Evidence map›Paper›PMID 34025895›Full record

ArticleBiomicrofluidics2021

A droplet acoustofluidic platform for time-controlled microbead-based reactions.

Zhenhua Liu, Anna Fornell, Maria Tenje

Open access · hybridAbstract read
In one paragraph

Article in Biomicrofluidics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 44% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. 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 at 1 institution in 1 country.

Zhenhua LiuDepartment of Materials Science and Engineering, Science for Life Laboratory, Uppsala University, SE-752 37 Uppsala, Sweden.ORCID 0000-0001-7960-5878
Maria TenjeDepartment of Materials Science and Engineering, Science for Life Laboratory, Uppsala University, SE-752 37 Uppsala, Sweden.ORCID 0000-0002-1264-1337
Uppsala University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Droplet microfluidics is a powerful method used to characterize chemical reactions at high throughput. Often detection is performed via in-line optical readout, which puts high demands on the detection system or makes detection of low concentration substrates challenging. Here, we have developed a droplet acoustofluidic chip for time-controlled reactions that can be combined with off-line optical readout. The principle of the platform is demonstrated by the enzymatic conversion of fluorescein diphosphate to fluorescein by alkaline phosphatase. The novelty of this work is that the time of the enzymatic reaction is controlled by physically removing the enzymes from the droplets instead of using chemical inhibitors. This is advantageous as inhibitors could potentially interact with the readout. Droplets containing substrate were generated on the chip, and enzyme-coupled microbeads were added into the droplets via pico-injection. The reaction starts as soon as the enzyme/bead complexes are added, and the reaction is stopped when the microbeads are removed from the droplets at a channel bifurcation. The encapsulated microbeads were focused in the droplets by acoustophoresis during the split, leaving the product in the side daughter droplet to be collected for the analysis (without beads). The time of the reaction was controlled by using different outlets, positioned at different lengths from the pico-injector. The enzymatic conversion could be measured with fluorescence readout in a separate PDMS based assay chip. We show the ability to perform time-controlled enzymatic assays in droplet microfluidics coupled to an off-line optical readout, without the need of enzyme inhibitors.

Identifiers

PMID34025895
PMCPMC8131108
OpenAlexW3161427399

What OpenQuestion holds

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LicenceCC BY
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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.