The effect of succinate on brain NADH/NAD+ redox state and high energy phosphate metabolism in acute traumatic brain injury
Bibliographic record
Abstract
Abstract A key pathophysiological process and therapeutic target in the critical early post-injury period of traumatic brain injury (TBI) is cell mitochondrial dysfunction; characterised by elevation of brain lactate/pyruvate (L/P) ratio in the absence of hypoxia. We previously showed that succinate can improve brain extracellular chemistry in acute TBI, but it was not clear if this translates to a change in downstream energy metabolism. We studied the effect of microdialysis-delivered succinate on brain energy state (phosphocreatine/ATP ratio (PCr/ATP)) with 31P MRS at 3T, and tissue NADH/NAD+ redox state using microdialysis (L/P ratio) in eight patients with acute major TBI (mean 7 days). Succinate perfusion was associated with increased extracellular pyruvate (+26%, p < 0.0001) and decreased L/P ratio (−13%, p < 0.0001) in patients overall (baseline-vs-supplementation over time), but no clear-cut change in 31P MRS PCr/ATP existed in our cohort (p > 0.4, supplemented-voxel-vs-contralateral voxel). However, the percentage decrease in L/P ratio for each patient following succinate perfusion correlated significantly with their percentage increase in PCr/ATP ratio (Spearman's rank correlation, r = −0.86, p = 0.024). Our findings support the interpretation that L/P ratio is linked to brain energy state, and that succinate may support brain energy metabolism in select TBI patients suffering from mitochondrial dysfunction.
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 | 0.001 |
| 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 | 0.000 | 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".