Leptin Improves Insulin Resistance and Hyperglycemia in a Mouse Model of Type 2 Diabetes
Bibliographic record
Abstract
Leptin has metabolic effects on peripheral tissues including muscle, liver, and pancreas, and it has been successfully used to treat lipodystrophic diabetes, a leptin-deficient state. To study whether leptin therapy can be used for treatment of more common cases of type 2 diabetes, we used a mouse model of type 2 diabetes (MKR mice) that show normal leptin levels and are diabetic due to a primary defect in both IGF-I and insulin receptors signaling in skeletal muscle. Here we show that leptin administration to the MKR mice resulted in improvement of diabetes, an effect that was independent of the reduced food intake. The main effect of leptin therapy was enhanced hepatic insulin responsiveness possibly through decreasing gluconeogenesis. In addition, the reduction of lipid stores in liver and muscle induced by enhancing fatty acid oxidation and inhibiting lipogenesis led to an improvement of the lipotoxic condition. Our data suggest that leptin could be a potent antidiabetic drug in cases of type 2 diabetes that are not leptin resistant.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".