Evidence map›Paper›PMID 38275060›Full record

ReviewCombinatorial chemistry & high throughput screening2025

Microfluidics-assisted Tumor Cell Separation Approaches for Clinical Applications: An Overview on Emerging Devices.

Nahid Shanehband, Seyed Morteza Naghib

Abstract readReview
PubMed Publisher
In one paragraph

Review in Combinatorial chemistry & high throughput screening, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
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

2 authors.

Nahid ShanehbandNanotechnology Department, School of Advanced Technologies, Iran University of Science and Technology, Tehran, Iran.
Seyed Morteza NaghibNanotechnology Department, School of Advanced Technologies, Iran University of Science and Technology, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advances in science and technology have led to revolutions in many scientific and industrial fields. The term lab on a chip, or in other words, performing a variety of complex analyses in just a short time and a minimal space, is a term that has become very common in recent years, and what used to be a dream has now come to life in practice. In this paper, we tried to investigate a specific type of lab technology on a chip, which is, of course, one of the most common, namely the knowledge and technology of cell separation by using a microfluidic technique that can be separated based on size and deformation, adhesion and electrical properties. The tissue of the human body is degraded due to injury or aging. It is often tried to treat this tissue disorder by using drugs, but they are not always enough. Stem cell-based medicine is a novel form that promises the restoration or regeneration of tissues and functioning organs. Although many models of microfluidic systems have been designed for cell separation, choosing the appropriate device to achieve a reliable result is a challenge. Therefore, in this study, Fluorescence Activated Cell Sorting (FACS), Dielectrophoresis (DEP), Magnetic Activated Cell Sorting (MACS), and Acoustic microfluidic system are four distinct categories of active microfluidic systems explored. Also, the advantages, disadvantages, and the current status of the devices mentioned in these methods are reviewed.

Indexed as

Cell SeparationLab-On-A-Chip DevicesMicrofluidic Analytical TechniquesMicrofluidicsNeoplasmsFlow CytometryHumanscell isolationdielectrophoresisfluorescence-activated cell sortingLab on a chipmagnetic activated cell sorting.microfulidics

Identifiers

PMID38275060

What OpenQuestion holds

Textmetadata
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.