Geospatial modelling of overlapping habitats for identification of tiger corridor networks in the Terai Arc landscape of India

Wildlife corridors in a landscape include local vegetation, topography, prey base, water and are associated with isolated wildlife habitat patches. They facilitate maintenance of ecological structure and function as well as provide connectivity to faunal populations supporting genetic transfers, and are elements critical to wildlife management. In this work, habitat patches for tiger, both inside as well as outside of Protected Areas have been identified by developing a Habitat Suitability Index model utilizing Remote Sensing and Geographical Information System datasets for the Terai Arc landscape, India. By using a computational approach based on the framework of theory of complex networks, for exclusively pairwise interactions between the habitat patches, a potential tiger corridor network has been structurally identified and studied in this landscape. The interactions between these habitat patches on a spatial scale has been analyzed as a clique of the corridor network. Further, the Clique Percolation Method has been applied to detect overlapping communities of habitat patches in the landscape. The Cliques required for maintaining contiguity between the habitat patches in order to support tiger movement are validated using field observations of tiger communities within the landscape matrix. The model developed for identification of tiger corridors in this study could potentially be of a vital importance for wildlife stakeholders to better understand and manage tiger populations both within and outside of protected areas. The study also highlights Critical Habitat Patches and their importance in maintaining landscape connectivity for tiger dispersal in the landscape. Using a report published by the Government of India as a benchmark, the model presented in the work is found to have an accuracy of 90.73% in predicting tiger carrying patches and the corridor network in the focal landscape

Antifungal Resistance Analysis of Environmental Isolates of Aspergillus in North India

Triazoles are the major group of antifungals for treating Aspergillus infections. The morbidity and mortality associated with these infections is high and rate of treatment failure is more in patients infected with azole resistant Aspergillus. The azole resistant Aspergillus isolates have been recovered from both azole treated and azole naive patients. Thus, there may be an environmental route of exposure to azole resistant Aspergillus. The present study was envisaged for the isolation and enumeration of environmental isolates of Aspergillus resistant to medically available antifungal azole drugs in North Indian environment. A total of 25 soil samples were collected from North Indian agricultural farms where azole pesticides were being used. The soil samples were screened for Aspergillus isolates by serial dilution pour plate method. Further, their drug susceptibility testing was performed using disc diffusion, E- strip and micro-broth dilution method against medically available triazoles: itraconazole, ketoconazole, fluconazole and voriconazole. A total of 41 Aspergillus species were isolated from the soil samples. Based on conventional microscopic assay, 13 of them were identified as Aspergillus fumigatus, 9 as Aspergillus niger, 5 as Aspergillus terreus, 3 as Aspergillus nidulans, 1 as Aspergillus flavus and 9 as other Aspergillus species. Resistance for all tested antifungal drugs was detected in 7.3% Aspergillus isolates and 43.7% isolates were resistant to any of the tested azole drugs. The results demonstrated that Aspergillus isolates resistant to medical triazoles are present in the agricultural farms

The major genetic determinants of HIV-1 control affect HLA class I peptide presentation.

Infectious and inflammatory diseases have repeatedly shown strong genetic associations within the major histocompatibility complex (MHC); however, the basis for these associations remains elusive. To define host genetic effects on the outcome of a chronic viral infection, we performed genome-wide association analysis in a multiethnic cohort of HIV-1 controllers and progressors, and we analyzed the effects of individual amino acids within the classical human leukocyte antigen (HLA) proteins. We identified >300 genome-wide significant single-nucleotide polymorphisms (SNPs) within the MHC and none elsewhere. Specific amino acids in the HLA-B peptide binding groove, as well as an independent HLA-C effect, explain the SNP associations and reconcile both protective and risk HLA alleles. These results implicate the nature of the HLA-viral peptide interaction as the major factor modulating durable control of HIV infection