Evidence map›Paper›PMID 30963149›Full record

ArticleLab on a chip2019

Droplet CAR-Wash: continuous picoliter-scale immunocapture and washing.

Steven R Doonan, Melissa Lin, Ryan C Bailey

Abstract read
In one paragraph

Article in Lab on a chip, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Dynamic sampling fromLab on a chip · 2024
    Article
  3. Article
  4. Active Flow Control and Dynamic Analysis in Droplet Microfluidics.Annual review of analytical chemistry (Palo Alto, Calif.) · 2021
    Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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

3 authors.

Steven R DoonanDepartment of Chemistry, University of Michigan, Ann Arbor, MI 48109, USA. ryancb@umich.edu.
Melissa Lin
Ryan C Bailey

Funding

Droplet Microfluidic Platform for Ultralow Input EpigeneticsR21CA191186 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BAILEY, RYAN C · 2015 to 2017
$647k
NCI NIH HHS R21 CA191186
6 · The paper itself

Abstract

To address current limitations in adapting solid phase sample capture and washing techniques to continuously flowing droplet microfluidics, we have developed the "Coalesce-Attract-Resegment Wash" (CAR-Wash) approach. This module provides efficient, high-throughput magnetic washing by electrocoalescing magnetic bead-laden input droplets with a washing buffer flow and magnetophoretically transporting beads through the buffer into a secondary droplet formation streamline. In this work, we first characterized the technology in terms of throughput, sample retention, and flow-based exclusion of waste volume, demonstrating >500 Hz droplet processing with >98% bead retention and >100-fold dilution in final droplets. Next, we showed that the technique can be adapted to alternative commercially available magnetic beads with lower magnetite content per particle. Then, we demonstrated the CAR-Wash module's effectiveness in washing away a small molecule competitive inhibitor to restore the activity of magnetic bead-immobilized β-galactosidase. Finally, we applied the system to immunomagnetically enrich a green fluorescent protein-histone H2B fusion protein from cell lysate while washing away mCherry and other lysate components. We believe this approach will bridge the gap between powerful biochemical and bioanalytical techniques and current droplet microfluidic capabilities, and we envision future application in droplet-based immunoassays, solid phase extraction, and other complex, multi-step operations.

Indexed as

Lab-On-A-Chip DevicesHeLa CellsHumansImmunoassayMagnetic PhenomenaMicrospheres

Identifiers

PMID30963149
PMCPMC6478530

What OpenQuestion holds

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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.