ArticleFrontiers in microbiology2015
Deciphering chemokine properties by a hybrid agent-based model of Aspergillus fumigatus infection in human alveoli.
Article in Frontiers in microbiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 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
24 citing papers in PubMed, 35 citations in OpenAlex.
- Article
- Partially-functional exhausted CD8+ T cells can contribute to short-term viral suppression: a computational prediction for children with perinatal HIV.bioRxiv : the preprint server for biology · 2025Article
- Complex-mediated evasion: modeling defense against antimicrobial peptides with application to human-pathogenic fungus Candida albicans.NPJ systems biology and applications · 2025Article
- Timing matters in macrophage/CD4+ T cell interactions: an agent-based model comparingmSystems · 2025Article
- Simulation approach for common female cancers: a brief review.Frontiers in oncology · 2025Review
- Spatiotemporal modeling quantifies cellular contributions to uptake of Aspergillus fumigatus in the human lung.Communications biology · 2024Article
- Surrogate infection model predicts optimal alveolar macrophage number for clearance of Aspergillus fumigatus infections.NPJ systems biology and applications · 2023Article
- Multi-scale mechanistic modelling of the host defence in invasive aspergillosis reveals leucocyte activation and iron acquisition as drivers of infection outcome.Journal of the Royal Society, Interface · 2022Article
- Novel Insights intoJournal of fungi (Basel, Switzerland) · 2022Review
- Dynamic optimization reveals alveolar epithelial cells as key mediators of host defense in invasive aspergillosis.PLoS computational biology · 2021Article
- Ex vivo immune profiling in patient blood enables quantification of innate immune effector functions.Scientific reports · 2021Article
- Editorial: Genetics Architecture and Underlying Molecular Mechanisms in Host-Pathogen Interactions.Frontiers in genetics · 2021Article
- Trends in mathematical modeling of host-pathogen interactions.Cellular and molecular life sciences : CMLS · 2020Review
- A biomathematical model of immune response and barrier function in mice with pneumococcal lung infection.PloS one · 2020Article
- Hybrid Agent-Based Modeling ofFrontiers in microbiology · 2020Article
- Comparative Assessment of Aspergillosis by Virtual Infection Modeling in Murine and Human Lung.Frontiers in immunology · 2019Article
- Quantitative Simulations Predict Treatment Strategies Against Fungal Infections in Virtual Neutropenic Patients.Frontiers in immunology · 2018Article
- Bacterial Adherence and Dwelling Probability: Two Drivers of Early Alveolar Infection byFrontiers in cellular and infection microbiology · 2018Article
- Predictive Virtual Infection Modeling of Fungal Immune Evasion in Human Whole Blood.Frontiers in immunology · 2018Article
- Toxicity of orally inhaled drug formulations at the alveolar barrier: parameters for initial biological screening.Drug delivery · 2017Article
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 at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The ubiquitous airborne fungal pathogen Aspergillus fumigatus is inhaled by humans every day. In the lung, it is able to quickly adapt to the humid environment and, if not removed within a time frame of 4-8 h, the pathogen may cause damage by germination and invasive growth. Applying a to-scale agent-based model of human alveoli to simulate early A. fumigatus infection under physiological conditions, we recently demonstrated that alveolar macrophages require chemotactic cues to accomplish the task of pathogen detection within the aforementioned time frame. The objective of this study is to specify our general prediction on the as yet unidentified chemokine by a quantitative analysis of its expected properties, such as the diffusion coefficient and the rates of secretion and degradation. To this end, the rule-based implementation of chemokine diffusion in the initial agent-based model is revised by numerically solving the spatio-temporal reaction-diffusion equation in the complex structure of the alveolus. In this hybrid agent-based model, alveolar macrophages are represented as migrating agents that are coupled to the interactive layer of diffusing molecule concentrations by the kinetics of chemokine receptor binding, internalization and re-expression. Performing simulations for more than a million virtual infection scenarios, we find that the ratio of secretion rate to the diffusion coefficient is the main indicator for the success of pathogen detection. Moreover, a subdivision of the parameter space into regimes of successful and unsuccessful parameter combination by this ratio is specific for values of the migration speed and the directional persistence time of alveolar macrophages, but depends only weakly on chemokine degradation rates.
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.