Evidence map›Paper›PMID 39796573›Full record

Trial reportNutrients2024

Association of Mucin-Degrading Gut Microbiota and Dietary Patterns with Colonic Transit Time in Constipation: A Secondary Analysis of a Randomized Clinical Trial.

Xuangao Wu, Hee-Jong Yang, Myeong-Seon Ryu, Su-Jin Jung, Kwangsu Ha, Do-Yeon Jeong, Sunmin Park

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Nutrients, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Review
  7. Safety evaluation ofToxicology reports · 2025
    Article
  8. Article
  9. Extraction of Active Compounds fromMaterials (Basel, Switzerland) · 2025
    Article
  10. Article
  11. Frontiers in microbiology · 2025
    Article
  12. Article
  13. Insomnia and intestinal microbiota: a narrative review.Sleep & breathing = Schlaf & Atmung · 2024
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Xuangao WuDepartment of Bioconvergence, Hoseo University, 165 Sechul-Ri, BaeBang-Yup, Asan 31499, ChungNam-do, Republic of Korea.ORCID 0000-0002-6293-7363
Hee-Jong YangDepartment of R&D, Microbial Institute for Fermentation Industry, 61-27 Minsokmaeul-gil, Sunchang-gun 56048, Republic of Korea.ORCID 0000-0002-7061-0782
Myeong-Seon RyuDepartment of R&D, Microbial Institute for Fermentation Industry, 61-27 Minsokmaeul-gil, Sunchang-gun 56048, Republic of Korea.ORCID 0000-0002-5164-4995
Su-Jin JungResearch Institute of Clinical Medicine, Jeonbuk National University, Jeonju 54907, Republic of Korea.ORCID 0000-0003-1103-7477
Kwangsu HaDepartment of R&D, Microbial Institute for Fermentation Industry, 61-27 Minsokmaeul-gil, Sunchang-gun 56048, Republic of Korea.
Do-Yeon JeongDepartment of R&D, Microbial Institute for Fermentation Industry, 61-27 Minsokmaeul-gil, Sunchang-gun 56048, Republic of Korea.
Sunmin ParkDepartment of Bioconvergence, Hoseo University, 165 Sechul-Ri, BaeBang-Yup, Asan 31499, ChungNam-do, Republic of Korea.ORCID 0000-0002-6092-8340

Funding

This work was supported by "functional research of fermented soybean food (safety monitoring)" under the Ministry of Agriculture, Food and Rural Affairs and partly Korea Agro-Fisheries and Food trade corporation. 2023-3
6 · The paper itself

Abstract

backgroundThe relationship between gut microbiota composition, lifestyles, and colonic transit time (CTT) remains poorly understood. This study investigated associations among gut microbiota profiles, diet, lifestyles, and CTT in individuals with subjective constipation.

methodsWe conducted a secondary analysis of data from our randomized clinical trial, examining gut microbiota composition, CTT, and dietary intake in baseline and final assessments of 94 participants with subjective constipation. Participants were categorized into normal-transit (<36 h) and slow-transit (≥36 h) groups based on CTT at baseline. Gut microbiota composition was measured using 16S rRNA sequencing, and dietary patterns were assessed through semi-quantitative food frequency questionnaires. Enterotype analysis, machine learning approaches, and metabolic modeling were employed to investigate microbiota-diet interactions. The constipated participants primarily belonged to Lachnospiraceae (ET-L).

resultsThe slow-transit group showed higher alpha diversity than the normal-transit group.

conclusionThese findings suggest dietary modulation of these bacterial populations as a potential therapeutic strategy for constipation. Moreover, our results reveal a potential immunometabolic mechanism where mucin-degrading bacteria and their metabolic interactions may influence intestinal transit, mucosal barrier function, and immune response.

Indexed as

ColonConstipationDietGastrointestinal MicrobiomeGastrointestinal TransitMucinsAdultBacteriaFemaleHumansMaleMiddle AgedRNA, Ribosomal, 16SSecondary Data AnalysisMucinsRNA, Ribosomal, 16Scolonic transit timeenterotypesfermented beansmucin-degrading bacteriasubjective constipation

Identifiers

PMID39796573
PMCPMC11722837

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.