Evidence map›Paper›PMID 35291562›Full record

ArticleOpen life sciences2022

Informatic analysis of the pulmonary microecology in non-cystic fibrosis bronchiectasis at three different stages.

Yuchao Wang, Ying Chen, Chao Wu, Xiaohong Yang

Open access · goldAbstract read
In one paragraph

Article in Open life sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 54% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. The presence of cystic fibrosis-related diabetes modifies the sputum microbiome in cystic fibrosis disease.American journal of physiology. Lung cellular and molecular physiology · 2024
    Article
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

4 authors at 2 institutions in 1 country.

Yuchao WangGraduate School, Xinjiang Medical University, 830001 Urumqi, China.
Ying ChenDepartment of Respiratory and Critical Care Medicine, People's Hospital of Xinjiang Uygur Autonomous Region, No. 91 Tianchi Road, Tianshan District, Urumqi 830001, China.
Chao WuDepartment of Respiratory and Critical Care Medicine, People's Hospital of Xinjiang Uygur Autonomous Region, No. 91 Tianchi Road, Tianshan District, Urumqi 830001, China.
Xiaohong YangDepartment of Respiratory and Critical Care Medicine, People's Hospital of Xinjiang Uygur Autonomous Region, No. 91 Tianchi Road, Tianshan District, Urumqi 830001, China.
People's Hospital of Xinjiang Uygur Autonomous Region · CNXinjiang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study explored the impact of pulmonary microecological changes on disease progression in non-cystic fibrosis bronchiectasis (nCFB). A careful search of the NCBI BioProject database revealed the 16S rRNA-based microbiological testing results of 441 pulmonary sputum samples from patients in the relatively stable (baseline), acute exacerbation, or recovery stage. After preliminary analysis and screening, we selected 152 samples for further analyses, including determination of the operational taxonomic unit (OTU) distribution at the phylum, class, order, family and genus levels, community structure, alpha diversity, beta diversity, microbial multivariables, correlations, and community structure after the abundances of intragroup samples were averaged. The recovery group showed significant differences in pulmonary microbiological changes (

Indexed as

genome sequencinginformaticsnetwork datasetnon-cystic fibrosis bronchiectasispulmonary microecology

Identifiers

PMID35291562
PMCPMC8886608
OpenAlexW4214886572

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.