Elevated sensitivity to diet-induced obesity and insulin resistance in mice lacking 4E-BP1 and 4E-BP2
Bibliographic record
Abstract
The most common pathology associated with obesity is insulin resistance, which results in the onset of type 2 diabetes mellitus. Several studies have implicated the mammalian target of rapamycin (mTOR) signaling pathway in obesity. Eukaryotic translation initiation factor 4E-binding (eIF4E-binding) proteins (4E-BPs), which repress translation by binding to eIF4E, are downstream effectors of mTOR. We report that the combined disruption of 4E-BP1 and 4E-BP2 in mice increased their sensitivity to diet-induced obesity. Increased adiposity was explained at least in part by accelerated adipogenesis driven by increased expression of CCAAT/enhancer-binding protein delta (C/EBPdelta), C/EBPalpha, and PPARgamma coupled with reduced energy expenditure, reduced lipolysis, and greater fatty acid reesterification in the adipose tissue of 4E-BP1 and 4E-BP2 double KO mice. Increased insulin resistance in 4E-BP1 and 4E-BP2 double KO mice was associated with increased ribosomal protein S6 kinase (S6K) activity and impairment of Akt signaling in muscle, liver, and adipose tissue. These data clearly demonstrate the role of 4E-BPs as a metabolic brake in the development of obesity and reinforce the idea that deregulated mTOR signaling is associated with the development of the metabolic syndrome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".