Sex-Specific Differences in the Gut Microbiome in Response to Dietary Fiber Supplementation in IL-10-Deficient Mice
Bibliographic record
Abstract
There is growing interest in studying dietary fiber to stimulate microbiome changes that might prevent or alleviate inflammatory bowel disease (IBD). However, dietary fiber effects have shown varying degrees of efficacy, for reasons that are unclear. This study examined whether the effects of isomaltodextrin on gut microbiota and IBD were dependent on dose or host sex, using an Interleukin (IL)-10 deficient murine colitis model. After 12 weeks, colonic IL-12p70 was depressed in male mice receiving high-dose isomaltodextrin supplementation compared to the control group (p = 0.04). Male mice receiving high-dose isomaltodextrin exhibited changes in microbial alpha-diversity, including enhanced richness and evenness (p = 0.01) and limited reduction in the relative abundance of Coprococcus (q = 0.08), compared to the control group. These microbial compositional changes were negatively associated with IL-12p70 levels in the male group (rs ≤ −0.51, q ≤ 0.08). In contrast, female mice receiving isomaltodextrin displayed a reduction in alpha-diversity and Coprococcus abundance and a high level of IL-12p70, as did the control group. Together, these results indicate that isomaltodextrin altered the gut microbial composition linking specific immune-regulatory cytokine responses, while the interactions among fiber, microbiota and immune response were dose dependent and largely sex specific. The results further indicate that interactions between environmental and host factors can affect microbiome manipulation in the host.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".