Metabolomic Profiling of the DASH Diet: Novel Insights for the Nutritional Epidemiology of Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Metabolic changes arising from DASH adherence and their relationships with incident T2DM have not been described. We aimed to determine metabolite clusters associated with adherence to a DASH-type diet in the Insulin Resistance Atherosclerosis Study (IRAS) cohort and explore if they predicted 5-year T2DM incidence. DASH adherence for 570 non-diabetic participants was determined using two scoring indices. Metabolite clusters associated with adherence to each of the indices were identified using partial least squares (PLS). Multivariable-adjusted logistic regression was used to explore associations between metabolite clusters and incident T2DM. Results indicated that acylcarnitines and fatty acids loaded strongly on the PLS components. Component 2 was inversely associated with incident T2DM after adjustment for covariates for the first index (odds ratio (OR):0.89; 95%CI:0.80-1.00), and prior to adjustments for the second index (OR:0.88; 95%CI:0.81-0.96). In conclusion, DASH adherence may contribute to reduced T2DM risk through modulations in acylcarnitine and fatty acid physiology.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".