ArticlemBio2019
Simulating Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model.
Article in mBio, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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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.
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Who cites it
19 citing papers in PubMed.
- Antechokinetics, the kinetics of antimicrobial resistance molecules.Frontiers in pharmacology · 2026Review
- Modelling Plasmid-Mediated Horizontal Gene Transfer in Biofilms.Bulletin of mathematical biology · 2024Article
- Membrane computing simulation of sexually transmitted bacterial infections in hotspots of individuals with various risk behaviors.Microbiology spectrum · 2024Article
- Antimicrobial Resistance in Bacteria from Meat and Meat Products: A One Health Perspective.Microorganisms · 2023Review
- Antimicrobial Resistance in the Global Health Network: Known Unknowns and Challenges for Efficient Responses in the 21st Century.Microorganisms · 2023Review
- Mathematical models to study the biology of pathogens and the infectious diseases they cause.iScience · 2022Review
- Simulating the efficacy of vaccines on the epidemiological dynamics of SARS-CoV-2 in a membrane computing model.microLife · 2022Article
- Evolutionary Pathways and Trajectories in Antibiotic Resistance.Clinical microbiology reviews · 2021Article
- Prevalence of multi-drug resistant bacteria associated with foods and drinks in Nigeria (2015-2020): A systematic review.Italian journal of food safety · 2021Article
- Mathematical Models of Plasmid Population Dynamics.Frontiers in microbiology · 2021Review
- The ecology of plasmid-coded antibiotic resistance: a basic framework for experimental research and modeling.Computational and structural biotechnology journal · 2021Review
- Antibiotic resistance: Time of synthesis in a post-genomic age.Computational and structural biotechnology journal · 2021Review
- Simulating the impact of non-pharmaceutical interventions limiting transmission in COVID-19 epidemics using a membrane computing model.microLife · 2021Article
- Allogenous Selection of Mutational Collateral Resistance: Old Drugs Select for New Resistance Within Antibiotic Families.Frontiers in microbiology · 2021Review
- Simulating the Influence of Conjugative-Plasmid Kinetic Values on the Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model.Antimicrobial agents and chemotherapy · 2020Article
- Horizontal Gene Transfer: From Evolutionary Flexibility to Disease Progression.Frontiers in cell and developmental biology · 2020Review
- Defining and combating antibiotic resistance from One Health and Global Health perspectives.Nature microbiology · 2019Review
- Mathematical modelling to study the horizontal transfer of antimicrobial resistance genes in bacteria: current state of the field and recommendations.Journal of the Royal Society, Interface · 2019Article
- Gene Transmission in the One Health Microbiosphere and the Channels of Antimicrobial Resistance.Frontiers in microbiology · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Membrane computing is a bio-inspired computing paradigm whose devices are the so-called membrane systems or P systems. The P system designed in this work reproduces complex biological landscapes in the computer world. It uses nested "membrane-surrounded entities" able to divide, propagate, and die; to be transferred into other membranes; to exchange informative material according to flexible rules; and to mutate and be selected by external agents. This allows the exploration of hierarchical interactive dynamics resulting from the probabilistic interaction of genes (phenotypes), clones, species, hosts, environments, and antibiotic challenges. Our model facilitates analysis of several aspects of the rules that govern the multilevel evolutionary biology of antibiotic resistance. We examined a number of selected landscapes where we predict the effects of different rates of patient flow from hospital to the community and vice versa, the cross-transmission rates between patients with bacterial propagules of different sizes, the proportion of patients treated with antibiotics, and the antibiotics and dosing found in the opening spaces in the microbiota where resistant phenotypes multiply. We also evaluated the selective strengths of some drugs and the influence of the time 0 resistance composition of the species and bacterial clones in the evolution of resistance phenotypes. In summary, we provide case studies analyzing the hierarchical dynamics of antibiotic resistance using a novel computing model with reciprocity within and between levels of biological organization, a type of approach that may be expanded in the multilevel analysis of complex microbial landscapes.
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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 OpenQuestion graph.