Exposure of the Pregnant Rat to Low Protein Diet Causes Impaired Glucose Homeostasis in the Young Adult Offspring by Different Mechanisms in Males and Females
Bibliographic record
Abstract
The understanding of the mechanisms by which gender dimorphisms are involved in the modulation of insulin sensitivity and glucose tolerance can be crucial to unravel the development of type 2 diabetes. Rats treated with a low protein diet (LP, 8% protein content) during pregnancy and lactation have a reduced beta-cell mass at birth and a reduced insulin secretion at weaning. In this study we examined the effect of LP diet on glucose homeostasis from birth to adulthood when offspring previously exposed to LP were subsequently switched to control diet (C, 20% protein content) at weaning. The LP group had a reduced body weight after weaning compared to the C-fed rats, although their food intake was not significantly different. Furthermore, LP males had a significant increase in visceral adiposity relative to their body weight (P < 0.05). Intraperitoneal glucose tolerance test (IGTT) showed that glucose clearance was unchanged until 130 days of age when LP-fed females showed elevated blood glucose compared to C, despite similar plasma insulin levels. Females also demonstrated a significant reduction in mean pancreatic islet number, individual islet size and beta cell mass. However, no differences in IGTT or islet morphometry were observed in LP males, although basal insulin levels were twofold higher. Akt phosphorylation in response to insulin was reduced in adipose and skeletal muscle of adult rats following exposure to LP diet in early life when compared to control-fed animals, but this was only apparent in males. Plasma testosterone levels were also reduced in males at 130 days age. These data suggest that the development of impaired glucose homeostasis in offspring of LP-fed rats is likely to occur by different mechanisms in males and females.
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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 | 0.001 | 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 | 0.001 |
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".