Towards Predictive Computational Models of Oncolytic Virus Therapy: Basis for Experimental Validation and Model Selection

Oncolytic viruses are viruses that specifically infect cancer cells and kill them, while leaving healthy cells largely intact. Their ability to spread through the tumor makes them an attractive therapy approach. While promising results have been observed in clinical trials, solid success remains elusive since we lack understanding of the basic principles that govern the dynamical interactions between the virus and the cancer. In this respect, computational models can help experimental research at optimizing treatment regimes. Although preliminary mathematical work has been performed, this suffers from the fact that individual models are largely arbitrary and based on biologically uncertain assumptions. Here, we present a general framework to study the dynamics of oncolytic viruses that is independent of uncertain and arbitrary mathematical formulations. We find two categories of dynamics, depending on the assumptions about spatial constraints that govern that spread of the virus from cell to cell. If infected cells are mixed among uninfected cells, there exists a viral replication rate threshold beyond which tumor control is the only outcome. On the other hand, if infected cells are clustered together (e.g. in a solid tumor), then we observe more complicated dynamics in which the outcome of therapy might go either way, depending on the initial number of cells and viruses. We fit our models to previously published experimental data and discuss aspects of model validation, selection, and experimental design. This framework can be used as a basis for model selection and validation in the context of future, more detailed experimental studies. It can further serve as the basis for future, more complex models that take into account other clinically relevant factors such as immune responses

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

Cities and their suburbs: "Go along to get along"

This dissertation examines the economic and policy relationships between center cities and their suburbs. It makes several contributions to the existing urban literature. First, this dissertation confirms previous research finding that center cities and their suburbs are economically linked. It confirms that the economic link exists over time (1970 to 1990) and that it endures even after controlling for the impact of the state economy. Second, it confirms the traditional expectation that metropolitan area government structure influences the direction of center city/suburb income disparity---but not in the way predicted by previous literature. Using an alternative conceptualization of local government fragmentation---the total number of local governments per square mile---it finds that the geographic density of local governments within a metropolitan area influences center city/suburb income disparities. The analysis suggests that geographic density of metropolitan area governments should be considered when examining the influence of fragmentation on local government policy decisions. Third, this dissertation finds mixed evidence regarding the impact of center city/suburb income disparity on metropolitan area economic health. Traditionally, it is thought that the center city is the regional economic engine, and that increasing income disparity favoring the suburbs undermines metropolitan area growth. Although this theory held true during the 1970s, the data unexpectedly reveals an opposite conclusion in the 1980s: increasing income disparity in favor of the suburbs was related to increasing metropolitan area economic health. If this finding proves stable using the 2000 Census data, it may signal a change in the nature of the metropolitan area economy that would be significant for future policy development. Finally, this dissertation examines the relationship between fragmentation and the incidence of local intergovernmental agreements. It finds that fragmented local governments can cooperate in the provision of certain goods and services. This cooperation is especially likely among geographically dense local governments providing capital-intensive goods and services that generate economies of scale. This finding reinforces the importance of density in future urban research and signals an opportunity to pursue new cooperative solutions that could achieve many of the benefits of consolidated government while preserving existing local governments

Estimation of Soil Texture and Plant Available Water by Correlation with the Laser Light-Scattering Method

From the Proceedings of the 1985 Meetings of the Arizona Section - American Water Resources Association and the Hydrology Section - Arizona-Nevada Academy of Science - April 27, 1985, Las Vegas, NevadaThis article is part of the Hydrology and Water Resources in Arizona and the Southwest collections. Digital access to this material is made possible by the Arizona-Nevada Academy of Science and the University of Arizona Libraries. For more information about items in this collection, contact [email protected]