Effects of glucagon on in vitro liquid production by lungs from fetal guinea pigs
Bibliographic record
Abstract
BACKGROUND: Lung liquid reabsorption in newborns with respiratory distress syndrome can be deficient. Respiratory distress syndrome is often seen in infants of diabetic mothers, in whom the neonatal surge of glucagon is suppressed. AIM: To investigate the possible effects of glucagon on lung liquid reabsorption. METHODS: Lungs from near term fetal guinea pigs (62 (2) days gestation; term = 67 days) were supported in vitro for three hours; lung liquid production and reabsorption were monitored by a dye dilution method. RESULTS: Untreated control preparations produced fluid at 1.75 (0.33) ml/h per kg body weight, and did not change significantly in three hours; those immersed in 10(-12) M glucagon during the middle hour showed no significant change, but those given higher concentrations all showed significant reductions in fluid production or even reabsorption (65.6 (10.3)% fall at 10(-11) M, 70.0 (6.3)% fall at 10(-10) M, and 90.6 (11.1)% fall at 10(-9) M; based on 54 preparations). At 10(-9) M glucagon, 12 out of 30 preparations reabsorbed fluid. The linear log dose-response curve (r(2) = 0.94) gave a theoretical threshold at 4 x 10(-15) M glucagon. Responses appeared to involve the amiloride sensitive Na(+) based reabsorptive system: responses to 10(-9) M glucagon appeared to be reduced by 10(-6) M amiloride, and were abolished by 10(-5) M amiloride (based on 72 preparations). CONCLUSIONS: The results suggest that the surge of glucagon at birth may help to drain the lungs of fluid. As glucagon liberates cAMP, which also stimulates surfactant, glucagon is worth consideration for possible use in neonatal respiratory distress.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".