Plasma Sphingolipids Mediate a Relationship Between Type 2 Diabetes and Memory Outcomes in Patients with Coronary Artery Disease Undertaking Exercise
Bibliographic record
Abstract
BACKGROUND: Exercise prevents recurrent cardiovascular events and it may combat cognitive decline in coronary artery disease (CAD); however, evidence in type 2 diabetes (T2DM) has been mixed. T2DM and memory decline have been associated with differences in the plasma sphingolipidome. OBJECTIVE: Here, we will investigate whether T2DM-related sphingolipids predict less memory improvement over an exercise intervention for CAD. METHODS: Among participants with CAD entering a 6-month exercise intervention, we matched 20 with T2DM to 40 without T2DM for age, sex, and body mass index. We assessed 45 sphingolipid species using high-performance liquid chromatography coupled electrospray ionization tandem mass spectrometry with multiple reaction monitoring. We assessed memory using the California Verbal Learning Test, 2nd Ed, and the revised Brief Visuospatial Learning Test. RESULTS: Partial least squares discriminant analysis identified 8 species that distinguished T2DM from non-T2DM groups with 83% (95% confidence interval [70%, 95%]) accuracy in a receiver operator characteristic curve (validated by internal resampling, 1000 permutations, p = 0.01). At baseline, T2DM-associated sphingolipids (ceramide C22 : 0, monohexylceramide C16 : 1, and lactosylceramide C24 : 0) were associated with poorer memory, attention, and psychomotor processing speed performance. Among 50 completers, an indirect effect of T2DM on less improvement in verbal memory was mediated by monohexylceramide C16 : 1 (0.86 fewer words recalled, 95% bootstrap confidence interval [-2.32, -0.24]), and an indirect effect of T2DM on less visuospatial memory improvement was mediated by ceramide C22 : 0 concentrations (0.42 fewer points, 95% bootstrap confidence interval [-1.17, -0.05]). CONCLUSIONS: Ceramide species associated with T2DM predicted poorer cognitive responses to exercise in patients with CAD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".