Evidence map›Paper›PMID 29511230›Full record

ArticleScientific reports2018

A Triplet Parallelizing Spiral Microfluidic Chip for Continuous Separation of Tumor Cells.

Hongmei Chen

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
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

18 citing papers in PubMed, 56 citations in OpenAlex.

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  9. Microfluidics for the Isolation and Detection of Circulating Tumor Cells.Advances in experimental medicine and biology · 2022
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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

1 author at 1 institution in 1 country.

Hongmei ChenSchool of Mathematics and Physics of Science and Engineering, Anhui University of Technology, Maanshan, 243002, China. hongmeichen@semi.ac.cn.
Anhui University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inertial and deformability- based particles separations gradually attract more significant attentions. In this work, we present a hybrid chip by combining the advantages of inertial and deformability -based principle. The chip is a triplet parallelizing spiral inertial microfluidic chip interconnected with numerable tilted slits (Spiral-Slits Chip) for continuous separation of circulating tumor cells. Utilizing the inertial lift and viscous drag forces, different sized particles achieve different equilibrium at distinct streamlines of the spiral microchannel. Numerable tilted slits are organized along the flow direction. They frequently transport segregated streamline particles into a paralleled smaller microchannel. These frequent dragging results in the amount of certain sized particles in the original microchannel gradually and dramatically reduced. Inertial separation of distinct sized particles could be achievable. Two arrays of numerable tilted slits function as bridges. This Spiral-Slits Chip could substitute for Red Blood Cells Lysis (RBCL) and is most effective for ultra-high throughput. The overall arrangement of this triplet parallelizing spiral inertial microfluidic reflects stable streamlines distribution in the first main microchannel. Combining with Ellipse filters, robust and reproducible capture of CTCs could be achieved at high flow rates. Optical absorption detection has been tentatively tested, and this could simplify the process.

Indexed as

Lab-On-A-Chip DevicesNeoplastic Cells, CirculatingCell SeparationHumansMCF-7 CellsMechanical PhenomenaMicrofluidics

Identifiers

PMID29511230
PMCPMC5840358
OpenAlexW2791350949

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.