Preventive effects of <scp>l</scp>-glutamine on gestational fructose-induced cardiac hypertrophy: involvement of pyruvate dehydrogenase kinase-4
Bibliographic record
Abstract
Gestational fructose exposure has detrimental health consequences on both the maternal and fetus or offspring in the early or later life, contributing to epidemic rise in cardiometabolic syndrome including cardiac events. l-Glutamine has been shown to mitigate cardiac metabolic stress. However, the effect of l-glutamine on cardiac hypertrophy induced by gestational fructose exposure is not known. We therefore hypothesized that l-glutamine would prevent gestational fructose-induced cardiac hypertrophy, possibly by suppression of pyruvate dehydrogenase kinase-4 (PDK-4). Pregnant Wistar rats were allotted into the control, l-glutamine, gestational fructose exposure, and gestational fructose exposure plus l-glutamine groups (6 rats in each group). The groups received distilled water (vehicle, per os), 1 g/kg body weight l-glutamine (per os), 10% fructose (w/v) and 10% fructose (w/v) plus 1 g/kg l-glutamine (per os), respectively, daily for 19 days. Data from this study showed that gestational fructose-enriched drink caused cardiac hypertrophy with correspondent body weight gain, glucose dysregulation, increased cardiac PDK-4, triglyceride, glycogen, lactate, and uric acid production. On the other hand, defective glutathione-dependent antioxidant barrier was also observed in pregnant rats taking fructose-enriched drink. However, the gestational fructose-induced cardiac hypertrophy and its correlates were attenuated by l-glutamine. The present results demonstrate that gestational fructose-enriched drink induces cardiac hypertrophy that is accompanied by increased PDK-4. The findings also suggest that the inhibitory effect of l-glutamine on PDK-4 prevents the development of cardiac hypertrophy, thereby implying that PDK-4 may be a potential novel therapeutic intervention for cardiac hypertrophy especially in pregnancy.
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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) | 0.001 | 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".