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Cited by 545

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

From in vitro to in vivo Models of Bacterial Biofilm-Related Infections

Open access
Lebeaux, David, Chauhan, Ashwini, Rendueles, Olaya, Beloin, Christophe·2013·Pathogens

Abstract

The influence of microorganisms growing as sessile communities in a large number of human infections has been extensively studied and recognized for 30–40 years, therefore warranting intense scientific and medical research. Nonetheless, mimicking the biofilm-life style of bacteria and biofilm-related infections has been an arduous task. Models used to study biofilms range from simple in vitro to complex in vivo models of tissues or device-related infections. These different models have progressively contributed to the current knowledge of biofilm physiology within the host context. While far from a complete understanding of the multiple elements controlling the dynamic interactions between the host and biofilms, we are nowadays witnessing the emergence of promising preventive or curative strategies to fight biofilm-related infections. This review undertakes a comprehensive analysis of the literature from a historic perspective commenting on the contribution of the different models and discussing future venues and new approaches that can be merged with more traditional techniques in order to model biofilm-infections and efficiently fight them.

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Metadata

Authors
Lebeaux, D., Chauhan, A., Rendueles, O., & Beloin, C.
Venue
Pathogens
Publisher
MDPI AG
Published
2013-05-13
Volume
2
Issue
2
Pages
288-356
ISSN
2076-0817 (ISSN-L)
OpenAlex
W2036596008
Cited by
545
References
26
FWCI
10.49
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: From in vitro to in vivo Models of Bacterial Biofilm-Related Infections. https://app.cochat.ai/papers/10.3390/pathogens2020288
The paper
Lebeaux, D., Chauhan, A., Rendueles, O., & Beloin, C. (2013). From in vitro to in vivo Models of Bacterial Biofilm-Related Infections. Pathogens. https://doi.org/10.3390/pathogens2020288

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

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