Carotid body afferent activity stimulation by PACAP is mediated through PKC pathway
Bibliographic record
Abstract
Pituitary adenylate cyclase‐activating polypeptide (PACAP) but not vasoactive intestinal peptide (VIP) injected into the common carotid artery stimulates ventilation, suggesting activation of PAC1 receptors within the primary peripheral respiratory chemoreceptor, the carotid body (CB). Possible biochemical pathways downstream of the PAC1 receptor include G‐proteins activation of (a) PLC which stimulates protein kinase C (PKC) and (b) cAMP which stimulates protein kinase A (PKA). Here we elucidate the relative importance of PKC and PKA in mediating PACAP's effects on carotid sinus nerve activity. We used an ex‐vivo artificially – perfused rat CB preparation and measured integrated CSN activity during normoxia (PO 2 ≃ 100 Torr/PCO 2 ≃ 35 Torr) and tested effects of PACAP 1–38 (100 nM) alone and against a background of : (a) PKC inhibitors – GF 109203X (GF;10 μM) and Chelerythrine chloride (CC;20 μM) and (b) PKA inhibitor – H89 (10 μM). We demonstrate PACAP stimulates CSN activity in a biphasic manner, with an initial transient stimulatory phase, followed by a steady‐state phase. PKC inhibitors, GF and CC (n=6) reduced both peak and steady state PACAP responses by over 50%. The PKA inhibitor H89 had no effect on the transient phase but reduced the steady state by 17%. In conclusion, PACAP induced stimulation of CSN activity is mediated primarily through a PLC‐IP 3 ‐ PKC, not a cAMP‐PKA pathway.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".