Antibiotic Resistance: Opportunities and Challenges

A special issue of Antibiotics (ISSN 2079-6382).

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 4572

Special Issue Editors

College of Light Industry and Food Science, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China
Interests: antimicrobial resistance; biofilms; viable but non-culturable (VBNC) and persistence; stress response; polymicrobial interaction
Special Issues, Collections and Topics in MDPI journals
Department of Microbiology and Immunology, Standford University School of Medicine, Stanford, CA, USA
Interests: infectious diseases; tuberculosis; malaria; antibiotic resistance; infection immunity; vaccines

Special Issue Information

Dear Colleagues,

Infectious diseases are a major cause of mortality. The advent of antibiotics markedly reduced infectious-disease-associated death and increased life expectancy, which underpin modern medicine. However, the number of infections is increasing globally, especially those which cannot be treated with the currently available antibiotics. Antibiotic resistance has become one of the greatest threats to human and animal health; it is predicted that antimicrobial-resistant infections will cause around 10 million deaths by 2050 and result in huge economic losses if no appropriate actions are taken. Therefore, it is critical that the latest achievements and challenges in antibiotic resistance are summarized.

This Special Issue aims to present recent advances in the area of antibiotic treatment and resistance. Original research manuscripts, short communications, reviews and case reports are all welcome. Topics of interest include, but are not limited to:

  • The origin and evaluation of antibiotics resistance;
  • Antibiotic resistance mechanisms in bacterial infection;
  • Current antibiotic use;
  • Current strategies in the management of antibiotics resistance;
  • The exploration of new and potential antibacterial agents;
  • The discovery of new antibiotics;
  • The immune responses against bacterial infection;
  • Host–microbiome–pathogen interaction.

Dr. Junyan Liu
Dr. Jing Guo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Antibiotics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • antibiotic resistance
  • bacterial infection
  • infectious diseases
  • polymicrobial interaction
  • stress response

Published Papers (1 paper)

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Review

11 pages, 650 KiB  
Review
Deep Learning and Antibiotic Resistance
by Stefan Lucian Popa, Cristina Pop, Miruna Oana Dita, Vlad Dumitru Brata, Roxana Bolchis, Zoltan Czako, Mohamed Mehdi Saadani, Abdulrahman Ismaiel, Dinu Iuliu Dumitrascu, Simona Grad, Liliana David, Gabriel Cismaru and Alexandru Marius Padureanu
Antibiotics 2022, 11(11), 1674; https://doi.org/10.3390/antibiotics11111674 - 21 Nov 2022
Cited by 7 | Viewed by 4055
Abstract
Antibiotic resistance (AR) is a naturally occurring phenomenon with the capacity to render useless all known antibiotics in the fight against bacterial infections. Although bacterial resistance appeared before any human life form, this process has accelerated in the past years. Important causes of [...] Read more.
Antibiotic resistance (AR) is a naturally occurring phenomenon with the capacity to render useless all known antibiotics in the fight against bacterial infections. Although bacterial resistance appeared before any human life form, this process has accelerated in the past years. Important causes of AR in modern times could be the over-prescription of antibiotics, the presence of faulty infection-prevention strategies, pollution in overcrowded areas, or the use of antibiotics in agriculture and farming, together with a decreased interest from the pharmaceutical industry in researching and testing new antibiotics. The last cause is primarily due to the high costs of developing antibiotics. The aim of the present review is to highlight the techniques that are being developed for the identification of new antibiotics to assist this lengthy process, using artificial intelligence (AI). AI can shorten the preclinical phase by rapidly generating many substances based on algorithms created by machine learning (ML) through techniques such as neural networks (NN) or deep learning (DL). Recently, a text mining system that incorporates DL algorithms was used to help and speed up the data curation process. Moreover, new and old methods are being used to identify new antibiotics, such as the combination of quantitative structure-activity relationship (QSAR) methods with ML or Raman spectroscopy and MALDI-TOF MS combined with NN, offering faster and easier interpretation of results. Thus, AI techniques are important additional tools for researchers and clinicians in the race for new methods of overcoming bacterial resistance. Full article
(This article belongs to the Special Issue Antibiotic Resistance: Opportunities and Challenges)
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