Cerebral oxidative metabolism during exhaustive exercise and recovery at sea level and high altitude (853.12)
Bibliographic record
Abstract
Cerebral oxidative carbohydrate metabolism (OCI) is reduced during moderate and exhaustive exercise at sea‐level (SL) and restored rapidly during recovery. In contrast, in normobaric hypoxia OCI remains unchanged at rest and during moderate exercise. It is unknown what happens to OCI during exhaustive exercise and recovery following partial acclimatization to high altitude (HA; 5050m). Therefore, we hypothesized that OCI will be reduced at HA compared with SL during rest, exercise and recovery. Cerebral metabolism was calculated from the arterial and jugular venous differences for oxygen (Ca‐vO2), glucose (Glua‐v), and lactate (Laca‐v) at 20,40,60,80,100% of the maximum achieved wattage (%Wmax) and during 1,2,4,6,8,10,15,20,25, and 30 minutes of recovery at both SL and HA. The OCI was calculated as an index of the cerebral molar carbohydrate uptake ratio: OCI = Ca‐vO2/Glua‐v + ½ Laca‐v. Resting OCI at HA was ~40% reduced compared with SL (4.0 ± 0.5 vs 6.7±1.0 µmol.100g‐1.min‐1, respectively). Compared to SL, exercise at HA resulted in an ~14, and 8% greater reduction in OCI from rest at 20 and 40%Wmax, an equal reduction at 60% Wmax and an ~ 25, and 29% lesser reduction at 80, and 100% Wmax. During recovery from exercise at SL, OCI remained below baseline values until 25 min whereas at HA the OCI return to baseline at 6 min. It appears that during exhaustive exercise and recovery at sea level the brain relies more on non‐oxidative metabolism than at high altitude. Grant Funding Source : Canadian Graham‐Bell Scholarship, National Science and Engineering Research Council
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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) | 0.001 | 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".