Prolonged exercise after diuretic-induced hypohydration: effects on substrate turnover and oxidation
Bibliographic record
Abstract
To determine the influence of a diuretic-induced reduction in plasma volume (PV) on substrate turnover and oxidation, 10 healthy young males were studied during 60 min of cycling exercise at 61% peak oxygen uptake on two separate occasions > or =1 wk apart. Exercise was performed under control conditions (CON; placebo), and after 4 days of diuretic administration (DIU; Novotriamazide; 100 mg triamterene and 50 mg hydrochlorothiazide). DIU resulted in a calculated reduction of PV by 14.6 +/- 3.3% (P < 0.05). Rates of glucose appearance (R(a)) and disappearance (R(d)) and glycerol R(a) were determined by using primed constant infusions of [6,6-(2)H]glucose and [(2)H(5)]glycerol, respectively. No differences in oxygen uptake during exercise were observed between trials. Main effects for condition (P < 0.05) were observed for plasma glucose and glycerol, such that the values observed for DIU were higher than for CON. No differences were observed in plasma lactate and serum free fatty acid concentrations either at rest or during exercise. Hypohydration led to lower (P < 0.05) glucose R(a) and R(d) at rest and at 15 and 30 min of exercise, but by 60 min, the effects were reversed (P < 0. 05). Hypohydration had no effect on rates of whole body lipolysis or total carbohydrate or fat oxidation. A main effect for condition (P < 0.05) was observed for plasma glucagon concentrations such that larger values were observed for DIU than for CON. A similar decline in plasma insulin occurred with exercise in both conditions. These results indicate that diuretic-induced reductions in PV decreases glucose kinetics during moderate-intensity dynamic exercise in the absence of changes in total carbohydrate and fat oxidation. The specific effect on glucose kinetics depends on the duration of the exercise.
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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) | 0.001 | 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) | 0.001 | 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".