Cytochrome P450-soluble epoxide hydrolase oxylipins, depression and cognition in type 2 diabetes
Bibliographic record
Abstract
This study examined serum cytochrome P450-soluble epoxide hydrolase (CYP450-sEH) oxylipins and depressive symptoms together in relation to cognitive performance in individuals with type 2 diabetes mellitus (T2DM). Clinically cognitively normal T2DM individuals were recruited (NCT04455867). Depressive symptom severity was assessed using the Beck Depression Inventory-II (BDI-II; total scores ≤13 indicated minimal depressive symptoms and ≥ 14 indicated significant depressive symptoms). Executive function and verbal memory were assessed. Fasting serum oxylipins were quantified by ultra-high-performance liquid chromatography tandem mass-spectrometry. The study included 85 participants with minimal depressive symptoms and 27 with significant symptoms (mean age: 63.3 ± 9.8 years, 49 % women). In all participants, higher concentrations of linoleic acid derived sEH (12,13-dihydroxyoctadecamonoenoic acid; DiHOME) and CYP450 (12(13)-epoxyoctadecamonoenoic acid; EpOME) metabolites were associated with poorer executive function (F1,101 = 6.094, p = 0.015 and F1,101 = 5.598, p = 0.020, respectively). Concentrations of multiple sEH substrates interacted with depressive symptoms to predict 1) poorer executive function, including 9(10)-EpOME (F1,100 = 12.137, p < 0.001), 5(6)-epoxyeicosatrienoic acid (5(6)-EpETrE; F1,100 = 6.481, p = 0.012) and 11(12)-EpETrE (F1,100 = 4.409, p = 0.038), and 2) verbal memory, including 9(10)-EpOME (F1,100 = 4.286, p = 0.041), 5(6)-EpETrE (F1,100 = 6.845, p = 0.010), 11(12)-EpETrE (F1,100 = 3.981, p = 0.049) and 14(15)-EpETrE (F1,100 = 5.019, p = 0.027). Associations of CYP450-sEH metabolites and depressive symptoms with cognition highlight the biomarker and therapeutic potential of the CYP450-sEH pathway in T2DM.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".