ArticlePloS one2014
Non-lethal control of the cariogenic potential of an agent-based model for dental plaque.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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.
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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
13 citing papers in PubMed, 35 citations in OpenAlex.
- Article
- Sweet Orange Juice Processing By-Product Extracts: A Caries Management Alternative to Chlorhexidine.Biomolecules · 2023Article
- Salivary microbiome and metabolome analysis of severe early childhood caries.BMC oral health · 2023Article
- In silico study of hyposalivation and sugar exposure on biofilm dysbiosis.JADA foundational science · 2023Article
- The Plaque Microbiota Community of Giant Panda (Frontiers in cellular and infection microbiology · 2022Article
- In Silico Modeling of Hyposalivation and Biofilm Dysbiosis in Root Caries.Journal of dental research · 2021Article
- Agent Based Models of Polymicrobial Biofilms and the Microbiome-A Review.Microorganisms · 2021Review
- Future directions for studying resilience of the oral ecosystem.British dental journal · 2020Article
- Oral Microbiome Alterations Associated with Early Childhood Caries Highlight the Importance of Carbohydrate Metabolic Activities.mSystems · 2019Article
- In silico modelling to differentiate the contribution of sugar frequency versus total amount in driving biofilm dysbiosis in dental caries.Scientific reports · 2017Article
- Article
- Biofilm formation affects surface properties of novel bioactive glass-containing composites.Dental materials : official publication of the Academy of Dental Materials · 2015Article
- Prospects of oral disease control in the future - an opinion.Journal of oral microbiology · 2014Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dental caries or tooth decay is a prevalent global disease whose causative agent is the oral biofilm known as plaque. According to the ecological plaque hypothesis, this biofilm becomes pathogenic when external challenges drive it towards a state with a high proportion of acid-producing bacteria. Determining which factors control biofilm composition is therefore desirable when developing novel clinical treatments to combat caries, but is also challenging due to the system complexity and the existence of multiple bacterial species performing similar functions. Here we employ agent-based mathematical modelling to simulate a biofilm consisting of two competing, distinct types of bacterial populations, each parameterised by their nutrient uptake and aciduricity, periodically subjected to an acid challenge resulting from the metabolism of dietary carbohydrates. It was found that one population was progressively eliminated from the system to give either a benign or a pathogenic biofilm, with a tipping point between these two fates depending on a multiplicity of factors relating to microbial physiology and biofilm geometry. Parameter sensitivity was quantified by individually varying the model parameters against putative experimental measures, suggesting non-lethal interventions that can favourably modulate biofilm composition. We discuss how the same parameter sensitivity data can be used to guide the design of validation experiments, and argue for the benefits of in silico modelling in providing an additional predictive capability upstream from in vitro experiments.
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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.