Roles of vitamin A status and retinoids in glucose and fatty acid metabolism
Bibliographic record
Abstract
The rising prevalence of metabolic diseases, such as obesity and diabetes, has become a public health concern. Vitamin A (VA, retinol) is an essential micronutrient for a variety of physiological processes, such as tissue differentiation, immunity, and vision. However, its role in glucose and lipid metabolism has not been clearly defined. VA activities are mediated by the metabolite of retinol catabolism, retinoic acid, which activates the retinoic acid receptor and retinoid X receptor (RXR). Since RXR is an obligate heterodimeric partner for many nuclear receptors involved in metabolism, it is reasonable to assume that VA status and retinoids contribute to glucose and lipid homeostasis. To date, the impacts of VA and retinoids on energy metabolism in animals and humans have been demonstrated in some basic and clinical investigations. This review summarizes the effects of VA status and retinoid treatments on metabolism of the liver, adipocytes, pancreatic β-cells, and skeletal muscle. It proposes a mechanism by which the dietary and hormonal signals converge on the promoter of sterol regulatory element-binding protein 1c gene to induce its expression, and in turn, the expression of lipogenic genes in hepatocytes. Future research projects relevant to the VA's roles in metabolic diseases are also discussed.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".