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Cited by 490

The DOI matches its Crossref record; 253 of the 253 references it cites were found in a registry or an index.

Antibiotic Resistance and the MRSA Problem

Open access
Vestergaard, Martin, Frees, Dorte, Ingmer, Hanne·2019·Microbiology Spectrum

Abstract

Staphylococcus aureus is capable of becoming resistant to all classes of antibiotics clinically available and resistance can develop through de novo mutations in chromosomal genes or through acquisition of horizontally transferred resistance determinants. This review covers the most important antibiotics available for treatment of S. aureus infections and a special emphasis is dedicated to the current knowledge of the wide variety of resistance mechanisms that S. aureus employ to withstand antibiotics. Since resistance development has been inevitable for all currently available antibiotics, new therapies are continuously under development. Besides development of new small molecules affecting cell viability, alternative approaches including anti-virulence and bacteriophage therapeutics are being investigated and may become important tools to combat staphylococcal infections in the future.

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Crossref · 10.1128/microbiolspec.gpp3-0057-2018

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Metadata

Authors
Vestergaard, M., Frees, D., & Ingmer, H.
Venue
Microbiology Spectrum
Published
2019-04-12
Volume
7
Issue
2
ISSN
2165-0497 (ISSN-L)
OpenAlex
W2923656972
Cited by
490
References
253
FWCI
24.02
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Antibiotic Resistance and the MRSA Problem. https://app.cochat.ai/papers/10.1128/microbiolspec.gpp3-0057-2018
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Vestergaard, M., Frees, D., & Ingmer, H. (2019). Antibiotic Resistance and the MRSA Problem. Microbiology Spectrum. https://doi.org/10.1128/microbiolspec.gpp3-0057-2018

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.