Evidence map›Paper›PMID 35694540›Full record

ArticleFrontiers in cellular and infection microbiology2022

Gut Microbiota Dysbiosis in BK Polyomavirus-Infected Renal Transplant Recipients: A Case-Control Study.

Jian Zhang, Hao Qin, Mingyu Chang, Yang Yang, Jun Lin

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 42% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

5 authors at 2 institutions in 1 country.

Jian ZhangDepartment of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Hao QinDepartment of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Mingyu ChangDepartment of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Yang YangDepartment of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Jun LinDepartment of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Capital Medical University · CNBeijing Friendship Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: BK polyomavirus infection results in renal allograft dysfunction, and it is important to find methods of prediction and treatment. As a regulator of host immunity, changes in the gut microbiota are associated with a variety of infections. However, the correlation between microbiota dysbiosis and posttransplant BK polyomavirus infection was rarely studied. Thus, this study aimed to characterize the gut microbiota in BK polyomavirus-infected renal transplant recipients in order to explore the biomarkers that might be potential therapeutic targets and establish a prediction model for posttransplant BK polyomavirus infection based on the gut microbiota. Methods: We compared the gut microbial communities of 25 BK polyomavirus-infected renal transplant recipients with 23 characteristic-matched controls, applying the 16S ribosomal RNA gene amplicon sequencing technique. Results: At the phylum level, Conclusions: BK polyomavirus-infected patients had gut microbiota dysbiosis in which the

Indexed as

BK VirusGastrointestinal MicrobiomeKidney TransplantationPolyomavirus InfectionsBiomarkersCase-Control StudiesDysbiosisHumansBiomarkersBK polyomavirusgut microbiotainfectionmicrobial dysbiosisrenal transplantation

Identifiers

PMID35694540
PMCPMC9186314
OpenAlexW4282014394

What OpenQuestion holds

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LicenceCC BY
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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.