Evidence map›Paper›PMID 33376807›Full record

ArticleBiology methods & protocols2020

Concomitant prediction of environmental fate and toxicity of chemical compounds.

Juan Antonio Garcia-Martin, Max Chavarría, Victor de Lorenzo, Florencio Pazos

Abstract read
In one paragraph

Article in Biology methods & protocols, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

4 authors.

Juan Antonio Garcia-MartinBioinformatics for Genomics and Proteomics, National Centre for Biotechnology (CNB-CSIC), 28049 Madrid, Spain.
Max ChavarríaEscuela de Química/CIPRONA Universidad de Costa Rica, 11501-2060 San José, Costa Rica.
Victor de LorenzoDepartment of Systems Biology, National Centre for Biotechnology (CNB-CSIC), 28049 Madrid, Spain.
Florencio PazosDepartment of Systems Biology, National Centre for Biotechnology (CNB-CSIC), 28049 Madrid, Spain.ORCID 0000-0002-2646-6226

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The environmental fate of many functional molecules that are produced on a large scale as precursors or as additives to specialty goods (plastics, fibers, construction materials, etc.), let alone those synthesized by the pharmaceutical industry, is generally unknown. Assessing their environmental fate is crucial when taking decisions on the manufacturing, handling, usage, and release of these substances, as is the evaluation of their toxicity in humans and other higher organisms. While this data are often hard to come by, the experimental data already available on the biodegradability and toxicity of many unusual compounds (including genuinely xenobiotic molecules) make it possible to develop machine learning systems to predict these features. As such, we have created a predictor of the "risk" associated with the use and release of any chemical. This new system merges computational methods to predict biodegradability with others that assess biological toxicity. The combined platform, named

Indexed as

biodegradationpredictionweb server

Identifiers

PMID33376807
PMCPMC7750720

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.