Relationship of potassium ions and blood lactate to ventilation during exercise
Bibliographic record
Abstract
Ventilatory control during exercise is a complex network of neural and humoral signals. One humoral input that has received little recent attention in the exercise literature is potassium ions [K(+)]. The purpose of this study was to examine the relationship between [K(+)] and ventilation during an incremental cycle test and to determine if the relationship between [K(+)] and ventilation differs when blood lactate [lac-] is manipulated. Eight experienced triathletes (4 of each sex) completed 2 incremental, progressive (5-min stages) cycle tests to volitional fatigue: 1 with normal glycogen stores and 1 with reduced glycogen. Minute ventilation was measured during the final minute of each stage, and blood [lac(-)] and [K+] were measured at the end of each exercise stage. Minute ventilation and [K(+)] increased with exercise intensity and were similar between trials (p > 0.5), despite lower [lac-] during the reduced-glycogen trial. The concordance correlations (R(c)) between [lac(-)] and minute ventilation were stronger for both trials (R(c) = approximately 0.88-0.96), but the slopes of the relationships were different than the relationships between [K(+)] and minute ventilation (R(c) = approximately 0.76-0.89). The slope of the relationship between [lac-] and minute ventilation was not as steep during the reduced-glycogen trial, compared with the normal trial (p = 0.002). Conversely, the slope of the relationships between [K(+)] and minute ventilation did not change between trials (p = 0.454). The consistent relationship of minute ventilation and blood [K(+)] during exercise suggests a role for this ion in the control of ventilation during exercise. Conversely, the inconsistent relationship between blood lactate and ventilation brings into question the importance of the relationship between lactate and ventilation during exercise.
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 | 0.003 |
| 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".