Evidence map›Paper›PMID 36831967›Full record

ArticleBiosensors2023

Eu

Aleksandar Mijajlović, Miloš Ognjanović, Dragan Manojlović, Filip Vlahović, Slađana Đurđić, Vesna Stanković, Dalibor Stanković

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

4 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
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

7 authors at 2 institutions in 2 countries.

Aleksandar MijajlovićFaculty of Chemistry, University of Belgrade, Studentski trg 12-16, 11000 Belgrade, Serbia.
Miloš Ognjanović"VINČA" Institute of Nuclear Sciences-National Institute of the Republic of Serbia, University of Belgrade, 11000 Belgrade, Serbia.ORCID 0000-0003-2889-4416
Dragan ManojlovićFaculty of Chemistry, University of Belgrade, Studentski trg 12-16, 11000 Belgrade, Serbia.ORCID 0000-0003-1388-6245
Filip VlahovićInstitute of Chemistry, Technology and Metallurgy-National Institute of the Republic of Serbia, University of Belgrade, Njegoševa 12, 11000 Belgrade, Serbia.ORCID 0000-0001-6172-6612
Slađana ĐurđićFaculty of Chemistry, University of Belgrade, Studentski trg 12-16, 11000 Belgrade, Serbia.ORCID 0000-0002-7828-3288
Vesna StankovićInstitute of Chemistry, Technology and Metallurgy-National Institute of the Republic of Serbia, University of Belgrade, Njegoševa 12, 11000 Belgrade, Serbia.ORCID 0000-0002-0394-0503
Dalibor StankovićFaculty of Chemistry, University of Belgrade, Studentski trg 12-16, 11000 Belgrade, Serbia.ORCID 0000-0001-7465-1373
University of Belgrade · RSSouth Ural State University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There are ten million people in the world who have Parkinson's disease. The most potent medicine for Parkinson's disease is levodopa (L-DOPA). However, long-term consumption of L-DOPA leads to the appearance of side effects, as a result of which the control and monitoring of its concentrations are of great importance. In this work, we have designed a new electrochemical sensor for detecting L-DOPA using a carbon paste electrode (CPE) modified with Eu

Indexed as

NanoparticlesParkinson DiseaseCarbonElectrochemical TechniquesElectrodesHumansLevodopaLimit of DetectionNeurotransmitter AgentsCarbonLevodopaNeurotransmitter Agentselectrochemical sensorhydrothermal synthesislevodopamicromolar detectionrare earth nanomaterial

Identifiers

PMID36831967
PMCPMC9953689
OpenAlexW4318476866

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.