PACAP is essential for the adaptive thermogenic response of brown adipose tissue to cold exposure
Bibliographic record
Abstract
Pituitary adenylate cyclase-activating polypeptide (PACAP) is a widely distributed neuropeptide that acts as a neurotransmitter, neuromodulator, neurotropic factor, neuroprotectant, secretagogue, and neurohormone. Owing to its pleiotropic biological actions, knockout of Pacap (Adcyap1) has been shown to induce several abnormalities in mice such as impaired thermoregulation. However, the underlying physiological and molecular mechanisms remain unclear. A previous report has shown that cold-exposed Pacap null mice cannot supply appropriate levels of norepinephrine (NE) to brown adipocytes. Therefore, we hypothesized that exogenous NE would rescue the impaired thermogenic response of Pacap null mice during cold exposure. We compared the adaptive thermogenic capacity of Pacap(-/-) to Pacap(+/+) mice in response to NE when housed at room temperature (24 °C) and after a 3.5-week cold exposure (4 °C). Biochemical parameters, expression of thermogenic genes, and morphological properties of brown adipose tissue (BAT) and white adipose tissue (WAT) were also characterized. Results showed that there was a significant effect of temperature, but no effect of genotype, on the resting metabolic rate in conscious, unrestrained mice. However, the normal cold-induced increase in the basal metabolic rate and NE-induced increase in thermogenesis were severely blunted in cold-exposed Pacap(-/-) mice. These changes were associated with altered substrate utilization, reduced β3-adrenergic receptor (β3-Ar (Adrb3)) and hormone-sensitive lipase (Hsl (Lipe)) gene expression, and increased fibroblast growth factor 2 (Fgf2) gene expression in BAT. Interestingly, Pacap(-/-) mice had depleted WAT depots, associated with upregulated uncoupling protein 1 expression in inguinal WATs. These results suggest that the impairment of adaptive thermogenesis in Pacap null mice cannot be rescued by exogenous NE perhaps in part due to decreased β3-Ar-mediated BAT activation.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".