Evidence map›Paper›PMID 42245561›Full record

ArticleFrontiers in nutrition2026

Resistant starch selectively depletes a putative pathobiont-enriched gut microbial module: evidence from multiple dietary fiber intervention cohorts.

Biao Dong, Mai Ye, Zhenjiang Zech Xu, Xiaochang Huang, Yichen Hu

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Biao DongState Key Laboratory of Food Science and Technology, Nanchang University, Nanchang, China.
Mai YeState Key Laboratory of Food Science and Technology, Nanchang University, Nanchang, China.
Zhenjiang Zech XuState Key Laboratory of Food Science and Technology, Nanchang University, Nanchang, China.
Xiaochang HuangState Key Laboratory of Food Science and Technology, Nanchang University, Nanchang, China.
Yichen HuState Key Laboratory of Food Science and Technology, Nanchang University, Nanchang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Dietary fiber, particularly resistant starch (RS), has been proposed to modulate the gut microbiota and immune microenvironment; however, individual intervention studies yield inconsistent results due to inter-study heterogeneity. This study aimed to identify reproducible gut microbiota responses to RS across multiple independent cohorts and explore the ecological basis by which RS shapes microbial community structure. Methods: Gut microbiota composition was analyzed in 586 paired fecal samples collected from healthy adults in multiple independent cohorts undergoing RS dietary interventions. All datasets were processed through a unified bioinformatics pipeline to minimize technical variability. Differential abundance analysis, co-occurrence network analysis, and validation against inflammatory bowel disease (IBD) populations were performed to identify reproducible microbial responses and assess their potential clinical relevance. Results: RS supplementation was associated a consistent reduction in alpha diversity and a reproducible, unidirectional taxonomic response: 22 specific taxa were consistently depleted across cohorts, including putative immunostimulatory pathobionts such as Conclusion: Across cohorts, RS intake was consistently associated with a selective ecological filter that consistently depletes a set of microbial taxa including putative immunostimulatory pathobionts, providing a mechanistic basis for its proposed role in dietary modulation of the gut immune microenvironment. These consistently depleted taxa may serve as candidate biomarkers to identify individuals most likely to benefit from RS-based dietary fiber interventions, while their utility for predicting individual responsiveness before intervention remains to be tested.

Indexed as

gut immune microenvironmentgut microbiotainflammatory bowel diseasemulti-cohort studyprecision nutritionresistant starch

Identifiers

PMID42245561
PMCPMC13230024

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.