Evidence map›Paper›PMID 37993701›Full record

ArticleWorld journal of microbiology & biotechnology2023

Characterization and seasonal variation in biofilms attached to leaves of submerged plant.

Jiawei Zhang, Kexuan Liu, Yaguang Li, Hong Deng, Deying Huang, Jibiao Zhang

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In one paragraph

Article in World journal of microbiology & biotechnology, 2023. 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
–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

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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. 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

6 authors.

Jiawei ZhangDepartment of Environmental Science and Engineering, Fudan Unersity, Shanghai, 200433, P.R. China.
Kexuan LiuDepartment of Environmental Science and Engineering, Fudan Unersity, Shanghai, 200433, P.R. China.
Yaguang LiDepartment of Environmental Science and Engineering, Fudan Unersity, Shanghai, 200433, P.R. China.
Hong DengSchool of Ecological and Environmental Science, Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, Institute of Eco-Chongming, East China Normal University, Shanghai, 200241, P.R. China.
Deying HuangDepartment of Chemistry, Fudan University, Shanghai, 200433, P.R. China. huangdeying@fudan.edu.cn.
Jibiao ZhangDepartment of Environmental Science and Engineering, Fudan Unersity, Shanghai, 200433, P.R. China. jbzhang@fudan.edu.cn.

Funding

Natural Science Foundation of Shanghai 22ZR1446500
6 · The paper itself

Abstract

The microorganisms and functional predictions of leaf biofilms on submerged plants (Vallisneria natans (Val)) and in water samples (surface water (S) and bottom water (B)) in different seasons were evaluated in this study. S and B groups had 3249 identical operational taxonomic units (OTUs) (50.03%), while the Val group only had 1201 (18.49%) unique OTUs. There was significant overlap between microbial communities of S and B groups in the same season, while Val group showed the greater diversity. The dominant microbial clades were Proteobacteria (18.2-47.3%), Cyanobacteria (3.74-39.3%), Actinobacteria (1.64-29.3%), Bacteroidetes (1.31-21.7%), and Firmicutes (1.10-15.72%). Furthermore, there was a significant relationship between total organic carbon and the distribution of microbial taxa (p = 0.047), and TN may have altered the status of Cyanobacteria by affecting its biological nitrogen fixation capacity and reproductive capacity. The correlation network analysis results showed that the whole system consisted of 249 positive correlations and 111 negative correlations, indicating strong interactions between microbial communities. Functional predictions indicated that microbial functions were related to seasonal variation. These findings would guide the use of submerged plants to improve the diversity and stability of wetland microbial communities.

Indexed as

CyanobacteriaHydrocharitaceaeBiofilmsPlant LeavesSeasonsWaterWaterFunctional predictionLeaf biofilmMicrobial diversitySubmerged plant

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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.