Evidence map›Paper›PMID 37392212›Full record

ArticleAnalytical and bioanalytical chemistry2023

Demand-driven active droplet generation and sorting based on positive pressure-controlled fluid wall.

Yiwei Zhang, Yiwei Lin, Xianzhe Hong, Chao Di, Yuelai Xin, Xinru Wang, Shuhong Qi, Bi-Feng Liu, Zhihong Zhang, Wei Du

Abstract read
PubMed Publisher
In one paragraph

Article in Analytical and bioanalytical chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 33% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. 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

10 authors at 2 institutions in 1 country.

Yiwei Zhang *The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Yiwei Lin *The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Xianzhe HongThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Chao DiThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Yuelai XinThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Xinru WangThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Shuhong QiThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Bi-Feng LiuThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Zhihong ZhangThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Wei DuThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China. weidu@mail.hust.edu.cn.
Huazhong University of Science and Technology · CNWuhan National Laboratory for Optoelectronics · CN

Funding

Fundamental Research Funds for the Central Universities 2020kfyXJJS034National Key R&D Program of China 2021YFA1101500National Natural Science Foundation of China 22074047
6 · The paper itself

Abstract

Droplet microfluidics is a rapidly advancing area of microfluidic technology, which offers numerous advantages for cell analysis, such as isolation and accumulation of signals, by confining cells within droplets. However, controlling cell numbers in droplets is challenging due to the uncertainty of random encapsulation which result in many empty droplets. Therefore, more precise control techniques are needed to achieve efficient encapsulation of cells within droplets. Here, an innovative microfluidic droplet manipulation platform had been developed, which employed positive pressure as a stable and controllable driving force for manipulating fluid within chips. The air cylinder, electro-pneumatics proportional valve, and the microfluidic chip were connected through a capillary, which enabled the formation of a fluid wall by creating a difference in hydrodynamic resistance between two fluid streams at the channel junction. Lowering the pressure of the driving oil phase eliminates hydrodynamic resistance and breaks the fluid wall. Regulating the duration of the fluid wall breakage controls the volume of the introduced fluid. Several important droplet microfluidic manipulations were demonstrated on this microfluidic platform, such as sorting of cells/droplets, sorting of droplets co-encapsulated cells and hydrogels, and active generation of droplets encapsulated with cells in a responsive manner. The simple, on-demand microfluidic platform was featured with high stability, good controllability, and compatibility with other droplet microfluidic technologies.

Indexed as

Co-encapsulated dropletsFluid wallFluorescence-activated droplet sortingMicrofluidic deviceOn-demand droplet formation

Identifiers

PMID37392212
OpenAlexW4382797940

What OpenQuestion holds

Textmetadata
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.