miR-155 Deletion in Female Mice Prevents Diet-Induced Obesity
Bibliographic record
Abstract
Obesity is a growing epidemic in developed countries. Obese individuals are susceptible to comorbidities, including cardiovascular disease and metabolic disorder. Increasing the ability of adipose tissue to expend excess energy could improve protection from obesity. One promising target is microRNA (miR)-155-5p. We demonstrate that deletion of miR-155 (-5p and -3p) in female mice prevents diet-induced obesity. Body weight gain did not differ between wild-type (WT) and miR-155 knockout (KO) mice fed control diet (CD); however, miR-155 KO mice fed high-fat diet (HFD) gained 56% less body weight and 74% less gonadal white adipose tissue (WAT) than WT mice. Enhanced WAT thermogenic potential, brown adipose tissue differentiation, and/or insulin sensitivity might underlie this obesity resistance. Indeed, miR-155 KO mice on HFD had 21% higher heat release than WT HFD mice. Compared to WT adipocytes, miR-155 KO adipocytes upregulated brown (Ucp1, Cidea, Pparg) and white (Fabp4, Pnpla2, AdipoQ, Fasn) adipogenic genes, and glucose metabolism genes (Glut4, Irs1). miR-155 deletion abrogated HFD-induced adipocyte hypertrophy and WAT inflammation. Therefore, miR-155 deletion increases adipogenic, insulin sensitivity, and energy uncoupling machinery, while limiting inflammation in WAT, which together could restrict HFD-induced fat accumulation. Our results identify miR-155 as a novel candidate target for improving obesity resistance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".