Evidence map›Paper›PMID 42495145›Full record

ArticleFrontiers in microbiology2026

Distribution patterns and community assembly processes of generalists and specialists in river affected by wastewater discharge from distilleries in typical Chinese spirits production area in China.

Lixi Deng, Ying Huang, Qihong Zhong, Yu Mu, Dong Li, Yaxi Liu, Hong Zhang, Chi Zhao, Shirui Yu, Fu Jiao and 1 more

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Lixi Deng *School of Food Engineering, Moutai Institute, Renhuai, China.
Ying Huang *School of Brewing Engineering, Moutai Institute, Renhuai, China.
Qihong ZhongSchool of Brewing Engineering, Moutai Institute, Renhuai, China.
Yu MuSchool of Food Engineering, Moutai Institute, Renhuai, China.
Dong LiSchool of Food Engineering, Moutai Institute, Renhuai, China.
Yaxi LiuSchool of Resources and Environment, Moutai Institute, Renhuai, China.
Hong ZhangSchool of Food Engineering, Moutai Institute, Renhuai, China.
Chi ZhaoSchool of Food Engineering, Moutai Institute, Renhuai, China.
Shirui YuSchool of Food Engineering, Moutai Institute, Renhuai, China.
Fu JiaoKweichow Moutai Co. Ltd., Renhuai, China.
Xiuyuan YangGuizhou Institute of Biology, Guizhou Academy of Sciences, Guiyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Understanding how bacterial communities respond to distillery wastewater discharge into rivers is crucial for restoring and maintaining aquatic ecosystem functions. However, feedback mechanisms involving bacterial generalists and specialists under distillery wastewater disturbance remain unexplored. Methods: This study employs high-throughput sequencing, neutral community models, and null models to analyze, for the first time, the distribution patterns, environmental adaptations, assembly processes, and driving factors of generalists and specialists upstream and downstream of a spirits wastewater discharge site in the Chishui River. Results: Proteobacteria emerged as the dominant phylum among both specialists and generalists, exhibiting significant changes before and after wastewater discharge. Specialists Conclusion: Our findings enhance the understanding of bacterial responses to spirits wastewater and provide valuable insights for the ecological restoration of polluted rivers.

Indexed as

community assemblydistillery wastewaterdistribution patternsenvironmental adaptabilityphylogenetics

Identifiers

PMID42495145
PMCPMC13393092

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Registered trials

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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.