Lactate accumulates in the cerebrospinal fluid after prolonged exercise
Bibliographic record
Abstract
The resting brain is fuelled by glucose with a small release of lactate. During exercise, the brain switches to extracting lactate from blood and this increases brain carbohydrate uptake in great excess to that of oxygen. The fate of this excess carbohydrate uptake is unknown. Studies investigating the fate of brain carbohydrate uptake use brief periods of brain activation and so it is possible that the dissociation between brain glucose and oxygen metabolism is temporal and not material. In 13 healthy humans, we induced sustained increases in brain carbohydrate uptake via 2 h of mixed-intensity cycling exercise and hypothesized that lactate accumulation in the cerebrospinal fluid would account for some of this excess carbohydrate uptake. Exercise shifted the brain from releasing to extracting lactate ( p = 0.034), causing an excess uptake of 14.3 ± 3.7 mmol of carbohydrate over 2 h of exercise. Although CSF glucose remained perfectly stable (3.0 ± 0.2 vs 3.0 ± 0.1 mmol/L; p = 1.0), CSF lactate concentration doubled (1.1 ± 0.05 vs 2.2 ± 0.3 mmol/L; p < 0.0001) and was correlated to cerebral lactate uptake ( r = 0.68, p = 0.015). This accumulation of lactate in CSF represents a 15% increase in carbohydrate-based ATP availability, but accounts for only 6% of the unexplained carbohydrate extracted by the brain during 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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".