Evidence map›Paper›PMID 35884313›Full record

ReviewBiosensors2022

Signal-Based Methods in Dielectrophoresis for Cell and Particle Separation.

Malihe Farasat, Ehsan Aalaei, Saeed Kheirati Ronizi, Atin Bakhshi, Shaghayegh Mirhosseini, Jun Zhang, Nam-Trung Nguyen, Navid Kashaninejad

Abstract readReview
In one paragraph

Review in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 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

8 authors.

Malihe FarasatSchool of Electrical and Computer Engineering, College of Engineering, Tehran University, Tehran 14399-57131, Iran.ORCID 0000-0003-2306-9708
Ehsan AalaeiSchool of Mechanical Engineering, Shiraz University, Shiraz 71936-16548, Iran.ORCID 0000-0002-1624-817X
Saeed Kheirati RoniziSchool of Mechanical Engineering, Shiraz University, Shiraz 71936-16548, Iran.ORCID 0000-0001-9069-6352
Atin BakhshiSchool of Electrical and Computer Engineering, College of Engineering, Tehran University, Tehran 14399-57131, Iran.ORCID 0000-0002-8718-7212
Shaghayegh MirhosseiniSchool of Electrical and Computer Engineering, College of Engineering, Tehran University, Tehran 14399-57131, Iran.
Jun ZhangQueensland Micro-Nanotechnology Centre, Griffith University, Nathan, QLD 4111, Australia.
Nam-Trung NguyenQueensland Micro-Nanotechnology Centre, Griffith University, Nathan, QLD 4111, Australia.ORCID 0000-0003-3626-5361
Navid KashaninejadQueensland Micro-Nanotechnology Centre, Griffith University, Nathan, QLD 4111, Australia.ORCID 0000-0002-4385-7771

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Separation and detection of cells and particles in a suspension are essential for various applications, including biomedical investigations and clinical diagnostics. Microfluidics realizes the miniaturization of analytical devices by controlling the motion of a small volume of fluids in microchannels and microchambers. Accordingly, microfluidic devices have been widely used in particle/cell manipulation processes. Different microfluidic methods for particle separation include dielectrophoretic, magnetic, optical, acoustic, hydrodynamic, and chemical techniques. Dielectrophoresis (DEP) is a method for manipulating polarizable particles' trajectories in non-uniform electric fields using unique dielectric characteristics. It provides several advantages for dealing with neutral bioparticles owing to its sensitivity, selectivity, and noninvasive nature. This review provides a detailed study on the signal-based DEP methods that use the applied signal parameters, including frequency, amplitude, phase, and shape for cell/particle separation and manipulation. Rather than employing complex channels or time-consuming fabrication procedures, these methods realize sorting and detecting the cells/particles by modifying the signal parameters while using a relatively simple device. In addition, these methods can significantly impact clinical diagnostics by making low-cost and rapid separation possible. We conclude the review by discussing the technical and biological challenges of DEP techniques and providing future perspectives in this field.

Indexed as

Microfluidic Analytical TechniquesCell SeparationElectrophoresisLab-On-A-Chip DevicesMicrofluidicscell separationClausius–Mossotti factorcrossover frequencydielectrophoresismicrofluidicsparticle sorting

Identifiers

PMID35884313
PMCPMC9313092

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.