Abstract TP267: Metabolomics Identifies a Branched Chain Amino Acid Profile in Acute Ischemic Stroke
Bibliographic record
Abstract
Background: There is limited information about changes in metabolism during acute ischemic stroke. The identification of circulating plasma metabolites modulated during cerebral infarction may provide insight into pathogenesis and identify novel biomarkers. Methods: We performed filament occlusion of the middle cerebral artery of Wistar rats compared to sham controls, collecting plasma and CSF two hours after onset of ischemia. Plasma samples from human acute stroke and TIA control subjects were also collected an average of 6 hours after stroke onset. All samples were analyzed using liquid chromatography followed by tandem mass spectrometry. Positively charged metabolites including amino acids, nucleotides and neurotransmitters were quantified using electrospray ionization followed by scheduled multiple reaction monitoring. Results: Several metabolites were altered in the setting of cerebral ischemia. We detected a 42% rise in glucose (P=0.006) in stroke subjects compared to TIA controls, consistent with prior observations. We confirmed the validity of the method by comparing glucose measured in our metabolomics platform to bedside glucometer measurements, and we found a correlation coefficient of 0.72 (P<0.0001). We also detected a consistent reduction in branched chain amino acids (BCAAs; valine, leucine, isoleucine) in rat plasma, rat CSF and human plasma compared to the respective controls. We detected a 17% decrease in the level of the branched chain amino acids (P<0.00005). In the human stroke cohort, lower BCAA level correlated with poor neurological outcome (mRS 3-6; Spearman correlation = -0.39, P=0.001). Conclusions: Our data support a role for BCAAs in ischemic stroke, which correlates with worse neurological outcome. Intriguingly, BCAAs serve an integral role in the glutamate/glutamine cycle between astrocytes and neurons, and are also a principal signal for energy homeostasis. The extent to which BCAAs are in a causal pathway or are an epi-phenomenon of ischemic stroke remains to be determined.
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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 | 0.001 | 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) | 0.002 | 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".