Alterations in basal glucose metabolism during late pregnancy in the conscious dog
Bibliographic record
Abstract
We assessed basal glucose metabolism in 16 female nonpregnant (NP) and 16 late-pregnant (P) conscious, 18-h-fasted dogs that had catheters inserted into the hepatic and portal veins and femoral artery approximately 17 days before the experiment. Pregnancy resulted in lower arterial plasma insulin (11 +/- 1 and 4 +/- 1 microU/ml in NP and P, respectively, P < 0.05), but plasma glucose (5.9 +/- 0.1 and 5.6 +/- 0.1 mg/dl in NP and P, respectively) and glucagon (39 +/- 3 and 36 +/- 2 pg/ml in NP and P, respectively) were not different. Net hepatic glucose output was greater in pregnancy (42.1 +/- 3.1 and 56.7 +/- 4.0 micromol. 100 g liver(-1).min(-1) in NP and P, respectively, P < 0.05). Total net hepatic gluconeogenic substrate uptake (lactate, alanine, glycerol, and amino acids), a close estimate of the gluconeogenic rate, was not different between the groups (20.6 +/- 2.8 and 21.2 +/- 1.8 micromol. 100 g liver(-1). min(-1) in NP and P, respectively), indicating that the increment in net hepatic glucose output resulted from an increase in the contribution of glycogenolytically derived glucose. However, total glycogenolysis was not altered in pregnancy. Ketogenesis was enhanced nearly threefold by pregnancy (6.9 +/- 1.2 and 18.2 +/- 3.4 micromol. 100 g liver(-1).min(-1) in NP and P, respectively), despite equivalent net hepatic nonesterified fatty acid uptake. Thus late pregnancy in the dog is not accompanied by changes in the absolute rates of gluconeogenesis or glycogenolysis. Rather, repartitioning of the glucose released from glycogen is responsible for the increase in hepatic glucose production.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".