Metabolomic alterations in human brain microvascular endothelial cells induced by traumatic injury
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Altered metabolic pathways are critical in the progression of traumatic brain injury (TBI). Identifying differentially abundant metabolites (DAMs) from specific cell types can offer valuable diagnostic and prognostic insights. OBJECTIVE: This study aimed to characterize the metabolomic profile of injured human brain microvascular endothelial cells (hBMEC) at 2-, 12-, 24-, and 48 h post-injury. METHODS: Using an in vitro TBI model, we analyzed metabolites in cell culture media through a combination of direct injection mass spectrometry and a custom reverse-phase LC-MS/MS assay. We evaluated 644 metabolites at each time point. RESULTS: Phosphatidylcholines were significantly upregulated across all time intervals. At 2- and 12 h post-injury, the most significantly upregulated metabolites included sphingomyelin (OH) C22:1, ethylmalonic acid, and methylhistidine, while guanosine and the combination of butyric acid + isobutyric acid were the most downregulated. At 24 and 48 h, deoxyadenosine and inosine, respectively, emerged as the most upregulated metabolites, with butyric acid + isobutyric acid and quinoline-4-carboxylic acid showing the greatest downregulation. CONCLUSION: Metabolomic profiling identified various DAMs after traumatic injury that are linked to human endothelial dysfunction. Future experiments should expand the number of metabolites measured to determine the underlying signaling pathways.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it