Evidence map›Paper›PMID 32292982›Full record

ArticleLab on a chip2020

Fluorescence-based sorting of Caenorhabditis elegans via acoustofluidics.

Jinxin Zhang, Jessica H Hartman, Chuyi Chen, Shujie Yang, Qi Li, Zhenhua Tian, Po-Hsun Huang, Lin Wang, Joel N Meyer, Tony Jun Huang

Open access · greenAbstract read
In one paragraph

Article in Lab on a chip, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.1field-weighted citation impact, top 14% 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

17 citing papers in PubMed, 43 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Microfluidic-AssistedCyborg and bionic systems (Washington, D.C.) · 2023
    Article
  12. Article
  13. Sonoporation: Past, Present, and Future.Advanced materials technologies · 2022
    Article
  14. Article
  15. Article
  16. Review
  17. 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

10 authors at 2 institutions in 2 countries.

Jinxin ZhangDepartment of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708, USA. tony.huang@duke.edu.
Jessica H Hartman
Chuyi Chen
Shujie Yang
Qi Li
Zhenhua Tian
Po-Hsun Huang
Lin Wang
Joel N Meyer
Tony Jun Huang
Duke University · USTriangle · US

Funding

Zebrafish as a Detector of Organophosphate ExposureP42ES010356 · NIEHS · DUKE UNIVERSITY · PI AMY H HERRING · 2000 to 2026
$56.2M
Proteomics CoreP30DK123704 · NIDDK · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI Caroline Westwater · 2020 to 2026
$8.8M
Development of an acoustofluidic-based C.elegans 3D imaging and sorting systemR43OD024963 · OD · ASCENT BIO-NANO TECHNOLOGIES, INC. · PI WANG, LIN · 2018 to 2019
$697k
Role of Mitochondrial CYP2E1 in Chemical Exposure-Driven NeurodegenerationF32ES027306 · NIEHS · DUKE UNIVERSITY · PI HARTMAN, JESSICA HELENE · 2016 to 2018
$171k
NIDDK NIH HHS P30 DK123704NIEHS NIH HHS F32 ES027306NIEHS NIH HHS P42 ES010356NIH HHS R43 OD024963
6 · The paper itself

Abstract

Effectively isolating and categorizing large quantities of Caenorhabditis elegans (C. elegans) based on different phenotypes is important for most worm research, especially genetics. Here we present an integrated acoustofluidic chip capable of identifying worms of interest based on expression of a fluorescent protein in a continuous flow and then separate them accordingly in a high-throughput manner. Utilizing planar fiber optics as the detection unit, our acoustofluidic device requires no temporary immobilization of worms for interrogation/detection, thereby improving the throughput. Implementing surface acoustic waves (SAW) as the sorting unit, our device provides a contact-free method to move worms of interest to the desired outlet, thus ensuring the biocompatibility for our chip. Our device can sort worms of different developmental stages (L3 and L4 stage worms) at high throughput and accuracy. For example, L3 worms can be processed at a throughput of around 70 worms per min with a sample purity over 99%, which remains over 90% when the throughput is increased to around 115 worms per min. In our acoustofluidic chip, the time period to complete the detection and sorting of one worm is only 50 ms, which outperforms nearly all existing microfluidics-based worm sorting devices and may be further reduced to achieve higher throughput.

Indexed as

Caenorhabditis elegansLab-On-A-Chip DevicesAnimalsFluorescenceProtein TransportSound

Identifiers

PMID32292982
PMCPMC7239761
OpenAlexW3015267753

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.