Fibrosis and Glucose Monitoring Using a Fully Integrated Wearable Platform. Proc. Natl. Acad. Sci. 2017, 114, 4625.
 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
* *