Evidence map›Paper›PMID 39494896›Full record

ArticleApplied and environmental microbiology2024

Potential health risk assessment of cyanobacteria across global lakes.

Hang Hu, Zhenyan Zhang, Bingfeng Chen, Qi Zhang, Nuohan Xu, Hans W Paerl, Tingzhang Wang, Wenjie Hong, Josep Penuelas, Haifeng Qian

Abstract read
In one paragraph

Article in Applied and environmental microbiology, 2024. 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

10 authors.

Hang HuCollege of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang, China.
Zhenyan ZhangCollege of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang, China.
Bingfeng ChenCollege of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang, China.ORCID 0009-0002-4090-7224
Qi ZhangThe Institute for Advanced Studies, Shaoxing University, Shaoxing, China.
Nuohan XuThe Institute for Advanced Studies, Shaoxing University, Shaoxing, China.
Hans W PaerlInstitute of Marine Sciences, University of North Carolina at Chapel Hill, Morehead City, North Carolina, USA.
Tingzhang WangKey Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, China.
Wenjie HongKey Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, China.
Josep PenuelasCSIC, Global Ecology Unit CREAF-CSIC-UAB, Barcelona, Catalonia, Spain.
Haifeng QianCollege of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang, China.ORCID 0000-0003-0807-9991

Funding

The synergistic effects of climate and anthropogenic drivers on toxic cyanobacterial bloomsP01ES028939 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Gregory James Dick, David Joseph Kennedy · 2018 to 2026
$3.7M
China Postdoctoral Science Foundation (China Postdoctoral Foundation Project) 2023M743100Foundation for the National Institutes of Health (FNIH) 1P01ES028939-01Fundación Ramón Areces (FRA) CIVP20A6621MOST | National Natural Science Foundation of China (NSFC) 21976161, 21777144, 22376187MOST | National Natural Science Foundation of China (NSFC) 42307158MOST | NSFC | NSFC-Zhejiang Joint Fund | | Natural Science Foundation of Zhejiang Province (ZJNSF) LZ23B070001National Science Foundation (NSF) 1831096, 1803697, 2108917NIEHS NIH HHS P01 ES028939the Catalan Government SGR2021-1333the Key Scientific and Technological Program of Hangzhou 2023SZD0058the Spanish Government TED2021-132627B-I00Zhejiang Provincial Postdoctoral Science Foundation ZJ2023058
6 · The paper itself

Abstract

Cyanobacterial blooms pose environmental and health risks due to their production of toxic secondary metabolites. While current methods for assessing these risks have focused primarily on bloom frequency and intensity, the lack of comprehensive and comparable data on cyanotoxins makes it challenging to rigorously evaluate these health risks. In this study, we examined 750 metagenomic data sets collected from 103 lakes worldwide. Our analysis unveiled the diverse distributions of cyanobacterial communities and the genes responsible for cyanotoxin production across the globe. Our approach involved the integration of cyanobacterial biomass, the biosynthetic potential of cyanotoxin, and the potential effects of these toxins to establish potential cyanobacterial health risks. Our findings revealed that nearly half of the lakes assessed posed medium to high health risks associated with cyanobacteria. The regions of greatest concern were East Asia and South Asia, particularly in developing countries experiencing rapid industrialization and urbanization. Using machine learning techniques, we mapped potential cyanobacterial health risks in lakes worldwide. The model results revealed a positive correlation between potential cyanobacterial health risks and factors such as temperature, N IMPORTANCE: Our research introduces a novel and comprehensive approach to potential cyanobacterial health risk assessment, offering insights into risk from a toxicity perspective. The distinct geographical variations in cyanobacterial communities coupled with the intricate interplay of environmental factors underscore the complexity of managing cyanobacterial blooms at a global scale. Our systematic and targeted cyanobacterial surveillance enables a worldwide assessment of cyanobacteria-based potential health risks, providing an early warning system.

Indexed as

CyanobacteriaLakesEnvironmental MonitoringEutrophicationHumansMicrocystinsRisk AssessmentMicrocystinscyanobacterial bloomcyanotoxinslakemachine learningmetagenomerisk assessment

Identifiers

PMID39494896
PMCPMC11577754

What OpenQuestion holds

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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.