Impairments in Local Heat Loss in Type 1 Diabetes during Exercise in the Heat
Bibliographic record
Abstract
UNLABELLED: Studies show that vasomotor and sudomotor activities are compromised in individuals with Type 1 diabetes mellitus (T1DM), which could lead to impaired skin blood flow (SkBF) and sweating during heat stress. However, recent work suggests the impairments may only be evidenced beyond a certain level of heat stress. PURPOSE: We examined T1DM-related differences in heat loss responses of SkBF and sweating during exercise performed at progressive increases in the requirement for heat loss. METHODS: Sixteen adults (10 males and six females) with (T1DM, n = 8) and without T1DM (control, n = 8) matched for age, sex, body surface area, and fitness cycled at fixed rates of metabolic heat production of 200, 250, and 300 W·m in the heat (35°C and 20% relative humidity). Each rate was performed sequentially for 30 min. Local sweat rate (LSR, ventilated capsule), sweat gland activation (modified iodine paper technique), and sweat gland output were measured on the forearm, upper back, and chest, whereas SkBF (laser Doppler) was measured on the forearm and upper back. RESULTS: Despite a similar requirement for heat loss, LSR was lower in T1DM on the forearm and chest relative to that in the control. Reductions were measured in the second (forearm: 0.68 ± 0.14 vs 0.85 ± 0.11 mg·min·cm, P = 0.004; chest: 0.58 ± 0.08 vs 0.82 ± 0.12 mg·min·cm, P = 0.046) and third exercise bouts (forearm: 0.75 ± 0.11 vs 0.98 ± 0.12 mg·min·cm, P = 0.005; chest: 0.66 ± 0.1 vs 1.02 ± 0.16 mg·min·cm, P = 0.032). Differences in forearm LSR were the result of a reduction in sweat gland output, whereas the decrease in chest LSR was due to lower sweat gland activation. SkBF did not differ between groups. CONCLUSIONS: We show that T1DM is associated with impairments in heat dissipation during exercise in the heat, as evidenced by attenuated LSR. However, these differences are only shown beyond a certain requirement for heat loss.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".