Evidence map›Paper›PMID 30189666›Full record

ReviewFoods (Basel, Switzerland)2018

Affinity Sensing Strategies for the Detection of Pesticides in Food.

Denise Capoferri, Flavio Della Pelle, Michele Del Carlo, Dario Compagnone

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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.

Denise CapoferriFaculty of Biosciences and Technologies for Food, Agriculture and Environment, University of Teramo, via R. Balzarini 1, 64100 Teramo, Italy. dcapoferri@unite.it.
Flavio Della PelleFaculty of Biosciences and Technologies for Food, Agriculture and Environment, University of Teramo, via R. Balzarini 1, 64100 Teramo, Italy. fdellapelle@unite.it.ORCID 0000-0002-8877-7580
Michele Del CarloFaculty of Biosciences and Technologies for Food, Agriculture and Environment, University of Teramo, via R. Balzarini 1, 64100 Teramo, Italy. mdelcarlo@unite.it.
Dario CompagnoneFaculty of Biosciences and Technologies for Food, Agriculture and Environment, University of Teramo, via R. Balzarini 1, 64100 Teramo, Italy. dcompagnone@unite.it.ORCID 0000-0001-7849-8943

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This is a review of recent affinity-based approaches that detect pesticides in food. The importance of the quantification and monitoring of pesticides is firstly discussed, followed by a description of the different approaches reported in the literature. The different sensing approaches are reported according to the different recognition element used: antibodies, aptamers, or molecularly imprinted polymers. Schemes of detection and the main features of the assays are reported and commented upon. The large number of affinity sensors recently developed and tested on real samples demonstrate that this approach is ready to be validated to monitor the amount of pesticides used in food commodities.

Indexed as

affinity sensorsaptamerselectrochemical detectionimmunosensorsmolecularly imprinted polymersoptical detectionpesticides

Identifiers

PMID30189666
PMCPMC6165126

What OpenQuestion holds

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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.