ArticleThe Journal of surgical research2013
Agent-based model of epithelial host-pathogen interactions in anastomotic leak.
Article in The Journal of surgical research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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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
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- Gut microbiota and postoperative complications in colorectal surgery and its potential association with intestinal permeability and NLRP6 inflammasome.Frontiers in immunology · 2025Pooled it
- Review
- Exploring the Modulatory Effects of Gut Microbiota in Anti-Cancer Therapy.Frontiers in oncology · 2021Review
- Intestinal Microbiota in Colorectal Cancer Surgery.Cancers · 2020Review
- Trends in mathematical modeling of host-pathogen interactions.Cellular and molecular life sciences : CMLS · 2020Review
- Intestinal Microbiota: A Novel Target to Improve Anti-Tumor Treatment?International journal of molecular sciences · 2019Review
- Facing the challenges of multiscale modelling of bacterial and fungal pathogen-host interactions.Briefings in functional genomics · 2017Review
- Gut Microbiota and Colorectal Surgery: Impact on Postoperative Complications.Clinics in colon and rectal surgery · 2016Review
- Augmenting Surgery via Multi-scale Modeling and Translational Systems Biology in the Era of Precision Medicine: A Multidisciplinary Perspective.Annals of biomedical engineering · 2016Review
- Investigation of inflammation and tissue patterning in the gut using a Spatially Explicit General-purpose Model of Enteric Tissue (SEGMEnT).PLoS computational biology · 2014Article
- Examining the pathogenesis of breast cancer using a novel agent-based model of mammary ductal epithelium dynamics.PloS one · 2013Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
backgroundThere is a growing recognition of the significance of host-pathogen interactions (HPIs) in gut biology leading to a reassessment of the role of bacteria in intestinal anastomotic leak. Understanding the complexities of the early postsurgical gut HPI requires integrating knowledge of both epithelial and bacterial behaviors to generate hypotheses of potential mechanisms of interaction. Agent-based modeling is a computational method well suited to achieve this goal, and we use an agent-based model (ABM) to examine alterations in the HPI affecting reestablishment of the epithelial barrier that may subsequently lead to anastomotic leak.
methodsComputational agents representing Pseudomonas aeruginosa were added to a previously validated ABM of epithelial restitution. Simulated experiments were performed examining the effect of radiation on bacterial binding to epithelial cells, plausibility of putative binding targets, and potential mechanisms of epithelial cell killing by virulent bacteria.
resultsSimulation experiments incorporating radiation effects on epithelial monolayers produced binding patterns akin to those seen in vitro and suggested that promotility integrin-laminin associations represent potential sites for bacterial binding and disruption of restitution. Simulations of potential mechanisms of epithelial cell killing suggested that an injected cytotoxin was the means by which virulent bacteria produced the tissue destruction needed to generate an anastomotic leak, a mechanism subsequently confirmed with genotyping of the virulent P aeruginosa strain.
conclusionsThis study emphasizes the utility of ABM as an adjunct to traditional research methods and provides insights into the potentially critical role of HPI in the pathogenesis of anastomotic leak.
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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.