Evidence map›Paper›PMID 32509051›Full record

ArticleBiomicrofluidics2020

High filling rate digital PCR through-hole array chip with double independent S-shaped flow channels.

Xu Gao, Jinze Li, Chuanyu Li, Zhiqi Zhang, Wei Zhang, Jia Yao, Ming Guan, Zhen Guo, Chao Li, Lianqun Zhou

Abstract read
In one paragraph

Article in Biomicrofluidics, 2020. 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
–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

4 citing papers in PubMed.

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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

10 authors.

Xu Gao
Jinze LiCAS Key Laboratory of Bio-medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, People's Republic of China.
Zhiqi Zhang
Wei Zhang
Jia Yao
Ming GuanHuashan Hospital, Fudan University, Shanghai 200040, People's Republic of China.
Zhen Guo
Chao LiCAS Key Laboratory of Bio-medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sample digital technology is a powerful method for absolute quantification of target molecules such as nucleic acids and proteins. The excellent sample stability and mass production capability has enabled the development of microwell array-based sample digitizing methods. However, in current microwell array chips, samples are loaded by the liquid scraping method, which requires complex manual operation and results in a low filling rate and limited hole filling uniformity. Here, we perform sample loading of a through-hole array chip by a microfluidics-driven method and design a double independent S-shaped flow channels sandwiched through-hole array chip. Because of the capillary force and capillary burst pressure, the sample flowing in the channel can be trapped into through-holes, but cannot flow through the other side. Via air flow and displacement of the remaining sample in the channel, the sample can be partitioned consistently, with zero surplus sample residue in the channel. We evaluated the actual performance of the sample-loading process: the chip enables 99.10% filling rate of 18 500 through-holes, with a grayscale coefficient of variation value of 6.03% determined from fluorescence images. In performing digital polymerase chain reaction on chip, the chip demonstrates good performance for the absolute quantification of target DNA. The simple and robust design of our chip, with excellent filling rate and microsample uniformity, indicates potential for use in a variety of sample digitization applications.

Identifiers

PMID32509051
PMCPMC7266645

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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.