Prebiotic fiber diet does not improve offspring ‘leaky gut’ from maternal low protein diet
Bibliographic record
Abstract
Metabolic endotoxemia can initiate obesity and insulin resistance. Prebiotic fiber can reduce metabolic endotoxemia and intestinal permeability as measured by plasma lipopolysaccharide (LPS). Offspring of rats fed a low protein diet during pregnancy are at high risk of obesity which may be related to increased intestinal permeability. Our objective was to determine if prebiotic fiber minimized this effect. Virgin Wistar dams received AIN‐93G (normal protein, NP) or a low protein (LP) diet (7% wt/wt) during pregnancy. Female offspring were weaned onto control or a high prebiotic fiber diet (21% wt/wt 1:1 oligofructose and inulin) (HF). Body composition was analyzed along with plasma LPS concentrations at 24 wk of age. Gene expression in the colon was analyzed for tight junction protein‐1 (TJP‐1). There was no difference in overall body weight but lean mass was greater in offspring consuming HF (P=0.013). HF was associated with higher plasma LPS in LP‐exposed versus NP‐exposed offspring (P=0.009). TJP1 mRNA levels were higher in NP‐exposed offspring whether consuming C or HF (P=0.05). A maternal diet low in protein is associated with a ‘leaky gut’ in female offspring which has the potential for negative metabolic effects. Contrary to adult obesity, HF was not able to correct metabolic endotoxemia in female offspring of LP dams.
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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) | 0.003 | 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".