Out-of-plane dielectric constant and insulator-superconductor transition in Bi_2Sr_2Dy_{1-x}Er_xCu_2O_8 single crystals

The out-of-plane dielectric constant of the parent insulator of the high-temperature superconductor Bi_2Sr_2(Dy,Er)Cu_2O_8 was measured and analysed from 80 to 300 K in the frequency range of 10^6-10^9 Hz. All the samples were found to show a fairly large value of 10-60, implying some kind of charge inhomogeneity in the CuO_2 plane. Considering that the superconducting sample Bi_2Sr_2(Ca,Pr)Cu_2O_8 also shows a similar dielectric constant, the charge inhomogeneity plays an important role in the insulator-superconductor transition.Comment: RevTex4 format, 5 pages, 3 figures, submitted to J. Phys. Condens. Ma

Anti-hepatitis B core antigen testing with detection and characterization of occult hepatitis B virus by an in-house nucleic acid testing among blood donors in Behrampur, Ganjam, Orissa in southeastern India: implications for transfusion

<p>Abstract</p> <p>Background</p> <p>Occult hepatitis B virus (HBV) infection might transmit viremic units into the public blood supply if only hepatitis B surface antigen (HBsAg) testing is used for donor screening. Our aim was to evaluate the prevalence of occult HBV infection among the HBsAg negative/antiHBc positive donations from a highly HIV prevalent region of India.</p> <p>Methods</p> <p>A total of 729 HBsAg negative donor units were included in this study. Surface gene and precore region were amplified by in house nucleic acid test (NAT) for detection of occult HBV infection and surface gene was analyzed after direct sequencing.</p> <p>Results</p> <p>A total of 220 (30.1%) HBsAg negative donors were antiHBc positive, of them 66 (30%) were HBV DNA positive by NAT. HBV DNA positivity among 164 antiHBc only group, was 27.1% and among 40 antiHBs positive group was 30.0%. HBV/D (93.3%) was predominant and prevalence of both HBV/C and HBV/A was 3.3%. Single or multiple amino acids substitutions were found in 95% samples.</p> <p>Conclusion</p> <p>Thus, a considerable number of HBV infected donors remain undiagnosed, if only HBsAg is used for screening. Addition of antiHBc testing for donor screening, although will lead to rejection of a large number of donor units, will definitely eliminate HBV infected donations and help in reducing HBV transmission with its potential consequences, especially among the immunocompromised population. The HBV genetic diversity found in this donor population are in accordance with other parts of India.</p

Characterization of the Occult Hepatitis B Virus Variants Circulating among the Blood Donors from Eastern India

A previous study from West Bengal documented very high rate of occult HBV infection (OBI) among the HBsAg negative blood donors. This study was aimed to characterize the OBI strains circulating among the blood donors and to estimate the risk associated with the prevailing viral variants/mutants. Blood samples from 2195 voluntary blood donors were included in the study. HBsAg, HBeAg, anti-HBc, and anti-HBs statuses of the samples were done by ELISA based detection. PCR amplification and sequencing were done to determine HBV genotypes, basal core promoter (BCP), and precore (Pre-C) mutations. Among the study samples, 268 were anti-HBc positive/HBsAg negative, among which 65 (24.25%) were HBV DNA positive. Phylogenetic analysis revealed the presence of HBV/D (87.23%), HBV/A (8.51%), and HBV/C (4.26%) (P<0.0001). HBV/D3 (65.85%) was the significantly prevalent subgenotype over HBV/D2 (26.83%) and HBV/D1 (7.31%) (P=0.0003). Considerable prevalence of differential BCP (1752C, 1753C, 1762T/1764A, 1753C+1762T/1764A, 1773C, and 1814C) and reverse transcriptase (rt) gene (rtI91L, rtL93P, rtS106C, rtR110G, rtN118T, rtS119T, rtY126H, rtG127W/R, rtC136R, and rtY158H) mutations was identified. Association of specific HBV subgenotypes with OBI was interesting and needs further study. Clinically relevant mutations were prevalent among the OBI strains which are of serious concern

Characterization of the Occult Hepatitis B Virus Variants Circulating among the Blood Donors from Eastern India

A previous study from West Bengal documented very high rate of occult HBV infection (OBI) among the HBsAg negative blood donors. This study was aimed to characterize the OBI strains circulating among the blood donors and to estimate the risk associated with the prevailing viral variants/mutants. Blood samples from 2195 voluntary blood donors were included in the study. HBsAg, HBeAg, anti-HBc, and anti-HBs statuses of the samples were done by ELISA based detection. PCR amplification and sequencing were done to determine HBV genotypes, basal core promoter (BCP), and precore (Pre-C) mutations. Among the study samples, 268 were anti-HBc positive/HBsAg negative, among which 65 (24.25%) were HBV DNA positive. Phylogenetic analysis revealed the presence of HBV/D (87.23%), HBV/A (8.51%), and HBV/C (4.26%) ( &lt; 0.0001). HBV/D3 (65.85%) was the significantly prevalent subgenotype over HBV/D2 (26.83%) and HBV/D1 (7.31%) ( = 0.0003). Considerable prevalence of differential BCP (1752C, 1753C, 1762T/1764A, 1753C+1762T/1764A, 1773C, and 1814C) and reverse transcriptase (rt) gene (rtI91L, rtL93P, rtS106C, rtR110G, rtN118T, rtS119T, rtY126H, rtG127W/R, rtC136R, and rtY158H) mutations was identified. Association of specific HBV subgenotypes with OBI was interesting and needs further study. Clinically relevant mutations were prevalent among the OBI strains which are of serious concern

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Integrated genomic characterization of oesophageal carcinoma

Oesophageal cancers are prominent worldwide; however, there are few targeted therapies and survival rates for these cancers remain dismal. Here we performed a comprehensive molecular analysis of 164 carcinomas of the oesophagus derived from Western and Eastern populations. Beyond known histopathological and epidemiologic distinctions, molecular features differentiated oesophageal squamous cell carcinomas from oesophageal adenocarcinomas. Oesophageal squamous cell carcinomas resembled squamous carcinomas of other organs more than they did oesophageal adenocarcinomas. Our analyses identified three molecular subclasses of oesophageal squamous cell carcinomas, but none showed evidence for an aetiological role of human papillomavirus. Squamous cell carcinomas showed frequent genomic amplifications of CCND1 and SOX2 and/or TP63, whereas ERBB2, VEGFA and GATA4 and GATA6 were more commonly amplified in adenocarcinomas. Oesophageal adenocarcinomas strongly resembled the chromosomally unstable variant of gastric adenocarcinoma, suggesting that these cancers could be considered a single disease entity. However, some molecular features, including DNA hypermethylation, occurred disproportionally in oesophageal adenocarcinomas. These data provide a framework to facilitate more rational categorization of these tumours and a foundation for new therapies

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

The determination of gold in ore samples by inductively coupled plasma optical emission spectrometry (ICP-OES)

Fire assay is the most common technique for the determination of precious metals in rock and ore samples, and is generally accurate for the determination of gold. However, with the development of modern laboratory techniques such as Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES) and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), alternative methods have become available which offer the advantages of rapid determination of small concentrations of gold in a number of samples for preliminary exploration studies. A multi-parametric linear regression model was used to estimate the observed interferences and using this model, the gold content in ores has been estimated. A simple analytical method for the determination of gold in ore samples using ICP-OES is reported and these results show that this method can be successfully applied when the gold concentration is high (above 0.7ppm) with an error in the range of 9-11% in ore samples. The advantage of thus method over conventionally adopted Fire Assay is small sample size and larger sample throughput

Computational models for prediction of protein–protein interaction in rice and Magnaporthe grisea

Introduction: Plant–microbe interactions play a vital role in the development of strategies to manage pathogen-induced destructive diseases that cause enormous crop losses every year. Rice blast is one of the severe diseases to rice Oryza sativa (O. sativa) due to Magnaporthe grisea (M. grisea) fungus. Protein–protein interaction (PPI) between rice and fungus plays a key role in causing rice blast disease. Methods: In this paper, four genomic information-based models such as (i) the interolog, (ii) the domain, (iii) the gene ontology, and (iv) the phylogenetic-based model are developed for predicting the interaction between O. sativa and M. grisea in a whole-genome scale. Results and Discussion: A total of 59,430 interacting pairs between 1,801 rice proteins and 135 blast fungus proteins are obtained from the four models. Furthermore, a machine learning model is developed to assess the predicted interactions. Using composition-based amino acid composition (AAC) and conjoint triad (CT) features, an accuracy of 88% and 89% is achieved, respectively. When tested on the experimental dataset, the CT feature provides the highest accuracy of 95%. Furthermore, the specificity of the model is verified with other pathogen–host datasets where less accuracy is obtained, which confirmed that the model is specific to O. sativa and M. grisea. Understanding the molecular processes behind rice resistance to blast fungus begins with the identification of PPIs, and these predicted PPIs will be useful for drug design in the plant science community

DataSheet_1_Computational models for prediction of protein–protein interaction in rice and Magnaporthe grisea.csv

IntroductionPlant–microbe interactions play a vital role in the development of strategies to manage pathogen-induced destructive diseases that cause enormous crop losses every year. Rice blast is one of the severe diseases to rice Oryza sativa (O. sativa) due to Magnaporthe grisea (M. grisea) fungus. Protein–protein interaction (PPI) between rice and fungus plays a key role in causing rice blast disease.MethodsIn this paper, four genomic information-based models such as (i) the interolog, (ii) the domain, (iii) the gene ontology, and (iv) the phylogenetic-based model are developed for predicting the interaction between O. sativa and M. grisea in a whole-genome scale.Results and DiscussionA total of 59,430 interacting pairs between 1,801 rice proteins and 135 blast fungus proteins are obtained from the four models. Furthermore, a machine learning model is developed to assess the predicted interactions. Using composition-based amino acid composition (AAC) and conjoint triad (CT) features, an accuracy of 88% and 89% is achieved, respectively. When tested on the experimental dataset, the CT feature provides the highest accuracy of 95%. Furthermore, the specificity of the model is verified with other pathogen–host datasets where less accuracy is obtained, which confirmed that the model is specific to O. sativa and M. grisea. Understanding the molecular processes behind rice resistance to blast fungus begins with the identification of PPIs, and these predicted PPIs will be useful for drug design in the plant science community.</p