Evidence map›Paper›PMID 24404030›Full record

ArticleBiomicrofluidics2013

Two dimensional barcode-inspired automatic analysis for arrayed microfluidic immunoassays.

Yi Zhang, Lingbo Qiao, Yunke Ren, Xuwei Wang, Ming Gao, Yunfang Tang, Jianzhong Jeff Xi, Tzung-May Fu, Xingyu Jiang

Abstract read
In one paragraph

Article in Biomicrofluidics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

9 authors.

Yi ZhangCollege of Engineering and School of Physics, Peking University, Beijing 100871, China ; National Center for Nanoscience and Technology, Beijing 100190, China.
Lingbo QiaoDepartment of Engineering Physics, Tsinghua University, Beijing 100084, China ; Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing 100084, China.
Yunke RenCollege of Engineering and School of Physics, Peking University, Beijing 100871, China.
Xuwei WangState Key Laboratory for Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100080, China.
Ming GaoDepartment of Engineering Physics, Tsinghua University, Beijing 100084, China.
Yunfang TangNational Center for Nanoscience and Technology, Beijing 100190, China.
Jianzhong Jeff XiCollege of Engineering and School of Physics, Peking University, Beijing 100871, China.
Tzung-May FuCollege of Engineering and School of Physics, Peking University, Beijing 100871, China.
Xingyu JiangNational Center for Nanoscience and Technology, Beijing 100190, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The usability of many high-throughput lab-on-a-chip devices in point-of-care applications is currently limited by the manual data acquisition and analysis process, which are labor intensive and time consuming. Based on our original design in the biochemical reactions, we proposed here a universal approach to perform automatic, fast, and robust analysis for high-throughput array-based microfluidic immunoassays. Inspired by two-dimensional (2D) barcodes, we incorporated asymmetric function patterns into a microfluidic array. These function patterns provide quantitative information on the characteristic dimensions of the microfluidic array, as well as mark its orientation and origin of coordinates. We used a computer program to perform automatic analysis for a high-throughput antigen/antibody interaction experiment in 10 s, which was more than 500 times faster than conventional manual processing. Our method is broadly applicable to many other microchannel-based immunoassays.

Identifiers

PMID24404030
PMCPMC3695989

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.