Evidence map›Paper›PMID 30867867›Full record

ArticleBiomicrofluidics2018

Two-way detection of image features and immunolabeling of lymphoma cells with one-step microarray analysis.

Yu Yang, Meng Zhao, Xiaodan Liu, Peng Ge, Fang Zheng, Tao Chen, Xuguo Sun

Abstract read
In one paragraph

Article in Biomicrofluidics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 45% 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

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
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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

7 authors at 4 institutions in 1 country.

Yu YangSchool of Medical Laboratory, Tianjin Medical University, Tianjin 300203, People's Republic of China.
Meng ZhaoSchool of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, People's Republic of China.
Xiaodan LiuSchool of Medical Laboratory, Tianjin Medical University, Tianjin 300203, People's Republic of China.
Peng GeDepartment of Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, People's Republic of China.
Fang ZhengSchool of Medical Laboratory, Tianjin Medical University, Tianjin 300203, People's Republic of China.
Tao ChenInstitute of Laser Engineering, Beijing University of Technology, Beijing 100124, People's Republic of China.
Xuguo SunSchool of Medical Laboratory, Tianjin Medical University, Tianjin 300203, People's Republic of China.ORCID 0000-0002-8017-5403
Tianjin Medical University · CNBeijing University of Technology · CNTianjin Medical University Cancer Institute and Hospital · CNTianjin University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detecting the number of pathological lymphoma cells and lymphocyte subtypes in blood is helpful for clinical diagnosis and typing of lymphoma. In the current study, cell type is identified by cell morphological features and immunolabeled lymphocyte subtypes. Red blood cells and leukocytes were separated using a microfluidic cell chip based on physical blood cell parameters, and leukocytes were identified using five characteristic parameters: energy variance, entropy variance, moment of inertia variance, color mean, and cell area individually. The number of red blood cells that could come into contact with the leukocyte membrane was ≤2 based on the microfluidic injection flow rate of microfluidic chips. Anti-CD3 and anti-CD19 antibodies were used for immunofluorescence staining of T-lymphocyte and B-lymphocyte surface antigens, respectively. The results suggested that the microfluidic assay could detect lymphocyte surface antigen markers and intact leukocytes. Therefore, we report a one-step microfluidic chip for classifying hematological lymphoma cells based on the physical parameters of cells, which can simultaneously measure the overall morphology of blood cells and immunolabeling of lymphocyte surface antigens in one step, solving the current problem of detecting subtypes of hematological lymphoma cells based on multiple methods and multi-step detection.

Identifiers

PMID30867867
PMCPMC6404911
OpenAlexW2908051237

What OpenQuestion holds

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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.