Modeling cancer progression: an integrated workflow extending data-driven kinetic models to bio-mechanical PDE models.

Computational modeling of cancer can help unveil dynamics and interactions that are hard to replicate experimentally. Thanks to the advancement in cancer databases and data analysis technologies, these models have become more robust than ever. There are many mathematical models which investigate cancer through different approaches, from sub-cellular to tissue scale, and from treatment to diagnostic points of view. In this study, we lay out a step-by-step methodology for a data-driven mechanistic model of the tumor microenvironment. We discuss data acquisition strategies, data preparation, parameter estimation, and sensitivity analysis techniques. Furthermore, we propose a possible approach to extend mechanistic ordinary differential equation models to PDE models coupled with mechanical growth. The workflow discussed in this article can help understand the complex temporal and spatial interactions between cells and cytokines in the tumor microenvironment and their effect on tumor growth.

Secondary mathematics teachers' descriptions of student engagement.

There is a need for a more robust conceptualization of engagement in mathematics education research. Investigating how teachers describe engagement can provide insight into relationships between purposes of engagement and dimensions of engagement. In this exploratory study, we examined how 28 secondary mathematics teachers in two states in the USA talked about their students' engagement. During interviews, we asked teachers to provide their definitions for engagement, describe their teaching strategies for engaging students, and describe their observations of engagement during a video clip from their own classroom. We interpreted teachers' talk to identify how they described the nature of mathematics engagement (dimensions such as behavioral, cognitive, affective, and/or social engagement) and purposes of engagement (engagement in learning or in schooling [Harris, 2011]). When teachers described the purpose of engagement as engagement in learning, they also tended to describe the nature of engagement with cognitive and social dimensions and with multiple dimensions of engagement.

Investigating the spatial interaction of immune cells in colon cancer.

The intricate network of interactions between cells and molecules in the tumor microenvironment creates a heterogeneous ecosystem. The proximity of the cells and molecules to their activators and inhibitors is essential in the progression of tumors. Here, we develop a system of partial differential equations coupled with linear elasticity to investigate the effects of spatial interactions on the tumor microenvironment. We observe interesting cell and cytokine distribution patterns, which are heavily affected by macrophages. We also see that cytotoxic T cells get recruited and suppressed at the site of macrophages. Moreover, we observe that anti-tumor macrophages reorganize the patterns in favor of a more spatially restricted cancer and necrotic core. Furthermore, the adjoint-based sensitivity analysis indicates that the most sensitive model's parameters are directly related to macrophages. The results emphasize the widely acknowledged effect of macrophages in controlling cancer cells population and spatially arranging cells in the tumor microenvironment.

Bio-Mechanical Model of Osteosarcoma Tumor Microenvironment: A Porous Media Approach.

Osteosarcoma is the most common malignant bone tumor in children and adolescents with a poor prognosis. To describe the progression of osteosarcoma, we expanded a system of data-driven ODE from a previous study into a system of Reaction-Diffusion-Advection (RDA) equations and coupled it with Biot equations of poroelasticity to form a bio-mechanical model. The RDA system includes the spatio-temporal information of the key components of the tumor microenvironment. The Biot equations are comprised of an equation for the solid phase, which governs the movement of the solid tumor, and an equation for the fluid phase, which relates to the motion of cells. The model predicts the total number of cells and cytokines of the tumor microenvironment and simulates the tumor's size growth. We simulated different scenarios using this model to investigate the impact of several biomedical settings on tumors' growth. The results indicate the importance of macrophages in tumors' growth. Particularly, we have observed a high co-localization of macrophages and cancer cells, and the concentration of tumor cells increases as the number of macrophages increases.

Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation.

We are rapidly approaching a future in which cancer patient digital twins will reach their potential to predict cancer prevention, diagnosis, and treatment in individual patients. This will be realized based on advances in high performance computing, computational modeling, and an expanding repertoire of observational data across multiple scales and modalities. In 2020, the US National Cancer Institute, and the US Department of Energy, through a trans-disciplinary research community at the intersection of advanced computing and cancer research, initiated team science collaborative projects to explore the development and implementation of predictive Cancer Patient Digital Twins. Several diverse pilot projects were launched to provide key insights into important features of this emerging landscape and to determine the requirements for the development and adoption of cancer patient digital twins. Projects included exploring approaches to using a large cohort of digital twins to perform deep phenotyping and plan treatments at the individual level, prototyping self-learning digital twin platforms, using adaptive digital twin approaches to monitor treatment response and resistance, developing methods to integrate and fuse data and observations across multiple scales, and personalizing treatment based on cancer type. Collectively these efforts have yielded increased insights into the opportunities and challenges facing cancer patient digital twin approaches and helped define a path forward. Given the rapidly growing interest in patient digital twins, this manuscript provides a valuable early progress report of several CPDT pilot projects commenced in common, their overall aims, early progress, lessons learned and future directions that will increasingly involve the broader research community.

Patient-Specific Mathematical Model of the Clear Cell Renal Cell Carcinoma Microenvironment.

The interactions between cells and molecules in the tumor microenvironment can give insight into the initiation and progression of tumors and their optimal treatment options. In this paper, we developed an ordinary differential equation (ODE) mathematical model of the interaction network of key players in the clear cell renal cell carcinoma (ccRCC) microenvironment. We then performed a global gradient-based sensitivity analysis to investigate the effects of the most sensitive parameters of the model on the number of cancer cells. The results indicate that parameters related to IL-6 have high a impact on cancer cell growth, such that decreasing the level of IL-6 can remarkably slow the tumor's growth.

A PDE Model of Breast Tumor Progression in MMTV-PyMT Mice.

The evolution of breast tumors greatly depends on the interaction network among different cell types, including immune cells and cancer cells in the tumor. This study takes advantage of newly collected rich spatio-temporal mouse data to develop a data-driven mathematical model of breast tumors that considers cells' location and key interactions in the tumor. The results show that cancer cells have a minor presence in the area with the most overall immune cells, and the number of activated immune cells in the tumor is depleted over time when there is no influx of immune cells. Interestingly, in the case of the influx of immune cells, the highest concentrations of both T cells and cancer cells are in the boundary of the tumor, as we use the Robin boundary condition to model the influx of immune cells. In other words, the influx of immune cells causes a dominant outward advection for cancer cells. We also investigate the effect of cells' diffusion and immune cells' influx rates in the dynamics of cells in the tumor micro-environment. Sensitivity analyses indicate that cancer cells and adipocytes' diffusion rates are the most sensitive parameters, followed by influx and diffusion rates of cytotoxic T cells, implying that targeting them is a possible treatment strategy for breast cancer.

Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model.

The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven mathematical model to investigate the dynamics of key cell types and cytokines involved in breast cancer development. We use time-course gene expression profiles of a mouse model to estimate the relative abundance of cells and cytokines. We then employ a least-squares optimization method to evaluate the model's parameters based on the mice data. The resulting dynamics of the cells and cytokines obtained from the optimal set of parameters exhibit a decent agreement between the data and predictions. We perform a sensitivity analysis to identify the crucial parameters of the model and then perform a local bifurcation on them. The results reveal a strong connection between adipocytes, IL6, and the cancer population, suggesting them as potential targets for therapies.

High Prevalence of Multidrug Resistance and Biofilm-Formation Ability Among Avian Escherichia coli Isolated from Broilers in Iran.

The present study was conducted to determine the antimicrobial resistance pattern and biofilm-formation ability in 100 Avian-Pathogenic Escherichia coli (APEC) isolated from colibacillosis-suspected broilers and 100 Avian Fecal E. coli (AFEC) isolates from healthy broilers in Hamedan, Iran. All isolates were screened by polymerase chain reaction for antimicrobial resistance genes, class 1 and 2 integrons, and biofilm-associated genes. Besides, we assessed the possible relationship between biofilm-formation ability antibiotic resistance patterns, genetic background, and the pathogenicity of APEC strains. 81% of APEC and 73% of AFEC isolates showed multidrug resistance (MDR) phenotype; in addition, 45% of the APEC and 21% of the AFEC strains showed biofilm-formation ability. This is the first report of the biofilm formation ability in E. coli isolated from broilers in Iran. The most prevalent antibiotic resistance gene in APEC strains was tetA (68%), followed by sul1 (63%), dfrA1-like (51%), and blaTEM (30%), whereas in AFEC strains, the frequencies of the antibiotic resistance genes were tetA (63%), sul1 (58%), dfrA1-like (49%), and blaTEM (22%). Out of 81 MDR APEC isolates, 53 (65.4%) and 38 (46.91%) isolates were positive for intI1 and intI2 genes, respectively. In the AFEC strains intI1 and intI2 genes were presented in 57 and 33 isolates, respectively. All APEC isolates belonging to phylogenetic groups B1, B2, and C were MDR. The results of the present study indicate that isolates with biofilm-forming ability show more MDR properties and probably have more pathogenicity to broilers.

A Mathematical Model of Breast Tumor Progression Based on Immune Infiltration.

Breast cancer is the most prominent type of cancer among women. Understanding the microenvironment of breast cancer and the interactions between cells and cytokines will lead to better treatment approaches for patients. In this study, we developed a data-driven mathematical model to investigate the dynamics of key cells and cytokines involved in breast cancer development. We used gene expression profiles of tumors to estimate the relative abundance of each immune cell and group patients based on their immune patterns. Dynamical results show the complex interplay between cells and molecules, and sensitivity analysis emphasizes the direct effects of macrophages and adipocytes on cancer cell growth. In addition, we observed the dual effect of IFN-γ on cancer proliferation, either through direct inhibition of cancer cells or by increasing the cytotoxicity of CD8+ T-cells.

Simple model of atherosclerosis in cylindrical arteries: impact of anisotropic growth on Glagov remodeling.

In 1987, Seymour Glagov observed that arteries went through a two-stage remodeling process as a result of plaque growth: first, a compensatory phase where the lumen area remains approximately constant and second, an encroachment phase where the lumen area decreases over time. In this paper, we investigate the effect of growth anisotropy on Glagov remodeling in five different cases: pure radial, pure circumferential, pure axial, isotropic and general anisotropic growth where the elements of the growth tensor are chosen to minimize the total energy. We suggest that the nature of anisotropy is inclined towards the growth direction that requires the least amount of energy. Our framework is the theory of morphoelasticity on an axisymmetric arterial domain. For each case, we explore their specific effect on the Glagov curves. For the latter two cases, we also provide the changes in collagen fiber orientation and length in the intima, media and adventitia. In addition, we compare the total energy produced by growth in radial, circumferential and axial direction and deduce that using a radially dominant anisotropic growth leads to lower strain energy than isotropic growth.

An integrated approach to simulating the vulnerable atherosclerotic plaque.

Analyses of individual atherosclerotic plaques are mostly descriptive, relying, for example, on histological classification by spectral analysis of ultrasound waves or staining and observing particular cellular components. Such passive methods have proved useful for characterizing the structure and vulnerability of plaques but have little quantitative predictive power. Our aim is to introduce and discuss a computational framework to provide insight to clinicians and help them visualize internal plaque dynamics. We use partial differential equations (PDEs) with macrophages, necrotic cells, oxidized lipids, oxygen concentration, and platelet-derived growth factor (PDGF) as primary variables coupled to a biomechanical model to describe vessel growth. The model is deterministic, providing mechanical, morphological, and histological characteristics of an atherosclerotic vessel at any desired future time point. We use our model to create computer-generated animations of a plaque evolution that are in qualitative agreement with published serial ultrasound images and hypothesize possible atherogenic mechanisms. A systems biology model consisting of five differential equations is able to capture the morphology of necrotic cores residing within vulnerable atherosclerotic plaque. In the context of the model, the distribution of oxidized low-density lipoprotein (Ox-LDL) particles, endothelial inflammation, plaque oxygenation (via the presence of vasa vasora), and intimal oxygenation are four important factors that drive changes in core morphology.NEW & NOTEWORTHY In this article, we propose a quantitative framework to describe the evolution of atherosclerotic plaque. We use partial differential equations (PDEs) with macrophages, necrotic cells, oxidized lipids, oxygen concentration, and PDGF as primary variables coupled to a biomechanical model to describe vessel growth. A feature of our method is that it outputs color-coded vessel sections corresponding to regions of the plaque that are necrotic and fibrous, qualitatively similar to images generated by enhanced intravascular ultrasound.

Survival rate and the determinants of progression from HIV to AIDS and from AIDS to the death in Iran: 1987 to 2016

Objective: To examine the prognostic factors of progression from HIV to AIDS and AIDS to the death in people living with HIV/AIDS in Iran. Methods: In this registry-based retrospective cohort study, we recruited 28 873 HIV-infected people from 158 Behavioral Diseases Counseling Centers of Iran. Two outcomes of interest included survival rates from HIV diagnosis to AIDS and from AIDS to the death. We used Kaplan-Meier and Cox regression model to investigate survival rate and factors affecting on survival controlling effect of confounding factors. Results: The one, three, five, and ten-year survival rate from HIV to AIDS were 85%, 73%, 61% and 32%, and for AIDS to death were 90%, 81%, 74% and 55%, respectively. Multivariate Cox regression analysis indicated that the risk of progression from AIDS phase toward death in individuals with CD4 less than 200/mm3, infected with tuberculosis (TB) and not treated by antiretroviral therapy (ART) was 2.17 (95% CI: 1.62-2.90), 1.49 (95% CI: 1.01-2.20) and 4.88 (95% CI: 3.42-6.96) times higher respectively. The risk of progression to AIDS in patients with baseline CD4 less than 200/mm3 was 2.32 (95% CI: 2.14, 2.51) times higher than patients with CD4 > 200/mm3 (P=0.001). On the other hand, tuberculosis increases the risk of death by 49.0% (P=0.04). The hazard ratio of death in patients who did not receive ART was 4.88 (95% CI: 3.42, 6.96) times higher than patients who received ART (P<0.001). Conclusion: The early detection of HIV, the screening and treatment of TB and receiving the ART improve the survival of HIV/AIDS patients significantly, and prevent the transmission of HIV to other people.

Trigonella foenum-graecum seed extract modulates expression of lipid metabolism-related genes in HepG2 cells

Objective: To investigate anti-dyslipidemic effects of hydroalcoholic fenugreek seed extracts, diosgenin, and 4-OH-Ile on HepG2 cell line. Methods: HepG2 cells were treated with hydroalcoholic fenugreek seed extracts, diosgenin, 4-OH-Ile, and orlistat. IC

Survival rate and the determinants of progression from HIV to AIDS and from AIDS to the death in Iran: 1987 to 2016

Objective: To examine the prognostic factors of progression from HIV to AIDS and AIDS to the death in people living with HIV/AIDS in Iran. Methods: In this registry-based retrospective cohort study, we recruited 28 873 HIV-infected people from 158 Behavioral Diseases Counseling Centers of Iran. Two outcomes of interest included survival rates from HIV diagnosis to AIDS and from AIDS to the death. We used Kaplan-Meier and Cox regression model to investigate survival rate and factors affecting on survival controlling effect of confounding factors. Results: The one, three, five, and ten-year survival rate from HIV to AIDS were 85%, 73%, 61% and 32%, and for AIDS to death were 90%, 81%, 74% and 55%, respectively. Multivariate Cox regression analysis indicated that the risk of progression from AIDS phase toward death in individuals with CD4 less than 200/mm

Biodiversity and prevalence of parasites of domestic pigeons (Columba livia domestica) in a selected semiarid zone of South Khorasan, Iran.

Five species of nematodes and cestodes were collected from alimentary canals of pigeons: the nematodes were two species: Ascaridia colombae (16.66%) and Hadjelia truncata (1.96%), while the cestodes were Cotugnia digonopora (13.79%), Raillietina magninumida (18.62%) and Raillietina achinobothridia (32.35%); fecal examination revealed: Eimeria spp. (40.19%) and Cryptosporidium oocysts (2.94%); and blood smears showed: Haemoproteus cloumbae (47/05%); in mouth, throat and larynx: Trichomonans gallinae (57.84%); four species of ectoparasites were collected from feathers and subcutaneous nodules as follows: feathers: Pseudolynchia canariensis (63.72%), Columbicola columbae (79.41%), Menopen gallinea (44.11%); subcutaneous nodules: Laminosioptes cysticola (1.96%). From the parasitic fauna identified in this study, it is imperative to institute an integrated parasitic control through constant changing of litter, regular use of antihelminthics, anticoccidials and dusting of birds with pesticides.

Prevalence of intestinal helminthes in owned dogs in Kerman city, Iran

OBJECTIVE@#To survey the prevalence of canine gastrointestinal helminthes in dogs presented to the Veterinary faculty of the University of Kerman between May and November 2011.@*METHODS@#A total of 70 fecal samples were evaluated by the fecal sedimentation method.@*RESULTS@#The prevalence of gastrointestinal helminthes was 7.14%. The parasites most frequently detected were Toxocara canis (T. canis) (4.3%); Toxascaris leonina (T. leonina) (1.4%) and Teania spp. (1.4%). The age distribution of intestinal parasites in dogs showed that the dog less than 1 year old had a higher overall prevalence than those dogs over 12 months of age but there was not significant (P>0.05). Also there was no significant difference in the prevalence between male (7.7%) and female (6.5%) dogs (P>0.05).@*CONCLUSIONS@#It is thought that the reduction in the frequency of the dogs with those helminthes may be mainly a result of the improvement in breeding environment and the routine use of antihelmintics. The significance of zoonotic diseases caused by intestinal helminthes makes it necessary for us to know the infection status of domestic dogs and to take measures for further control. It is concluded that veterinarians have an important role in educating dog owners of these potential risks and means for preventing or minimizing zoonotic transmission.

Estimation of the Frequency of Intravenous Drug Users in Hamadan City, Iran, Using the Capture-recapture Method / 한국역학회지

OBJECTIVES: The number of illicit drug users is prone to underestimation. This study aimed to use the capture-recapture method as a statistical procedure for measuring the prevalence of intravenous drug users (IDUs) by estimating the number of unknown IDUs not registered by any of the registry centers. METHODS: This study was conducted in Hamadan City, the west of Iran, in 2012. Three incomplete data sources of IDUs, with partial overlapping data, were assessed including: (a) Volunteer Counseling and Testing Centers (VCTCs); (b) Drop in Centers (DICs); and (c) Outreach Teams (ORTs). A log-linear model was applied for the analysis of three-sample capture-recapture results. Two information criteria were used for model selection including Akaike's Information Criterion and the Bayesian Information Criterion. RESULTS: Out of 1,478 IDUs registered by three centers, 48% were identified by VCTCs, 32% by DICs, and 20% by ORTs. After exclusion of duplicates, 1,369 IDUs remained. According to our findings, there were 9,964 (95% CI, 6,088 to 17,636) IDUs not identified by any of the centers. Hence, the real number of IDUs is expected to be 11,333. Based on these findings, the overall completeness of the three data sources was around 12% (95% CI, 7% to 18%). CONCLUSION: There was a considerable number of IDUs not identified by any of the centers. Although the capture-recapture method is a useful and practical approach for estimating unknown populations, due to the assumptions and limitations of the method, the results must be interpreted with caution.

Prevalence of ixodid ticks on cattle and sheep southeast of Iran.

A survey was carried out to investigate the prevalence of hard tick species (Acari: Ixodidae) on cattle and sheep southeast of Iran. A total of 972 ticks were collected from 280 infested cattle and 1,207 ticks were collected from 632 infested sheep during activating seasons of ticks in 2008-2009. The species collected from cattle were Hyalomma marginatum marginatum (50.92%), Hyalomma anatolicum excavatum (25.61%), Hyalomma anatolicum anatolicum (8.12%), Hyalomma asiaticum asiaticum (1.85%), and Rhipicephalus sanguineus (13.47%) while the species collected from sheep were R. sanguineus (36.37%), H. marginatum marginatum (30.65%), H. anatolicum excavatum (19.05%), H. asiaticum asiaticum (10.52%), Hyalomma detritum (3.14%), and Dermacentor marginatus (0.24%). The results show that, H. marginatum marginatum, H. anatolicum excavatum, and R. sanguineus are dominant tick species in the surveyed area.

Anticancer activity of a new gonadotropin releasing hormone analogue.

Gonadotropin releasing hormone (GnRH) has a pivotal role in the biology of reproduction processes. In extrapituitary compartments GnRH and its receptor act as a part of the autocrin regulatory system of cell proliferation, resulting in its anticancer activity. Here the anticancer activity of a new analogue of GnRH has been investigated. Results indicate that proliferation of human breast and ovarian cancer cell lines is dose-dependently inhibited. The inhibitory efficiency of this new analogue is proved to be higher than the original triptorelin. In addition to its antimitogenic activity, evidence was found for the involvement of the apoptotic mechanism in the action of the new analogue. Furthermore the presence of chemical groups in the peptide sequence is thought to increase the protease stability of the new analogue in comparison with triptorelin. Consequently our new analogue can be considered as a good pharmaceutical candidate.