Abstract WP257: Metabolic Profiling in the Plasma of Rats in Response to Aging and Ischemic Stroke by Nuclear Magnetic Resonance Spectroscopy
Bibliographic record
Abstract
Introduction: Metabolic dysfunction is a common hallmark of aging, and it influences the neurodegenerative diseases including stroke incidence and outcome. Several metabolomics-based studies have revealed metabolite biomarkers in stroke patients and yet metabolic changes as a result of aging and focal ischemia/reperfusion (I/R) time are not completely elucidated. In this study, we examined the dysregulation of metabolites in the plasma as a function of age and cerebral ischemic injury. Methods: We compared the metabolic pattern in young (3 months) and older rats (12 months) before, and 2 days after I/R injury. Stroke was induced by middle cerebral artery occlusion. For time course study, plasma samples from younger animals were collected at day 1, 2, 3, 7, 14 and 21 of I/R (n=3). We used Nuclear Magnetic Resonance spectroscopy and compared the metabolite peaks using spectral binning and targeted profiling. The data was analyzed using one way analysis of variance, principal component analysis (PCA) and hierarchical clustering. Pathway enrichment and topological analysis tools were used to identify the age and stroke responsive metabolic pathways. Results: PCA revealed global differences in plasma of naïve young and old rats, with old rats showing significantly lower glucose levels, and higher formate levels. Also, older animals showed reduced levels of acetate and formate and very high levels of 3-hydroxybutyrate 2 days after I/R. Younger rats showed significant differences starting from day 3 onwards with lower glucose concentration and increased 3-hydroxybutyrate, creatine, formate and glycine concentrations, which remained at a higher level on day 7 of I/R. Interestingly, the metabolic profile of plasma at day 21 of I/R showed similar pattern as that of control naïve animals. Pathway topology analysis revealed enrichment of citric acid cycle and glycine, serine and threonine metabolic pathways in older animals as early as 2 days after I/R. However, younger animals showed a delayed metabolic response after day 3 of I/R. Conclusions: We have demonstrated that the metabolic profile of plasma is altered as a function of age, ischemic stroke and time of reperfusion. These results suggests an important role for imbalance in metabolites in stroke pathogenesis.
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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) | 0.000 | 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".