The influence of <i>angiotensin converting enzyme</i> and <i>bradykinin receptor B<sub>2</sub></i> gene variants on voluntary fluid intake and fluid balance in healthy men during moderate-intensity exercise in the heat
Bibliographic record
Abstract
Angiotensin converting enzyme (ACE) and bradykinin receptor B2 (B2R) genetic variation may affect thirst because of effects on angiotensin II production and bradykinin activity, respectively. To examine this, 45 healthy Caucasian men completed 60 min of cycle exercise at 62% ± 5% peak oxygen uptake in a room heated to 30.5 ± 0.3 °C with ad libitum fluid intake. Blood samples were collected pre-, mid-, and immediately post-cycle. Fluid intake, body mass loss (BML), sweat loss (determined via changes in body mass and fluid intake), and thirst sensation were recorded. All participants were genotyped for the ACE insert fragment (I) and the B2R insert sequence (P). Participants were homozygous for the wild-type allele (WW or MM), heterozygous (WI or MP) or homozygous for the insert (II or PP). No differences between genotype groups were found in mean (±SD) voluntary fluid intake (WW: 613 ± 388, WI: 753 ± 385, II: 862 ± 421 mL, p = 0.31; MM: 599 ± 322, MP: 745 ± 374, PP: 870 ± 459 mL, p = 0.20), percentage BML or any other fluid balance variables for both the ACE and B2R genes, respectively. Mean thirst perception in the B2R PP group, however, was higher (p < 0.05) than both MM and MP at 30, 45, and 60 min. In conclusion, the results of this study suggest that voluntary fluid intake and fluid balance in healthy men performing 60 min of moderate-intensity exercise in the heat are not predominantly influenced by ACE or B2R genetic variation.
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 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) | 0.001 | 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".