Pituitary adenylate cyclase-activating peptide and lung-liquid reabsorption in vitro by lungs from fetal guinea-pigs
Bibliographic record
Abstract
Pituitary adenylate cyclase-activating peptide (PACAP) is present in the lungs, notably in their internal neuroendocrine system; however, its use is not clear. It was investigated for its possible ability to cause lung-liquid reabsorption around birth. Lungs from 31 late-term fetal guinea-pigs (at 60 ± 2 days of gestation) were supported in vitro for 3 h; lung-liquid movements were monitored by a dye-dilution method. Untreated control preparations (n = 9) produced fluid at 1.85 ± 0.40 mL·kg1 body mass·h1 (mean ± SD), with no significant change (ANOVA, regression analysis). Those given 108 M PACAP in the middle hour turned to reabsorption (n = 3) or reduced production markedly (n = 3) (average fall 84.4 ± 5.4%; significant at P < 0.0010.0005); effects continued and increased after the PACAP was removed. Preparations given 109 M PACAP reacted similarly, but there was partial recovery after treatment (five reabsorbed, four reduced production; average fall 91.4 ± 14.3%; significant at P < 0.010.0005). Preparations given 1010 M PACAP all reduced production, with partial recovery (average fall 43.5 ± 8.2%; significant at P < 0.0050.0005). Preparations given 1011 M PACAP showed little or no effect. The linear log doseresponse curve became maximal at 109 M (r2 = 0.98; theoretical threshold 1013 M). The results increase the likelihood that the neuroendocrine system is important in lung-liquid reabsorption, and suggest that PACAP could combine its relaxation of airways with lung-liquid removal, and therefore aid the first attempts of the newborn to breathe.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".