36-LB: Linoleic Acid Derived Oxylipins, Memory, and Microvascular Retinal Complications in Patients with Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Introduction: Memory decline is accelerated in type 2 diabetes mellitus (T2DM), and it is thought that microvascular disease may be a contributor. Oxylipins, bioactive lipid species derived from polyunsaturated free fatty acids such as linoleic acid, can act on small vessels. Cytochrome p450 derived epoxides may be immunologically active, whereas their hydrolysis into diols by soluble epoxide hydrolase (sEH) may render them inactive or cytotoxic. We examine linoleic acid epoxide and diol concentrations in peripheral blood and their associations with memory performance and retinal microvascular disease in patients with T2DM or prediabetes. Methods: Patients with T2DM or prediabetes were recruited from 3 sites. Memory was assessed via California Verbal Learning Test 2nd Edition (CVLT-II). Patient history of retinopathy was recorded. Serum oxylipin concentrations were measured via ultra-high-performance liquid chromatography tandem mass-spectrometry. Results: In people with T2DM or prediabetes (n=76, 55% women, 63±9 years old, HbA1C=7.4±1.2% mmol/mol, duration of diabetes 8±10 years), 9.2% had retinopathy, and the mean CVLT-II was -0.07±1.01 Z-score units (indicating generally average performance). The linoleic acid derived epoxide 12(13)-epoxyoctadecenoic acid concentration was negatively correlated with CVLT-II performance (β=-0.298, p=0.003), whereas the diol derived from that species (12,13-dihydroxyoctadecenoic acid) was elevated in people with retinopathy (9.1±4.1 nM vs. 6.5±11.5 nM, U=72.0, p=0.008). Discussion: Oxylipins generated by cytochrome p450 and sEH should be explored as potential biomarkers for cognitive complications and microvascular disease in T2DM. The observed relationships might suggest the presence of a cytochrome p450-mediated response that may generate differential response and lack benefit in T2DM, possibly due to sEH-mediated conversion of epoxides into diols, warranting further study. Disclosure S.K. Wong: None. M.M. Nguyen: None. C. Major-Orfao: None. K.L. Lanctôt: None. N. Herrmann: None. P. Oh: None. B.R. Shah: None. J. Gilbert: Speaker’s Bureau; Self; Abbott, Amgen, Ascensia Diabetes Care. Other Relationship; Self; AstraZeneca, Boehringer Ingelheim (Canada) Ltd., Dexcom, Inc., Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk Inc., Sanofi. A. Assal: None. I. Halperin: Advisory Panel; Self; Tandem Diabetes Care. Speaker’s Bureau; Self; Abbott, Boehringer Ingelheim (Canada) Ltd., Dexcom, Inc., Novo Nordisk Inc., Sanofi. P. Yang: None. T. Pedersen: None. A. Taha: None. W. Swardfager: None. Funding Canadian Institutes of Health Research (410010992)
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".