Sex-specific effects of low protein diet on <i>in utero</i> programming of renal G-protein coupled receptors
Bibliographic record
Abstract
Intrauterine growth restriction (IUGR) is an important risk factor for development of hypertension, diabetes and the metabolic syndrome. Maternal low protein (LP) intake during rat pregnancy leads to IUGR in male and female offspring, although females may be resistant to the development of effect. Current evidence suggests that changes in the renin-angiotensin system (RAS) in utero contribute to this programmed hypertension, via sex-specific mechanisms. The previously orphaned G-protein coupled receptor (GPR91) was identified as a central player in the development of hypertension in adult mice, through a RAS-dependent pathway. However, whether the GPR91 pathway contributes to fetal programming is unknown. Furthermore, the nature of involvement of downstream modulators of the RAS including Gqα/11α and GαS has not been investigated in IUGR-LP rats. Therefore, we postulated that renal GPR91, in conjunction with RAS, is differentially impacted in a sex-specific manner from LP-induced IUGR rats. Pregnant Wistar rats were fed control (C, 20% protein) or LP (8% protein) diet until embryonic day 19 (E19) or postnatal d21. At E19, GPR91 protein and mRNA were increased in both male and female LP kidneys (P<0.05), whereas renin and angiotensin converting enzyme (ACE) were only increased in males (P=0.06 and P<0.05, respectively). On d21, AT1R and Gqα/11α were increased in LP males, while in LP females, AT2R protein was elevated and renin expression was decreased (P<0.05). This study demonstrates that in IUGR-LP rats, up regulation of GPR91 in fetal kidney is mirrored by increased ACE and renin in males. These in utero alterations, when combined with postnatal increases in AT1R-Gqα/11α specifically in male offspring, may predispose to the development of hypertension.
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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 | 0.000 | 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) | 0.002 | 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".