Evidence map›Paper›PMID 38138408›Full record

ArticleMicromachines2023

Assessing the Discriminatory Capabilities of iEK Devices under DC and DC-Biased AC Stimulation Potentials.

Nuzhet Nihaar Nasir Ahamed, Carlos A Mendiola-Escobedo, Victor H Perez-Gonzalez, Blanca H Lapizco-Encinas

Abstract read
In one paragraph

Article in Micromachines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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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.

Nuzhet Nihaar Nasir AhamedMicroscale Bioseparations Laboratory, Biomedical Engineering Department, Rochester Institute of Technology, 160 Lomb Memorial Drive, Rochester, NY 14623, USA.ORCID 0000-0002-2466-6216
Carlos A Mendiola-EscobedoSchool of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, Mexico.ORCID 0000-0002-7773-4227
Victor H Perez-GonzalezSchool of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, Mexico.ORCID 0000-0003-4503-7774
Blanca H Lapizco-EncinasMicroscale Bioseparations Laboratory, Biomedical Engineering Department, Rochester Institute of Technology, 160 Lomb Memorial Drive, Rochester, NY 14623, USA.ORCID 0000-0001-6283-8210

Funding

Federico Baur Endowed Chair in Nanotechnology at Tecnologico de Monterrey 0020240I03Kate Gleason College of Engineering NANano- Sensors & Devices Research Group at Tecnologico de Monterrey 0020209I06National Science Foundation 2127592
6 · The paper itself

Abstract

There is a rising need for rapid and reliable analytical methods for separating microorganisms in clinical and biomedical applications. Microscale-insulator-based electrokinetic (iEK) systems have proven to be robust platforms for assessing a wide variety of microorganisms. Traditionally, iEK systems are usually stimulated with direct-current (DC) potentials. This work presents a comparison between using DC potentials and using DC-biased alternating-current (AC) potentials in iEK systems for the separation of microorganisms. The present study, which includes mathematical modeling and experimentation, compares the separation of bacterial and yeast cells in two distinct modes by using DC and DC-biased AC potentials. The quality of both separations, assessed in terms of separation resolution (Rs), showed a complete separation (Rs = 1.51) with the application of a DC-biased low-frequency AC signal but an incomplete separation (Rs = 0.55) with the application of an RMS-equivalent DC signal. Good reproducibility between experimental repetitions (<10%) was obtained, and good agreement (~18% deviation) was observed between modeling and experimental retention times. The present study demonstrates the potential of extending the limits of iEK systems by employing DC-biased AC potentials to perform discriminatory separations of microorganisms that are difficult to separate with the application of DC potentials.

Indexed as

electrokineticselectroosmosiselectropherogramelectrophoresisseparation

Identifiers

PMID38138408
PMCPMC10745336

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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.