Evidence map›Paper›PMID 35493445›Full record

ReviewFrontiers in immunology2022

miRNAs Can Affect Intestinal Epithelial Barrier in Inflammatory Bowel Disease.

Xiangjun Xiao, Xiangbing Mao, Daiwen Chen, Bing Yu, Jun He, Hui Yan, Jianping Wang

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 7% 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

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.

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  16. The Role of microRNAs in Inflammatory Bowel Disease.International journal of molecular sciences · 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

7 authors at 2 institutions in 1 country.

Xiangjun XiaoInstitute of Animal Nutrition, Sichuan Agricultural University, Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Key Laboratory of Animal Disease-Resistant Nutrition and Feed of China Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Disease-Resistant Nutrition of Sichuan Province, Chengdu, China.
Xiangbing MaoInstitute of Animal Nutrition, Sichuan Agricultural University, Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Key Laboratory of Animal Disease-Resistant Nutrition and Feed of China Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Disease-Resistant Nutrition of Sichuan Province, Chengdu, China.
Daiwen ChenInstitute of Animal Nutrition, Sichuan Agricultural University, Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Key Laboratory of Animal Disease-Resistant Nutrition and Feed of China Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Disease-Resistant Nutrition of Sichuan Province, Chengdu, China.
Bing YuInstitute of Animal Nutrition, Sichuan Agricultural University, Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Key Laboratory of Animal Disease-Resistant Nutrition and Feed of China Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Disease-Resistant Nutrition of Sichuan Province, Chengdu, China.
Jun HeInstitute of Animal Nutrition, Sichuan Agricultural University, Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Key Laboratory of Animal Disease-Resistant Nutrition and Feed of China Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Disease-Resistant Nutrition of Sichuan Province, Chengdu, China.
Hui YanInstitute of Animal Nutrition, Sichuan Agricultural University, Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Key Laboratory of Animal Disease-Resistant Nutrition and Feed of China Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Disease-Resistant Nutrition of Sichuan Province, Chengdu, China.
Jianping WangInstitute of Animal Nutrition, Sichuan Agricultural University, Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Key Laboratory of Animal Disease-Resistant Nutrition and Feed of China Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Disease-Resistant Nutrition of Sichuan Province, Chengdu, China.
Ministry of Agriculture and Rural Affairs · CNSichuan Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The most obvious pathological characterization of inflammatory bowel disease (IBD) is intestinal epithelium erosion and severe inflammation invasion. Micro-ribonucleic acids (miRNA or microRNA), single-stranded noncoding RNAs of ~22 nucleotides, have been considered as the potential therapeutic targets in the pathogenesis of IBD. Many previous studies have focused on the mechanisms that miRNAs use to regulate inflammation, immunity, and microorganisms in IBD. The review highlights in detail the findings of miRNAs in the intestinal epithelial barrier of IBD, and focuses on their gene targets, signaling pathways associated with IBD, and some potential therapies. It will be beneficial for the elucidation of the interaction between miRNAs and the intestinal epithelial barrier in IBD and provide a theoretical reference for preventing and treating IBD in the future.

Indexed as

Inflammatory Bowel DiseasesMicroRNAsHumansInflammationIntestinal MucosaIntestinesMicroRNAsgene targetsinflammatory bowel diseaseintestinal epithelial barriermiRNAsignaling pathways

Identifiers

PMID35493445
PMCPMC9043318
OpenAlexW4223645914

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.