Evidence map›Paper›PMID 27214269›Full record

ArticleJournal of visualized experiments : JoVE2016

A Microfluidic Model of Biomimetically Breathing Pulmonary Acinar Airways.

Rami Fishler, Josué Sznitman

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In one paragraph

Article in Journal of visualized experiments : JoVE, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
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  9. Article
  10. Through the Looking Glass:Applied in vitro toxicology · 2018
    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

2 authors.

Rami FishlerDepartment of Biomedical Engineering, Technion - Israel Institute of Technology.
Josué SznitmanDepartment of Biomedical Engineering, Technion - Israel Institute of Technology; sznitman@bm.technion.ac.il.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantifying respiratory flow characteristics in the pulmonary acinar depths and how they influence inhaled aerosol transport is critical towards optimizing drug inhalation techniques as well as predicting deposition patterns of potentially toxic airborne particles in the pulmonary alveoli. Here, soft-lithography techniques are used to fabricate complex acinar-like airway structures at the truthful anatomical length-scales that reproduce physiological acinar flow phenomena in an optically accessible system. The microfluidic device features 5 generations of bifurcating alveolated ducts with periodically expanding and contracting walls. Wall actuation is achieved by altering the pressure inside water-filled chambers surrounding the thin PDMS acinar channel walls both from the sides and the top of the device. In contrast to common multilayer microfluidic devices, where the stacking of several PDMS molds is required, a simple method is presented to fabricate the top chamber by embedding the barrel section of a syringe into the PDMS mold. This novel microfluidic setup delivers physiological breathing motions which in turn give rise to characteristic acinar air-flows. In the current study, micro particle image velocimetry (µPIV) with liquid suspended particles was used to quantify such air flows based on hydrodynamic similarity matching. The good agreement between µPIV results and expected acinar flow phenomena suggest that the microfluidic platform may serve in the near future as an attractive in vitro tool to investigate directly airborne representative particle transport and deposition in the acinar regions of the lungs.

Indexed as

LungMicrofluidicsModels, BiologicalPulmonary AlveoliAnimalsHumansRespiration

Identifiers

PMID27214269
PMCPMC4942038

What OpenQuestion holds

Textmetadata
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.