A new ghost cell/level set method for moving boundary problems:application to tumor growth

In this paper, we present a ghost cell/level set method for the evolution of interfaces whose normal velocity depend upon the solutions of linear and nonlinear quasi-steady reaction-diffusion equations with curvature-dependent boundary conditions. Our technique includes a ghost cell method that accurately discretizes normal derivative jump boundary conditions without smearing jumps in the tangential derivative; a new iterative method for solving linear and nonlinear quasi-steady reaction-diffusion equations; an adaptive discretization to compute the curvature and normal vectors; and a new discrete approximation to the Heaviside function. We present numerical examples that demonstrate better than 1.5-order convergence for problems where traditional ghost cell methods either fail to converge or attain at best sub-linear accuracy. We apply our techniques to a model of tumor growth in complex, heterogeneous tissues that consists of a nonlinear nutrient equation and a pressure equation with geometry-dependent jump boundary conditions. We simulate the growth of glioblastoma (an aggressive brain tumor) into a large, 1 cm square of brain tissue that includes heterogeneous nutrient delivery and varied biomechanical characteristics (white matter, gray matter, cerebrospinal fluid, and bone), and we observe growth morphologies that are highly dependent upon the variations of the tissue characteristics—an effect observed in real tumor growth

Floods stress in lowland rice production: experiences of rice farmers in Kilombero and Lower-Rufiji floodplains, Tanzania

The resilience of rice production to floods is a crucial aspect of agricultural development in flood-prone regions. However, little is known about the farming practices and challenges of rice farmers in two river basins in Tanzania: Lower-Rufiji and Kilombero, where rice is the main crop grown. This study aimed to investigate the experiences of farmers in these two rice-growing floodplains regarding the impact of floods on lowland rice production and farmer livelihoods, and the strategies they use to cope with floods. The study used a mixed-methods approach that involved household surveys, key informant interviews, and transect walks to collect data from 180 rice farmers and 14 experts and community leaders. The data analysis revealed that floods were the dominant stressor affecting rice production, occurring mostly during the long rainy season and experienced by all farmers in both locations. Floods not only caused significant crop losses, especially in Lower-Rufiji where farmers reported losing between 75 and 100% of their yield in cases of extreme floods, but also made it difficult to establish and manage crops, leading to crop land abandonment. Floods also affected the livelihoods of rice farmers by forcing them to abandon, rent, or sell their farms. Coexistence of floods with other biotic and abiotic stresses such as crop diseases and droughts also limited the use of short maturing high yielding rice varieties. Farmers have adopted on-farm strategies such as adjusting planting schedules, using different varieties of rice, changing to other crops or activities after the floods to cope with floods, but these practices face numerous challenges. The study recommends the development of early warning systems, breeding for flood-tolerant rice varieties, introgression of tolerance traits to multiple stresses and improving crop establishment methods to enhance the resilience of farmers to floods and other extreme climate events

Predicting drug pharmacokinetics and effect in vascularized tumors using computer simulation

In this paper, we investigate the pharmacokinetics and effect of doxorubicin and cisplatin in vascularized tumors through two-dimensional simulations. We take into account especially vascular and morphological heterogeneity as well as cellular and lesion-level pharmacokinetic determinants like P-glycoprotein (Pgp) efflux and cell density. To do this we construct a multi-compartment PKPD model calibrated from published experimental data and simulate 2-h bolus administrations followed by 18-h drug washout. Our results show that lesion-scale drug and nutrient distribution may significantly impact therapeutic efficacy and should be considered as carefully as genetic determinants modulating, for example, the production of multidrug-resistance protein or topoisomerase II. We visualize and rigorously quantify distributions of nutrient, drug, and resulting cell inhibition. A main result is the existence of significant heterogeneity in all three, yielding poor inhibition in a large fraction of the lesion, and commensurately increased serum drug concentration necessary for an average 50% inhibition throughout the lesion (the IC50 concentration). For doxorubicin the effect of hypoxia and hypoglycemia (“nutrient effect”) is isolated and shown to further increase cell inhibition heterogeneity and double the IC50, both undesirable. We also show how the therapeutic effectiveness of doxorubicin penetration therapy depends upon other determinants affecting drug distribution, such as cellular efflux and density, offering some insight into the conditions under which otherwise promising therapies may fail and, more importantly, when they will succeed. Cisplatin is used as a contrast to doxorubicin since both published experimental data and our simulations indicate its lesion distribution is more uniform than that of doxorubicin. Because of this some of the complexity in predicting its therapeutic efficacy is mitigated. Using this advantage, we show results suggesting that in vitro monolayer assays using this drug may more accurately predict in vivo performance than for drugs like doxorubicin. The nonlinear interaction among various determinants representing cell and lesion phenotype as well as therapeutic strategies is a unifying theme of our results. Throughout it can be appreciated that macroscopic environmental conditions, notably drug and nutrient distributions, give rise to considerable variation in lesion response, hence clinical resistance. Moreover, the synergy or antagonism of combined therapeutic strategies depends heavily upon this environment

Internet of Things for Water Sustainability

The water is a finite resource. The issue of sustainable withdrawal of freshwater is a vital concern being faced by the community. There is a strong connection between the energy, food, and water which is referred to as water-food-energy nexus. The agriculture industry and municipalities are struggling to meet the demand of water supply. This situation is particularly exacerbated in the developing countries. The projected increase in world population requires more fresh water resources. New technologies are being developed to reduce water usage in the field of agriculture (e.g., sensor guided autonomous irrigation management systems). Agricultural water withdrawal is also impacting ground and surface water resources. Although the importance of reduction in water usage cannot be overemphasized, major efforts for sustainable water are directed towards the novel technology development for cleaning and recycling. Moreover, currently, energy technologies require abundant water for energy production. Therefore, energy sustainability is inextricably linked to water sustainability. The water sustainability IoT has a strong potential to solve many challenges in water-food-energy nexus. In this chapter, the architecture of IoT for water sustainability is presented. An in-depth coverage of sensing and communication technologies and water systems is also provided

3D Multi-Cell Simulation of Tumor Growth and Angiogenesis

We present a 3D multi-cell simulation of a generic simplification of vascular tumor growth which can be easily extended and adapted to describe more specific vascular tumor types and host tissues. Initially, tumor cells proliferate as they take up the oxygen which the pre-existing vasculature supplies. The tumor grows exponentially. When the oxygen level drops below a threshold, the tumor cells become hypoxic and start secreting pro-angiogenic factors. At this stage, the tumor reaches a maximum diameter characteristic of an avascular tumor spheroid. The endothelial cells in the pre-existing vasculature respond to the pro-angiogenic factors both by chemotaxing towards higher concentrations of pro-angiogenic factors and by forming new blood vessels via angiogenesis. The tumor-induced vasculature increases the growth rate of the resulting vascularized solid tumor compared to an avascular tumor, allowing the tumor to grow beyond the spheroid in these linear-growth phases. First, in the linear-spherical phase of growth, the tumor remains spherical while its volume increases. Second, in the linear-cylindrical phase of growth the tumor elongates into a cylinder. Finally, in the linear-sheet phase of growth, tumor growth accelerates as the tumor changes from cylindrical to paddle-shaped. Substantial periods during which the tumor grows slowly or not at all separate the exponential from the linear-spherical and the linear-spherical from the linear-cylindrical growth phases. In contrast to other simulations in which avascular tumors remain spherical, our simulated avascular tumors form cylinders following the blood vessels, leading to a different distribution of hypoxic cells within the tumor. Our simulations cover time periods which are long enough to produce a range of biologically reasonable complex morphologies, allowing us to study how tumor-induced angiogenesis affects the growth rate, size and morphology of simulated tumors

Prevalence and determinants of unintended pregnancies amongst women attending antenatal clinics in Pakistan

Background: Unintended pregnancies are a global public health concern and contribute significantly to adverse maternal and neonatal health, social and economic outcomes and increase the risks of maternal deaths and neonatal mortality. In countries like Pakistan where data for the unintended pregnancies is scarce, studies are required to estimate its accurate prevalence and predictors using more specific tools such as the London Measure of Unplanned Pregnancies (LMUP). Methods: We conducted a hospital based cross sectional survey in two tertiary care hospitals in Pakistan. We used a pre tested structured questionnaire to collect the data on socio-demographic characteristics, reproductive history, awareness and past experience with contraceptives and unintended pregnancies using six item the LMUP. We used Univariate and multivariate analysis to explore the association between unintended pregnancies and predictor variables and presented the association as adjusted odds ratios. We also evaluated the psychometric properties of the Urdu version of the LMUP. Results: Amongst 3010 pregnant women, 1150 (38.2%) pregnancies were reported as unintended. In the multivariate analysis age \u3c 20 years (AOR 3.5 1.1-6.5), being illiterate (AOR 1.9 1.1-3.4), living in a rural setting (1.7 1.2-2.3), having a pregnancy interval of = \u3c 12 months (AOR 1.7 1.4-2.2), having a parity of \u3e2 (AOR 1.4 1.2-1.8), having no knowledge about contraceptive methods (AOR 3.0 1.7-5.4) and never use of contraceptive methods (AOR 2.3 1.4-5.1) remained significantly associated with unintended pregnancy. The Urdu version of the LMUP scale was found to be acceptable, valid and reliable with the Cronbach\u27s alpha of 0.85. Conclusions: This study explores a high prevalence of unintended pregnancies and important factors especially those related to family planning. Integrated national family program that provides contraceptive services especially the modern methods to women during pre-conception and post-partum would be beneficial in averting unintended pregnancies and their related adverse outcomes in Pakistan