Cytochrome P450-soluble epoxide hydrolase derived linoleic acid oxylipins and cognitive performance in type 2 diabetes
Bibliographic record
Abstract
Type 2 diabetes mellitus (T2DM) increases the risk of cognitive decline and dementia. Disruptions in the cytochrome P450-soluble epoxide hydrolase (CYP450-sEH) pathway have been reported in T2DM, obesity and cognitive impairment. We examine linoleic acid (LA)-derived CYP450-sEH oxylipins and cognition in T2DM and explore potential differences between obese and nonobese individuals. The study included 51 obese and 57 nonobese participants (mean age 63.0 ± 9.9, 49% women) with T2DM. Executive function was assessed using the Stroop Color-Word Interference Test, FAS-Verbal Fluency Test, Digit Symbol Substitution Test, and Trails Making Test-Part B. Verbal memory was assessed using the California Verbal Learning Test, second Edition. Four LA-derived oxylipins were analyzed by ultra-high-pressure–LC/MS, and the 12,13-dihydroxyoctadecamonoenoic acid (12,13-DiHOME) considered the main species of interest. Models controlled for age, sex, BMI, glycosylated hemoglobin A1c, diabetes duration, depression, hypertension, and education. The sEH-derived 12,13-DiHOME was associated with poorer executive function scores (F 1,98 = 7.513, P = 0.007). The CYP450-derived 12(13)-epoxyoctadecamonoenoic acid (12(13)-EpOME) was associated with poorer executive function and verbal memory scores (F 1,98 = 7.222, P = 0.008 and F 1,98 = 4.621, P = 0.034, respectively). There were interactions between obesity and the 12,13-DiHOME/12(13)-EpOME ratio (F 1,97 = 5.498, P = 0.021) and between obesity and 9(10)-epoxyoctadecamonoenoic acid (9(10)-EpOME) concentrations (F 1,97 = 4.126, P = 0.045), predicting executive function such that relationships were stronger in obese individuals. These findings suggest that the CYP450-sEH pathway as a potential therapeutic target for cognitive decline in T2DM. For some markers, relationships may be obesity dependent.
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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".