Evidence map›Paper›PMID 39301087›Full record

ArticleBiomicrofluidics2024

Insights into the fluid dynamics of bioaerosol formation in a model respiratory tract.

Sudipta Saha, Manish Kumar Manna, Aranyak Chakravarty, Sourav Sarkar, Achintya Mukhopadhyay, Swarnendu Sen

Abstract read
In one paragraph

Article in Biomicrofluidics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

6 authors.

Sudipta SahaSchool of Nuclear Studies and Application, Jadavpur University (Salt Lake campus), Kolkata 700106, India.ORCID https://orcid.org/0009-0009-1577-9065
Manish Kumar MannaDepartment of Mechanical Engineering, Jadavpur University, Kolkata 700032, India.ORCID https://orcid.org/0009-0003-1806-5849
Aranyak ChakravartySchool of Nuclear Studies and Application, Jadavpur University (Salt Lake campus), Kolkata 700106, India.ORCID https://orcid.org/0000-0002-4864-7036
Sourav SarkarDepartment of Mechanical Engineering, Jadavpur University, Kolkata 700032, India.ORCID https://orcid.org/0000-0003-0722-5221
Achintya MukhopadhyayDepartment of Mechanical Engineering, Jadavpur University, Kolkata 700032, India.ORCID https://orcid.org/0000-0002-0622-0616
Swarnendu SenDepartment of Mechanical Engineering, Jadavpur University, Kolkata 700032, India.ORCID https://orcid.org/0000-0001-5580-4901

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bioaerosols produced within the respiratory system play an important role in respiratory disease transmission. These include infectious diseases such as common cold, influenza, tuberculosis, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among several others. It is, therefore, of immense interest to understand how bioaerosols are produced within the respiratory system. This has not been extensively investigated. The present study computationally investigates how bioaerosols are produced in a model respiratory tract due to hydrodynamic interactions between breathed air and a thin mucus layer, which lines the inner surface of the tract. It is observed that Kelvin-Helmholtz instability is established in the thin mucus layer due to associated fluid dynamics. This induces interfacial surface waves which fragment forming bioaerosols under certain conditions. A regime map is created-based on pertinent dimensionless parameters-to enable identification of such conditions. Analysis indicates that bioaerosols may be produced even under normal breathing conditions, contrary to expectations, depending on mucus rheology and thickness of the mucus layer. This is possible during medical conditions as well as during some treatment protocols. However, such bioaerosols are observed to be larger (

Identifiers

PMID39301087
PMCPMC11410387

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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.