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Record W2462084194 · doi:10.1113/jp271990

The interactive contributions of Na <sup>+</sup> /K <sup>+</sup> ‐ATPase and nitric oxide synthase to sweating and cutaneous vasodilatation during exercise in the heat

2016· article· en· W2462084194 on OpenAlexaff
Jeffrey C. Louie, Naoto Fujii, Robert D. Meade, Glen P. Kenny

Bibliographic record

VenueThe Journal of Physiology · 2016
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsNitric oxide synthaseVasodilationChemistryNitric oxideOuabainATP synthaseATPaseEndocrinologyInternal medicineThermoregulationSodiumEnzymeMedicineBiochemistry

Abstract

fetched live from OpenAlex

KEY POINTS: Nitric oxide synthase (NOS) contributes to sweating and cutaneous vasodilatation during exercise in the heat. Similarly, reports show that Na(+) /K(+) -ATPase activation can modulate sweating and microvascular circulation. In light of the fact that NO can activate Na(+) /K(+) -ATPase, we evaluated whether there is an interaction between Na(+) /K(+) -ATPase and NOS in the regulation of heat loss responses during an exercise-induced heat stress. We demonstrate that Na(+) /K(+) -ATPase and NOS do not synergistically influence local forearm sweating during moderate intensity (fixed rate of metabolic heat production of 500 W) exercise in the heat (35°C). Conversely, we show an interactive role between NOS and Na(+) /K(+) -ATPase in the modulation of cutaneous vasodilatation. These findings provide novel insight regarding the mechanisms underpinning the control of sweating and cutaneous vasodilatation during exercise in the heat. Given that ouabain may be prescribed as a cardiac glycoside in clinical settings, potential heat loss impairments with ouabain administration should be explored. ABSTRACT: Nitric oxide (NO) synthase (NOS) contributes to the heat loss responses of sweating and cutaneous vasodilatation. Given that NO can activate Na(+) /K(+) -ATPase, which also contributes to sweating and microvasculature regulation, we evaluated the separate and combined influence of Na(+) /K(+) -ATPase and NOS on sweating and cutaneous vasodilatation. Thirteen young (23±3 years) males performed two 30 min semi-recumbent cycling bouts in the heat (35°C) at a fixed rate of metabolic heat production (500 W) followed by 20 and 40 min recoveries, respectively. Local sweat rate (LSR) and cutaneous vascular conductance (CVC) were measured at four forearm skin sites continuously perfused via intradermal microdialysis with either: (1) lactated Ringer solution (Control); (2) 6 mᴍ ouabain (Ouabain), a Na(+) /K(+) -ATPase inhibitor; (3) 10 mᴍ l-N(G) -nitroarginine methyl ester (l-NAME), a NOS inhibitor; or (4) 6 mᴍ ouabain and 10 mᴍ l-NAME (Ouabain+l-NAME). At the end of both exercise bouts relative to Control, LSR was attenuated with Ouabain (54-60%), l-NAME (12-13%) and Ouabain+l-NAME (68-74%; all P < 0.05). Moreover, the sum of attenuations from Control induced by independent administration of Ouabain and l-NAME was similar to the combined infusion of Ouabain+l-NAME (both P ≥ 0.74). Compared to Control, CVC at the end of both exercise bouts was similar with Ouabain (both P ≥ 0.30), but attenuated with l-NAME (%CVCmax reduction from Control, 24-25%). Furthermore, CVC at the Ouabain+l-NAME site (38-39%; all P < 0.01) was attenuated compared to Control and did not differ from baseline resting values (both P ≥ 0.81). We show that Na(+) /K(+) -ATPase and NOS do not synergistically mediate sweating, whereas they influence cutaneous blood flow in an interactive manner during exercise in the heat.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.285
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations25
Published2016
Admission routes1
Has abstractyes

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