Evidence map›Paper›PMID 30944642›Full record

ArticleOncology letters2019

Label-free microfluidic chip for the identification of mesothelial cell clusters in pleural effusion.

Lili Zhao, Meng Zhao, Yu Yang, Yajun Gu, Fang Zheng, Xuan Wang, Zhiyuan Zheng, Xuguo Sun

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2019. 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
0.2field-weighted citation impact, top 51% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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 at 4 institutions in 1 country.

Lili ZhaoDepartment of Laboratory Science, School of Laboratory Medicine, Tianjin Medical University, Tianjin 300203, P.R. China.
Meng ZhaoKey Laboratory of Computer Vision and System of Ministry of Education, School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, P.R. China.
Yu YangDepartment of Laboratory Science, School of Laboratory Medicine, Tianjin Medical University, Tianjin 300203, P.R. China.
Yajun GuDepartment of Laboratory Science, School of Laboratory Medicine, Tianjin Medical University, Tianjin 300203, P.R. China.
Fang ZhengDepartment of Laboratory Science, School of Laboratory Medicine, Tianjin Medical University, Tianjin 300203, P.R. China.
Xuan WangDepartment of Clinical Laboratory, Tianjin Chest Hospital, Tianjin 300051, P.R. China.
Zhiyuan ZhengDepartment of Bone Science, North China University of Science and Technology Affiliated Hospital, Tangshan, Hebei 063000, P.R. China.
Xuguo SunDepartment of Laboratory Science, School of Laboratory Medicine, Tianjin Medical University, Tianjin 300203, P.R. China.
Tianjin Medical University · CNNorth China University of Science and Technology · CNTianjin Chest Hospital · CNTianjin University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The detection of tumor cells and clusters in pleural effusion assists in the diagnosis of lung cancer. The proportion of tumor cells and clusters to the total number of cells in each patient varies substantially due to individual differences and the severity of the disease. The identification of one tumor cell or cluster from a large number of pleural effusions is the main challenge for hydrothorax tumor cell detection techniques. In the present study, by using A549 lung cancer and Met-5A mesothelial cell lines, a label-free microfluidic chip based on cell cluster size was designed. By setting the parameters of the chip, individual cells and clusters were able to enter different microfluidic channels. Subsequent to non-specific staining, the recovered components were stained using acridine orange (AO). A charge-coupled device camera was used to captured images of the cell, and the features of these cells were analyzed in their R and G channels using Matlab software to establish the characteristics and finally differentiate between the tumor and non-tumor cell or clusters. According to the results, when inlet A and B were under a velocity of 10 and 8.5 ml/h, respectively, the tumor cell clusters were successfully collected through microfluidic channels III-V, with a recovery rate of ~80%. Subsequent to staining with AO, the feature values in the R and G channels were identified, and initial differentiation was achieved. The present study combined the microfluidic chip, which is based on cluster size, with a computer identification method for pleural effusion. The successful differentiation of tumor cell clusters from non-tumor clusters provides the basis for the identification of tumor clusters in hydrothorax.

Indexed as

acridine orangecell clusterimage processinglung cancermesothelial cellmicrofluidic chippleural effusion

Identifiers

PMID30944642
PMCPMC6444474
OpenAlexW2920649985

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.