Housing temperature dictates the systemic and tissue-specific molecular responses to cancer in mice
Bibliographic record
Abstract
Summary Cancer cachexia is a metabolic condition affecting up to 80% of patients with cancer. Cachexia is mediated by reduced muscle and fat mass and impaired function, and it lowers survival for patients. With no approved drugs to treat cachexia, preclinical efforts focus on understanding the molecular mechanisms underlying this condition to reveal treatment targets. Housing laboratory mice at ambient temperature imposes cold stress, leading to induced thermogenic activity and consequent whole-body metabolic adaptations. Yet, the impact of housing temperature in in vivo preclinical cachexia remains unknown. We found that thermoneutral (TN) housing in C26 carcinoma-bearing (C26) mice affected lean and fat mass, but not muscle weight or force. TN housing improved glucose tolerance in C26 mice, while enhancing circulating abundance of FGF21 and IL-6. Thermogenic tissues, especially brown adipose tissue, exhibited housing temperature-dependent molecular responses to cancer in oxygen consumption, ATP levels and SERCA ATPase activity, which are all crucial for cancer-induced whole-body metabolic adaptations. We conclude that molecular and systemic adaptations to cancer in mice critically depend on housing temperature, which should be considered in the design and interpretation of preclinical cancer studies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".