Evidence map›Paper›PMID 31547397›Full record

ArticleMicromachines2019

Microfluidic-Based Mechanical Phenotyping of Androgen-Sensitive and Non-sensitive Prostate Cancer Cells Lines.

Na Liu, Panpan Du, Xiaoxiao Xiao, Yuanyuan Liu, Yan Peng, Chen Yang, Tao Yue

Open access · goldAbstract read
In one paragraph

Article in Micromachines, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

15 citing papers in PubMed, 19 citations in OpenAlex.

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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 2 institutions in 1 country.

Na LiuSchool of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China. liuna_sia@shu.edu.cn.
Panpan DuSchool of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China. dpp_shu@163.com.
Xiaoxiao XiaoSchool of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China. xxx229471513@163.com.
Yuanyuan LiuSchool of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China. yuanyuan_liu@shu.edu.cn.
Yan PengSchool of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China. pengyan@shu.edu.cn.
Chen YangFudan Institute of Urology, Fudan University, Shanghai 200433, China. YangC_Huashan@163.com.
Tao YueSchool of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China. tao_yue@shu.edu.cn.ORCID 0000-0001-8321-1898
Shanghai University · CNFudan University · CN

Funding

National Natural Science Foundation of China 61703265, 61403245, 61803250Shanghai Sailing Program Foundation 17YF1406100, 17YF1406200
6 · The paper itself

Abstract

Cell mechanical properties have been identified to characterize cells pathologic states. Here, we report our work on high-throughput mechanical phenotyping of androgen-sensitive and non-sensitive human prostate cancer cell lines based on a morphological rheological microfluidic method. The theory for extracting cells' elastic modulus from their deformation and area, and the used experimental parameters were analyzed. The mechanical properties of three types of prostate cancer cells lines with different sensitivity to androgen including LNCaP, DU145, and PC3 were quantified. The result shows that LNCaP cell was the softest, DU145 was the second softest, and PC3 was the stiffest. Furthermore, atomic force microscopy (AFM) was used to verify the effectiveness of this high-throughput morphological rheological method.

Indexed as

cell deformabilitycellular mechanicshigh-throughputmicrofluidicmorphological rheologysingle-cell analysis

Identifiers

PMID31547397
PMCPMC6780375
OpenAlexW2973073277

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.