Cited by 535Probiotics and Fermented FoodsGut microbiota and healthAnimal Nutrition and Physiology

The DOI matches its Crossref record; 106 of the 106 references it cites were found in a registry or an index; none of the 75 sources its claims cite is checked for support yet.

Probiotics Regulate Gut Microbiota: An Effective Method to Improve Immunity

Open access
Wang, Xinzhou, Zhang, Peng, Zhang, Xin·2021·Molecules

Abstract

Probiotics are beneficial active microorganisms that colonize the human intestines and change the composition of the flora in particular parts of the host. Recently, the use of probiotics to regulate intestinal flora to improve host immunity has received widespread attention. Recent evidence has shown that probiotics play significant roles in gut microbiota composition, which can inhibit the colonization of pathogenic bacteria in the intestine, help the host build a healthy intestinal mucosa protective layer, and enhance the host immune system. Based on the close relationship between the gut microbiota and human immunity, it has become an extremely effective way to improve human immunity by regulating the gut microbiome with probiotics. In this review, we discussed the influence of probiotics on the gut microbiota and human immunity, and the relationship between immunity, probiotics, gut microbiota, and life quality. We further emphasized the regulation of gut microflora through probiotics, thereby enhancing human immunity and improving people’s lives.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This narrative review argues that probiotics regulate gut microbiota composition and thereby improve host immunity through barrier maintenance, pathogen inhibition, and immune modulation. It also links gut microbiota and probiotics to obesity, sleep, and skin conditions as examples of immunity-related quality-of-life outcomes.

Key findings

  • Probiotics can shift gut microbiota composition: in obese animals, probiotic treatment decreased Firmicutes and increased Actinobacteria, and probiotic-treated mice showed increased beneficial bacteria such as Oscillibacter and Prevotella and increased short-chain fatty acid concentrations.
  • Probiotics support the epithelial barrier and inhibit pathogens: examples include *L. plantarum* BMCM12 extracellular proteins weakening pathogen adhesion, VSL#3 or *L. rhamnosus* GG maintaining epithelial barrier integrity, probiotic *E. coli* Nissle 1917 secreting DegP to inhibit enterohemorrhagic *E. coli*, and *Bacillus* isolates inhibiting *S. aureus* colonization via Agr signaling interference.
  • Gut microbiota is required for normal immune development: germ-free mice had significantly lower ovalbumin-specific antibody titers than untreated controls, absent mucous layer, altered IgA secretion, and defective gut-associated lymphoid tissue development.
  • The review reports links between immunity, sleep, and microbiota: after influenza vaccination, subjects sleeping 8 h/day had twice the influenza virus-specific antibody concentration measured 10 days after vaccination compared with subjects sleeping 4 h/day; sleep fragmentation decreased gut microbiota diversity, while *Lactobacillus casei* strain Shirota improved sleep duration and quality.

Methods

  • Narrative review of existing literature on probiotics, gut microbiota, and immunity; no primary experiments or systematic review protocol are described.
  • Synthesizes animal and human studies, including germ-free mouse models, probiotic supplementation trials, vaccination studies, and disease examples such as allergy, colorectal cancer, depression, obesity, sleep, and skin disorders.
  • Main analysis is qualitative: mechanisms and disease associations are discussed without meta-analysis or quantitative pooling.

Limitations

  • The paper does not state limitations.
  • Evident from the text: as a narrative review, it lacks systematic search and inclusion criteria, risk-of-bias assessment, and meta-analysis.
  • Many cited findings come from animal models or associative human studies, and the review does not report primary sample sizes or effect estimates for most claims.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.3390/molecules26196076

Cites

106 of 106 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

0 of 75 cited sources checked · 0 supported · 0 flagged

Show all 77 claims

  • It may state two separate claims as one. 17
  • Probably not a substantial claim. 4
20 of 20
  • The paper relies on this without support.

    Findings from animal models and in vitro studies about probiotics, gut microbiota, and immunity can be extrapolated to humans.

    “Based on the close relationship between the gut microbiota and human immunity, it has become an extremely effective way to improve human immunity by regulating the gut microbiome with probiotics.”
  • The paper relies on this without support.

    Effects of specific probiotic strains studied can be generalized to probiotics as a class.

    “In general, probiotics are considered to be dietary factors that can influence the human gut microbiota and also have a regulatory effect on the composition and structure of the intestinal flora.”
2 of 2

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Citation [101] is attributed to Scher et al.

    Minor

    The text names Scher et al. as the authors of reference 101, which instead lists Myers et al.

  • Citation [102] is attributed to Masallat et al.

    Minor

    The text attributes reference 102 to Masallat et al., but the listed reference is by Yan et al.

  • Opposite Actinobacteria findings are described as the same result

    Minor

    The text first says Actinobacteria increased significantly in patients with psoriasis, then calls a finding that Actinobacteria were less abundant in patients than in healthy controls "the same results."

  • Citation [26] is attributed to a different author

    Minor

    The text attributes citation [26] to Caballero-Franco et al., but reference 26 lists Monteagudo-Mera et al.

4 of 4

Citations

Cites

Flagged first, then by citations

Show all 106 references

Cited by

Sorted by citations

Items 101–200 of 535

Metadata

Authors
Wang, X., Zhang, P., & Zhang, X.
Affiliations
  • Department of Food Science and Engineering, Ningbo University, Ningbo 315211, China
  • Xinyang Normal University (CN)
  • Ningbo University (CN)
Corresponding author
  • Zhang, Peng
  • Zhang, Xin
Venue
Molecules
Publisher
MDPI AG
Published
2021-10-08
Volume
26
Issue
19
Pages
6076
ISSN
1420-3049 (ISSN-L)
OpenAlex
W3204396902
Cited by
529
References
106
Citations by year
2026: 87 · 2025: 170 · 2024: 162 · 2023: 75 · 2022: 35
FWCI
6.36
Type
journal article
Language
en
Open access
Locations
  • Molecules (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
the Key Research and development program of Zhejiang Province (2018C02023)
Topics
  • Life Sciences › Agricultural and Biological Sciences › Food Science › Probiotics and Fermented Foods
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Animal Nutrition and Physiology
Keywords
probiotics, gut microbiota, host immunity, quality of life
MeSH terms
Gastrointestinal Microbiome, Bacteria, Humans, Immune System, Probiotics

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

A language model drew the claims from the paper on 2026-10-09, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).

A second model labelled each claim on 2026-10-09 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review