Killer Ig-like receptors (KIRs) are expressed on CD4+CD28null T cells, a highly oligoclonal subset of T cells that is expanded in patients with rheumatoid arthritis. It is unclear at what stage of development these T cells acquire KIR expression. To determine whether KIR expression is a consequence of clonal expansion and replicative senescence, multiple CD4+CD28null T cell clones expressing the in vivo dominant TCR β-chain sequences were identified in three patients and analyzed for their KIR gene expression pattern. Based on sharing of TCR sequences, the clones were grouped into five clone families. The repertoire of KIRs was diverse, even within each clone family; however, the gene expression was not random. Three particular receptors, KIR2DS2, KIR2DL2, and KIR3DL2, had significant differences in gene expression frequencies between the clone families. These data suggest that KIRs are successively acquired after TCR rearrangement, with each clone family developing a dominant expression pattern. The patterns did not segregate with the individual from whom the clones were derived, indicating that peripheral selection in the host environment was not a major shaping force. Several models were examined using a computer algorithm that was designed to simulate the expression of KIRs at various times during T cell proliferation. The computer simulations favored a model in which KIR gene expression is inducible for a limited time during the initial stages of clonal expansion.

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Replication-competent viruses are being tested as tumor therapy agents. The fundamental premise of this therapy is the selective infection of the tumor cell population with the amplification of the virus. Spread of the virus in the tumor ultimately should lead to eradication of the cancer. Tumor virotherapy is unlike any other form of cancer therapy as the outcome depends on the dynamics that emerge from the interaction between the virus and tumor cell populations both of which change in time. We explore these interactions using a model that captures the salient biological features of this system in combination with in vivo data. Our results show that various therapeutic outcomes are possible ranging from tumor eradication to oscillatory behavior. Data from in vivo studies support these conclusions and validate our modeling approach. Such realistic models can be used to understand experimental observations, explore alternative therapeutic scenarios and develop techniques to optimize therapy.

Tumor therapy with replication competent viruses is an exciting approach to cancer eradication where viruses are engineered to specifically infect, replicate, spread and kill tumor cells. The outcome of tumor virotherapy is complex due to the variable interactions between the cancer cell and virus populations as well as the immune response. Oncolytic viruses are highly efficient in killing tumor cells in vitro, especially in a 2D monolayer of tumor cells, their efficiency is significantly lower in a 3D environment, both in vitro and in vivo. This indicates that the spatial dimension may have a major influence on the dynamics of virus spread. We study the dynamic behavior of a spatially explicit computational model of tumor and virus interactions using a combination of in vitro 2D and 3D experimental studies to inform the models. We determine the number of nearest neighbor tumor cells in 2D (median = 6) and 3D tumor spheroids (median = 16) and how this influences virus spread and the outcome of therapy. The parameter range leading to tumor eradication is small and even harder to achieve in 3D. The lower efficiency in 3D exists despite the presence of many more adjacent cells in the 3D environment that results in a shorter time to reach equilibrium. The mean field mathematical models generally used to describe tumor virotherapy appear to provide an overoptimistic view of the outcomes of therapy. Three dimensional space provides a significant barrier to efficient and complete virus spread within tumors and needs to be explicitly taken into account for virus optimization to achieve the desired outcome of therapy.

Although the RM during bariatric surgery represents an effective method for improving intraoperative oxygenation, it does not significantly affect the desflurane blood concentrations during anesthesia or its elimination during emergence.

Background:Interstitial brachytherapy for localised prostate cancer may be followed by transient increases in prostate-specific antigen (PSA) that resolve without therapy. Such PSA bounces may be associated with an improved outcome but often cause alarm in the patient and physician, and have defied explanation.Methods:We developed a mathematical model to capture the interactions between the tumour, radiation and anti-tumour immune response. The model was fitted to data from a large cohort of patients treated exclusively with interstitial brachytherapy. Immunohistological analysis for T-cell infiltration within the same tumours was also performed.Results:Our minimal model captures well the dynamics of the tumour after therapy, and suggests that a strong anti-tumour immune response coupled with the therapeutic effect of radiation on the tumour is responsible for the PSA bounce. Patients who experience a PSA bounce had a higher density of CD3 and CD8 cells within the tumour that likely contribute to the PSA bounce and the overall better outcomes observed.Conclusions:Our observations provide a novel and unifying explanation for the PSA bounce in patients with early prostate cancer and also have implications for the use of immune-based therapies in such patients to improve outcomes.

resulting in the establishment of a higher than baseline cytosolic Ca 2+ concentration.Mathematical modeling showed that slow activation was critical to the sustained oscillation induced by the "slow" PMCA4b pump. The modeling and experimental results indicated that the distinct properties of PMCA isoforms differentially regulate the pattern of SOCE-mediated Ca 2+ transients, which would thus affect the activation of downstream signaling pathways.

Tumor selective, replication competent viruses are being tested for cancer gene therapy. This approach introduces a new therapeutic paradigm due to potential replication of the therapeutic agent and induction of a tumor-specific immune response. However, the experimental outcomes are quite variable, even when studies utilize highly inbred strains of mice and the same cell line and virus. Recognizing that virotherapy is an exercise in population dynamics, we utilize mathematical modeling to understand the variable outcomes observed when B16ova malignant melanoma tumors are treated with vesicular stomatitis virus in syngeneic, fully immunocompetent mice. We show how variability in the initial tumor size and the actual amount of virus delivered to the tumor have critical roles on the outcome of therapy. Virotherapy works best when tumors are small, and a robust innate immune response can lead to superior tumor control. Strategies that reduce tumor burden without suppressing the immune response and methods that maximize the amount of virus delivered to the tumor should optimize tumor control in this model system.