Evidence map›Paper›PMID 35884278›Full record

ArticleBiosensors2022

Generalized Analytical Model for Enzymatic BioFET Transistors.

Cristian Ravariu, Avireni Srinivasulu, Dan Eduard Mihaiescu, Sarada Musala

Abstract read
In one paragraph

Article in Biosensors, 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
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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

4 authors.

Cristian RavariuBioNEC Group, Department of Electronic Devices Circuits and Architectures, Faculty of Electronics ETTI, Polytechnic University of Bucharest, Splaiul Independentei 313, 060042 Bucharest, Romania.ORCID 0000-0002-1483-2583
Avireni SrinivasuluSchool of Engineering & Technology, K.R. Mangalam University, Gurugram 122103, Haryana, India.ORCID 0000-0001-6254-7990
Dan Eduard MihaiescuOrganic Chemistry Department, Faculty of Chemistry, Polytechnic University of Bucharest, Splaiul Independentei 313, 060042 Bucharest, Romania.
Sarada MusalaDepartment of Electronics and Communication Engineering, Vignan's Foundation for Science, Technology and Research, Guntur 522213, Andhra Pradesh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Software tools that are able to simulate the functionality or interactions of an enzyme biosensor with Metal Oxide Semiconductor (MOS), or any Field Effect Transistor (FET) as transducer, represent a gap in the market. Bio-devices, or Enzyme-FET, cannot be simulated by Atlas or equivalent software. This paper resolves this issue for the enzymatic block coupled with FETs' role within biosensors. The first block has the concentration of biological analyte as the input signal and concentration of ions from the enzymatic reaction as the output signal. The modeling begins from the Michaelis-Menten formalism and analyzes the time dependence of the product concentrations that become the input signal for the next FET block. Comparisons within experimental data are provided. The analytical model proposed in this paper represents a general analytical tool in the design stage for enzymatic transistors used in clinical practices.

Indexed as

Biosensing TechniquesTransistors, ElectronicIonsIonsbio-nano-electronicsENFET modelingenzyme kinetics

Identifiers

PMID35884278
PMCPMC9313200

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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.