Adaptation to tolerate high doses of arabinoxylan is associated with fecal levels of <i>Bifidobacterium longum</i>
Bibliographic record
Abstract
Dietary fiber supplements are a strategy to close the ‘fiber gap’ and induce targeted modulations of the gut microbiota. However, higher doses of fiber supplements cause gastrointestinal (GI) symptoms that differ among individuals. What determines these inter-individual differences is insufficiently understood. Here we analyzed findings from a six-week randomized controlled trial that evaluated GI symptoms to corn bran arabinoxylan (AX; n = 15) relative to non-fermentable microcrystalline cellulose (MCC; n = 16) at efficacious supplement doses of 25 g/day (females) or 35 g/day (males) in adults with excess weight. Self-reported flatulence, bloating, and stomach aches were evaluated weekly. Bacterial taxa involved in AX fermentation were identified by bioorthogonal non-canonical amino acid tagging. Associations between GI symptoms, fecal microbiota features, and diet history were systematically investigated. AX supplementation increased symptoms during the first three weeks relative to MCC (p < 0.05, Mann-Whitney tests), but subjects ‘adapted’ with symptoms reverting to baseline levels toward the end of treatment. Symptom adaptations were individualized and correlated with the relative abundance of Bifidobacterium longum at baseline (rs = 0.74, p = 0.002), within the bacterial community that utilized AX (rs = 0.69, p = 0.006), and AX-induced shifts in acetate (rs = 0.54, p = 0.039). Lower baseline consumption of animal-based foods and higher whole grains associated with less severity and better adaptation. These findings suggest that humans do ‘adapt’ to tolerate efficacious fiber doses, and this process is linked to their microbiome and dietary factors known to interact with gut microbes, providing a basis for the development of strategies for improved tolerance of dietary fibers.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".