Pituitary adenylate cyclase-activating polypeptide drives cardiorespiratory responses to heat stress in neonatal mice
Bibliographic record
Abstract
The neuropeptide pituitary adenylate cyclase-activating polypeptide (PACAP) has emerged as a principal and rate-limiting regulator of physiological stress responses in adult rodents and has been implicated in sudden infant death syndrome (SIDS). Recent studies show that PACAP plays a role in neonatal cardiorespiratory responses to hypoxia, hypercapnia, and hypothermia, but not hyperthermia, which is often associated with SIDS. Here we tested the hypothesis that, consistent with a role in SIDS, PACAP is involved in regulating the neonatal cardiorespiratory responses to severe heat. To address this, we used head-out plethysmography and surface ECG electrodes to study the cardiorespiratory physiology of conscious neonatal PACAP-null and wild-type mice at ambient temperatures of 32°C (baseline) and 40°C (heat stress). We also assessed body surface temperature as an indicator of cutaneous heat loss. Our results show that wild-type neonatal mice respond to heat stress by increasing ventilation ( P = 0.007) and associated expired CO2( P = 0.041), heart rate ( P < 0.001), and cutaneous heat loss ( P < 0.001). In PACAP-null neonates, this heat response is impaired, as indicated by a decrease in ventilation ( P = 0.04) and associated expired CO2( P = 0.006) and a blunted increase in heart rate ( P = 0.001) and cutaneous heat loss ( P = 0.0002). In addition, heart rate variability at baseline was lower in PACAP-null neonates than wild-type controls ( P < 0.01). These results suggest that, during heat stress, PACAP is important for neonatal cardiorespiratory responses that help regulate body temperature. Abnormal PACAP regulation could, therefore, contribute to neonatal disorders in which the autonomic response to stress is impaired, such as SIDS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".