Evidence map›Paper›PMID 33467753›Full record

ArticleBiosensors2021

Surface Plasmon Resonance Based on Molecularly Imprinted Polymeric Film for l-Phenylalanine Detection.

Duygu Çimen, Nilay Bereli, Adil Denizli

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.9field-weighted citation impact, top 6% 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

8 citing papers in PubMed, 42 citations in OpenAlex.

  1. Observational
  2. Review
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  6. [Advances in separation and analysis of aromatic amino acids in food].Se pu = Chinese journal of chromatography · 2022
    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

3 authors at 1 institution in 1 country.

Duygu ÇimenDepartment of Chemistry, Hacettepe University, Beytepe, 06800 Ankara, Turkey.
Nilay BereliDepartment of Chemistry, Hacettepe University, Beytepe, 06800 Ankara, Turkey.
Adil DenizliDepartment of Chemistry, Hacettepe University, Beytepe, 06800 Ankara, Turkey.ORCID 0000-0001-7548-5741
Hacettepe University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we designed a simple, rapid, sensitive and selective surface plasmon resonance (SPR) sensor for detection of L-phenylalaine by utilizing molecular imprinting technology. l-phenylalanine imprinted and non-imprinted poly(2-hydroxyethyl methacrylate-methacryloyl-l-phenylalanine) polymeric films were synthesized onto SPR chip surfaces using ultraviolet polymerization. l-phenyalanine imprinted and non-imprinted SPR sensors were characterized by using contact angle, atomic force microscopy and ellipsometry. After characterization studies, kinetic studies were carried out in the concentration range of 5.0-400.0 μM. The limit of detection and quantification were obtained as 0.0085 and 0.0285 μM, respectively. The response time for the test including equilibration, adsorption and desorption was approximately 9 min. The selectivity studies of the l-phenylalanine imprinted SPR sensor was performed in the presence of d-phenylalanine and l-tryptophan. Validation studies were carried out via enzyme-linked immunosorbent analysis technique in order to demonstrate the applicability and superiority of the l-phenylalanine imprinted SPR sensor.

Indexed as

AdsorptionBiosensing TechniquesHumansKineticsLimit of DetectionMethylmethacrylatesMicroscopy, Atomic ForceMolecular ImprintingPhenylalaninePolymersSurface Plasmon ResonanceMethylmethacrylatesPhenylalaninePolymersdetectionl-phenylalainemolecular imprinting technologysensorsurface plasmon resonance

Identifiers

PMID33467753
PMCPMC7830203
OpenAlexW3120115043

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.