Evidence map›Paper›PMID 32354070›Full record

ReviewSensors (Basel, Switzerland)2020

A Review on Electrochemical Sensors and Biosensors Used in Phenylalanine Electroanalysis.

Ancuta Dinu, Constantin Apetrei

Open access · goldAbstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.6field-weighted citation impact, top 10% 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, 46 citations in OpenAlex.

  1. Observational
  2. Article
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  7. Review
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  9. 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

2 authors at 1 institution in 1 country.

Ancuta DinuDepartment of Chemistry, Physics and Environment, Faculty of Sciences and Environment, "Dunărea de Jos" University of Galaţi, 47 Domneasca Street, 800008 Galaţi, Romania.
Constantin ApetreiDepartment of Chemistry, Physics and Environment, Faculty of Sciences and Environment, "Dunărea de Jos" University of Galaţi, 47 Domneasca Street, 800008 Galaţi, Romania.ORCID 0000-0002-3823-4174
"Dunarea de Jos" University of Galati · RO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Phenylalanine is an amino acid found in breast milk and in many foods, being an essential nutrient. This amino acid is very important for the human body because it is transformed into tyrosine and, subsequently, into catecholamine neurotransmitters. However, there are individuals who were born with a genetic disorder called phenylketonuria. The accumulation of phenylalanine and of some metabolites in the body is dangerous and may cause convulsions, brain damage and mental retardation. Determining the concentration of phenylalanine in different biologic fluids is very important because it can provide information about the health status of the individuals envisaged. Since such determinations may be made by using electrochemical sensors and biosensors, numerous researchers have developed such sensors for phenylalanine detection and different sensitive materials were used in order to improve the selectivity, sensitivity and detection limit. The present review aims at presenting the design and performance of some electrochemical bio (sensors) traditionally used for phenylalanine detection as reported in a series of relevant scientific papers published in the last decade.

Indexed as

Biosensing TechniquesElectrochemical TechniquesEquipment DesignHumansPhenylalaninePhenylketonuriasPhenylalaninebiosensorelectrochemistryphenylalaninephenylketonuriasensor

Identifiers

PMID32354070
PMCPMC7249663
OpenAlexW3021400861

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.