Mutations in RpoB Gene and Their Association with Rifampicin-resistance Levels in Clinical Isolates of Mycobacterium Tuberculosis

Present study was aimed to identify most frequent mutations in rpoB gene region and to evaluate the association between mutations in rpoB gene and resistance levels to Rifampicin in clinical isolates of Mycobacterium tuberculosis of different geographical regions of India. A total of 100 clinical isolates of Mycobacterium tuberculosis were included in this study. Drug susceptibility testing against first line anti-tuberculosis drugs was performed on LJ medium by conventional minimal inhibitory concentration (MIC) method and the mutation(s) in rpoB gene of M. tuberculosis isolates were analyzed by sequencing method. Of the 100 M. tuberculosis isolates, 31 (31.0%) and 18 (18.0%) were found resistant and susceptible for all four first-line anti-tuberculosis drugs. The genetic mutations were observed in 96% (72/75) rifampicin-resistant M. tuberculosis isolates, while 4% (3/75) of rifampicin-resistant isolates did not have any mutation in rpoB gene. The mutation TCG531TTG (Ser531Leu) was found as most common and frequent mutation in 69.3% (52/75) of rifampicin-resistant isolates of M. tuberculosis with MIC level (≥ 512mg/l). The mutation at codon 511 was associated with low degree (128mg/l) of rifampicin-resistance, deletions at codons 514-516 or substitution at codon 516 were found to be associated with moderate degree (256mg/l) of rifampicin-resistance and mutations at codon 526, 531 were associated with the high degree (512mg/l) of rifampicin-resistance in M. tuberculosis isolates of Indian origin. The findings of this study will be useful for the development of raid and more specific indigenous molecular tools for the early diagnosis of multidrug-resistant tuberculosis in the country

Hemagglutinin Receptor Binding Avidity Drives Influenza A Virus Antigenic Drift

Refer to Web version on PubMed Central for supplementary material.Rapid antigenic evolution in the influenza A virus hemagglutinin precludes effective vaccination with existing vaccines. To understand this phenomenon, we passaged virus in mice immunized with influenza vaccine. Neutralizing antibodies selected mutants with single–amino acid hemagglutinin substitutions that increased virus binding to cell surface glycan receptors. Passaging these high-avidity binding mutants in naïve mice, but not immune mice, selected for additional hemagglutinin substitutions that decreased cellular receptor binding avidity. Analyzing a panel of monoclonal antibody hemagglutinin escape mutants revealed a positive correlation between receptor binding avidity and escape from polyclonal antibodies. We propose that in response to variation in neutralizing antibody pressure between individuals, influenza A virus evolves by adjusting receptor binding avidity via amino acid substitutions throughout the hemagglutinin globular domain, many of which simultaneously alter antigenicity.National Institute of Mental Health (U.S.). Division of Intramural ResearchNational Institute of Allergy and Infectious Diseases (U.S.)Singapore-MIT Alliance for Research and TechnologyNational Institute of General Medical Sciences (U.S.) (GM 57073)National Institute of General Medical Sciences (U.S.) (U54GM62116

Analysis of multi-location data of hybrid rice trials reveals complex genotype by environment interaction

The All India Coordinated Rice Improvement Project of ICAR-Indian Institute of Rice Research, Hyderabad organizes multi-location testing of elite lines and hybrids to test and identify new rice cultivars for the release of commercial cultivation in India. Data obtained from Initial Hybrid Rice Trials of three years were utilized to understand the genotype × environment interaction (GEI) patterns among the test locations of five different agro-ecological regions of India using GGE and AMMI biplot analysis. The combined analysis of variance and AMMI ANOVA for a yield of rice hybrids were highly significant for GEI. The GGE biplots first two PC explained 54.71%, 51.54% and 59.95% of total G + GEI variation during 2010, 2011 and 2012, respectively, whereas AMMI biplot PC1 and PC2 explained 46.62% in 2010, 36.07% in 2011 and 38.33% in 2012 of the total GEI variation. Crossover interactions, i.e. genotype rank changes across locations were observed. GGE biplot identified hybrids, viz. PAN1919, TNRH193, DRH005, VRH639, 26P29, Signet5051, KPH385, VRH667, NIPH101, SPH497, RH664 Plus and TNRH222 as stable rice hybrids. The discriminative locations identified in different test years were Coimbatore, Maruteru, VNR, Jammu, Raipur, Ludhiana, Karjat and Dabhoi. The AMMI1 biplot identified the adaptable rice hybrids viz., CNRH102, DRH005, NK6303, NK6320, DRRH78, NIPH101, Signet5050, BPH115, Bio452, NPSH2003, and DRRH83. The present study demonstrated that AMMI and GGE biplots analyses were successful in assessing genotype by environment interaction in hybrid rice trials and aided in the identification of stable and adaptable rice hybrids with higher mean and stable yields

Analysis of multi-location data of hybrid rice trials reveals complex genotype by environment interaction

The All India Coordinated Rice Improvement Project of ICAR-Indian Institute of Rice Research, Hyderabad organizes multi-location testing of elite lines and hybrids to test and identify new rice cultivars for the release of commercial cultivation in India. Data obtained from Initial Hybrid Rice Trials of three years were utilized to understand the genotype × environment interaction (GEI) patterns among the test locations of five different agro-ecological regions of India using GGE and AMMI biplot analysis. The combined analysis of variance and AMMI ANOVA for a yield of rice hybrids were highly significant for GEI. The GGE biplots first two PC explained 54.71%, 51.54% and 59.95% of total G + GEI variation during 2010, 2011 and 2012, respectively, whereas AMMI biplot PC1 and PC2 explained 46.62% in 2010, 36.07% in 2011 and 38.33% in 2012 of the total GEI variation. Crossover interactions, i.e. genotype rank changes across locations were observed. GGE biplot identified hybrids, viz. PAN1919, TNRH193, DRH005, VRH639, 26P29, Signet5051, KPH385, VRH667, NIPH101, SPH497, RH664 Plus and TNRH222 as stable rice hybrids. The discriminative locations identified in different test years were Coimbatore, Maruteru, VNR, Jammu, Raipur, Ludhiana, Karjat and Dabhoi. The AMMI1 biplot identified the adaptable rice hybrids viz., CNRH102, DRH005, NK6303, NK6320, DRRH78, NIPH101, Signet5050, BPH115, Bio452, NPSH2003, and DRRH83. The present study demonstrated that AMMI and GGE biplots analyses were successful in assessing genotype by environment interaction in hybrid rice trials and aided in the identification of stable and adaptable rice hybrids with higher mean and stable yields

Magnetic Proximity induced efficient charge-to-spin conversion in large area PtSe2_{2}/Ni80_{80}Fe20_{20} heterostructures

As a topological Dirac semimetal with controllable spin-orbit coupling and conductivity, PtSe$_2$, a transition-metal dichalcogenide, is a promising material for several applications from optoelectric to sensors. However, its potential for spintronics applications is yet to be explored. In this work, we demonstrate that PtSe$_{2}$/Ni$_{80}$Fe$_{20}$ heterostructure can generate a large damping-like current-induced spin-orbit torques (SOT), despite the absence of spin-splitting in bulk PtSe$_{2}$. The efficiency of charge-to-spin conversion is found to be $(-0.1 \pm 0.02)$~nm$^{-1}$ in PtSe$_{2}$/Ni$_{80}$Fe$_{20}$, which is three times that of the control sample, Ni$_{80}$Fe$_{20}$/Pt. Our band structure calculations show that the SOT due to the PtSe$_2$ arises from an unexpectedly large spin splitting in the interfacial region of PtSe$_2$ introduced by the proximity magnetic field of the Ni$_{80}$Fe$_{20}$ layer. Our results open up the possibilities of using large-area PtSe$_{2}$ for energy-efficient nanoscale devices by utilizing the proximity-induced SOT.Comment: 18 pages, 4 figure

Birthing practices of traditional birth attendants in South Asia in the context of training programmes

Traditional Birth Attendants (TBA) training has been an important component of public health policy interventions to improve maternal and child health in developing countries since the 1970s. More recently, since the 1990s, the TBA training strategy has been increasingly seen as irrelevant, ineffective or, on the whole, a failure due to evidence that the maternal mortality rate (MMR) in developing countries had not reduced. Although, worldwide data show that, by choice or out of necessity, 47 percent of births in the developing world are assisted by TBAs and/or family members, funding for TBA training has been reduced and moved to providing skilled birth attendants for all births. Any shift in policy needs to be supported by appropriate evidence on TBA roles in providing maternal and infant health care service and effectiveness of the training programmes. This article reviews literature on the characteristics and role of TBAs in South Asia with an emphasis on India. The aim was to assess the contribution of TBAs in providing maternal and infant health care service at different stages of pregnancy and after-delivery and birthing practices adopted in home births. The review of role revealed that apart from TBAs, there are various other people in the community also involved in making decisions about the welfare and health of the birthing mother and new born baby. However, TBAs have changing, localised but nonetheless significant roles in delivery, postnatal and infant care in India. Certain traditional birthing practices such as bathing babies immediately after birth, not weighing babies after birth and not feeding with colostrum are adopted in home births as well as health institutions in India. There is therefore a thin precarious balance between the application of biomedical and traditional knowledge. Customary rituals and perceptions essentially affect practices in home and institutional births and hence training of TBAs need to be implemented in conjunction with community awareness programmes

Chronic Obstructive Pulmonary Disease Self-Management in Three LMICs: A Pilot Randomized Trial

INTRODUCTION: Chronic obstructive pulmonary disease (COPD) disproportionately affects low- and middle-income countries (LMICs). Health systems are ill-prepared to manage the increase in COPD cases. METHODS: We carried out a pilot effectiveness-implementation randomized field trial of a community health worker (CHW)-supported, one-year self-management intervention in individuals with COPD grade B-D. The study took place in low-resource settings of Nepal, Peru, and Uganda. The primary outcome was the St. George's Respiratory Questionnaire (SGRQ) score at one year. We evaluated differences in moderate-to-severe exacerbations, all-cause hospitalizations and the EuroQol score (EQ5D-3L) at 12 months. RESULTS: We randomly assigned 239 participants (119 control, 120 intervention) with grade B-D COPD to a multi-component, CHW-supported intervention or standard of care and COPD education. 25 participants (21%) died or were lost to follow-up in the control arm compared to 11 (9%) in the intervention arm. At 12 months, there was no difference in mean total SGRQ scores between intervention and control arms (34.7 vs. 34.0 points; adjusted mean difference 1.0, 95% CI -4.2 to 6.1; p=0.71). The intervention arm had a higher proportion of hospitalizations (10% vs 5.2%; adjusted odds ratio 2.2, 95% CI 0.8-7.5; p=0.15) at 12 months compared to controls. CONCLUSION: A CHW-based intervention to support self-management of acute exacerbations of COPD in three resource-poor settings did not result in differences in SGRQ scores at one year. Fidelity was high, and intervention engagement was moderate. While results cannot differentiate between a failed intervention or implementation, it nonetheless suggests that we need to revisit our strategy. Clinical trial registration available at www. CLINICALTRIALS: gov, ID: NCT03359915

Identification of Yeast Transcriptional Regulation Networks Using Multivariate Random Forests

The recent availability of whole-genome scale data sets that investigate complementary and diverse aspects of transcriptional regulation has spawned an increased need for new and effective computational approaches to analyze and integrate these large scale assays. Here, we propose a novel algorithm, based on random forest methodology, to relate gene expression (as derived from expression microarrays) to sequence features residing in gene promoters (as derived from DNA motif data) and transcription factor binding to gene promoters (as derived from tiling microarrays). We extend the random forest approach to model a multivariate response as represented, for example, by time-course gene expression measures. An analysis of the multivariate random forest output reveals complex regulatory networks, which consist of cohesive, condition-dependent regulatory cliques. Each regulatory clique features homogeneous gene expression profiles and common motifs or synergistic motif groups. We apply our method to several yeast physiological processes: cell cycle, sporulation, and various stress conditions. Our technique displays excellent performance with regard to identifying known regulatory motifs, including high order interactions. In addition, we present evidence of the existence of an alternative MCB-binding pathway, which we confirm using data from two independent cell cycle studies and two other physioloigical processes. Finally, we have uncovered elaborate transcription regulation refinement mechanisms involving PAC and mRRPE motifs that govern essential rRNA processing. These include intriguing instances of differing motif dosages and differing combinatorial motif control that promote regulatory specificity in rRNA metabolism under differing physiological processes

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation