Metabolic effects of short-term caloric restriction in mice with reduced insulin gene dosage
Bibliographic record
Abstract
Caloric restriction (CR) is the only environmental intervention with robust evidence that it extends lifespan and delays the symptoms of aging, but its mechanisms are incompletely understood. Based on the prolonged longevity of knockout models, it was hypothesized that the insulin-IGF pathway could be a target for developing a CR mimic. This study aimed to test whether CR has additive effects on glucose homeostasis and beta-cell function in mice with reduced insulin gene dosage. To study models with a range of basal insulin levels, wild-type C57BL/6J and mice on an Ins2 − / − background, were put on 8 weeks of 40% CR at various ages. Both male and female mice rapidly lost weight due to a reduced WAT mass. Glucose tolerance was improved and fasting glucose levels were reduced by CR in both wild type and 45- and 70-week-old Ins2 − / − mice. The effects of CR and reduced insulin on glucose tolerance were non-additive in 20-week-old mice. Interestingly, mice on CR generally exhibited an inability to further depress blood glucose after insulin injection, pointing to possible alterations in insulin sensitivity. In conclusion, our results demonstrate that CR can cause weight loss in the context of reduced insulin production, but that CR-improved glucose homeostasis does not occur near the ‘insulin floor’ in young mice. Collectively, these data shed further light on the relationships between CR, insulin and glucose homeostasis.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".