Evidence map›Paper›PMID 39212282›Full record

ReviewJournal of water and health2024

Review of the occurrence, treatment technologies, and detection methods for saxitoxins in freshwaters.

Shardula Gawankar, Susan J Masten, Rebecca H Lahr

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of water and health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. 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

3 authors.

Shardula GawankarDepartment of Civil and Environmental Engineering, Michigan State University, East Lansing, MI, USA E-mail: gawankar@msu.edu.ORCID https://orcid.org/0000-0001-7704-0172
Susan J MastenDepartment of Civil and Environmental Engineering, Michigan State University, East Lansing, MI, USA.ORCID https://orcid.org/0000-0002-4983-4933
Rebecca H LahrThe City of Ann Arbor, Department of Water Treatment, Ann Arbor, MI, USA.ORCID https://orcid.org/0000-0002-7988-7649

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing occurrence of saxitoxins in freshwaters is becoming a concern for water treatment facilities owing to its structural properties which make it resistant to oxidation at pH < 8. Hence, it is crucial to be able to monitor these toxins in surface and drinking water to protect public health. This review aims to outline the current state of knowledge related to the occurrence of saxitoxins in freshwaters and its removal strategies and provide a critical assessment of the detection methods to provide a basis for further development. Temperature and nutrient content are some of the factors that influence the production of saxitoxins in surface waters. A high dose of sodium hypochlorite with sufficient contact time or activated carbon has been shown to efficiently remove extracellular saxitoxins to meet the drinking water guidelines. While HILIC-MS has proven to be a powerful technology for more sensitive and reliable detection of saxitoxin and variants after solid phase extraction, ELISA is cost-effective and easy to use and is used by Ohio EPA for surveillance with a limit of detection of 0.015 μg/L. However, there is a need for the development of cost-effective and sensitive techniques that can quantify the variants of saxitoxin.

Indexed as

Environmental MonitoringFresh WaterSaxitoxinWater Pollutants, ChemicalWater PurificationSaxitoxinWater Pollutants, ChemicalELISAfreshwaterHILIC-MSoxidationsaxitoxinswater treatment

Identifiers

PMID39212282

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.