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Cited by 367

The DOI matches its Crossref record; 117 of the 117 references it cites were found in a registry or an index.

Micro- and Nanotopography Sensitive Bacterial Attachment Mechanisms: A Review

Open access
Cheng, Yifan, Feng, Guoping, Moraru, Carmen I.·2019·Frontiers in Microbiology

Abstract

Bacterial attachment to material surfaces can lead to the development of biofilms that cause severe economic and health problems. The outcome of bacterial attachment is determined by a combination of bacterial sensing of material surfaces by the cell and the physicochemical factors in the near-surface environment. This paper offers a systematic review of the effects of surface topography on a range of antifouling mechanisms, with a focus on how topographical scale, from micro- to nanoscale, may influence bacterial sensing of and attachment to material surfaces. A good understanding of these mechanisms can facilitate the development of antifouling surfaces based on surface topography, with applications in various sectors of human life and activity including healthcare, food, and water treatment.

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Registry

Crossref · 10.3389/fmicb.2019.00191

Cites

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Metadata

Authors
Cheng, Y., Feng, G., & Moraru, C. I.
Venue
Frontiers in Microbiology
Published
2019-02-21
Volume
10
Pages
191-191
ISSN
1664-302X (ISSN-L)
OpenAlex
W2917489700
Cited by
367
References
117
FWCI
11.82
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Micro- and Nanotopography Sensitive Bacterial Attachment Mechanisms: A Review. https://app.cochat.ai/papers/10.3389/fmicb.2019.00191
The paper
Cheng, Y., Feng, G., & Moraru, C. I. (2019). Micro- and Nanotopography Sensitive Bacterial Attachment Mechanisms: A Review. Frontiers in Microbiology. https://doi.org/10.3389/fmicb.2019.00191

Data sources

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.