Hyper-variability in Circulating Insulin Levels and Physiological Outcomes to High Fat Feeding in Male <i>Ins1</i> <sup>−/−</sup> : <i>Ins2</i> <sup>+/−</sup> Mice in a Specific Pathogen-free Facility
Bibliographic record
Abstract
Abstract Insulin is an essential hormone with key roles in energy homeostasis and body composition. Mice and rats, unlike other mammals, have two insulin genes: the rodent-specific Ins1 gene and the ancestral Ins2 gene. The relationships between insulin gene dosage and obesity has previously been explored in male and female Ins2 −/− mice with full or reduced Ins1 dosage, as well as in female Ins1 −/− mice with full or partial Ins2 dosage. We report herein unexpected hyper-variability in circulating insulin and physiological responses to high fat feeding in male Ins1 −/− : Ins2 +/− mice. Two large cohorts of Ins1 −/− :Ins2 +/− mice and their Ins1 −/− : Ins2 +/+ littermates were fed chow diet or high fat diet (HFD) from weaning and housed in specific pathogen-free (SPF) conditions. Cohort A and cohort B were studied one year apart. Contrary to female mice from the same litters, inactivating one Ins2 allele on the complete Ins1 -null background did not cause a consistent reduction of circulating insulin in male mice. In cohort A, HFD-fed males showed an equivalent degree of insulin hypersecretion and weight gain, regardless of Ins2 dosage. In cohort B, Ins1 −/− : Ins2 +/− males showed decreased insulin levels and body mass, compared to Ins1 −/− : Ins2 +/+ littermates. While experimental conditions were held consistent between cohorts, we found that HFD-fed Ins1 −/− : Ins2 +/− mice with lower insulin levels had increased corticosterone. Collectively, these observations highlight the hyper-variability and range of phenotypic characteristics modulated by Ins2 gene dosage, specifically in male mice.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".