Evidence map›Paper›PMID 36498883›Full record

ArticleInternational journal of molecular sciences2022

Use of Hierarchical Carbon Nanofibers Decorated with NiCo Nanoparticles for Highly Sensitive Vortioxetine Determination.

Joanna Smajdor, Marcel Zambrzycki, Beata Paczosa-Bator, Robert Piech

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2022. 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
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Carbon-Based Nanomaterials 4.0.International journal of molecular sciences · 2024
    Article
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.

Joanna SmajdorDepartment of Analytical Chemistry and Biochemistry, Faculty of Materials Science and Ceramics, AGH University of Science and Technology, Al. Mickiewicza, 30-059 Krakow, Poland.ORCID 0000-0001-7732-0019
Marcel ZambrzyckiDepartment of Analytical Chemistry and Biochemistry, Faculty of Materials Science and Ceramics, AGH University of Science and Technology, Al. Mickiewicza, 30-059 Krakow, Poland.ORCID 0000-0002-7941-426X
Beata Paczosa-BatorDepartment of Analytical Chemistry and Biochemistry, Faculty of Materials Science and Ceramics, AGH University of Science and Technology, Al. Mickiewicza, 30-059 Krakow, Poland.ORCID 0000-0002-2838-462X
Robert PiechDepartment of Analytical Chemistry and Biochemistry, Faculty of Materials Science and Ceramics, AGH University of Science and Technology, Al. Mickiewicza, 30-059 Krakow, Poland.ORCID 0000-0001-9551-0609

Funding

AGH University of Science and Technology Excellence initiative-research university
6 · The paper itself

Abstract

A new voltammetry method for the highly sensitive antidepressant drug vortioxetine (VOR) is presented using glassy carbon electrodes modified with hierarchical carbon nanofibers with NiCo nanoparticles (eCNF/CNT/NiCo-GCE). The electrochemical behavior of VOR was investigated by cyclic voltammetry, which indicates that its oxidation is an adsorption-controlled process with the exchange of two electrons and one proton. The effects of various factors on the VOR peak, such as supporting electrolyte type, preconcentration time, and potential, or influence of interferents, were tested using the square wave voltammetry technique (SWV). The linear voltametric response for the analyte was obtained in the concentration range from 0.01·10

Indexed as

CarbonNanoparticlesAdsorptionElectrochemical TechniquesElectrodesVortioxetineCarbonVortioxetinecarbon nanofiberselectrode modifiernanoparticlesvoltammetryvortioxetine

Identifiers

PMID36498883
PMCPMC9739381

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.