Micronutrients in High‐Fat Diet Modify Insulin Resistance and Its Regulatory Genes in Adult Male Mice
Bibliographic record
Abstract
SCOPE: Obesity and insulin resistance (IR) are associated with epigenetic changes of gene expression. However, the relationship between micronutrients, epigenetic regulation of gene expression, and IR during development of diet-induced obesity has yet to be defined. Our objective is to describe the effect of micronutrient addition to diets on IR and its related genes during obesity development. METHODS AND RESULTS: Male C57BL/6J mice are fed a high-fat (HFD) or low-fat (LFD) diets with or without a multi-vitamin mineral mix (MVM) addition containing vitamins A, B1, B6, B12, and Zn, and Se for 9 weeks. Compared to LFD mice, HFD mice have higher body weight, IR, fasting glucose, insulin, C-peptide, leptin, and hepatic triglyceride concentrations, and dysregulated gene expression in liver, muscle, pancreas, and fat tissues (p < 0.05). The addition of MVM reduces these HFD-induced effects. HFD downregulates 27 genes associated with insulin regulation and adipose tissue function across all tissues by an average of 47% and upregulates five genes by 230% (p < 0.001). Adding MVM downregulates five genes and upregulates one in HFD-fed mice. Both HFD and MVM alter one-carbon metabolites. CONCLUSION: Addition of micronutrients to the HFD decreases IR and modifies associated gene expression in obese and lean mice.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".