Insights from the analysis of conserved motifs and permitted amino acid exchanges in the human, the fly and the worm GPCR clusters

G-protein coupled receptors (GPCRs) belong to biologically important and functionally diverse and largest super family of membrane proteins. GPCRs retain a characteristic membrane topology of seven alpha helices with three intracellular, three extracellular loops and flanking N' and C' terminal residues. Subtle differences do exist in the helix boundaries (TM-domain), loop lengths, sequence features such as conserved motifs, and substituting amino acid patterns and their physiochemical properties amongst these sequences (clusters) at intra-genomic and inter-genomic level (please re-phrase into 2 statements for clarity). In the current study, we employ prediction of helix boundaries and scores derived from amino acid substitution exchange matrices to identify the conserved amino acid residues (motifs) as consensus in aligned set of homologous GPCR sequences. Co-clustered GPCRs from human and other genomes, organized as 32 clusters, were employed to study the amino acid conservation patterns and species-specific or cluster-specific motifs. Critical analysis on sequence composition and properties provide clues to connect functional relevance within and across genome for vast practical applications such as design of mutations and understanding of disease-causing genetic abnormalities

Cooking practices, air quality, and the acceptability of advanced cookstoves in Haryana, India: an exploratory study to inform large-scale interventions.

BackgroundIn India, approximately 66% of households rely on dung or woody biomass as fuels for cooking. These fuels are burned under inefficient conditions, leading to household air pollution (HAP) and exposure to smoke containing toxic substances. Large-scale intervention efforts need to be informed by careful piloting to address multiple methodological and sociocultural issues. This exploratory study provides preliminary data for such an exercise from Palwal District, Haryana, India.MethodsTraditional cooking practices were assessed through semi-structured interviews in participating households. Philips and Oorja, two brands of commercially available advanced cookstoves with small blowers to improve combustion, were deployed in these households. Concentrations of particulate matter (PM) with a diameter <2.5 μm (PM2.5) and carbon monoxide (CO) related to traditional stove use were measured using real-time and integrated personal, microenvironmental samplers for optimizing protocols to evaluate exposure reduction. Qualitative data on acceptability of advanced stoves and objective measures of stove usage were also collected.ResultsTwenty-eight of the thirty-two participating households had outdoor primary cooking spaces. Twenty households had liquefied petroleum gas (LPG) but preferred traditional stoves as the cost of LPG was higher and because meals cooked on traditional stoves were perceived to taste better. Kitchen area concentrations and kitchen personal concentrations assessed during cooking events were very high, with respective mean PM2.5 concentrations of 468 and 718 µg/m3. Twenty-four hour outdoor concentrations averaged 400 µg/m3. Twenty-four hour personal CO concentrations ranged between 0.82 and 5.27 ppm. The Philips stove was used more often and for more hours than the Oorja.ConclusionsThe high PM and CO concentrations reinforce the need for interventions that reduce HAP exposure in the aforementioned community. Of the two stoves tested, participants expressed satisfaction with the Philips brand as it met the local criteria for usability. Further understanding of how the introduction of an advanced stove influences patterns of household energy use is needed. The preliminary data provided here would be useful for designing feasibility and/or pilot studies aimed at intervention efforts locally and nationally

Development of land-use regression models for fine particles and black carbon in peri-urban South India

Land-use regression (LUR) has been used to model local spatial variability of particulate matter in cities of high-income countries. Performance of LUR models is unknown in less urbanized areas of low-/middle-income countries (LMICs) experiencing complex sources of ambient air pollution and which typically have limited land use data. To address these concerns, we developed LUR models using satellite imagery (e.g., vegetation, urbanicity) and manually-collected data from a comprehensive built-environment survey (e.g., roads, industries, non-residential places) for a peri-urban area outside Hyderabad, India. As part of the CHAI (Cardiovascular Health effects of Air pollution in Telangana, India) project, concentrations of fine particulate matter (PM2.5) and black carbon were measured over two seasons at 23 sites. Annual mean (sd) was 34.1 (3.2) mug/m(3) for PM2.5 and 2.7 (0.5) mug/m(3) for black carbon. The LUR model for annual black carbon explained 78% of total variance and included both local-scale (energy supply places) and regional-scale (roads) predictors. Explained variance was 58% for annual PM2.5 and the included predictors were only regional (urbanicity, vegetation). During leave-one-out cross-validation and cross-holdout validation, only the black carbon model showed consistent performance. The LUR model for black carbon explained a substantial proportion of the spatial variability that could not be captured by simpler interpolation technique (ordinary kriging). This is the first study to develop a LUR model for ambient concentrations of PM2.5 and black carbon in a non-urban area of LMICs, supporting the applicability of the LUR approach in such settings. Our results provide insights on the added value of manually-collected built-environment data to improve the performance of LUR models in settings with limited data availability. For both pollutants, LUR models predicted substantial within-village variability, an important feature for future epidemiological studies

Case studies on heat stress related perceptions in different industrial sectors in southern India

Linkages between thermal loads and its physiological consequences have been widely studied in non-tropical developed country settings. In many developing countries like India, despite the widespread recognition of the problem, limited attempts have been made to estimate health impacts related to occupational heat stress and fewer yet to link heat stress with potential productivity losses. This is reflected in the ubiquity of workplaces with limited or no controls to reduce exposures. As a prelude to understanding the feasibility of alternative interventions in different industrial sectors, we present case studies from 10 different industrial units in Tamil Nadu, Chennai, which describe perceptions of occupational heat stress among the workers and supervisors/management