Evidence map›Paper›PMID 33084996›Full record

ArticleMikrochimica acta2020

A paper-based colorimetric sensor array for discrimination and simultaneous determination of organophosphate and carbamate pesticides in tap water, apple juice, and rice.

Mohammad Mahdi Bordbar, Tien Anh Nguyen, Fabiana Arduini, Hasan Bagheri

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Article in Mikrochimica acta, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
4.9field-weighted citation impact, top 4% 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

18 citing papers in PubMed, 94 citations in OpenAlex.

  1. Review
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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

4 authors at 3 institutions in 3 countries.

Mohammad Mahdi BordbarChemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
Tien Anh NguyenDepartment of Physics, Le Quy Don Technical University, Hanoi, Vietnam.
Fabiana ArduiniDepartment of Chemical Science and Technologies, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133, Rome, Italy.
Hasan BagheriChemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran. h.bagheri@bmsu.ac.ir.ORCID 0000-0003-2895-6189
Baqiyatallah University of Medical Sciences · IRLe Quy Don Technical University · VNUniversity of Rome Tor Vergata · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A colorimetric paper-based sensor is proposed for the rapid monitoring of six major organophosphate and carbamate pesticides. The assay was constructed by dropping gold and silver nanoparticles on the hydrophilic zones of a paper substrate. The nanoparticles were modified by L-arginine, quercetin, and polyglutamic acid. The mechanism of sensing is based on the interaction between the pesticide and the nanoparticles. The color of nanoparticles changed during the interactions. A digital camera recorded these changes. The assay provided a unique response for each studied pesticide. This method can determine six individual pesticides including carbaryl, paraoxon, parathion, malathion, diazinon, and chlorpyrifos. The limit of detection for these pesticides were 29.0, 22.0, 32.0, 17.0, 45.0, and 36.0 ng mL

Indexed as

CarbamatesColorimetryFood ContaminationFruit and Vegetable JuicesGoldMalusMetal NanoparticlesOrganophosphatesOryzaPaperPesticidesSilverWaterWater Pollutants, ChemicalCarbamatesGoldOrganophosphatesPesticidesSilverWaterWater Pollutants, ChemicalColorimetric detectionEnzymeless sensorsPaper-based deviceSensor arrayStatistical multivariate analysis

Identifiers

PMID33084996
OpenAlexW3093751884

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.