Evidence map›Paper›PMID 35548645›Full record

ArticleRSC advances2018

An efficient strategy for a controllable droplet merging system for digital analysis.

Yi Qiao, Jiye Fu, Fang Yang, Mengqin Duan, Mengting Huang, Jing Tu, Zuhong Lu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in RSC advances, 2018. 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
  2. Article
  3. Article
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.

Yi QiaoState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University Nanjing 210096 China jtu@seu.edu.cn zhlu@seu.edu.cn +86-025-83793779.
Jiye FuState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University Nanjing 210096 China jtu@seu.edu.cn zhlu@seu.edu.cn +86-025-83793779.
Fang YangState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University Nanjing 210096 China jtu@seu.edu.cn zhlu@seu.edu.cn +86-025-83793779.
Mengqin DuanState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University Nanjing 210096 China jtu@seu.edu.cn zhlu@seu.edu.cn +86-025-83793779.
Mengting HuangState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University Nanjing 210096 China jtu@seu.edu.cn zhlu@seu.edu.cn +86-025-83793779.
Jing TuState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University Nanjing 210096 China jtu@seu.edu.cn zhlu@seu.edu.cn +86-025-83793779.ORCID https://orcid.org/0000-0002-1310-5915
Zuhong LuState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University Nanjing 210096 China jtu@seu.edu.cn zhlu@seu.edu.cn +86-025-83793779.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Droplet merging is an important part of droplet manipulation approaches. Droplet merging methods with expansions inside channels can merge droplets in pairs through simple structures. However, they have a low success rate of merging under unstable fluidic conditions since the one-to-one pairing strategy is sensitive to fluctuation. This study presents a one-to-a-cluster pairing strategy to improve the success rate of merging under fluctuation. The one-to-a-cluster method was suitable for digital analysis and droplet MDA was performed in merged droplets successfully.

Identifiers

PMID35548645
PMCPMC9086890

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.