ArticlePloS one2013
Predictive computational modeling of the mucosal immune responses during Helicobacter pylori infection.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05449028 (Helicobacter Pylori Eradication Therapy in Portugal), which is not on this map. Cited by 37 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.
Helicobacter Pylori Eradication Therapy in Portugal: Prospective, Randomized, Blind and Multicentre Trial on the Efficacy of Quadruple Therapies and Their Clinical Impact, and Immunological and Gut Microbiota Changes
Who cites it
37 citing papers in PubMed, 61 citations in OpenAlex.
- M cells targeted H. pylori antigen SAM-FAdE displayed on bacterium-like particles induce protective immunity.Journal of nanobiotechnology · 2025Article
- Current research on the interaction between Helicobacter pylori and macrophages.Molecular biology reports · 2024Review
- Article
- Role of Gastric Microorganisms Other thanBioMed research international · 2022Review
- MicroRNA Modulation of Host Immune Response and Inflammation Triggered byInternational journal of molecular sciences · 2021Review
- A Dynamic Quantitative Systems Pharmacology Model of Inflammatory Bowel Disease: Part 1 - Model Framework.Clinical and translational science · 2021Article
- Trends in mathematical modeling of host-pathogen interactions.Cellular and molecular life sciences : CMLS · 2020Review
- The Role of Gastric Mucosal Immunity in Gastric Diseases.Journal of immunology research · 2020Review
- Agent-based models of inflammation in translational systems biology: A decade later.Wiley interdisciplinary reviews. Systems biology and medicine · 2019Review
- High-resolution computational modeling of immune responses in the gut.GigaScience · 2019Article
- Multiscale Agent-Based and Hybrid Modeling of the Tumor Immune Microenvironment.Processes (Basel, Switzerland) · 2019Article
- Dynamic balance of pro- and anti-inflammatory signals controls disease and limits pathology.Immunological reviews · 2018Review
- Challenges in Personalized Nutrition and Health.Frontiers in nutrition · 2018Article
- Multiscale positive feedbacks contribute to unidirectional gastric disease progression induced by helicobacter pylori infection.BMC systems biology · 2017Article
- Cooperation of Gastric Mononuclear Phagocytes withJournal of immunology (Baltimore, Md. : 1950) · 2017Article
- Facing the challenges of multiscale modelling of bacterial and fungal pathogen-host interactions.Briefings in functional genomics · 2017Review
- Solving Immunology?Trends in immunology · 2017Review
- Article
- Mathematical Models for Immunology: Current State of the Art and Future Research Directions.Bulletin of mathematical biology · 2016Review
- Mucosal Interactions between Genetics, Diet, and Microbiome in Inflammatory Bowel Disease.Frontiers in immunology · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 2 institutions in 1 country.
Funding
Abstract
T helper (Th) cells play a major role in the immune response and pathology at the gastric mucosa during Helicobacter pylori infection. There is a limited mechanistic understanding regarding the contributions of CD4+ T cell subsets to gastritis development during H. pylori colonization. We used two computational approaches: ordinary differential equation (ODE)-based and agent-based modeling (ABM) to study the mechanisms underlying cellular immune responses to H. pylori and how CD4+ T cell subsets influenced initiation, progression and outcome of disease. To calibrate the model, in vivo experimentation was performed by infecting C57BL/6 mice intragastrically with H. pylori and assaying immune cell subsets in the stomach and gastric lymph nodes (GLN) on days 0, 7, 14, 30 and 60 post-infection. Our computational model reproduced the dynamics of effector and regulatory pathways in the gastric lamina propria (LP) in silico. Simulation results show the induction of a Th17 response and a dominant Th1 response, together with a regulatory response characterized by high levels of mucosal Treg) cells. We also investigated the potential role of peroxisome proliferator-activated receptor γ (PPARγ) activation on the modulation of host responses to H. pylori by using loss-of-function approaches. Specifically, in silico results showed a predominance of Th1 and Th17 cells in the stomach of the cell-specific PPARγ knockout system when compared to the wild-type simulation. Spatio-temporal, object-oriented ABM approaches suggested similar dynamics in induction of host responses showing analogous T cell distributions to ODE modeling and facilitated tracking lesion formation. In addition, sensitivity analysis predicted a crucial contribution of Th1 and Th17 effector responses as mediators of histopathological changes in the gastric mucosa during chronic stages of infection, which were experimentally validated in mice. These integrated immunoinformatics approaches characterized the induction of mucosal effector and regulatory pathways controlled by PPARγ during H. pylori infection affecting disease outcomes.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.