Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel MYB transcription factor regulates ascorbic acid synthesis and affects cold tolerance.

Dehydroascorbate reductase (DHAR) plays an important role in stress responses, but the transcriptional regulation of DHAR in response to abiotic stress is still poorly understood. In this study, we isolated a novel R2R3-type MYB transcription factor from Pyrus betulaefolia by yeast one-hybrid screening, designated as PbrMYB5. PbrMYB5 was localized in the nucleus and could bind specifically to the promoter of PbrDHAR2. PbrMYB5 was greatly induced by cold and salt but slightly by dehydration. Overexpression of PbrMYB5 in tobacco conferred enhanced tolerance to chilling stresses, whereas down-regulation of PbrMYB5 in P. betulaefolia by virus-induced gene silencing resulted in elevated chilling sensitivity. Transgenic tobacco exhibited higher expression levels of NtDHAR2 and accumulated larger amount of ascorbic acid (AsA) than the wild-type plants. Virus-induced gene silencing of PbrMYB5 in P. betulaefolia down-regulated PbrDHAR2 abundance and decreased AsA level, accompanied by an increased sensitivity to the chilling stress. Taken together, these results demonstrated that PbrMYB5 was an activator of AsA biosynthesis and may play a positive role in chilling tolerance, at least in part, due to the modulation of AsA synthesis by regulating the PbrDHAR2 expression.
The bifurcated stem loop 4 (SL4) is crucial for efficient packaging of mouse mammary tumor virus (MMTV) genomic RNA

ABSTRACT Packaging the mouse mammary tumor virus (MMTV) genomic RNA (gRNA) requires the entire 5ʹ untranslated region (UTR) in conjunction with the first 120 nucleotides of the gag gene. This region includes several palindromic (pal) sequence(s) and stable stem loops (SLs). Among these, stem loop 4 (SL4) adopts a bifurcated structure consisting of three stems, two apical loops, and an internal loop. Pal II, located in one of the apical loops, mediates gRNA dimerization, a process intricately linked to packaging. We thus hypothesized that the bifurcated SL4 structure could constitute the major gRNA packaging determinant. To test this hypothesis, the two apical loops and the flanking sequences forming the bifurcated SL4 were individually mutated. These mutations all had deleterious effects on gRNA packaging and propagation. Next, single and compensatory mutants were designed to destabilize then recreate the bifurcated SL4 structure. A structure-function analysis using bioinformatics predictions and RNA chemical probing revealed that mutations that led to the loss of the SL4 bifurcated structure abrogated RNA packaging and propagation, while compensatory mutations that recreated the native SL4 structure restored RNA packaging and propagation to wild type levels. Altogether, our results demonstrate that SL4 constitutes the principal packaging determinant of MMTV gRNA. Our findings further suggest that SL4 acts as a structural switch that can not only differentiate between RNA for translation versus packaging/dimerization, but its location also allows differentiation between spliced and unspliced RNAs during gRNA encapsidation.
Shift work and risk of cardiovascular disease morbidity and mortality: A dose–response meta-analysis of cohort studies

Background Previous studies have suggested that shift work is associated with a higher risk of cardiovascular disease. However, the quantitative dose–response relationship between duration of shift work and cardiovascular disease risk is still unknown. We aimed to evaluate the dose–response association between duration of shift work and risk of cardiovascular disease morbidity and mortality. Design A systematic review and meta-analysis. Methods PubMed and Embase were searched from inception to 1 December 2017. Prospective cohort studies that reported the associations between duration of shift work and cardiovascular disease risk with at least three categories were included. Data were pooled by using fixed or random effect models. The continuous dose–response associations were assessed by using fixed effect restricted cubic splines with four knots. Results Five prospective cohort studies with 10 reports were included. No evidence of a curvilinear association was observed between duration of shift work and risk of cardiovascular disease, similar findings were observed in cardiovascular disease morbidity and mortality. The summary relative risk (RR) of an increase of 5 years of shift work was 1.05 (1.04–1.07) with moderate heterogeneity (P = 0.142, I2 = 33.2%) for cardiovascular disease, 1.06 (1.04–1.08) with low heterogeneity (P = 0.279, I2 = 21.7%) for cardiovascular disease morbidity, and 1.04 (1.02–1.06) with moderate heterogeneity (P = 0.135, I2 = 38.5%) for cardiovascular disease mortality, respectively. Conclusions Shift work could probably increase the risk of cardiovascular disease and cardiovascular disease mortality in a dose–response way. These findings could have implications for guideline recommendations regarding the risk related to shift schedules.
A Survey on Public Auditing for Shared Data with Efficient User Revocation in the Cloud

Distributed computing has as of late developed as another worldview for facilitating and conveying administrations over the Internet. Distributed computing is appealing to entrepreneurs as it kills the prerequisite for clients to arrange ahead for provisioning, and permits undertakings to begin from the little and expansion assets just when there is an ascent in administration request. In any case, regardless of the way that distributed computing offers immense chances to the IT business, the improvement of distributed computing innovation is at present at its early stages, with numerous issues still to be tended to. With information stockpiling and sharing administrations in the cloud, clients can undoubtedly adjust and share information as a gathering. To guarantee shared information respectability can be checked freely, clients in the gathering need to register marks on every one of the pieces in shared information. Diverse squares in shared information are for the most part marked by various clients because of information changes performed by various clients. For security reasons, once a client is disavowed from the gathering, the squares which were already marked by this denied client must be re-marked by a current client. The straight forward system, which permits a current client to download the comparing a portion of shared information and re-sign it amid client disavowal, is wasteful because of the extensive size of shared information in the cloud. In this paper, we propose a novel open examining system for the uprightness of imparted information to proficient client renouncement personality a top priority. What's more, an open verifier is constantly ready to review the uprightness of shared information without recovering the whole information from the cloud, regardless of the possibility that some piece of shared information has been re-marked by the cloud.
Potential role of microRNAs in the regulation of adipocytes liposecretion and adipose tissue physiology

Adipose tissue is a dynamic endocrine organ playing a pivotal role in metabolism modulation. Adipocytes differentiation requires a highly orchestrated series of changes of gene expression in precursor cells. At the same time, white mature adipocytes are plastic cells able to reversibly transdifferentiate toward fibroblast‐like cells via the liposecretion process, returning back to a non‐committed status of the cells. In particular, adipose tissue microenvironment along with external signaling molecules such as adipokines, cytokines and growth factors can regulate adipocytes physiology through complex molecular networks. MicroRNAs (miRNAs), a type of non‐coding RNA, acting as fine regulators of biological processes and their expression is sensible to the environment and cellular status changes. MiRNAs are thought to play a pivotal role in regulating the physiology of adipose tissue as well as in the development of obesity and associated metabolic disturbances, although the underlying mechanisms have not been identified so far. Elucidating the molecular mechanisms orchestrating adipose tissue biology is required to better characterize obesity and its associated diseases. In this respect, the review aims to analyze the microRNAs potentially involved in adipogenesis highlighting their role in the process of liposecretion, adipocyte proliferation, and adipokines secretion. The role of microRNAs in the development of obesity and obesity‐associated disorders is also discussed.
Motor imagery signal classification using spiking neural network

A brain-computer interface (BCI) is both a hardware and software based communication system that allows cerebral activity to control computers or external devices. The instantaneous aim of BCI research is to offer communication abilities to severely disabled people who are ‘locked in’ by neurological disorders such as amyotrophic lateral sclerosis, brain stem stroke or spinal cord injury. “Electroencephalography”, a non-invasive approach, has been widely used for BCI system. In recent times, several classifiers have been used in analyzing EEG signals measured in the planning and relaxed state. The key work addressed is the classification of EEG signals (motor imagery signals) using spiking neural classifier. The dataset (Planning and relaxed state data) is a benchmark data taken from UCI (University of California, Irvine) repository. Online Meta-neuron based Learning Algorithm (OMLA), is a newly evolved network applied for the EEG signal classification task. Spiking neural classifier performs better than the other classifiers due to the use of both global and local information of the network.
Updated clinical overview on cardiac laminopathies: an electrical and mechanical disease

ABSTRACT Cardiac laminopathies, associated with mutations in the LMNA gene, encompass a wide spectrum of clinical manifestations, involving electrical and mechanical alterations of cardiomyocytes. Thus, dilated cardiomyopathy, bradyarrhythmias and atrial or ventricular tachyarrhythmias may occur in a number of combined phenotypes. Nowadays, some attempt has been made to identify clinical predictors for the most life-threatening complications of LMNA-associated heart disease, i.e. sudden cardiac death and end-stage heart failure. The goal of this manuscript is to combine the most recent evidences in an updated review to show the state-of-the-art of such a complex disease group. This is supposed to be the starting point to collect more data and design new ad hoc studies to identify clinically useful predictors to stratify risk in mutation carriers, including probands and their asymptomatic relatives.
Mosaics in Big Data: Stratosphere, Apache Flink, and Beyond

The global database research community has greatly impacted the functionality and performance of data storage and processing systems along the dimensions that define "big data", i.e., volume, velocity, variety, and veracity. Locally, over the past five years, we have also been working on varying fronts. Among our contributions are: (1) establishing a vision for a database-inspired big data analytics system, which unifies the best of database and distributed systems technologies, and augments it with concepts drawn from compilers (e.g., iterations) and data stream processing, as well as (2) forming a community of researchers and institutions to create the Stratosphere platform to realize our vision. One major result from these activities was Apache Flink, an open-source big data analytics platform and its thriving global community of developers and production users. Although much progress has been made, when looking at the overall big data stack, a major challenge for database research community still remains. That is, how to maintain the ease-of-use despite the increasing heterogeneity and complexity of data analytics, involving specialized engines for various aspects of an end-to-end data analytics pipeline, including, among others, graph-based, linear algebra-based, and relational-based algorithms, and the underlying, increasingly heterogeneous hardware and computing infrastructure. At TU Berlin, DFKI, and the Berlin Big Data Center (BBDC), we aim to advance research in this field via the Mosaics project. Our goal is to remedy some of the heterogeneity challenges that hamper developer productivity and limit the use of data science technologies to just the privileged few, who are coveted experts.
In silico molecular interaction of bisphenol analogues with human nuclear receptors reveals their stronger affinity vs. classical bisphenol A

Abstract Background: Bisphenol A (BPA) is known for endocrine disrupting activity. In order to replace BPA, a number of bisphenol analogues have been designed. However, their activity profile is poorly described and little information exists about their endocrine disrupting potential and interactions with nuclear receptors. An understanding of such interaction may unravel mechanism of their molecular action and provide valuable inputs for risk assessment. BPA binds and activates peroxisome proliferator-activated receptors (PPARs) and retinoid X receptors (RXRs) which act as transcription factors and regulate genes involved in glucose, lipid, and cholesterol metabolism and adipogenesis. Methods: We studied binding efficiency of 18 bisphenol analogues and BPA with human PPARs and RXRs. Using Maestro Schrodinger 9.4, docking scores of bisphenols were compared with the known endogenous and exogenous ligands of hPPARs and hRXRs. Results: BPA showed good binding efficiency. Several analogues also showed higher binding efficiency than BPA. BPPH which has high tendency to be absorbed in tissues showed the strongest binding with hPPARα, hPPARβ, hPPARγ, and hRXRα whereas two of the most toxic bisphenols, BPM and BPAF showed strongest binding with hRXRβ and hRXRγ. Conclusions: Some of the bisphenol analogues showed a stronger binding affinity with PPAR and RXR compared to BPA implying that BPA substitutes may not be fully safe and chemico-biological interactions indicate their toxic potential. These results may also serve to plan further studies for determining safety profile of bisphenol analogues and be helpful in risk characterization.
Exploring Gender and Racial/Ethnic Differences in the Effects of Child Sexual Abuse

ABSTRACT Child sexual abuse (CSA) has been linked to a number of adverse effects including hypersexuality (HYP), substance use (SUB), suicidality (SUI), and depression (DEP). Despite a plethora of research on CSA, little is known about how it affects adolescents and the cultural factors that influence their coping styles. This study was founded on social-cultural coping theory and the model of traumagenic dynamics of sexual abuse, suggesting that CSA consequences lead to maladaptive coping mechanisms influenced by sociocultural factors. Using archival data, loglinear analysis was conducted to examine gender differences within racial/ethnic groups in HYP, SUI, DEP, and SUB among adolescent survivors of CSA in a National sample of 13,583 male and female high school students. The purpose of the study was to identify differences in the effects of CSA as manifested by variations of maladaptive coping across racial/ethnic groups and gender. Boys were significantly more likely to use substances, while girls were more likely to experience depressive symptoms and suicidality. Notably, this study did not reveal any significant racial/ethnic differences in adolescent coping. These findings can inform treatment planning and interventions for adolescents who may present with DEP, SUI, SUB, or risky sexual behaviors, but may have underlying trauma from CSA. This study contributes to the knowledge base about the processes that take place within adolescent CSA survivors, shedding light on cultural nuances among adolescent coping and informing culturally competent practice.
ADHD Symptoms in Pathological and Problem Gamblers in Singapore

Background: There is relatively little research examining the relationship between Attention-Deficit/Hyperactivity Disorder (ADHD) and gambling addiction. This study seeks to explore for ADHD symptoms in adult gambling addiction patients and to evaluate their gambling-related cognitions. Materials and Methods: A cross-sectional survey was conducted at National Addictions Management Service, Institute of Mental Health, in Singapore. Patients presenting for gambling treatment were screened for ADHD symptoms and assessed for severity of gambling-related cognitions. The primary objective was to observe the rate of patients screening positive for ADHD. Results: 20% of the sample screened positive for ADHD. These individuals also had lower levels of gambling-related cognitions. No significant correlation was noted between ADHD symptoms and gambling-related cognition scores. Conclusions: Positive screening results for ADHD occurred frequently in our sample of Pathological Gambling (PG) and Problem Gambling patients and these affected individuals also exhibited lower levels of gambling-related cognitions. This finding may suggest that the gambling behavior in patients with ADHD-PG comorbidity is driven by impulsivity rather than gambling-related cognitions, which has implication on treatment considerations. Further research with a larger sample size is indicated.
Face super-resolution via semi-kernel partial least squares and dictionaries coding

In this paper, a patch-based super-resolution (SR) method is proposed to hallucinate facial images. Two steps are involved in this method. In the first step, we combine semi-kernel partial least squares (semi-KPLS) algorithm with collaborative representation (CR) to infer an initial high-resolution (HR) face. In the second step, sparse representation in gradient domain is employed to compensate the global face with detailed inartificial facial features. Furthermore, the gradient images, obtained from sparse representation, are integrated with the gradient of initial HR face. Based on the integrated gradient images, a generalized Poisson solver is used to reconstruct the final high resolution image. The experiments conducted on FERET database demonstrate the proposed algorithm can generate better results, in comparison with some state-of-the-art approaches.
Enhancement of antimicrobial activity of antibiotics and antifungals by the use of natural products from Pityrogramma calomelanos (L.) link

extract and methanol fraction of Pityrogramma calomelanos (L.) link were evaluated for antibacte- rial, antifungal and modulatory activities against strains of Escherichia coli, Pseudomonas aeruginosa, Staphylococcus au- reus, Candida albicans, C. krusei and C. tropicalis. The antimicrobial activity of the natural products was evaluated by the microdilution method associated or not with aminoglycosides and antifungals. The ethanol extract and methanol fraction of P. calomelanos showed good activity against S. aureus when associated with aminoglycosides and with benzoilmetron- idazol against species of the genus Candida. These results indicate that P. calomelanos should be studied as a possible source of natural products to combat bacteria and fungi either directly or by modulating the mechanisms of resistance of these microorganisms, enhancing the antimicrobial activity of these drugs and combating microbial resistance.
A brain network model for depression: From symptom understanding to disease intervention

Understanding the neural substrates of depression is crucial for diagnosis and treatment. Here, we review recent studies of functional and effective connectivity in depression, in terms of functional integration in the brain. Findings from these studies, including our own, point to the involvement of at least four networks in patients with depression. Elevated connectivity of a ventral limbic affective network appears to be associated with excessive negative mood (dysphoria) in the patients; decreased connectivity of a frontal‐striatal reward network has been suggested to account for loss of interest, motivation, and pleasure (anhedonia); enhanced default mode network connectivity seems to be associated with depressive rumination; and diminished connectivity of a dorsal cognitive control network is thought to underlie cognitive deficits especially ineffective top‐down control of negative thoughts and emotions in depressed patients. Moreover, the restoration of connectivity of these networks—and corresponding symptom improvement—following antidepressant treatment (including medication, psychotherapy, and brain stimulation techniques) serves as evidence for the crucial role of these networks in the pathophysiology of depression.
A machine learning approach to classify news articles based on location

With the influx of myriad news accompanied with busy lifestyle, there is a pressing need to classify news according to the requirements of an individual. People are generally more interested what is going on, in their immediate surroundings. In this paper, we model this problem by classifying the news articles based on cities and providing the entity with the collection of city specific news. We have developed our own web crawler for content extraction from the HTML pages of news articles. Random Forests, Naive Bayes and SVM classifiers have been employed and their accuracy has been noted. Results exhibit that machine learning techniques can be harnessed to achieve our goal and thus calls for further research to improve the efficiency of solving this issue.
Effect of self-leadership on job satisfaction-standardizing model using regression

To extensively analyze and study the impact of the self-leadership trait that induces in the intrinsic and extrinsic job satisfaction among the university students, Marketing professionals and self-employed. The self-leadership performs a critical role in the student's life and professionals in achieving the targeted goal. The study is based on the 150 samples from the university students, self-employed and employees of IT and Pharmaceutical sectors from the cities Bengaluru, Chennai, Mumbai, and Tiruchirapalli. The collected data have been analyzed through statistical tools such as descriptive analysis, Friedman test, and Regression. The self-leadership factors highly contribute to the extrinsic and intrinsic job satisfaction. Hence these factors are to be taken at most care to ensure high performance.
Computational Methods for Predicting Protein‐Protein Interactions Using Various Protein Features

Understanding protein‐protein interactions (PPIs) in a cell is essential for learning protein functions, pathways, and mechanism of diseases. PPIs are also important targets for developing drugs. Experimental methods, both small‐scale and large‐scale, have identified PPIs in several model organisms. However, results cover only a part of PPIs of organisms; moreover, there are many organisms whose PPIs have not yet been investigated. To complement experimental methods, many computational methods have been developed that predict PPIs from various characteristics of proteins. Here we provide an overview of literature reports to classify computational PPI prediction methods that consider different features of proteins, including protein sequence, genomes, protein structure, function, PPI network topology, and those which integrate multiple methods. © 2018 by John Wiley & Sons, Inc.
ATM Expression and Activation in the Testis 1

Department of Endocrinology, 3 Faculty of Biology, Utrecht University, Padualaan 8, 3584 CH Utrecht, the Netherlands Department of Cell Biology, 4 UMCU, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands Department of Radiotherapy, 5 UMCU, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands Polaris Venture Partners, 6 1000 Winter Street Suite 3350, Waltham MA 02451, USA Department of Genetics, 7 Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06510, USA