Housing matters: Experimental variables shaping metabolism in obese mice
Bibliographic record
Abstract
Diet-induced obesity in mice is an important model for investigating host-diet interactions as well as dietary and pharmacological treatments of metabolic diseases. Experimental reproducibility is, however, a recurrent challenge. To determine key controllable experimental drivers of mouse metabolism, we distributed 338C57BL/6JBomTac mice (males and females) into six research units across two countries, divided them into a variety of housing conditions (i.e., diets, cage types, temperatures, group-housing vs. single-housing) and kept 26 reference mice at the vendor. We applied linear mixed models to rank the influence of each variable on metabolic phenotype (i.e., body weight gain, glucose intolerance, liver, and visceral adipose tissue weight). Group-housing was the most potent driver of metabolic dysfunction apart from sex and diet. Accordingly, single-housed mice exhibited reduced weight gain (∼50%), increased energy expenditure, and diminished respiratory exchange ratio concomitant with improved glucose tolerance (∼20%) compared to their group-housed counterparts. Our results may aid in clarifying the impact of experimental design and promote rational, transparent reporting to increase reproducibility.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".