Long-term effects of a maternal high-fat: high-fructose diet on offspring growth and metabolism and impact of maternal taurine supplementation
Bibliographic record
Abstract
OBJECTIVE: Maternal obesity is associated with obesity and metabolic disorders in offspring. However, there remains a paucity of data on strategies to reverse the effects of maternal obesity on maternal and offspring health. With maternal undernutrition, taurine supplementation improves outcomes in offspring mediated in part via improved glucose-insulin homeostasis. The efficacy of taurine supplementation in the setting of maternal obesity on health and well-being of offspring is unknown. We examined the effects of taurine supplementation on outcomes related to growth and metabolism in offspring in a rat model of maternal obesity. DESIGN: Wistar rats were randomised to: 1) control diet during pregnancy and lactation (CON); 2) CON with 1.5% taurine in drinking water (CT); 3) maternal obesogenic diet (MO); or 4) MO with taurine (MOT). Offspring were weaned onto the control diet for the remainder of the study. RESULTS: At day 150, offspring body weights and adipose tissue weights were increased in MO groups compared to CON. Adipose tissue weights were reduced in MOT versus MO males but not females. Plasma fasting leptin and insulin were increased in MO offspring groups but were not altered by maternal taurine supplementation. Plasma homocysteine concentrations were reduced in all maternal taurine-supplemented offspring groups. There were significant interactions across maternal diet, taurine supplementation and sex for response to an oral glucose tolerance test , a high-fat dietary preference test and pubertal onset in offspring. CONCLUSIONS: These results demonstrate that maternal taurine supplementation can partially ameliorate adverse developmental programming effects in offspring in a sex-specific manner.
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 | 0.000 |
| 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".