Evidence map›Paper›PMID 27725672›Full record

ArticleNature communications2016

Large-scale microfluidics providing high-resolution and high-throughput screening of Caenorhabditis elegans poly-glutamine aggregation model.

Sudip Mondal, Evan Hegarty, Chris Martin, Sertan Kutal Gökçe, Navid Ghorashian, Adela Ben-Yakar

Abstract read
In one paragraph

Article in Nature communications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.

0numbers the graph read from it
0cells of the map it votes in
61citing 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

61 citing papers in PubMed.

  1. Article
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  4. Application ofBiomolecules & therapeutics · 2026
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  7. High-Throughput Toxicity Screening withEnvironmental science & technology · 2026
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  9. Automated Platforms inMicromachines · 2025
    Review
  10. Review
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  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Lab on a chip · 2023
    Article

1 more citing papers are in PubMed but not listed here.

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

6 authors.

Sudip MondalDepartment of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.
Evan HegartyDepartment of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.
Chris MartinDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.
Sertan Kutal GökçeDepartment of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.
Navid GhorashianDepartment of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.
Adela Ben-YakarDepartment of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.

Funding

High-speed opto-fluidics to screen entire nervous system in aging and diseaseR01AG041135 · NIA · UNIVERSITY OF TEXAS AT AUSTIN · PI BEN-YAKAR, ADELA, PIERCE, JONATHAN THOMAS · 2011 to 2015
$2.8M
Comprehensive Training Program in Imaging Science and InformaticsT32EB007507 · NIBIB · UNIVERSITY OF TEXAS AT AUSTIN · PI MARKEY, MIA K, RYLANDER, HENRY GRADY · 2009 to 2024
$2.7M
NIA NIH HHS R01 AG041135NIBIB NIH HHS T32 EB007507
6 · The paper itself

Abstract

Next generation drug screening could benefit greatly from in vivo studies, using small animal models such as Caenorhabditis elegans for hit identification and lead optimization. Current in vivo assays can operate either at low throughput with high resolution or with low resolution at high throughput. To enable both high-throughput and high-resolution imaging of C. elegans, we developed an automated microfluidic platform. This platform can image 15 z-stacks of ∼4,000 C. elegans from 96 different populations using a large-scale chip with a micron resolution in 16 min. Using this platform, we screened ∼100,000 animals of the poly-glutamine aggregation model on 25 chips. We tested the efficacy of ∼1,000 FDA-approved drugs in improving the aggregation phenotype of the model and identified four confirmed hits. This robust platform now enables high-content screening of various C. elegans disease models at the speed and cost of in vitro cell-based assays.

Indexed as

Models, BiologicalProtein AggregatesAnimalsAutomationCaenorhabditis elegansDisease Models, AnimalDrug ApprovalDrug Evaluation, PreclinicalHigh-Throughput Screening AssaysImaging, Three-DimensionalMicrofluidicsPeptidesReproducibility of ResultsUnited StatesUnited States Food and Drug AdministrationPeptidespolyglutamineProtein Aggregates

Identifiers

PMID27725672
PMCPMC5062571

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.