Raciolinguistic Entanglements and Transraciolinguistic Transgressions: A Collaborative Autoethnography of Three South Asian TESOLers in the US

Research Articl

In Conversations with Scholars on Contemporary Issues and Research Agendas in Language Ideologies

Intervie

Effect of Duration and Intermittency of Rifampin on Tuberculosis Treatment Outcomes: A Systematic Review and Meta-Analysis

In a systematic review of randomized controlled trials on tuberculosis treatment, Dick Menzies and colleagues find shorter courses of rifampin to be associated with poorer treatment outcomes

OptCircuit: An optimization based method for computational design of genetic circuits

<p>Abstract</p> <p>Background</p> <p>Recent years has witnessed an increasing number of studies on constructing simple synthetic genetic circuits that exhibit desired properties such as oscillatory behavior, inducer specific activation/repression, etc. It has been widely acknowledged that that task of building circuits to meet multiple inducer-specific requirements is a challenging one. This is because of the incomplete description of component interactions compounded by the fact that the number of ways in which one can chose and interconnect components, increases exponentially with the number of components.</p> <p>Results</p> <p>In this paper we introduce OptCircuit, an optimization based framework that automatically identifies the circuit components from a list and connectivity that brings about the desired functionality. Multiple literature sources are used to compile a comprehensive compilation of kinetic descriptions of promoter-protein pairs. The dynamics that govern the interactions between the elements of the genetic circuit are currently modeled using deterministic ordinary differential equations but the framework is general enough to accommodate stochastic simulations. The desired circuit response is abstracted as the maximization/minimization of an appropriately constructed objective function. Computational results for a toggle switch example demonstrate the ability of the framework to generate the complete list of circuit designs of varying complexity that exhibit the desired response. Designs identified for a genetic decoder highlight the ability of OptCircuit to suggest circuit configurations that go beyond the ones compatible with digital logic-based design principles. Finally, the results obtained from the concentration band detector example demonstrate the ability of OptCircuit to design circuits whose responses are contingent on the level of external inducer as well as pinpoint parameters for modification to rectify an existing (non-functional) biological circuit and restore functionality.</p> <p>Conclusion</p> <p>Our results demonstrate that OptCircuit framework can serve as a design platform to aid in the construction and finetuning of integrated biological circuits.</p

Classification and Regression Tree and Spatial Analyses Reveal Geographic Heterogeneity in Genome Wide Linkage Study of Indian Visceral Leishmaniasis

Genome wide linkage studies (GWLS) have provided evidence for loci controlling visceral leishmaniasis on Chromosomes 1p22, 6q27, 22q12 in Sudan and 6q27, 9p21, 17q11-q21 in Brazil. Genome wide studies from the major focus of disease in India have not previously been reported.We undertook a GWLS in India in which a primary ∼10 cM (515 microsatellites) scan was carried out in 58 multicase pedigrees (74 nuclear families; 176 affected, 353 total individuals) and replication sought in 79 pedigrees (102 nuclear families; 218 affected, 473 total individuals). The primary scan provided evidence (≥2 adjacent markers allele-sharing LOD≥0.59; nominal P≤0.05) for linkage on Chromosomes 2, 5, 6, 7, 8, 10, 11, 20 and X, with peaks at 6p25.3-p24.3 and 8p23.1-p21.3 contributed to largely by 31 Hindu families and at Xq21.1-q26.1 by 27 Muslim families. Refined mapping confirmed linkage across all primary scan families at 2q12.2-q14.1 and 11q13.2-q23.3, but only 11q13.2-q23.3 replicated (combined LOD = 1.59; P = 0.0034). Linkage at 6p25.3-p24.3 and 8p23.1-p21.3, and at Xq21.1-q26.1, was confirmed by refined mapping for primary Hindu and Muslim families, respectively, but only Xq21.1-q26.1 replicated across all Muslim families (combined LOD 1.49; P = 0.0045). STRUCTURE and SMARTPCA did not identify population genetic substructure related to religious group. Classification and regression tree, and spatial interpolation, analyses confirm geographical heterogeneity for linkages at 6p25.3-p24.3, 8p23.1-p21.3 and Xq21.1-q26.1, with specific clusters of families contributing LOD scores of 2.13 (P = 0.0009), 1.75 (P = 0.002) and 1.84 (P = 0.001), respectively.GWLS has identified novel loci that show geographical heterogeneity in their influence on susceptibility to VL in India

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.Peer reviewe