Simultaneous Multiclass Analysis of Cyanotoxins in Cyanobacterial Samples Using Hydrophilic Interaction Liquid Chromatography-Tandem Mass Spectrometry.

Rosemary Bergin, Siobhan Peters, Simon Mitrovic, David P Bishop

Abstract read

In one paragraph

Article in Journal of separation science, 2025. 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.

Multiclass Cyanotoxins in Aquatic Environments: Occurrence, Impacts and Detection Techniques.Toxins · 2026
Review

4 · The record

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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

4 authors.

Rosemary BerginHyphenated Mass Spectrometry Laboratory, School of Mathematical and Physical Sciences, University of Technology Sydney, Ultimo, New South Wales, Australia.ORCID https://orcid.org/0000-0003-0868-1800

Siobhan PetersHyphenated Mass Spectrometry Laboratory, School of Mathematical and Physical Sciences, University of Technology Sydney, Ultimo, New South Wales, Australia.

Simon MitrovicSchool of Life Sciences, University of Technology Sydney, Ultimo, New South Wales, Australia.

David P BishopHyphenated Mass Spectrometry Laboratory, School of Mathematical and Physical Sciences, University of Technology Sydney, Ultimo, New South Wales, Australia.ORCID https://orcid.org/0000-0002-6533-4410

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The proliferation of cyanobacteria can result in algal blooms, which may cause environmental and biological harm due to the production and release of secondary metabolites, or cyanotoxins, into the affected waterway. Cyanobacteria can produce multiple classes of cyanotoxins; therefore, to understand the full toxic load of algal blooms, it is necessary to perform analyses that quantify each class. These classes are generally monitored individually due to the challenges associated with the differing physicochemical properties of the cyanotoxins. Hydrophilic interaction liquid chromatography (HILIC) is a form of chromatography capable of retaining multiple classes of cyanotoxins that differ in physicochemical properties. Here an HILIC-MS/MS method was developed and validated to detect 3 microcystins, 11 saxitoxins, and 2 anatoxins. The chromatographic conditions were optimized to allow for the separation of multiple pairs of saxitoxin epimers, and in-source fragmentation in the MS interface was used to develop unique MRMs between the pairs. The method was validated and had low limits of detection (LODs, between 0.00770 and 9.75 µg L

Indexed as

Bacterial ToxinsCyanobacteriaMicrocystinsSaxitoxinChromatography, LiquidCyanobacteria ToxinsHydrophobic and Hydrophilic InteractionsTandem Mass SpectrometryBacterial ToxinsCyanobacteria ToxinsMicrocystinsSaxitoxinalgal bloomscyanobacteriacyanotoxinshydrophilic interaction liquid chromatographymulticlass analysis

Identifiers

PMID40108890

DOI10.1002/jssc.70121

PMCPMC11923511

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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.