ReviewACS omega2025
Challenges and Opportunities: Interplay between Infectious Disease and Antimicrobial Resistance in Medical Device Surface Applications.
Review in ACS omega, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Mapping the Convergence of Frontier Technologies for Major Environmental Challenges: A Chemical and Molecular Perspective on the Use of AI for Climate Action and Antimicrobial Resistance.Molecules (Basel, Switzerland) · 2026Review
- AI-Driven Discovery and Design of Antimicrobial Peptides: Progress, Challenges, and Opportunities.Probiotics and antimicrobial proteins · 2026Review
- Biosurfactants as Antibiofilm Agents for Medical Devices: Mechanisms, Evidence and Integration into Infection Prevention and Control.Microorganisms · 2026Review
- Artificial Intelligence-Driven Discovery and Optimization of Antimicrobial Peptides Targeting ESKAPE Pathogens and Multidrug-Resistant Fungi.Microorganisms · 2026Review
- Dental devices and antimicrobial resistance: challenges, innovations, and regulatory compliances.Frontiers in medical technology · 2026Review
- Special Issue "Natural Compounds: Advances in Antimicrobial Activity".International journal of molecular sciences · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Antimicrobial resistance (AMR) is a growing silent pandemic driven by multidrug-resistant infections, particularly those associated with medical devices such as dental implants, heart valves, and urinary catheters. This review addresses the urgent need for alternative antimicrobial strategies by exploring the integration of artificial intelligence (AI) in the discovery of antimicrobial peptides (AMPs) and the rational design of bioactive surfaces. We describe how AI-based models accelerate the identification and optimization of peptide candidates with potent antibiofilm activity. Moreover, we examine recent advancements in surface engineering, such as biomimetic coatings, quorum sensing inhibitors, and enzyme-based strategies, that disrupt bacterial colonization and biofilm formation. The novelty of this work lies in its unified perspective that bridges computational prediction, materials science, and microbial pathogenesis to inform the next generation of antimicrobial surfaces. By highlighting innovative AI-assisted approaches and emerging hybrid strategies, this review underscores their potential to mitigate device-associated infections and address the broader challenge of AMR in healthcare settings.
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.