Accumulating experimental and clinical evidence suggest that the immune response to cancer is not exclusively anti -tumor. Indeed, the pro-tumor roles of the immune system -as suppliers of growth and pro-angiogenic factors or defenses against cytotoxic immune attacks, for example -have been long appreciated, but relatively few theoretical works have considered their effects. Inspired by the recently proposed "immune-mediated" theory of metastasis, we develop a mathematical model for tumor-immune interactions at two anatomically distant sites, which includes both anti -and pro-tumor immune effects, and the experimentally observed tumor-induced phenotypic plasticity of immune cells (tumor "education" of the immune cells). Upon confrontation of our model to experimental data, we use it to evaluate the implications of the immune-mediated theory of metastasis. We find that tumor education of immune cells may explain the relatively poor performance of immunotherapies, and that many metastatic phenomena, including metastatic blow-up, dormancy, and metastasis to sites of injury, can be explained by the immune-mediated theory of metastasis. Our results suggest that further work is warranted to fully elucidate the pro-tumor effects of the immune system in metastatic cancer. biological processes beginning with the development, growth, and local invasion of a primary tumor, and followed by the preparation of a pre-metastatic niche, entrance into, travel through, and exit from the vascular system, and concluding with the growth and development of a secondary, metastatic tumor. The metastatic cascade is depicted in Figure 1, with special attention paid to the immune effects at each step. We now highlight the specific immune cells involved at each step of the metastatic cascade and outline their roles.

We use a mathematical model to investigate cancer resistance to radiation, based on dedifferentiation of non-stem cancer cells into cancer stem cells. Experimental studies by Iwasa 2008, using human non-small cell lung cancer (NSCLC) cell lines in mice, have implicated the inhibitor of apoptosis protein survivin in cancer resistance to radiation. A marked increase in radio-sensitivity was observed, after inhibiting survivin expression with a specific survivin inhibitor YM155 (sepantronium bromide). It was suggested that these observations are due to survivin-dependent dedifferentiation of non-stem cancer cells into cancer stem cells. Here, we confirm this hypothesis with a mathematical model, which we fit to Iwasa's data on NSCLC in mice. We investigate the timing of combination therapies of YM155 administration and radiation. We find an interesting dichotomy. Sometimes it is best to hit a cancer with a large radiation dose right at the beginning of the YM155 treatment, while in other cases, it appears advantageous to wait a few days until most cancer cells are sensitized and then radiate. The optimal strategy depends on the nature of the cancer and the dose of radiation administered.

Accumulating experimental and clinical evidence suggest that the immune response to cancer is not exclusively anti -tumor. Indeed, the pro-tumor roles of the immune system -as suppliers of growth and pro-angiogenic factors or defenses against cytotoxic immune attacks, for example -have been long appreciated, but relatively few theoretical works have considered their effects. Inspired by the recently proposed "immune-mediated" theory of metastasis, we develop a mathematical model for tumor-immune interactions at two anatomically distant sites, which includes both anti -and pro-tumor immune effects, and the experimentally observed tumor-induced phenotypic plasticity of immune cells (tumor "education" of the immune cells). Upon confrontation of our model to experimental data, we use it to evaluate the implications of the immune-mediated theory of metastasis. We find that tumor education of immune cells may explain the relatively poor performance of immunotherapies, and that many metastatic phenomena, including metastatic blow-up, dormancy, and metastasis to sites of injury, can be explained by the immune-mediated theory of metastasis. Our results suggest that further work is warranted to fully elucidate the pro-tumor effects of the immune system in metastatic cancer.

We present a novel circle detection technique based on the desirable properties of Gabor wavelet filters. We describe the technique and its Gabor wavelet origins, and perform multiple experiments using both synthetic images and real microscopic images of red blood cells. Our experiments show the proposed technique's ability to detect single and overlapping circles, with improved results over traditional techniques including both the Circular Hough Transform and its modifications which include edge orientation. The improved results are demonstrated under high levels of noise and for partially defined overlapping circles.

We introduce a new stochastic model for metastatic growth, which takes the form of a branching stochastic process with settlement. The moving particles are interpreted as clusters of cancer cells, while stationary particles correspond to micro-tumours and metastases. The analysis of expected particle location, their locational variance, the furthest particle distribution and the extinction probability leads to a common type of differential equation, namely, a non-local integro-differential equation with distributed delay. We prove global existence and uniqueness results for this type of equation. The solutions’ asymptotic behaviour for long time is characterized by an explicit index, a metastatic reproduction number $R_0$: metastases spread for $R_{0}>1$ and become extinct for $R_{0}<1$. Using metastatic data from mouse experiments, we show the suitability of our framework to model metastatic cancer.

Received on (day month year)]We introduce a new stochastic model for metastatic growth, which takes the form of a branching stochastic process with settlement. The moving particles are interpreted as clusters of cancer cells while stationary particles correspond to micro-tumors and metastases. The analysis of expected particle location, their locational variance, the furthest particle distribution, and the extinction probability leads to a common type of differential equation, namely, a non-local integro-differential equation with distributed delay. We prove global existence and uniqueness results for this type of equation. The solutions' asymptotic behavior for long time is characterized by an explicit index, a metastatic reproduction number R 0 : metastases spread for R 0 > 1 and become extinct for R 0 < 1. Using metastatic data from mouse experiments, we show the suitability of our framework to model metastatic cancer.

Metastatic seeding of distant organs can occur in the very early stages of primary tumor development. Once seeded, these micrometastases may enter a dormant phase that can last decades. Curiously, the surgical removal of the primary tumor can stimulate the accelerated growth of distant metastases, a phenomenon known as metastatic blow-up. Although several theories have been proposed to explain metastatic dormancy and blow-up, most mathematical investigations have ignored the important pro-tumor effects of the immune system. In this work, we address that shortcoming by developing an ordinary differential equation model of the immune-mediated theory of metastasis. We include both anti-and pro-tumor immune effects, in addition to the experimentally observed phenomenon of tumor-induced immune cell phenotypic plasticity. Using geometric singular perturbation analysis, we derive a rather simple model that captures the main processes and, at the same time, can be fully analyzed. Literature-derived parameter estimates are obtained, and model robustness is demonstrated through a sensitivity analysis. We determine conditions under which the parameterized model can successfully explain both metastatic dormancy and blow-up. Numerical simulations suggest a novel measure to predict the occurrence of future metastatic blow-up, in addition to new potential avenues for treatment of clinically undetectable micrometastases.

Purpose: Uncontrolled hypertension is serious and may lead to severe cardiovascular events and death. To better educate and empower patients to meet their blood pressure (BP) management goals, a large, integrated academic healthcare system implemented the Blood Pressure Goals Achievement Program (BPGAP), a longitudinal intervention embedding community pharmacists within healthcare teams. This study evaluated BPGAP on its ability to promote patient BP management goals. Methods: A pre-/post-intervention analysis was conducted whereby BP measurements were evaluated longitudinally within acuity groups determined by k-means clustering. Generalized linear mixed models evaluated trends in BP by time period, and proportions of patients meeting BP management goals (<140/90 mmHg) were assessed in relation to BPGAP enrollment date. Results: There were 5,125 patients who were clustered into Uncontrolled, Borderline, and Controlled blood pressure groups; 2,108 patients had BP measurements across 4 time periods before and after BPGAP enrollment. Groups differed by patient age, sex, and other demographics (p<0.0001). Patients in the Uncontrolled and Borderline BP clusters demonstrated significant BP decreases after BPGAP enrollment, continuing at least to 1-year post-intervention; Controlled cluster patients maintained BPs throughout the study period. The proportion of patients with controlled BPs increased from 56% immediately pre-BPGAP to 74% in the 3- to 6-months following enrollment. Conclusion: BPGAP is effective at helping patients achieve their BP management goals. Pharmacists may play a key role in hypertension control through measuring BPs and including updates and recommendations in the electronic health record, educating patients, and engaging in communication with healthcare teams.