Environmental temperature effects on adipose tissue growth in a hibernator
Bibliographic record
Abstract
Obligate hibernators express circannual patterns of body mass and hibernation, which persist under constant laboratory conditions. Brown Adipose Tissue (BAT) is important for thermogenesis during arousals from hibernation, whereas White Adipose Tissue (WAT) serves as energy storage and thermal insulation. The goal of this study was to investigate the effects of environmental temperature on BAT and WAT. We hypothesized that changes to environmental temperature would not influence the pattern of mass gain or BAT and WAT volume in the thirteen-lined ground squirrel (Ictidomys tridecemlineatus). To test this, we housed animals thermoneutral 25°C (warm-housed) or 5°C (cold-housed), with the same photoperiod (12 h light:12 h dark) over an entire year. Throughout the year we measured the volume and water-fat ratio of WAT and BAT using magnetic resonance imaging (MRI). We found no evidence of torpor in the warm-housed animals, indicating that this species might not be an obligate hibernator, as previously assumed. Regardless of ambient temperature BAT volume increased prior to winter, then decreased in late winter with no change in water-fat ratio. By contrast both body mass and WAT volume of cold-housed animals declined throughout the winter and recovered after hibernation, but thermoneutral housing produced no circannual pattern in body mass, even though WAT volume declined in late winter. Cold exposure appears to be a primary regulator for WAT but BAT may exhibit an endogenous circannual rhythm in terms of depot volume.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".