Evidence map›Paper›PMID 35726253›Full record

ArticleACS measurement science au2022

Novel, User-Friendly Experimental and Analysis Strategies for Fast Voltammetry: Next Generation FSCAV with Artificial Neural Networks.

Sergio Mena, Marco Visentin, Colby E Witt, Lauren E Honan, Nathan Robins, Parastoo Hashemi

Open access · goldAbstract read
In one paragraph

Article in ACS measurement science au, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

9 citing papers in PubMed, 20 citations in OpenAlex.

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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

6 authors at 2 institutions in 2 countries.

Sergio MenaDepartment of Bioengineering, Imperial College London, London SW7 2AZ, United Kingdom.
Marco VisentinDepartment of Bioengineering, Imperial College London, London SW7 2AZ, United Kingdom.
Colby E WittDepartment of Chemistry and Biochemistry, University of South Carolina, Columbia, South Carolina 29208, United States.
Lauren E HonanDepartment of Chemistry and Biochemistry, University of South Carolina, Columbia, South Carolina 29208, United States.
Nathan RobinsDepartment of Bioengineering, Imperial College London, London SW7 2AZ, United Kingdom.
Parastoo HashemiDepartment of Bioengineering, Imperial College London, London SW7 2AZ, United Kingdom.ORCID https://orcid.org/0000-0002-0180-767X
Imperial College London · GBUniversity of South Carolina · US

Funding

An In Vivo Voltammetric Serotonin Biomarker for Antidepressant EfficacyR01MH106563 · NIMH · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI HASHEMI, PARASTOO · 2016 to 2020
$1.6M
NIMH NIH HHS R01 MH106563
6 · The paper itself

Abstract

Fast-scan adsorption-controlled voltammetry (FSCAV) was recently derived from fast-scan cyclic voltammetry to estimate the absolute concentrations of neurotransmitters by using the innate adsorption properties of carbon fiber microelectrodes. This technique has improved our knowledge of serotonin dynamics

Identifiers

PMID35726253
PMCPMC9204809
OpenAlexW4226180097

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.