Evidence map›Paper›PMID 26651055›Full record

ArticleJournal of visualized experiments : JoVE2015

A Microfluidic Platform for Precision Small-volume Sample Processing and Its Use to Size Separate Biological Particles with an Acoustic Microdevice.

Erika J Fong, Chao Huang, Julie Hamilton, William J Benett, Mihail Bora, Alison Burklund, Thomas R Metz, Maxim Shusteff

Abstract read
In one paragraph

Article in Journal of visualized experiments : JoVE, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. 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

8 authors.

Erika J FongMaterials Engineering Division, Lawrence Livermore National Laboratory; Department of Biomedical Engineering, Boston University.
Chao HuangMaterials Engineering Division, Lawrence Livermore National Laboratory.
Julie HamiltonMaterials Engineering Division, Lawrence Livermore National Laboratory.
William J BenettMaterials Engineering Division, Lawrence Livermore National Laboratory.
Mihail BoraMaterials Engineering Division, Lawrence Livermore National Laboratory.
Alison BurklundMaterials Engineering Division, Lawrence Livermore National Laboratory.
Thomas R MetzMaterials Engineering Division, Lawrence Livermore National Laboratory.
Maxim ShusteffMaterials Engineering Division, Lawrence Livermore National Laboratory; shusteff1@llnl.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A major advantage of microfluidic devices is the ability to manipulate small sample volumes, thus reducing reagent waste and preserving precious sample. However, to achieve robust sample manipulation it is necessary to address device integration with the macroscale environment. To realize repeatable, sensitive particle separation with microfluidic devices, this protocol presents a complete automated and integrated microfluidic platform that enables precise processing of 0.15-1.5 ml samples using microfluidic devices. Important aspects of this system include modular device layout and robust fixtures resulting in reliable and flexible world to chip connections, and fully-automated fluid handling which accomplishes closed-loop sample collection, system cleaning and priming steps to ensure repeatable operation. Different microfluidic devices can be used interchangeably with this architecture. Here we incorporate an acoustofluidic device, detail its characterization, performance optimization, and demonstrate its use for size-separation of biological samples. By using real-time feedback during separation experiments, sample collection is optimized to conserve and concentrate sample. Although requiring the integration of multiple pieces of equipment, advantages of this architecture include the ability to process unknown samples with no additional system optimization, ease of device replacement, and precise, robust sample processing.

Identifiers

PMID26651055
PMCPMC4692749

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.