Evidence map›Paper›PMID 36976974›Full record

ArticleToxics2023

QSAR Models for the Prediction of Dietary Biomagnification Factor in Fish.

Linda Bertato, Nicola Chirico, Ester Papa

Open access · goldAbstract read
In one paragraph

Article in Toxics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.9field-weighted citation impact, top 17% of its field
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

6 citing papers in PubMed, 12 citations in OpenAlex.

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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 at 1 institution in 1 country.

Linda BertatoDepartment of Theoretical and Applied Sciences, University of Insubria, 21100 Varese, Italy.ORCID 0000-0002-3784-4894
Nicola ChiricoDepartment of Theoretical and Applied Sciences, University of Insubria, 21100 Varese, Italy.
Ester PapaDepartment of Theoretical and Applied Sciences, University of Insubria, 21100 Varese, Italy.
University of Insubria · IT

Funding

University of Insubria PhD Program in Chemical and Environmental Sciences (DiSCA, University of Insubria) (PhD scholarship to Linda Bertato).
6 · The paper itself

Abstract

Xenobiotics released in the environment can be taken up by aquatic and terrestrial organisms and can accumulate at higher concentrations through the trophic chain. Bioaccumulation is therefore one of the PBT properties that authorities require to assess for the evaluation of the risks that chemicals may pose to humans and the environment. The use of an integrated testing strategy (ITS) and the use of multiple sources of information are strongly encouraged by authorities in order to maximize the information available and reduce testing costs. Moreover, considering the increasing demand for development and the application of new approaches and alternatives to animal testing, the development of in silico cost-effective tools such as QSAR models becomes increasingly important. In this study, a large and curated literature database of fish laboratory-based values of dietary biomagnification factor (BMF) was used to create externally validated QSARs. The quality categories (high, medium, low) available in the database were used to extract reliable data to train and validate the models, and to further address the uncertainty in low-quality data. This procedure was useful for highlighting problematic compounds for which additional experimental effort would be required, such as siloxanes, highly brominated and chlorinated compounds. Two models were suggested as final outputs in this study, one based on good-quality data and the other developed on a larger dataset of consistent Log BMF

Indexed as

alternatives to animal testingbioaccumulationbiomagnificationdata qualityMLRQSAR

Identifiers

PMID36976974
PMCPMC10054725
OpenAlexW4321789595

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.