Literature DB >> 26045728

The microfluidics of the eccrine sweat gland, including biomarker partitioning, transport, and biosensing implications.

Z Sonner1, E Wilder2, J Heikenfeld1, G Kasting2, F Beyette1, D Swaile3, F Sherman4, J Joyce4, J Hagen5, N Kelley-Loughnane5, R Naik6.   

Abstract

Non-invasive and accurate access of biomarkers remains a holy grail of the biomedical community. Human eccrine sweat is a surprisingly biomarker-rich fluid which is gaining increasing attention. This is especially true in applications of continuous bio-monitoring where other biofluids prove more challenging, if not impossible. However, much confusion on the topic exists as the microfluidics of the eccrine sweat gland has never been comprehensively presented and models of biomarker partitioning into sweat are either underdeveloped and/or highly scattered across literature. Reported here are microfluidic models for eccrine sweat generation and flow which are coupled with review of blood-to-sweat biomarker partition pathways, therefore providing insights such as how biomarker concentration changes with sweat flow rate. Additionally, it is shown that both flow rate and biomarker diffusion determine the effective sampling rate of biomarkers at the skin surface (chronological resolution). The discussion covers a broad class of biomarkers including ions (Na(+), Cl(-), K(+), NH4 (+)), small molecules (ethanol, cortisol, urea, and lactate), and even peptides or small proteins (neuropeptides and cytokines). The models are not meant to be exhaustive for all biomarkers, yet collectively serve as a foundational guide for further development of sweat-based diagnostics and for those beginning exploration of new biomarker opportunities in sweat.

Entities:  

Year:  2015        PMID: 26045728      PMCID: PMC4433483          DOI: 10.1063/1.4921039

Source DB:  PubMed          Journal:  Biomicrofluidics        ISSN: 1932-1058            Impact factor:   2.800


  70 in total

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Journal:  JAMA       Date:  1975-02-10       Impact factor: 56.272

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Journal:  J Physiol       Date:  1956-04-27       Impact factor: 5.182

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Journal:  J Appl Physiol (1985)       Date:  1991-01

4.  Label-Free Impedance Biosensors: Opportunities and Challenges.

Authors:  Jonathan S Daniels; Nader Pourmand
Journal:  Electroanalysis       Date:  2007-05-16       Impact factor: 3.223

5.  The relationship between exercise intensity and the sweat lactate excretion rate.

Authors:  Michael J Buono; Nanette V L Lee; Paul W Miller
Journal:  J Physiol Sci       Date:  2009-12-16       Impact factor: 2.781

6.  Use of saliva for monitoring unbound free cortisol levels in serum.

Authors:  T Umeda; R Hiramatsu; T Iwaoka; T Shimada; F Miura; T Sato
Journal:  Clin Chim Acta       Date:  1981-03-05       Impact factor: 3.786

Review 7.  The current status of sweat testing for drugs of abuse: a review.

Authors:  N De Giovanni; N Fucci
Journal:  Curr Med Chem       Date:  2013       Impact factor: 4.530

8.  Pharmacologic responsiveness of isolated single eccrine sweat glands.

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Journal:  Am J Physiol       Date:  1981-01

Review 9.  Ammonium metabolism in humans.

Authors:  Maria M Adeva; Gema Souto; Natalia Blanco; Cristóbal Donapetry
Journal:  Metabolism       Date:  2012-08-24       Impact factor: 8.694

10.  Uric acid and urea in human sweat.

Authors:  Chien-Tsai Huang; Mei-Lien Chen; Li-Ling Huang; I-Fang Mao
Journal:  Chin J Physiol       Date:  2002-09-30       Impact factor: 1.764

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  83 in total

Review 1.  Wearable biosensors for healthcare monitoring.

Authors:  Jayoung Kim; Alan S Campbell; Berta Esteban-Fernández de Ávila; Joseph Wang
Journal:  Nat Biotechnol       Date:  2019-02-25       Impact factor: 54.908

2.  Flexible Thin-Film Electrodes on Porous Polyester Membranes for Wearable Sensors.

Authors:  Aveek Gangopadhyay; Brian J Nablo; Mulpuri V Rao; Darwin R Reyes
Journal:  Adv Eng Mater       Date:  2017       Impact factor: 3.862

Review 3.  Wearable sensors: modalities, challenges, and prospects.

Authors:  J Heikenfeld; A Jajack; J Rogers; P Gutruf; L Tian; T Pan; R Li; M Khine; J Kim; J Wang; J Kim
Journal:  Lab Chip       Date:  2018-01-16       Impact factor: 6.799

Review 4.  Accessing analytes in biofluids for peripheral biochemical monitoring.

Authors:  Jason Heikenfeld; Andrew Jajack; Benjamin Feldman; Steve W Granger; Supriya Gaitonde; Gavi Begtrup; Benjamin A Katchman
Journal:  Nat Biotechnol       Date:  2019-02-25       Impact factor: 54.908

5.  Soft, skin-mounted microfluidic systems for measuring secretory fluidic pressures generated at the surface of the skin by eccrine sweat glands.

Authors:  Jungil Choi; Yeguang Xue; Wei Xia; Tyler R Ray; Jonathan T Reeder; Amay J Bandodkar; Daeshik Kang; Shuai Xu; Yonggang Huang; John A Rogers
Journal:  Lab Chip       Date:  2017-07-25       Impact factor: 6.799

6.  Wearable Electrochemical Alcohol Biosensors.

Authors:  Alan S Campbell; Jayoung Kim; Joseph Wang
Journal:  Curr Opin Electrochem       Date:  2018-05-23

7.  Wearable flexible sweat sensors for healthcare monitoring: a review.

Authors:  Michael Chung; Giuseppino Fortunato; Norbert Radacsi
Journal:  J R Soc Interface       Date:  2019-10-09       Impact factor: 4.118

Review 8.  Sweat as a Source of Next-Generation Digital Biomarkers.

Authors:  Noé Brasier; Jens Eckstein
Journal:  Digit Biomark       Date:  2019-12-05

9.  A soft, wearable microfluidic device for the capture, storage, and colorimetric sensing of sweat.

Authors:  Ahyeon Koh; Daeshik Kang; Yeguang Xue; Seungmin Lee; Rafal M Pielak; Jeonghyun Kim; Taehwan Hwang; Seunghwan Min; Anthony Banks; Philippe Bastien; Megan C Manco; Liang Wang; Kaitlyn R Ammann; Kyung-In Jang; Phillip Won; Seungyong Han; Roozbeh Ghaffari; Ungyu Paik; Marvin J Slepian; Guive Balooch; Yonggang Huang; John A Rogers
Journal:  Sci Transl Med       Date:  2016-11-23       Impact factor: 17.956

10.  Principles of long-term fluids handling in paper-based wearables with capillary-evaporative transport.

Authors:  Timothy Shay; Tamoghna Saha; Michael D Dickey; Orlin D Velev
Journal:  Biomicrofluidics       Date:  2020-06-09       Impact factor: 2.800

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