Cost-Effectiveness Analysis of Combination Therapies for Visceral Leishmaniasis in the Indian Subcontinent

Visceral leishmaniasis (VL) is a serious health problem in the Indian subcontinent affecting the rural poor. It has a significant economic impact on concerned households. The development of drug resistance is a major problem and threatens control efforts under the VL elimination initiative. With an unprecedented choice of antileishmanial drugs (but no newer compound in clinical development), policies that protect these drugs against the emergence of resistance are required. A possible strategy that has been successfully used for malaria and tuberculosis is the use of combination therapies. This study is the first comprehensive assessment of the cost-effectiveness of all possible mono- and combination therapies for the treatment of visceral leishmaniasis in the Indian subcontinent. The analysis was done from the societal perspective, including both health provider and household costs. The present work shows that combination treatments are a cost-effective alternative to current monotherapy for VL. Given their expected impact on emergence of drug resistance, the use of combination therapy should be considered in the context of the VL elimination programme in the Indian subcontinent

Primal-Dual 2-Approximation Algorithm for the Monotonic Multiple Depot Heterogeneous Traveling Salesman Problem

We study a Multiple Depot Heterogeneous Traveling Salesman Problem (MDHTSP) where the cost of the traveling between any two targets depends on the type of the vehicle. The travel costs are assumed to be symmetric, satisfy the triangle inequality, and are monotonic, i.e., the travel costs between any two targets monotonically increases with the index of the vehicles. Exploiting the monotonic structure of the travel costs, we present a 2-approximation algorithm based on the primal-dual method

Using Processing Digital Image Methods for Documenting Tumorogenic Breast Disease Cells

We identified and isolated CD44-CD24/low Lineage tumor cells in eight of nine individuals. In mice, tumors might grow from 100 cells with these traits, but not from thousands with other phenotypes. On each serial passage, tumorigenic cells contributed to the tumor’s CD44-CD24/low Lineage tumor-causing cell as well as phenotypically variable no tumor-causing cell groupings. They are called tumorigenic or cancer-initiating cells because they constantly create malignancies, unlike additional cancer cell types. This work proposes a unique approach to identify breast asymmetry as well as tumorigenic cancer cells utilizing extremely efficient digital image processing methods that are not previously used in this research field. Chi-square tests and t-tests were used for categorical as well as continuous data. All p-values under 0.05 proved significant