ArticleFrontiers in immunology2015
Mathematical Modeling of Early Cellular Innate and Adaptive Immune Responses to Ischemia/Reperfusion Injury and Solid Organ Allotransplantation.
Article in Frontiers in immunology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Macrophages tune responses to pathogen dynamics through TLR4 stimulation memory and by licensing susceptibility to IL-10.bioRxiv : the preprint server for biology · 2026Article
- Understanding Immune Dynamics in Liver Transplant Through Mathematical Modeling.Bulletin of mathematical biology · 2025Article
- Integrative lymph node-mimicking models created with biomaterials and computational tools to study the immune system.Materials today. Bio · 2022Review
- Modeling the Potential of Treg-Based Therapies for Transplant Rejection: Effect of Dose, Timing, and Accumulation Site.Transplant international : official journal of the European Society for Organ Transplantation · 2022Article
- The Effects of Tacrolimus on Tissue-Specific, Protein-Level Inflammatory Networks in Vascularized Composite Allotransplantation.Frontiers in immunology · 2021Article
- Divergent COVID-19 Disease Trajectories Predicted by a DAMP-Centered Immune Network Model.Frontiers in immunology · 2021Article
- A case for the reuse and adaptation of mechanistic computational models to study transplant immunology.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2020Review
- Circulating mitochondria in organ donors promote allograft rejection.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2019Article
- The innate immune response to ischemic injury: a multiscale modeling perspective.BMC systems biology · 2018Article
- Combining Theoretical and Experimental Techniques to Study Murine Heart Transplant Rejection.Frontiers in immunology · 2016Article
- The Intersection of Regional Anesthesia and Cancer Progression: A Theoretical Framework.Cancer control : journal of the Moffitt Cancer CenterArticle
- Antibody-mediated rejection in xenotransplantation: Can it be prevented or reversed?XenotransplantationReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
A mathematical model of the early inflammatory response in transplantation is formulated with ordinary differential equations. We first consider the inflammatory events associated only with the initial surgical procedure and the subsequent ischemia/reperfusion (I/R) events that cause tissue damage to the host as well as the donor graft. These events release damage-associated molecular pattern molecules (DAMPs), thereby initiating an acute inflammatory response. In simulations of this model, resolution of inflammation depends on the severity of the tissue damage caused by these events and the patient's (co)-morbidities. We augment a portion of a previously published mathematical model of acute inflammation with the inflammatory effects of T cells in the absence of antigenic allograft mismatch (but with DAMP release proportional to the degree of graft damage prior to transplant). Finally, we include the antigenic mismatch of the graft, which leads to the stimulation of potent memory T cell responses, leading to further DAMP release from the graft and concomitant increase in allograft damage. Regulatory mechanisms are also included at the final stage. Our simulations suggest that surgical injury and I/R-induced graft damage can be well-tolerated by the recipient when each is present alone, but that their combination (along with antigenic mismatch) may lead to acute rejection, as seen clinically in a subset of patients. An emergent phenomenon from our simulations is that low-level DAMP release can tolerize the recipient to a mismatched allograft, whereas different restimulation regimens resulted in an exaggerated rejection response, in agreement with published studies. We suggest that mechanistic mathematical models might serve as an adjunct for patient- or sub-group-specific predictions, simulated clinical studies, and rational design of immunosuppression.
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.