High-physiological and supra-physiological 1,2-<sup>13</sup>C<sub>2</sub> glucose focal supplementation to the traumatised human brain
Bibliographic record
Abstract
How to optimise glucose metabolism in the traumatised human brain remains unclear, including whether injured brain can metabolise additional glucose when supplied. We studied the effect of microdialysis-delivered 1,2-13C2 glucose at 4 and 8 mmol/L on brain extracellular chemistry using bedside ISCUSflex, and the fate of the 13C label in the 8 mmol/L group using high-resolution NMR of recovered microdialysates, in 20 patients. Compared with unsupplemented perfusion, 4 mmol/L glucose increased extracellular concentrations of pyruvate (17%, p = 0.04) and lactate (19%, p = 0.01), with a small increase in lactate/pyruvate ratio (5%, p = 0.007). Perfusion with 8 mmol/L glucose did not significantly influence extracellular chemistry measured with ISCUSflex, compared to unsupplemented perfusion. These extracellular chemistry changes appeared influenced by the underlying metabolic states of patients’ traumatised brains, and the presence of relative neuroglycopaenia. Despite abundant 13C glucose supplementation, NMR revealed only 16.7% 13C enrichment of recovered extracellular lactate; the majority being glycolytic in origin. Furthermore, no 13C enrichment of TCA cycle-derived extracellular glutamine was detected. These findings indicate that a large proportion of extracellular lactate does not originate from local glucose metabolism, and taken together with our earlier studies, suggest that extracellular lactate is an important transitional step in the brain’s production of glutamine.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".