Evidence map›Paper›PMID 33842999›Full record

ReviewEnvironmental science and pollution research international2021

Selective removal of common cyanotoxins: a review.

Shulian Wang, Yiying Jiao, Zhi Rao

Abstract readReview
PubMed Publisher
In one paragraph

Review in Environmental science and pollution research international, 2021. 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

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. 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

3 authors.

Shulian WangHubei Key Laboratory of Ecological Remediation for Rivers-Lakes and Algal Utilization, School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan, 430068, China.ORCID http://orcid.org/0000-0002-4055-8928
Yiying JiaoHubei Key Laboratory of Ecological Remediation for Rivers-Lakes and Algal Utilization, School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan, 430068, China.
Zhi RaoHubei Key Laboratory of Ecological Remediation for Rivers-Lakes and Algal Utilization, School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan, 430068, China. rz721521@126.com.

Funding

National Natural Science Foundation of China 51909082
6 · The paper itself

Abstract

The development of cyanobacterial blooms can have adverse effects on water bodies and may produce cyanotoxins. Several physical and chemical methods have been applied to remove cyanotoxins, but they have been significantly challenged due to extensive energy footprint and over-used chemicals, which limits practical application on a large scale. Selective removal has been regarded as the most promising approach recently for the elimination of prevalent and major bloom-forming cyanotoxins (e.g., microcystins and cylindrospermopsin) as natural organic matters and radical scavengers are ineluctably present in real scenarios. This paper reviews current advancements in research on selective oxidation and adsorption of cyanotoxins. Its goal is to provide comprehensive information on the treatment mechanism and the process feasibility involved in the cyanotoxin removal from real-world waters. Moreover, perspectives of cyanotoxin control and in situ selective elimination approaches are also reviewed. It is expected that the information gathered and discussed in this review can provide a useful and novel reference and direction for future pilot-scale applications.

Indexed as

Bacterial ToxinsCyanobacteriaMicrocystinsUracilBacterial ToxinsMicrocystinsUracilAdsorptionCyanobacteriaCyanotoxinsCylindrospermopsinMicrocystinsSelective removal

Identifiers

What OpenQuestion holds

Textmetadata
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.