Targeted Disruption of the Pituitary Adenylate Cyclase-Activating Polypeptide Gene Results in Early Postnatal Death Associated with Dysfunction of Lipid and Carbohydrate Metabolism
Bibliographic record
Abstract
Pituitary adenylate cyclase-activating polypeptide (PACAP) is a hormone belonging to the glucagon superfamily of hormones. These hormones are known to play important roles in metabolism and growth. PACAP is a neuropeptide that causes accumulation of cAMP in a number of tissues and affects the secretion of other hormones, vasodilation, neural and immune functions, as well as the cell cycle. To determine whether PACAP is essential for survival and to evaluate its function(s), we have generated mice lacking the PACAP gene via homologous recombination. We found that most PACAP null mice died in the second postnatal week in a wasted state with microvesicular fat accumulation in liver, skeletal muscle, and heart. Gas chromatography-mass spectrometry showed that fatty acid beta-oxidation in liver mitochondria of PACAP(-/-) mice was not blocked based on the distribution of 3-hydroxy-fatty acids (C6-16) in the plasma. Instead, increased metabolic flux through the beta-oxidation pathway was suggested by the presence of ketosis. Also, serum triglycerides and cholesterol were significantly higher (2- to 3-fold) in PACAP null mice than littermates. In the fed state, both serum insulin and blood glucose were normal in 5-d-old null mice compared with their littermates. In contrast, fasted PACAP null pups had a significant increase in insulin, but a decrease in blood glucose compared with littermates. Glycogen in the liver was reduced. These results suggest PACAP is a critical hormonal regulator of lipid and carbohydrate metabolism.
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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 | 0.001 |
| 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 | 0.001 |
| 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".