Evidence map›Paper›PMID 32566890›Full record

ArticleAPL bioengineering2020

An organosynthetic soft robotic respiratory simulator.

Markus A Horvath, Lucy Hu, Tanja Mueller, Jon Hochstein, Luca Rosalia, Kathryn A Hibbert, Charles C Hardin, Ellen T Roche

Abstract read
In one paragraph

Article in APL bioengineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Markus A Horvath
Tanja Mueller
Jon Hochstein
Luca Rosalia
Kathryn A Hibbert
Charles C Hardin

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work, we describe a benchtop model that recreates the motion and function of the diaphragm using a combination of advanced robotic and organic tissue. First, we build a high-fidelity anthropomorphic model of the diaphragm using thermoplastic and elastomeric material based on clinical imaging data. We then attach pneumatic artificial muscles to this elastomeric diaphragm, pre-programmed to move in a clinically relevant manner when pressurized. By inserting this diaphragm as the divider between two chambers in a benchtop model-one representing the thorax and the other the abdomen-and subsequently activating the diaphragm, we can recreate the pressure changes that cause lungs to inflate and deflate during regular breathing. Insertion of organic lungs in the thoracic cavity demonstrates this inflation and deflation in response to the pressures generated by our robotic diaphragm. By tailoring the input pressures and timing, we can represent different breathing motions and disease states. We instrument the model with multiple sensors to measure pressures, volumes, and flows and display these data in real-time, allowing the user to vary inputs such as the breathing rate and compliance of various components, and so they can observe and measure the downstream effect of changing these parameters. In this way, the model elucidates fundamental physiological concepts and can demonstrate pathology and the interplay of components of the respiratory system. This model will serve as an innovative and effective pedagogical tool for educating students on respiratory physiology and pathology in a user-controlled, interactive manner. It will also serve as an anatomically and physiologically accurate testbed for devices or pleural sealants that reside in the thoracic cavity, representing a vast improvement over existing models and ultimately reducing the requirement for testing these technologies in animal models. Finally, it will act as an impactful visualization tool for educating and engaging the broader community.

Identifiers

PMID32566890
PMCPMC7286700

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.