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The Effects of Local NOS‐inhibition and Ascorbate Administration on Cutaneous Vasodilation and Sweating During Exercise‐heat Stress in Adults With and Without Hypertension

2020· article· en· W3016911232 on OpenAlexaffabout
Madison D. Schmidt, Robert D. Meade, Caroline M. Muia, Naoto Fujii, Pierre Boulay, Ronald J. Sigal, Glen P. Kenny

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsUniversity of CalgaryUniversité de SherbrookeUniversity of Ottawa
Fundersnot available
KeywordsMicrodialysisVasodilationNitric oxideSodium nitroprussideOxidative stressMedicineChemistryAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Aging is associated with oxidative stress in the skin resulting from an accumulation of radical oxygen species. Hypertension exacerbates oxidative stress, leading to a reduced contribution of nitric oxide (NO) to cutaneous vasodilation during whole‐body passive heat stress. We recently demonstrated that local administration of the non‐selective anti‐oxidant ascorbate did not modify NO‐dependent cutaneous vasodilation and sweating in older adults exercising in the heat (35°C). The effect of ascorbate on those responses in individuals with hypertension, however, remains uncertain. We therefore evaluated the hypothesis that local ascorbate administration improves NO‐dependent cutaneous vasodilation and sweating in adults with hypertension. Middle‐aged adults with (HYPE, mean [SD] age: 60 [5] years; n=7, 5 women) and without (CON, age: 63 [6] years; n=7, 2 women) hypertension performed two 30‐min bouts of cycling in the heat (35°C, 20% RH) at an external work rate eliciting ~50% peak aerobic power. The first (Ex1) and second (Ex2) bouts were separated by a 20‐min recovery. Four skin sites were perfused continuously via microdialysis with either 1) lactated Ringer’s (control site); 2) 10 mM ascorbate (anti‐oxidant treated); 3) 10 mM L‐NAME (NO‐inhibited); or 4) a combination of both agents. Cutaneous vascular conductance (CVC; presented as a % of maximum during sodium nitroprusside administration, CVC max ) and sweat rate were measured at each site. The effect of each treatment (i.e., change from the control site) was evaluated separately within each group. No differences in CVC at the control site were observed between HYPE (Ex1: 68 [20]%CVC max ; Ex2: 74 [25]%CVC max ) and CON (Ex1: 63 [16]%CVC max ; Ex2: 68 [20]%CVC max ; both p>.74). In the HYPE, ascorbate augmented CVC during Ex1 (7 [4]%CVC max , P=.003) and Ex2 (8 [6]%CVC max , P=.014‐‐). By contrast, L‐NAME reduced CVC alone (Ex1: −26 [19]%CVC max ; Ex2: −29 [16]%CVC max ; both p<.013) and when administered with ascorbate (Ex1: −19 [15]%CVC max ; Ex2: −19 [14]%CVC max ; both p<.017). In CON, an effect of ascorbate was not observed (Ex1: −5 [20]%CVC max ; Ex2: −11 [21]%CVC max ; both p>.18) and L‐NAME attenuated CVC with (Ex1: −22 [18]%CVC max ; Ex2: −23 [22]%CVC max ; both p<.026) and without ascorbate (Ex1: −24 [14]%CVC max ; Ex2: −22 [23]%CVC max ; both p<.031). Sweat rate was reduced in the HYPE compared to CON group during Ex1 (.39 [15] vs .78 [.31] mg·min −1 ·cm −2 ; p=.011) and Ex2 (.39 [15] vs .78 [.31] mg·min −1 ·cm −2 ; p=.011) at the control site. Sweating was not influenced by any treatment in HYPE (all p>.07). In CON, ascorbate augmented sweating during Ex 1 (.14 [.16] mg·min −1 ·cm −2 ; p=.038) but not Ex2 (.09 [.23] mg·min −1 ·cm −2 ; p=.31). No effect on sweating was seen at either NO‐inhibited site in CON (all p>.13). Therefore, in individuals with hypertension exercising in the heat, local administration of ascorbate augments NO‐dependent cutaneous vasodilation but not sweating, while in individuals without hypertension, ascorbate did not affect either heat loss response. Support or Funding Information Natural Sciences and Engineering Research Council of Canada.

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 score0.003

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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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".

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Citations0
Published2020
Admission routes2
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