Voltage control performance of AWS connected for grid operation

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Genetic variability of Indian yaks using random amplified polymorphic DNA markers

Indian yaks are categorized into common yaks, bisonian yaks and bareback yaks. Genetic similarities and divergence among them was analyzed by random amplified polymorphic DNA (RAPD) technique using ten decamer oligonuclotide primers. Only five primers (ILO 526, OPAV 15, ILO 1127, ILO 1065 and ILO 876) out of the ten primers tried produced consistant polymorphic fingerprints. Of the 76 fingerprints produced, 49 were present in all types, 21 were individual specific and 6 were polymorphic for different types. The pair wise comparison studied for different primers indicated the average bands sharing ranged from 78% in bareback to 88% in common type. There was no significant difference (P .0.05%) between the mean average percentage (MAPD) values observed between Indian yaks.Key words: Yak types, RAPD, DNA fingerprints

Ukraine–Russia Conflict and Stock Markets Reactions in Europe

This paper analyses the impact of Ukraine–Russia conflict on stock markets in Europe. We consider the stock markets of nine EU countries and Russia. The analysis consists of day-firm which includes the time between 24 November 2021 and 23 May 2022. We consider ordinary least squared (OLS) and fixed effects as baseline models. Additionally, we consider the impact of this conflict on stock return for several months, the elasticity test, the instrumental variable—two-stage least squared (2SLS) approach for the robustness test and endogeneity concerns. We find evidence of the negative impact of the Ukraine–Russia conflict on stock return of that stock markets. In addition, our finding indicates that the impact of this war on the mining construction and manufacturing sectors is greater than on other sectors because Russia and Ukraine are the key suppliers or exporters of mining and manufacturing sector. Our finding also indicates that Ukraine–Russia conflict largely affects stock return of Russian stocks because Russia is directly involved in the conflict

Novel Retinoic Acid Receptor Alpha Agonists for Treatment of Kidney Disease

Development of pharmacologic agents that protect podocytes from injury is a critical strategy for the treatment of kidney glomerular diseases. Retinoic acid reduces proteinuria and glomerulosclerosis in multiple animal models of kidney diseases. However, clinical studies are limited because of significant side effects of retinoic acid. Animal studies suggest that all trans retinoic acid (ATRA) attenuates proteinuria by protecting podocytes from injury. The physiological actions of ATRA are mediated by binding to all three isoforms of the nuclear retinoic acid receptors (RARs): RARα, RARβ, and RARγ. We have previously shown that ATRA exerts its renal protective effects mainly through the agonism of RARα. Here, we designed and synthesized a novel boron-containing derivative of the RARα-specific agonist Am580. This new derivative, BD4, binds to RARα receptor specifically and is predicted to have less toxicity based on its structure. We confirmed experimentally that BD4 binds to RARα with a higher affinity and exhibits less cellular toxicity than Am580 and ATRA. BD4 induces the expression of podocyte differentiation markers (synaptopodin, nephrin, and WT-1) in cultured podocytes. Finally, we confirmed that BD4 reduces proteinuria and improves kidney injury in HIV-1 transgenic mice, a model for HIV-associated nephropathy (HIVAN). Mice treated with BD4 did not develop any obvious toxicity or side effect. Our data suggest that BD4 is a novel RARα agonist, which could be used as a potential therapy for patients with kidney disease such as HIVAN

Phenomenological Aspects of Gauge Mediation with Sequestered Supersymmetry Breaking in light of Dark Matter Detection

In a recent work, a model of gauge mediation with sequestered supersymmetry (SUSY) breaking was proposed. In this model, the mass of the gravitino is O(100) GeV without causing the flavor-changing neutral-current problem. In contrast to traditional gauge mediation, the gravitino is not the lightest SUSY particle and the neutralino is the candidate of the dark matter. In this paper, we investigate phenomenological aspects of this model and discuss the possibility of the direct detection of the dark matter. In particular, we focus on the light neutralino case and find that the light-Higgsino scenario such as the focus point is interesting, taking account of the recent CDMS result.Comment: 17 pages, 8 figures; v2:references added, some corrections; v3:version accepted for publication in JHE

Telomerase activity as an adjunct to high-risk human papillomavirus types 16 and 18 and cytology screening in cervical cancer

Telomerase is a ribonucleoprotein comprising an RNA template, the telomerase-associated protein and its catalytic subunit, human telomerase reverse transcriptase (hTERT). Telomerase activation is a critical step in cellular immortalisation and development of cancer. Enhanced telomerase activity has been demonstrated in cervical cancer. In the present study telomerase activity and hTERT mRNA expression were evaluated and correlated with the presence of human papillomavirus (HPV) infection and cytological changes in the cervical lesions. Telomerase activity was assayed by telomeric repeat amplification protocol, hTERT mRNA expression by reverse transcriptase polymerase chain reaction and presence of high risk HPV (HR-HPV) infection by polymerase chain reaction. Out of 154 cervical samples of different cytology, 90 (58.44%) were positive for HR-HPV types 16/18, while among 55 normal cervical scrapes, 10 (18.18%) were HPV DNA positive. All 59 invasive cancer samples showed a very high telomerase activity. Among dysplasia, seven (63.6%) mild dysplasia, 18 (100%) of moderate, 20 (100%) of severe dysplasia and 6 (100%) carcinoma in situ (CIS) samples were positive with mild to moderate to high to very high telomerase activity respectively. Seven (12.7%) samples of apparently normal cervical scrapes were weakly positive for telomerase activity. We observed a good correlation (P<0.001) between telomerase activity and HR-HPV 16/18 positivity with a sensitivity of 88.1% for HPV and 100% for telomerase activity. It is suggested that telomerase activity may be used as an adjunct to cytology and HPV DNA testing in triaging women with cervical lesions

Success Factors of European Syndromic Surveillance Systems: A Worked Example of Applying Qualitative Comparative Analysis

Introduction: Syndromic surveillance aims at augmenting traditional public health surveillance with timely information. To gain a head start, it mainly analyses existing data such as from web searches or patient records. Despite the setup of many syndromic surveillance systems, there is still much doubt about the benefit of the approach. There are diverse interactions between performance indicators such as timeliness and various system characteristics. This makes the performance assessment of syndromic surveillance systems a complex endeavour. We assessed if the comparison of several syndromic surveillance systems through Qualitative Comparative Analysis helps to evaluate performance and identify key success factors. Materials and Methods: We compiled case-based, mixed data on performance and characteristics of 19 syndromic surveillance systems in Europe from scientific and grey literature and from site visits. We identified success factors by applying crisp-set Qualitative Comparative Analysis. We focused on two main areas of syndromic surveillance application: seasonal influenza surveillance and situational awareness during different types of potentially health threatening events. Results: We found that syndromic surveillance systems might detect the onset or peak of seasonal influenza earlier if they analyse non-clinical data sources. Timely situational awareness during different types of events is supported by an automated syndromic surveillance system capable of analysing multiple syndromes. To our surprise, the analysis of multiple data sources was no key success factor for situational awareness. Conclusions: We suggest to consider these key success factors when designing or further developing syndromic surveillance systems. Qualitative Comparative Analysis helped interpreting complex, mixed data on small-N cases and resulted in concrete and practically relevant findings

A Primer on Regression Methods for Decoding cis-Regulatory Logic

The rapidly emerging field of systems biology is helping us to understand the molecular determinants of phenotype on a genomic scale [1]. Cis-regulatory elements are major sequence-based determinants of biological processes in cells and tissues [2]. For instance, during transcriptional regulation, transcription factors (TFs) bind to very specific regions on the promoter DNA [2,3] and recruit the basal transcriptional machinery, which ultimately initiates mRNA transcription (Figure 1A). Learning cis-Regulatory Elements from Omics Data A vast amount of work over the past decade has shown that omics data can be used to learn cis-regulatory logic on a genome-wide scale [4-6]--in particular, by integrating sequence data with mRNA expression profiles. The most popular approach has been to identify over-represented motifs in promoters of genes that are coexpressed [4,7,8]. Though widely used, such an approach can be limiting for a variety of reasons. First, the combinatorial nature of gene regulation is difficult to explicitly model in this framework. Moreover, in many applications of this approach, expression data from multiple conditions are necessary to obtain reliable predictions. This can potentially limit the use of this method to only large data sets [9]. Although these methods can be adapted to analyze mRNA expression data from a pair of biological conditions, such comparisons are often confounded by the fact that primary and secondary response genes are clustered together--whereas only the primary response genes are expected to contain the functional motifs [10]. A set of approaches based on regression has been developed to overcome the above limitations [11-32]. These approaches have their foundations in certain biophysical aspects of gene regulation [26,33-35]. That is, the models are motivated by the expected transcriptional response of genes due to the binding of TFs to their promoters. While such methods have gathered popularity in the computational domain, they remain largely obscure to the broader biology community. The purpose of this tutorial is to bridge this gap. We will focus on transcriptional regulation to introduce the concepts. However, these techniques may be applied to other regulatory processes. We will consider only eukaryotes in this tutorial

PeakRegressor Identifies Composite Sequence Motifs Responsible for STAT1 Binding Sites and Their Potential rSNPs

How to identify true transcription factor binding sites on the basis of sequence motif information (e.g., motif pattern, location, combination, etc.) is an important question in bioinformatics. We present “PeakRegressor,” a system that identifies binding motifs by combining DNA-sequence data and ChIP-Seq data. PeakRegressor uses L1-norm log linear regression in order to predict peak values from binding motif candidates. Our approach successfully predicts the peak values of STAT1 and RNA Polymerase II with correlation coefficients as high as 0.65 and 0.66, respectively. Using PeakRegressor, we could identify composite motifs for STAT1, as well as potential regulatory SNPs (rSNPs) involved in the regulation of transcription levels of neighboring genes. In addition, we show that among five regression methods, L1-norm log linear regression achieves the best performance with respect to binding motif identification, biological interpretability and computational efficiency

Transcription factor AP-1 in esophageal squamous cell carcinoma: Alterations in activity and expression during Human Papillomavirus infection

<p>Abstract</p> <p>Background</p> <p>Esophageal squamous cell carcinoma (ESCC) is a leading cause of cancer-related deaths in Jammu and Kashmir (J&K) region of India. A substantial proportion of esophageal carcinoma is associated with infection of high-risk HPV type 16 and HPV18, the oncogenic expression of which is controlled by host cell transcription factor Activator Protein-1 (AP-1). We, therefore, have investigated the role of DNA binding and expression pattern of AP-1 in esophageal cancer with or without HPV infection.</p> <p>Methods</p> <p>Seventy five histopathologically-confirmed esophageal cancer and an equal number of corresponding adjacent normal tissue biopsies from Kashmir were analyzed for HPV infection, DNA binding activity and expression of AP-1 family of proteins by PCR, gel shift assay and immunoblotting respectively.</p> <p>Results</p> <p>A high DNA binding activity and elevated expression of AP-1 proteins were observed in esophageal cancer, which differed between HPV positive (19%) and HPV negative (81%) carcinomas. While JunB, c-Fos and Fra-1 were the major contributors to AP-1 binding activity in HPV negative cases, Fra-1 was completely absent in HPV16 positive cancers. Comparison of AP-1 family proteins demonstrated high expression of JunD and c-Fos in HPV positive tumors, but interestingly, Fra-1 expression was extremely low or nil in these tumor tissues.</p> <p>Conclusion</p> <p>Differential AP-1 binding activity and expression of its specific proteins between HPV - positive and HPV - negative cases indicate that AP-1 may play an important role during HPV-induced esophageal carcinogenesis.</p