A high fructose diet during pregnancy significantly affects markers of intestinal permeability in the offspring (816.2)
Bibliographic record
Abstract
Maternal diet in pregnancy has been shown to affect offspring development but few studies have examined changes in the gut. Gut barrier dysfunction may allow components of the microbiota to pass into the circulation, which has been linked to the development of obesity and the metabolic syndrome. This study examined the effect of a maternal diet that is high in fructose on gut permeability markers in pregnant offspring. Female Wistar rats were placed on 10% fructose (F1) or water (W1) at 8 weeks of age and were mated at 10 weeks; the intervention continued throughout pregnancy. Female offspring continued on the same diet as their dams (W2, n=10 and F2, n=10) from 4 weeks of age, were mated at 10 weeks, and tissue was collected at gestational day 20. Ileum and jejunum expression of occludin (OCLN), claudin 3 (CLDN3) and zonulin 1 (ZO1) were used as markers of intestinal permeability. F2 pups had a lower birth weight but similar weights at 13 weeks of age compared with W2. F2 also had a significantly higher % fat mass and reduced gut length vs W2. Expression of ZO1 (W2=1.64±0.28; F2=0.64±0.09), OCLN (W2=1.27±0.15; F2=0.51±0.09), but not CLDN3 (W2=1.09±0.19; F2=2.15±0.45) was reduced in the jejunum (p<0.05) but not different in the ileum. A high fructose diet during pregnancy increases intestinal permeability in pregnant offspring. Further studies will examine the effect of the fructose diet on the microbiome during pregnancy.
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) | 0.002 | 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".