Temperature-Sensitive Phenotype in Mice Lacking Pituitary Adenylate Cyclase-Activating Polypeptide
Bibliographic record
Abstract
Pituitary adenylate cyclase-activating polypeptide (PACAP) is a highly conserved hormone. Targeted disruption of the PACAP gene has revealed a role for this peptide in lipid metabolism, carbohydrate metabolism, and the sympathetic response to insulin stress. We report here that PACAP null mice are temperature sensitive. When raised at 21 C, only 11% of the PACAP null mice survived past the first 2 wk after birth, but when raised at 24 C, most (76%) of the PACAP null mice survived. The question is the mechanism by which the absence of PACAP affects thermoregulation. Brown adipose tissue is the major site of adaptive thermogenesis in neonates and rodents. We show that PACAP null mice have brown adipocytes that differentiate normally and express two enzymes involved in thermogenesis, hormone-sensitive lipase and uncoupling protein 1. Likewise, levels of catecholamines in the adrenal medulla and plasma are normal in PACAP null mice raised at a lower temperature. In contrast, norepinephrine and its precursor dopamine extracted from brown adipose tissue are present at significantly lower levels in the PACAP null mice compared with controls. Also, PACAP null mice showed a greater loss of core body temperature compared with wild-type controls at 21 C. We conclude that under prolonged but mild cold stress, lack of PACAP results in inadequate heat production due to insufficient norepinephrine stimulation of brown adipose tissue.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
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".