Evidence map›Paper›PMID 26387763›Full record

ArticleLab on a chip2015

Digital quantification of miRNA directly in plasma using integrated comprehensive droplet digital detection.

Kaixiang Zhang, Dong-Ku Kang, M Monsur Ali, Linan Liu, Louai Labanieh, Mengrou Lu, Hamidreza Riazifar, Thi N Nguyen, Jason A Zell, Michelle A Digman and 3 more

Open access · greenAbstract read
In one paragraph

Article in Lab on a chip, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.8field-weighted citation impact, top 17% 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

19 citing papers in PubMed, 66 citations in OpenAlex.

  1. Article
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  5. Review
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  14. Review
  15. Article
  16. dPCR: A Technology Review.Sensors (Basel, Switzerland) · 2018
    Review
  17. Article
  18. Article
  19. Discovery in Droplets.Analytical chemistry · 2016
    Review
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

13 authors at 7 institutions in 5 countries.

Kaixiang ZhangDepartment of Chemistry, Beijing Key Laboratory for Analytical Methods and Instrumentation, Tsinghua University, Beijing, 100084, China. jhli@mail.tsinghua.edu.cn.
Dong-Ku Kang
M Monsur Ali
Linan Liu
Louai Labanieh
Mengrou Lu
Hamidreza Riazifar
Thi N Nguyen
Jason A Zell
Michelle A Digman
Enrico Gratton
Jinghong Li
Weian Zhao
Edwards Lifesciences (United States) · USEdwards (United Kingdom) · GBTsinghua University · CNUniversity of California, Irvine · USOrange (Poland) · PLU-M Rogel Cancer CenterUniversity of California System · US

Funding

Univ.of Calif., Irvine Cancer Center Support GrantP30CA062203 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI Christine Hui · 1994 to 2026
$57.9M
UC Irvine Alzheimer's Disease Research Center Induced Pluripotent Stem Cell CoreP50AG016573 · NIA · UNIVERSITY OF CALIFORNIA-IRVINE · PI LAFERLA, FRANK M · 2000 to 2019
$37.0M
University of California Health Participation in the National COVID Cohort Collaborative (N3C)UL1TR001414 · NCATS · UNIVERSITY OF CALIFORNIA-IRVINE · PI COOPER, DAN M, VILAIN, ERIC J. · 2015 to 2023
$35.1M
Uncover Strategies Used By Biological SystemsP50GM076516 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI LANDER, ARTHUR D · 2007 to 2016
$25.1M
TRD4: Phasor analysisP41GM103540 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI GRATTON, ENRICO · 2012 to 2020
$12.5M
Institute for Clinical and Translational ScienceUL1TR000153 · NCATS · UNIVERSITY OF CALIFORNIA-IRVINE · PI COOPER, DAN M · 2012 to 2015
$12.1M
Integrated Comprehensive Droplet Digital Detection (IC 3D) system for rapid detection of bacteria andantimicrobial resistanceR01AI117061 · NIAID · UNIVERSITY OF CALIFORNIA-IRVINE · PI ZHAO, WEIAN · 2015 to 2019
$5.1M
NCATS NIH HHS UL1 TR000153NCATS NIH HHS UL1 TR001414NCI NIH HHS P30 CA062203NCI NIH HHS P30CA062203NIAID NIH HHS R01 AI117061NIA NIH HHS P50 AG016573NIGMS NIH HHS P41 GM103540NIGMS NIH HHS P50 GM076516NIGMS NIH HHS P50-GM076516
6 · The paper itself

Abstract

Quantification of miRNAs in blood can be potentially used for early disease detection, surveillance monitoring and drug response evaluation. However, quantitative and robust measurement of miRNAs in blood is still a major challenge in large part due to their low concentration and complicated sample preparation processes typically required in conventional assays. Here, we present the 'Integrated Comprehensive Droplet Digital Detection' (IC 3D) system where the plasma sample containing target miRNAs is encapsulated into microdroplets, enzymatically amplified and digitally counted using a novel, high-throughput 3D particle counter. Using Let-7a as a target, we demonstrate that IC 3D can specifically quantify target miRNA directly from blood plasma at extremely low concentrations ranging from 10s to 10 000 copies per mL in ≤3 hours without the need for sample processing such as RNA extraction. Using this new tool, we demonstrate that target miRNA content in colon cancer patient blood is significantly higher than that in healthy donor samples. Our IC 3D system has the potential to introduce a new paradigm for rapid, sensitive and specific detection of low-abundance biomarkers in biological samples with minimal sample processing.

Indexed as

Lab-On-A-Chip DevicesSystems IntegrationBlood Chemical AnalysisColonic NeoplasmsHumansLimit of DetectionMicroRNAsMicroRNAsmirnlet7 microRNA, human

Identifiers

PMID26387763
PMCPMC4631652
OpenAlexW1832113087

What OpenQuestion holds

Textmetadata
LicenceTDM
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.