Lean Phenotype and Resistance to Diet-Induced Obesity in Vitamin D Receptor Knockout Mice Correlates with Induction of Uncoupling Protein-1 in White Adipose Tissue
Bibliographic record
Abstract
Increased adiposity is a feature of aging in both mice and humans, but the molecular mechanisms underlying age-related changes in adipose tissue stores remain unclear. In previous studies, we noted that 18-month-old normocalcemic vitamin D receptor (VDR) knockout (VDRKO) mice exhibited atrophy of the mammary adipose compartment relative to wild-type (WT) littermates, suggesting a role for VDR in adiposity. Here we monitored body fat depots, food intake, metabolic factors, and gene expression in WT and VDRKO mice on the C57BL6 and CD1 genetic backgrounds. Regardless of genetic background, both sc and visceral white adipose tissue depots were smaller in VDRKO mice than WT mice. The lean phenotype of VDRKO mice was associated with reduced serum leptin and compensatory increased food intake. Similar effects on adipose tissue, leptin and food intake were observed in mice lacking Cyp27b1, the 1alpha-hydroxylase enzyme that generates 1,25-dihydroxyvitamin D(3), the VDR ligand. Although VDR ablation did not reduce expression of peroxisome proliferator-activated receptor-gamma or fatty acid synthase, PCR array screening identified several differentially expressed genes in white adipose tissue from WT and VDRKO mice. Uncoupling protein-1, which mediates dissociation of cellular respiration from energy production, was greater than 25-fold elevated in VDRKO white adipose tissue. Consistent with elevation in uncoupling protein-1, VDRKO mice were resistant to high-fat diet-induced weight gain. Collectively, these studies identify a novel role for 1,25-dihydroxyvitamin D(3) and the VDR in the control of adipocyte metabolism and lipid storage in vivo.
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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) | 0.000 | 0.000 |
| 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 | 0.000 | 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".