Evidence map›Paper›PMID 40574379›Full record

SynthesisBiotechnology and bioengineering2025

Magnetic-Assisted Manipulation of Rare Blood Cells for Diagnosis: A Systematic Review.

Poornima Ramesh Iyer, Xian Wu, Hyeon Choe, Linh Nguyen T Tran, Karla Mercedes Paz González, Bahareh Rezaei, Shahriar Mostufa, Ebrahim Azizi, Ioannis H Karampelas, Kai Wu and 2 more

Abstract readSystematic Review
In one paragraph

Synthesis in Biotechnology and bioengineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Magnetic nanoparticles for cancer theranostics.Biomedical physics & engineering express · 2026
    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

12 authors.

Poornima Ramesh IyerWilliam G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, Ohio, USA.ORCID https://orcid.org/0009-0009-0527-6202
Xian WuWilliam G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, Ohio, USA.
Hyeon ChoeWilliam G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, Ohio, USA.
Linh Nguyen T TranDepartment of Chemical Engineering, Texas Tech University, Lubbock, Texas, USA.
Karla Mercedes Paz GonzálezDepartment of Chemical Engineering, Texas Tech University, Lubbock, Texas, USA.
Bahareh RezaeiDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, Texas, USA.
Shahriar MostufaDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, Texas, USA.
Ebrahim AziziDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, Texas, USA.
Ioannis H KarampelasNemak USA, Inc., Sheboygan, Wisconsin, USA.
Kai WuDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, Texas, USA.
Jeffrey ChalmersWilliam G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, Ohio, USA.ORCID https://orcid.org/0000-0003-1723-9774
Jenifer Gomez-PastoraDepartment of Chemical Engineering, Texas Tech University, Lubbock, Texas, USA.

Funding

Fractionation of Aged RBCs Based on Hemoglobin ContentR01HL131720 · NHLBI · OHIO STATE UNIVERSITY · PI CHALMERS, JEFFREY JOHN, PALMER, ANDRE FRANCIS · 2017 to 2020
$2.7M
NHLBI NIH HHS R01 HL131720This study was funded by Texas Tech University through HEF New Faculty Startup, NRUF Startup, and Core Research Support Fund. We also wish to thank the National Heart, Lung, and Blood Institute (1R01HL131720-01A1) for financial assistance. Jenifer Gomez-Pastora gratefully acknowledges support from The Welch Foundation under Grant Number D-2236-20250403 and the Cancer Prevention & Research Institute of Texas under Grant Number RP250634.
6 · The paper itself

Abstract

The precise isolation and analysis of rare cells from blood are crucial for biomedical research and clinical diagnostics. This review examines recent advancements in magnetic-based separation techniques, focusing on their efficiency in capturing rare cells such as circulating tumor cells (CTCs), circulating fetal cells, and diseased red blood cells (RBCs). These methods use magnetophoresis under external magnetic fields for highly specific isolation with minimal contamination, offering advantages over traditional techniques in speed, cost-effectiveness, and robustness. Magnetic separation is categorized into label-based methods, which use immunomagnetic nanoparticles (IMNs) to target specific cell markers, and label-free methods, which exploit differences in magnetic susceptibility. Both approaches have achieved up to 99% efficiency in isolating diseased RBCs and CTCs. However, challenges remain in improving purity, scalability, and clinical applicability. A key limitation of label-based methods is the need to detach cells from magnetic beads without compromising viability. Label-free technologies, such as magnetic levitation, enable ligand-free separation based on density and susceptibility. Future research should focus on optimizing paramagnetic media, integrating machine learning for enhanced accuracy, and developing high-gradient magnetic fields (~1000 T/m) to improve efficiency. Advancements in IMNs with stronger magnetic properties will further enhance separation performance, driving clinical translation.

Indexed as

Cell SeparationImmunomagnetic SeparationNeoplastic Cells, CirculatingErythrocytesHumansMagnetite NanoparticlesMagnetite NanoparticlesCTCsfetal cellsinfected or anemic RBCslabeledlabel‐freemagnetic‐based separation

Identifiers

PMID40574379
PMCPMC12233183

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.