The DOI matches its Crossref record.
Individual variations in structure and function of human eccrine sweat gland
Abstract
The mechanisms underlying variations in perspiration rate at the glandular level are still poorly understood. Human eccrine sweat glands were dissected from the back of 12 adults, cannulated, and stimulated in vitro with methacholine (Mch). The maximal sweat rate and pKA for Mch determined from the dose-response curve for each individual were compared with the anatomic dimensions of the isolated secretory tubules. There was significant correlation between Mch sensitivity (pKA) and the size of the sweat gland, sweat rate per gland, sweat rate per unit length of the secretory tubule, and sweat rate per unit glandular volume. The sweat glands from individuals judged to be poor sweaters exhibited smaller size, lower secretory activity both in vivo and in vitro, and decreased Mch sensitivity compared with glands from physically fit individuals. We conclude that the increased Mch sensitivity and glandular hypertrophy are the two important features of functionally active sweat glands and infer that these parameters could improve as a result of acclimatization to physical exercise and/or heat.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The specific designs described can retain ~50 μL of sweat corresponding to an effective working time of 1 to 6 hours of exercise, depending on the rate of sweat loss and the mounting location on the body (12 to 120 μL/hour per cm2) (32).”
From A soft, wearable microfluidic device for the capture, storage, and colorimetric sensing of sweat (2016) · cites this paper as [32]
Citations
Cites
Still being checked.
Cited by
Sorted by citations
Items 201–214 of 214
Influence of hormonal variations on the performance and pacing of female cyclists in the heat
Hutchins, K. P. (2021) · Queensland University of Technology · doi:10.5204/thesis.eprints.207214
Senthilnathan, C. V., Vaishnavi, G., Keerthana, G., Nandhakumar, S., & Dr.Kotteeswaran (2021) · International Journal of Life Science and Pharma Research · doi:10.22376/ijpbs/lpr.2021.11.5.l11-19
On the Antecedents of Palmar Hyperhidrosis
Kerassidis, S. (2009) · Activitas Nervosa Superior · doi:10.1007/bf03380038
Variation in CFTR-dependent ‘β-sweating’ among healthy adults
DeRose, L., Kim, J., Farahmand, M., Shinbashi, M. Y., Joo, N. S., & Wine, J. J. (2022) · PLoS ONE · doi:10.1371/journal.pone.0265432
Correlating the Effect of Dynamic Variability in the Sensor Environment on Sensor Design
Bhushan, P. (2021) · FIU - Digital Commons (Florida International University) · doi:10.25148/etd.fidc009698
Effect of Emoji on Autonomic Nervous System: Evidence from EDA and RSA studiesPreprint
Patel, D., Dixit, A., & Bhagat, O. L. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.13.589339
Electrochemical Paper Fluidic Device for Extended Real-time Cocaine Monitoring in Simulated SweatPreprint
Hoilett, O. S., Foust, J., Davé, N., Balash, B. M., Moryl, D. L., Kumar, A., & Linnes, J. C. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.03.13.643163
A deep learning strategy to estimate the sweat rate per gland from digital sweat sensing
Haakma, J. R., Turco, S., Esselaar, E., Mischi, M., & Peri, E. (2026) · Discover Sensors · doi:10.1007/s44397-026-00040-6
Domenico, H. D. (2023) · theses.fr (ABES) · doi:10.70675/99cdde1dza6ffz482ez840ez34bade84539a
D’Amelio, T. A., Garbagnoli, T. G., Cuello, J. R., Lewis-Healey, E., Pallavicini, C., Cavanna, F., Bruno, N. M., de la Fuente, L. A., Muller, S. A., Copa, D., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.30.721872
Jimenez, F., & Schambach, M.-A. (2026) · Methods in molecular biology · doi:10.1007/978-1-0716-5253-4_22
Inter- and intra-site reliability of forearm sweating induced by pilocarpine iontophoresis
Wang, H., Lu, M., Otsuka, J., Kato, H., & Amano, T. (2026) · The Journal of Physiological Sciences · doi:10.1016/j.jphyss.2026.100089
Lu, M., Yoshida, T., Oshima, S., Wang, H., Fujii, N., & Amano, T. (2026) · European Journal of Applied Physiology · doi:10.1007/s00421-026-06407-2
Metadata
- Authors
- Sato, K., & Sato, F.
- ORCID
- Sato, F.
- Venue
- American Journal of Physiology-Regulatory, Integrative and Comparative Physiology
- Publisher
- American Physiological Society
- Published
- 1983-08-01
- Volume
- 245
- Issue
- 2
- Pages
- R203-R208
- ISSN
- 0363-6119 (ISSN-L)
- 1522-1490
- OpenAlex
- W2119527242
- Cited by
- 215
- References
- 0
- Citations by year
- 2026: 5 · 2025: 10 · 2024: 8 · 2023: 14 · 2022: 9 · 2021: 15 · 2020: 11 · 2019: 4 · 2018: 7 · 2017: 12 · 2016: 9 · 2015: 6 · 2014: 7 · 2013: 7 · 2012: 8
- FWCI
- 2.88
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Physiology-Regulatory, Integrative and Comparative Physiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Physiology (medical) › Thermoregulation and physiological responses
- Health Sciences › Medicine › Physiology (medical) › Cardiovascular and exercise physiology
- Health Sciences › Medicine › Dermatology › Sympathectomy and Hyperhidrosis Treatments
- Keywords
- eccrine sweat glands, interindividual variability, sweat rate, glandular hypertrophy, physical activity, heat acclimatization, sweat gland function
- MeSH terms
- Adult, Eccrine Glands, Humans, Male, Sweat Glands, Sweating
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review