Evidence map›Paper›PMID 29086360›Full record

ArticleEnvironmental science and pollution research international2018

Evaluation of genotoxic effects in Brazilian agricultural workers exposed to pesticides and cigarette smoke using machine-learning algorithms.

Jamile Silveira Tomiazzi, Meire Aparecida Judai, Gisele Alborghetti Nai, Danillo Roberto Pereira, Patricia Alexandra Antunes, Ana Paula Alves Favareto

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 29% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 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

6 authors at 1 institution in 1 country.

Jamile Silveira TomiazziGraduate Program in Environment and Regional Development, University of Western São Paulo - UNOESTE, Presidente Prudente, SP, Brazil.
Meire Aparecida JudaiFaculty of Health Sciences, University of Western São Paulo - UNOESTE, Presidente Prudente, SP, Brazil.
Gisele Alborghetti NaiGraduate Program in Health Sciences, University of Western São Paulo - UNOESTE, Presidente Prudente, SP, Brazil.
Danillo Roberto PereiraGraduate Program in Environment and Regional Development, University of Western São Paulo - UNOESTE, Presidente Prudente, SP, Brazil.
Patricia Alexandra AntunesGraduate Program in Environment and Regional Development, University of Western São Paulo - UNOESTE, Presidente Prudente, SP, Brazil.
Ana Paula Alves FavaretoGraduate Program in Environment and Regional Development, University of Western São Paulo - UNOESTE, Presidente Prudente, SP, Brazil. anafavareto@unoeste.br.
Universidade do Oeste Paulista · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monitoring exposure to xenobiotics by biomarker analyses, such as a micronucleus assay, is extremely important for the precocious detection and prevention of diseases, such as oral cancer. The aim of this study was to evaluate genotoxic effects in rural workers who were exposed to cigarette smoke and/or pesticides and to identify possible classification patterns in the exposure groups. The sample included 120 participants of both sexes aged between 18 and 39, who were divided into the following four groups: control group (CG), smoking group (SG), pesticide group (PG), and smoking + pesticide group (SPG). Their oral mucosa cells were stained with Giemsa for cytogenetic analysis. The total numbers of nuclear abnormalities (CG = 27.16 ± 14.32, SG = 118.23 ± 74.78, PG = 184.23 ± 52.31, and SPG = 191.53 ± 66.94) and micronuclei (CG = 1.46 ± 1.40, SG = 12.20 ± 10.79, PG = 21.60 ± 8.24, and SPG = 20.26 ± 12.76) were higher (p < 0.05) in the three exposed groups compared to the GC. In this study, we considered several different classification algorithms (the artificial neural network, K-nearest neighbors, support vector machine, and optimum path forest). All of the algorithms displayed good classification (accuracy > 80%) when using dataset2 (without the redundant exposure type SPG). It is clear that the data form a robust pattern and that classifiers could be successfully trained on small datasets from the exposure groups. In conclusion, exposing agricultural workers to pesticides and/or tobacco had genotoxic potential, but concomitant exposure to xenobiotics did not lead to additive or potentiating effects.

Indexed as

DNA DamageMachine LearningSmokingAdultBrazilFarmersFemaleHumansMaleMutagensOccupational ExposurePesticidesYoung AdultMutagensPesticidesAgricultureGenotoxicityMachine learningMicronucleusPesticideSmoking

Identifiers

PMID29086360
OpenAlexW2765816897

What OpenQuestion holds

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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.