Miracle-dz/UniFAR-FTUs huggingface dataset:
Venoms versus Vasculature and Hemostasis: In Search for Non-Hemorrhagic Anti- Hemostatic Venom Components

Snake venoms target multiple essential organ systems, among them the hemostatic system and the vasculature. Both snake venom serine proteinases (SVSPs) and snake venom metalloproteinases (SVMPs) exist which cleave coagulation factors, platelet receptors and/or extracellular matrix (ECM) components. To treat vascular occlusion and ischemic diseases, cleavage of coagulation factors and platelet receptors is a treatment goal, whereas degradation of the vessel wall ECM results in unwanted and life-threatening hemorrhages. Identification of anticoagulant and antithrombotic snake venom proteinases, which are non-hemorrhagic, provides potential new pharmacological tools. While larger forms of SVMPs belonging to the P-III and P-IIsubclasses are hemorrhagic in general, some P-I-SVMPs and SVSPs offer the potential to cleave fibrinogen thereby forming easily dissolvable clots or degrading fibrin, without attacking the vascular ECM. However, it is unclear which features of the molecular structures determine whether a P-I-SVMP belongs to this medically relevant group of fibrin(ogen)olytic, nonhemorrhagic snake venom proteinases.
Prediction of Chronic Diseases using Machine Learning Classifiers

Since there are no symptoms of chronic kidney disease (CKD) is a life-threatening state, and very difficult to diagnose early. A predictive model for estimating CKD is the aim of the proposed research, which aims to develop and validate this model. This problem most frequently affects adults and the elderly at this time. For preprocessing and cleaning, we will use the Decision Tree Classifier to input the data, and for analysis, we will use the Naive Bayes Classifier for the best prediction and accuracy. We used a clustering algorithm as a predictor; the clusters corresponded to the target categories; after that, we had a predictive model and various clusters to examine for each category. Then, we trained two different-sized neural nets and compared various supervised models by combining them with Principal Component Analysis.
Can retention harvests help conserve wildlife? Evidence for vertebrates in the boreal forest

Retention harvesting, or the approach of leaving live mature trees behind during forest harvest, is used in natural disturbance-based management to mitigate the effects of logging on biodiversity. However, responses of many boreal vertebrates to variable retention harvesting are unknown. We investigated the influence of different retention levels in forest harvests on stand use by wildlife 15–18 yr postharvest using a combination of surveys of wildlife signs (scats, middens) and camera trapping. Site-level measures of forest structure, including canopy cover, horizontal cover, tree height, tree diameter, basal area, cover of downed coarse woody material, and understory plant cover, were used to describe post-harvest differences in habitats used by common wildlife species in northwest Alberta’s boreal forest. Stand use of six species (black bear, coyote, fisher, red squirrel, wolverine, woodland caribou) increased with level of retention, while stand use of two species (grouse, snowshoe hare) declined with retention level. Retention level did not significantly affect stand use of five species (American marten, Canada lynx, deer, gray wolf, moose). Higher levels of retention characterized by greater canopy cover, basal area, and abundance of deadwood were associated with use of forest habitats by late-seral species. Woodland caribou, a species of conservation concern, was detected only in harvested stands with at least 20% retention. Greater understory and horizontal cover characterized lower levels of retention being attractive for early-seral species. These findings demonstrate the value of retention harvesting for conservation of wildlife species in boreal forest, while highlighting the challenge of managing forests for multiple species with different habitat
Streptozotocin-induced molecular and metabolic targets in pancreatic beta-cell toxicity

Background/Aim: The prevalence of diabetes is on the rise globally causing excessive burden on the health systems. Pancreatic beta-cell mass destruction/neogenesis/proliferation (seen in type1diabetes) and/or malfunction (type 2 diabetes) have been implicated in the aetiology, pathology, progression as well as in responses towards therapies and disease managements. Oxidative stress and alterations in mitochondrial energy metabolism play important roles in diabetes-induced cellular complications. Several studies, including our own, have suggested that Rin-5F pancreatic beta cells are extremely susceptible to oxidative stress due to excessive production of endogenous and exogenous reactive oxygen/nitrogen species (ROS/RNS) and low antioxidant defences, particularly, associated with GSH metabolism. Our aim was to investigate the molecular mechanism of streptozotocin (STZ), a beta cell-specific antibiotic, cytotoxicity in pancreatic cells. Methods: Rin-5F cells were treated with STZ under varying conditions to study oxidative stress-related changes. Results: Our studies have suggested that treatment of Rin-5F cells with STZ, inhibits cell survival and induces cytotoxicity by altering cellular survival and apoptotic signalling and gene expressions. Increased oxidative stress with increased DNA fragmentation and oxidative protein carbonylation were seen in STZ-treated cells. We also observed that beta cells treated with high glucose (up to 25mM) exhibited enhanced cytotoxicity. Cells exposed to conditions mimicking diabetes (hyperglycaemia) were under elevated oxidative stress and showed increased apoptosis and altered redox homeostasis leading to increased cytotoxicity. N-acetyl cysteine (NAC) treatment attenuated these changes in STZ-treated cells. Conclusion: These results may have implications in understanding the mechanism of beta cell survival/death in response to potential therapeutics/managements as well as in the aetiology and pathophysiology of diabetes.
Morphological and Molecular Analysis of In Vitro Tubular Structures from Bovine Yolk Sac-Derived MSCs

The yolk sac is an extraembryonic membrane, of saccular form, connected to the ventral region of the embryo. It is the main source of nutrition for the embryo during the period when the placenta is not fully formed. The aim of this study was to generate tubular structures using mesenchymal stem cells from the bovine yolk sac (bYS-MSCs) and determine if these structures can be a model for in vitro vasculogenesis. The evaluation of this tissue by histochemistry revealed a strong marking of collagen fibers and PAS technique negativity. In transmission electron microscopy, cytoplasmic organelles with large nuclei were observed. The vessel formation assay on a Matrigel substrate showed that the mesenchymal cells of the yolk sac without growth factors (VEGF) are capable of forming branches, sprouting cells, and tubular structures similar to capillary blood. These tubular structures were xenotransplanted subcutaneously into the mesentery of BALB/c/nude mice; after 45 days, vascularized tissue and extensions of blood vessels around the tubular structures could be observed. Real-time PCR (qPCR) demonstrated an expression of the VEGF gene in different gestational age groups. No difference in distribution or expression was detected among groups. Our results suggest that the spontaneous formation of tubules from the yolk sac can be an experimental model to elucidate initial organogenesis and the possible formation of blood capillaries from in vitro mesenchymal cells and possible route of organoid production.
CHARACTERIZATION OF ENDOPHYTIC BACILLUS ISOLATED FROM SHALLOT ROOT AS BIOCONTROL OF BACTERIAL LEAF BLIGHT DISEASE

Characterization of Endophytic Bacillus Isolated from Shallot Root as Biocontrol of Bacterial Leaf Blight Disease. Endophytic Bacillus isolated from the roots of healthy shallots has potential as biological control agent of bacterial leaf blight (BLB) disease. Based on the in planta screening, four endophytic bacteria that capable of controlling BLB diseases from the group of Bacillus were obtained, such as Bacillus cereus P14, Bacillus cereus Se07, Bacillus sp. HI, and Bacillus sp. SJI. The aims of this study were to investigate the characteristics of endophytic Bacillus that capable of controlling BLB disease and to determine the characteristic that most responsible in the disease control. This study method was descriptive. The characteristics observed were production of antibiotics by paper disc method, production of salicylic acid by capillary electrophoresis, and root colonization by in planta method. Linear regression analysis was used to determine the characteristic most responsible in the disease control. The results showed that four endophytic Bacillus were capable of producing salicylic acid and colonizing the root, and three of them were also capable of producing antibiotic. Salicylic acid production varied ranging from 13.96 to 14.72 ppm mL-1. Three endophytic Bacillus were capable of producing antibiotic with inhibition zone of 16.25 to 20.25 mm. Endophytic Bacillus was able to colonize the shallot roots with a population of bacteria ranged from 3.20 × 105-6, 20 × 105 CFU g-1 root. Based on the correlation coefficient of linear regression analysis, the root colonization of endophytic bacteria played the role in decreasing BLB disease.
Predicting circRNA-RBP interaction sites using a codon-based encoding and hybrid deep neural networks

Circular RNAs (circRNAs), with their crucial roles in gene regulation and disease development, have become a rising star in the RNA world. A lot of previous wet-lab studies focused on the interaction mechanisms between circRNAs and RNA-binding proteins (RBPs), as the knowledge of circRNA-RBP association is very important for understanding functions of circRNAs. Recently, the abundant CLIP-Seq experimental data has made the large-scale identification and analysis of circRNA-RBP interactions possible, while no computational tool based on machine learning has been developed yet. We present a new deep learning-based method, CRIP (CircRNAs Interact with Proteins), for the prediction of RBP binding sites on circRNAs, using only the RNA sequences. In order to fully exploit the sequence information, we propose a stacked codon-based encoding scheme and a hybrid deep learning architecture, in which a convolutional neural network (CNN) learns high-level abstract features and a recurrent neural network (RNN) learns long dependency in the sequences. We construct 37 datasets including sequence fragments of binding sites on circRNAs, and each set corresponds to one RBP. The experimental results show that the new encoding scheme is superior to the existing feature representation methods for RNA sequences, and the hybrid network outperforms conventional classifiers by a large margin, where both the CNN and RNN components contribute to the performance improvement. To the best of our knowledge, CRIP is the first machine learning-based tool specialized in the prediction of circRNA-RBP interactions, which is expected to play an important role for large-scale function analysis of circRNAs.
Disclosure of Information about Internet Banking Security on Bank Websites: The Role of the Internet in the Diffusion of Innovations

Abstract Purpose: This paper aims to analyze the level of disclosure of information about Internet Banking security on bank websites, as well as its determinants. Methodology: The analysis of the disclosure level was based on a framework consisting of 25 items divided into physical, administrative and technical measures. We adopted quantitative (descriptive statistics and multivariate regression analysis) and qualitative (content analysis) approaches for data analysis. Originality / Value: Considering that security is one of the main determinants of Internet Banking adoption, this study aims to expand the discussion on banking services and information security, focusing on a topic that has still been little explored in the Brazilian scenario. Findings: The main results showed that the level of security information disclosed by banks on their websites is low. Banks with a greater number of branches, with higher profitability and private banks showed better levels of disclosure. Theoretical / methodological contributions: At the theoretical level, the study brings contributions to the literature by addressing a topic that has been little explored, especially in Brazil. In addition, this research addresses this issue considering both a quantitative and qualitative perspective, which allows a greater detail on the items to be considered by financial institutions when offering electronic services to their customers. Managerial implications: The results of the study may help banks to assess and improve the level of information being disclosed to their customers in order to increase consumer trust in Internet Banking and, consequently, the diffusion of this technology.
Interaction of HelQ helicase with RPA modulates RPA-DNA binding and stimulates HelQ to unwind DNA through a protein roadblock

Cells reactivate compromised DNA replication forks using enzymes that include DNA helicases for separating DNA strands and remodelling protein-DNA complexes. HelQ helicase promotes replication-coupled DNA repair in mammals in a network of interactions with other proteins. We report newly identified HelQ helicase activities, when acting alone and when interacting with RPA. HelQ helicase was strongly inhibited by a DNA-protein barrier (BamHIE111A), and by an abasic site in the translocating DNA strand. Interaction of HelQ with RPA activated DNA unwinding through the protein barrier, but not through the abasic site. Activation was lost when RPA was replaced with bacterial SSB or DNA binding-defective RPA, RPAARO1. We observed stable HelQ-RPA-DNA ternary complex formation, and present evidence that an intrinsically disordered N-terminal region of HelQ (N-HelQ) interacts with RPA, destabilising RPA-DNA binding. Additionally, SEC-MALS showed that HelQ multimers are converted into catalytically active dimers when ATP-Mg2+ is bound. HelQ and RPA are proposed to jointly promote replication fork recovery by helicase-catalysed displacement of DNA-bound proteins, after HelQ gains access to ssDNA through its N-terminal domain interaction with RPA.
An experimental investigation of the condensation of silicate grains. [in interstellar matter]

Results are presented for a series of laboratory experiments designed to investigate the nucleation of small silicate grains from a vapor of astrophysically significant elements and compounds. In the experiments, magnesium silicate grains were condensed by simultaneously evaporating Mg and SiO solids into an atmosphere of argon or hydrogen at a pressure of a few torr. The results show that at low temperatures (up to a few hundred degrees C) the condensates are amorphous grains and have widely varying stoichiometries. The thermodynamically most stable compounds (Mg2SiO4, MgSiO3, SiO2) do not form readily, but all initial condensates can be converted to crystalline forsterite (Mg2SiO4) by heating to 1000 C in vacuum. At higher temperatures (above 700 K) it becomes more difficult to nucleate any silicates, and those that do form are amorphous, indicating that surface energies and kinetic effects are very important in determining under what conditions condensation will occur. The IR spectra of the experimentally produced magnesium silicates are found to have a strong resemblance to those observed in many astronomical clouds.
Effect of Probiotics and Chelated Zinc on E. coli Infected Broilers

This study was carried out to illustrate the effects of Bacillus subtilis probiotic (Baymix®) and chelated zinc (Availa zinc®) in prevention of E. coli in poultry farms and also to examine their effects on some blood biochemical, immunological parameters and antioxidant status in broiler chickens. One hundred and fifty one day old cobb chicks were used in this study. The chicks were divided into six groups, each group contain 25 chick, the 1st group was (control) non infected and fed balanced diet without additives, 2ndgroup was non-infected treated with probiotic (NPRO), 3rd group was non-infected treated with chelated zinc (NZn), 4thgroup was infected non treated (INT),5thgroup was infected treated with probiotic (IPRO) and 6thgroup was infected treated with chelated zinc (IZn). The infection by E.coli (078) occurred at 21st day of age. Blood samples collected for biochemical parameters, phagocytic activity detection. Liver tissues collected for some antioxidant parameters (MDA and GPx), some immunological parameters interleukin-1β (IL-1β), interferon gamma (IFNγ) and interleukin-10 (IL-10), The results showed that were no significant changes in serum uric acid, creatinine, ALT and AST and significant decrease in malonaldehyde (MDA) and increases in glutathione peroxidase (GPx), phagocytic activity and immunological parameters (IL-1β,IFNγ, IL-10) in NPRO and NZn groups compared to control group and significant decreases in serum uric acid ,creatinine, ALT and AST and significant decrease in MDA and significant increase in glutathione peroxidase (GPx), phagocytic activity and immunological parameters IPRO and NZn groups compared to INT group.From this study we could conclude that the use of B. subtilis probiotic and chelated zinc improve kidney and liver functions, antioxidant status, phagocytic activity and immune response in broilers chickens infected with E. coli (078).
FIRST YEAR COMPUTER SCIENCE EDUCATION IN NORWAY: A mapping study of computer science study programs in Norway focusing on the first year

The need for ICT knowledge in Norway is increasing and the demand for candidates is currently higher than the number of students graduating. It has been identified that the first-year experience is crucial to student motivation and throughput of study programs, therefore it is interesting to look at the state of the art of computer science study programs in Norway. In this paper we present a survey and study of the number of undergraduate computer science programs in Norway and map their characteristics in order to gather an up to date overview of the selection of programs. Through a systematic review of all Norwegian undergraduate programs using data from national databases we have found that there are 12 institutions offering 56 different programs in Norway in 2018. The study showed that the characteristics of these programs vary, that is, the amount of computer science courses during the first year, the number of students, admission requirements, student satisfaction and time commitment. This article presents these findings along with an analysis of what characteristics impact the students’ contentment and learning experience.
The Phenetic Distances of Jordanian Arabs from Other Human Populations Suggest a Major Genetic Drift from the Caucasoid Race

The objectives were to determine the expression frequency and sexual dimorphism of 16 non-metric crown traits on the permanent dentitions of the living Jordanians, and to assess the biological affinity of this sample to 21 high-order groups based on these traits. 360 Jordanian school children (176 males, 184 females; mean ages 15.5, sd = 0.4 years) were studied in 2009. The traits were classified using the Arizona State University dental anthropology system, counted with the individual count method, and dichotomized according to Scott and Turner criteria for the purpose of group comparisons. Z-value test was used to assess sexual dimorphism in these traits. Smith’s Mean Measure of Divergence was used to measure all pairwise distance values among the groups. Sexual dimorphism was found in only three traits (i.e., Carabelli’s tubercle/cusp, metaconule and hypoconulid absence). This study revealed that the dental pattern of living Jordanians is sufficiently distinct from the Caucasoid pattern and all other known dental patterns to warrant a unique dental pattern for this population. Moreover, the relatively large distance values between the living Jordanians and all other world groups considered including the Western Eurasian groups suggest a major genetic drift for this population from the Caucasoid race.
A Classification Approach for Genome Structural Variations Detection

Background: Finding accurate genome structural variations (SVs) is important for understanding phenotype diversity and complex diseases. Limited research using classification to find SVs from next-generation sequencing is available. Additionally, the existing algorithms are mainly dependent on an analysis of the alignment signatures of paired-end reads for the prediction of different types of variations. Here, the candidate SV regions and their features are computed using single reads only. Classification is used to predict the variation types of these regions. Results: Our approach utilizes reads with multi-part alignments to define a possible set of SV regions. To annotate these regions, we extract novel features based on the reads at the breakpoints. We then build three random forest classifiers to identify regions with deletions, inversions, or tandem duplications. Conclusions: This paper proposes a random forest-based classification approach, MPRClassify, which addresses the issue of finding SVs using single reads only. These single-reads are used to define candidate regions and extract their features. Experimental results show that single reads are sufficient to find SVs without the need for paired-end read signatures. Our proposed approach outperforms existing approaches and serves as a basis for future studies finding SVs using single reads.
Cost prediction on fabricated substation considering SVM via optimized QPSO

At present, the prediction of the life cycle cost of fabricated substation is of great significance for the construction of fabricated substation. An enhanced prediction model based on quantum particle swarm optimization(QPSO) via least squares support vector machine is established. The relevant characteristic index of the life cycle of the fabricated substation is used as the input of the model, and the output is the life cycle cost. The simulation results are compared with the prediction results of QPSO optimized LS-SVM, PSO optimized LS-SVM, traditional LS-SVM, and BP neural network, which shows that the QPSO optimized LS-SVM model has better prediction accuracy, can predict and evaluate the life cycle cost more quickly, and can improve the benefits of fabricated substation construction.
Dinâmica temporal, subtipos e características epidemiológicas da infecção pelo HIV-1, Brasil Central

Introduction: The objective of this study was to identify the major subtypes of HIV-1 circulating in Mato Grosso do Sul (MS), Central Brazil. Methods:This is a cross-sectional study of time series with data from laboratory and disease report, analyzed by period of diagnosis and sociodemographic and clinical variables. Results: Subtype B HIV-1 predominated when periods were analyzed (85.4% vs 85.3%). In addition, an increase in the frequency of HIV-1 subtype C was detected, but no significant difference was seen between the two periods. After univariate analysis, the age range between 25 and 45 years (p = 0.004) and the masculine gender (p = 0.04) were found to be associated with subtype B HIV-1. The findings related to the resistance of HIV-1 to ARV showed that 30.6% of the investigated patients diagnosed AIDS between 1985 and 2012 who underwent genotyping tests (212) were resistant to more than three ARV classes (MDR). Conclusions: Studies on the genetic diversity, as well as the profile of resistance mutations in HIV-1, are important tools for both the historical reconstruction of regional epidemics and local epidemiological surveillance and treatment guidelines.