The kidney is resistant to chronic hypoglycaemia in late-gestation fetal sheep
Bibliographic record
Abstract
We imposed a sustained reduction in glucose supply to late-gestation fetal sheep to see whether the reduction in glucose and insulin levels affected renal growth, renin expression and synthesis, and renal function. Maternal glucose concentrations were lowered to 1.7-1.9 mmol/L for 12-13 days by i.v. insulin infusion (n = 9, 121 days gestation, term = 150 days). Control ewes (n = 7) received vehicle. Maternal and fetal glucose concentrations were 40% and 31% lower than in controls (p < 0.001), respectively. Fetal plasma insulin levels fell 36% +/- 7% by day 7 (p < 0.05); IGF-I levels were unchanged. Arterial PO2 and pH increased and PCO2 fell (p < 0.05). Renal function was largely unaffected. Longitudinal growth was 28% slower and spleen weights were 36% smaller (p < 0.05); body and kidney weights were not affected. Renal renin levels and renin, angiotensinogen, and angiotensin receptor mRNA levels were similar to those of controls. Plasma renin levels increased from 2.1 +/- 0.6 to 7.6 +/- 2.8 ng angiotensin I.mL-1.h-1 (p = 0.01). Thus reductions in fetal glucose and insulin levels in late gestation that were sufficient to retard skeletal growth had no effect on kidney growth or function or the renal renin-angiotensin system, possibly because IGF-I levels were not reduced. There was, however, increased activity of the circulating renin-angiotensin system similar to that seen during insulin-induced hypoglycaemia.
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 | 0.001 |
| 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) | 0.000 | 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".