Evidence map›Paper›PMID 29244741›Full record

ReviewBiosensors2017

Fluorescent and Colorimetric Electrospun Nanofibers for Heavy-Metal Sensing.

Idelma A A Terra, Luiza A Mercante, Rafaela S Andre, Daniel S Correa

Abstract readReview
In one paragraph

Review in Biosensors, 2017. 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
–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

18 citing papers in PubMed.

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  12. Electrospun Nanofibers for Sensing and Biosensing Applications-A Review.International journal of molecular sciences · 2021
    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.

Idelma A A TerraNanotechnology National Laboratory for Agriculture (LNNA), Embrapa Instrumentação, São Carlos 13560-970, SP, Brazil. iaterra@yahoo.com.br.
Luiza A MercanteNanotechnology National Laboratory for Agriculture (LNNA), Embrapa Instrumentação, São Carlos 13560-970, SP, Brazil. lamercante@gmail.com.ORCID 0000-0003-4206-6545
Rafaela S AndreNanotechnology National Laboratory for Agriculture (LNNA), Embrapa Instrumentação, São Carlos 13560-970, SP, Brazil. lela_rsa@hotmail.com.
Daniel S CorreaNanotechnology National Laboratory for Agriculture (LNNA), Embrapa Instrumentação, São Carlos 13560-970, SP, Brazil. daniel.correa@embrapa.br.ORCID 0000-0002-5592-0627

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The accumulation of heavy metals in the human body and/or in the environment can be highly deleterious for mankind, and currently, considerable efforts have been made to develop reliable and sensitive techniques for their detection. Among the detection methods, chemical sensors appear as a promising technology, with emphasis on systems employing optically active nanofibers. Such nanofibers can be obtained by the electrospinning technique, and further functionalized with optically active chromophores such as dyes, conjugated polymers, carbon-based nanomaterials and nanoparticles, in order to produce fluorescent and colorimetric nanofibers. In this review we survey recent investigations reporting the use of optically active electrospun nanofibers in sensors aiming at the specific detection of heavy metals using colorimetry and fluorescence methods. The examples given in this review article provide sufficient evidence of the potential of optically electrospun nanofibers as a valid approach to fabricate highly selective and sensitive optical sensors for fast and low-cost detection of heavy metals.

Indexed as

Biosensing TechniquesColorimetryFluorescenceMetals, HeavyNanofibersMetals, Heavyelectrospinningheavy metalsoptical sensors

Identifiers

PMID29244741
PMCPMC5746784

What OpenQuestion holds

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LicenceCC BY
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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.