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Cited by 270

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Particle size and pathogenicity in the respiratory tract

Open access
Thomas, Richard James·2013·Virulence

Abstract

Particle size dictates where aerosolized pathogens deposit in the respiratory tract, thereafter the pathogens potential to cause disease is influenced by tissue tropism, clearance kinetics and the host immunological response. This interplay brings pathogens into contact with a range of tissues spanning the respiratory tract and associated anatomical structures. In animal models, differential deposition within the respiratory tract influences infection kinetics for numerous select agents. Greater numbers of pathogens are required to infect the upper (URT) compared with the lower respiratory tract (LRT), and in comparison the URT infections are protracted with reduced mortality. Pathogenesis in the URT is characterized by infection of the URT lymphoid tissues, cervical lymphadenopathy and septicemia, closely resembling reported human infections of the URT. The olfactory, gastrointestinal, and ophthalmic systems are also infected in a pathogen-dependent manner. The relevant literature is reviewed with respect to particle size and infection of the URT in animal models and humans.

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Metadata

Authors
Thomas, R. J.
Venue
Virulence
Published
2013-11-15
Volume
4
Issue
8
Pages
847-858
ISSN
  • 2150-5594 (ISSN-L)
  • 2150-5608
OpenAlex
W2055982648
Cited by
270
References
6
FWCI
3.41
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Particle size and pathogenicity in the respiratory tract. https://app.cochat.ai/papers/10.4161/viru.27172
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Thomas, R. J. (2013). Particle size and pathogenicity in the respiratory tract. Virulence. https://doi.org/10.4161/viru.27172

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.