Evidence map›Paper›PMID 38435094›Full record

ArticleFrontiers in nutrition2024

Personalized probiotic strategy considering bowel habits: impacts on gut microbiota composition and alleviation of gastrointestinal symptoms via Consti-Biome and Sensi-Biome.

Uigi Min, Yoo-Jeong Jin, You Jin Jang, Jonghyun Lim, Byung-Yong Kim

Open access · goldAbstract read
In one paragraph

Article in Frontiers in nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
4.0field-weighted citation impact, top 6% of its field
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

17 citing papers in PubMed, 17 citations in OpenAlex.

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  14. Engineered Tissue Models to Decode Host-Microbiota Interactions.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
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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

5 authors at 1 institution in 1 country.

Uigi MinR&D Center, Chong Kun Dang Healthcare, Seoul, Republic of Korea.
Yoo-Jeong JinR&D Center, Chong Kun Dang Healthcare, Seoul, Republic of Korea.
You Jin JangR&D Center, Chong Kun Dang Healthcare, Seoul, Republic of Korea.
Jonghyun LimR&D Center, Chong Kun Dang Healthcare, Seoul, Republic of Korea.
Byung-Yong KimR&D Center, Chong Kun Dang Healthcare, Seoul, Republic of Korea.
Chong Kun Dang Bio (South Korea) · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Personalized probiotic regimens, taking into account individual characteristics such as stool patterns, have the potential to alleviate gastrointestinal disorders and improve gut health while avoiding the variability exhibited among individuals by conventional probiotics. This study aimed to explore the efficacy of personalized probiotic interventions in managing distinct stool patterns (constipation and diarrhea) by investigating their impact on the gut microbiome and gastrointestinal symptoms using a prospective, randomized, double-blind, placebo-controlled clinical trial design. This research leverages the multi-strain probiotic formulas, Consti-Biome and Sensi-Biome, which have previously demonstrated efficacy in alleviating constipation and diarrhea symptoms, respectively. Improvement in clinical symptoms improvement and compositional changes in the gut microbiome were analyzed in participants with predominant constipation or diarrhea symptoms. Results indicate that tailored probiotics could improve constipation and diarrhea by promoting

Indexed as

constipationdiarrheafunctional gastrointestinal disordergut microbiomemicrobiome diversitypersonalized probioticsprobioticsstool consistency

Identifiers

PMID38435094
PMCPMC10904615
OpenAlexW4391880052

What OpenQuestion 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 OpenQuestion graph.