Serum oxylipins indicate subcortical ischemic vascular disease in patients with clinical stroke
Bibliographic record
Abstract
Abstract Background Subcortical ischemic vascular disease (SIVD) is the most common vascular pathology found in patients with late onset dementia. The soluble epoxide hydrolase (sEH) enzyme inactivates anti‐inflammatory and vasoactive cytochrome p450 derived polyunsaturated fatty acid epoxides by converting them into cytotoxic dihydroxy (diol) oxylipin species. Previously, we found that the ratios of linoleic acid (LA) diols to epoxides were associated with more white matter hyperintensity (WMH) in patients with transient ischemic attack; however, it remains univestigated if these oxylipins can identify SIVD in patients with ischemic stroke of heterogenous cerebrovascular pathologies such as large vessel occlusion and lacunar infarcts. Method The study cohort comprises patients from the Ontario Neurodegenerative Disease Research Initiative, who has clinical stroke of either large or small vessel etiology (according to TOAST criteria). 4 LA oxylipins (12,13‐dihydroxyoctadecamonoenoic acid (12,13‐DiHOME), 12,13‐epoxyoctadecenoic acid (12,13‐EpOME), 9,10‐DiHOME, 9,10‐EpOME) were extracted from blood and quantified with a targeted ultrahigh pressure liquid chromatography mass spectrometry (UPLC‐MS/MS) WMH and perivascular spaces (PVS) were quantified from structural MRI scans using a personalized semi‐automatic processing pipeline (Lesion Explorer). The associations between oxylipins and small vessel disease markers were examined using linear regression models. Result In 80 stroke patients (n=50 large vessel disease and n=30 lacunar infarcts), the ratio of 12,13‐DiHOME to its epoxide sEH substrate 12,13‐EpOME was higher among patients with small vessel etiology (F1,79 = 4.55, p = 0.036). In linear regression models controlling for age, sex, APOE, waist hip ratio, diabetes, and hyperlipidemia, the same ratio, and the ratio of 9,10‐DiHOME/9,10‐EpOME were positively associated with volume of deep (β = 0.338, p = 0.004; β = 0.288, p = 0.012, respectively) and periventricular (β = 0.316, p = 0.003; β = 0.400, p < 0.001, respectively) WMH. The same ratios were associated with higher volumes of perivascular spaces in the white matter (β = 0.293, p = 0.013; β = 0.276, p = 0.016, respectively) but not in the basal ganglia (β = 0.145, p = 0.212; β = 0.086, p = 0.450, respectively). Conclusion Oxylipins derived from sEH activity may contribute to cerebral small vessel disease and to stroke of small vessel etiology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".