Miracle-dz/UniFAR-FTUs huggingface dataset:
Bluetongue Viruses Act as Novel Oncolytic Viruses to Effectively Inhibit Human Renal Cancer Cell Growth In Vitro and In Vivo

Background The bluetongue virus (BTV) is the prototype virus in the genus Orbivirus within the family Reoviridae. Recent studies indicate that BTVs are capable of infecting and selectively lysing human hepatic carcinoma cells (Hep-3B) and prostate carcinoma cells (pc-3). This study was designed to evaluate the oncolytic potential of BTV in experimental models of human renal cancer in vitro and in vivo. Material/Methods Five human renal cancer cell lines, ACHN, CAKI-1, OS-RC-2, 786-O, and A498, were used in this study to analyze BTV replication. These cells were lysed by oncolysis compared to normal control. Xenograft models were used to assess the efficacy and toxicity of BTVs in vivo. Data were analyzed by one-way ANOVA or two-sided unpaired t tests. Results The results showed HPTEC cells to be relatively resistant to cytotoxic effects of BTVs and exhibited normal growth rate even at high dose of BTVs. Nonetheless, the renal cancer cells showed a remarkably higher sensitivity to BTVs. Moreover, the ultramicroscopic subcellular changes were also detected in the renal cells. The viral particles were observed in all the RCC cell lines, but not in HPTEC cells. Intratumoral injections of BTVs significantly decreased the tumor volume as compared to animals that received no virus treatment. Infection with BTVs significantly increased the percentage of apoptotic renal cancer cells but not the HPTEC cells. Moreover, BTV triggered apoptosis in renal cancer cells via a mitochondria-mediated pathway. Conclusions This study for the first time demonstrated the oncolytic potential of BTV in experimental models of human renal cancer. BTV exhibits the potential to inhibit human renal cancer cell growth in vitro and in vivo.
An Information Theory Approach to Aesthetic Assessment of Visual Patterns

The question of beauty has inspired philosophers and scientists for centuries. Today, the study of aesthetics is an active research topic in fields as diverse as computer science, neuroscience, and psychology. Measuring the aesthetic appeal of images is beneficial for many applications. In this paper, we will study the aesthetic assessment of simple visual patterns. The proposed approach suggests that aesthetically appealing patterns are more likely to deliver a higher amount of information over multiple levels in comparison with less aesthetically appealing patterns when the same amount of energy is used. The proposed approach is evaluated using two datasets; the results show that the proposed approach is more accurate in classifying aesthetically appealing patterns compared to some related approaches that use different complexity measures.
Risk factors for postpartum hemorrhage following cesarean delivery

Abstract Objective To identify risk factors for postpartum hemorrhage (PPH) following cesarean delivery (CD). Methods A retrospective study of all women who underwent CD in a university-affiliated tertiary hospital (2014–15). PPH was defined as any of the following: clinical PPH (≥1000 ml estimated blood loss), hemoglobin (Hb) drop ≥3 g/dl (the difference between pre-CD Hb level within a 24 h prior to the delivery) and post-CD (nadir level during the first 72 h after CD)) or the need for blood products transfusion. The characteristics of women with PPH following CD were compared to a control group of those with CD without PPH. Results Of the 15,564 deliveries during the study period, 3208 (20.6%) women met inclusion criteria, of them, 307 (9.6%) had PPH and 2901 (90.4%) served as controls. Women in the PPH group were younger (32.6 ± 5.3 vs. 33.5 ± 5.4, p = .006) and more often nulliparous (45.9% vs. 33.3%, p<.001) compared to the controls. However, there were no differences between the groups regarding the rate of multiple gestations, maternal diabetes mellitus, hypertensive disorders, polyhydramnios, and macrosomia. The rates of induction of labor (16.3% vs. 8.6%, p<.001) and urgent CD (47.9% vs. 32.0%, p<.001) were higher in the PPH group compared to the controls. In multivariate logistic regression, predictors for PPH following CD were (odds ratio, 95% confidence interval) urgent CS (1.57, 1.78–2.11, p = .002), CD duration (1.02, 1.01–1.03, p<.001), and the number of previous CDs (0.74, 0.62–0.90, p = .003). Conclusions In women undergoing cesarean section, urgent CD, the duration of the surgery, and the number of the previous CD are associated with the risk of PPH and should be taken into consideration during the postpartum assessment.
DEVELOPMENT AND VALIDATION OF PALIPERIDONE IN BULK AND PHARMACEUTICAL FORMULATION BY RP-HPLC

A simple, specific, accurate, and precise reverse phase high performance liquid chromatographic (RP-HPLC) method was developed and validated for the estimation of Paliperidone in pharmaceutical dosage form. The chromatographic separation of Paliperidone was achieved on a Verian C-18 column with 250 x 4.6 mm i.d. and 5 μm particle size, using UV detection at 238nm. The optimized mobile phase was consisted of Acetonitrile: Methanol: KH2PO4 buffer pH 2.5 (30: 30 : 40 v/v). The flow rate was 1ml / min and effluents were monitored at 238 nm. Chromatogram showed the main peak at a retention time of 2.586 ± 0.02 min. The linearity was found in the concentration range of 10-60 (μg/ml). The Correlation coefficient was 0.9998. The limit of detection and limit of quantitation for estimation of Paliperidone was found to be 0.038 (μg/ml) and 0.116 (μg/ml) respectively. Recovery of Paliperidone was found to be in the range of 99.97-100.03 %. Proposed method was successfully applied for the quantitative determination of Paliperidone in pharmaceutical dosage form.
On the Use of Regression Calibration in a Complex Sampling Design With Application to the Hispanic Community Health Study/Study of Latinos.

Regression calibration is the most widely used method to adjust regression parameter estimates for covariate measurement error. Yet, its application in the context of a complex sampling design, for which the common bootstrap variance estimator can be less straightforward, has been less studied. We propose two variance estimators for a multi-stage probability-based sampling design, a parametric and a resampling-based multiple imputation approach, where a latent mean exposure needed for regression calibration is the target of imputation. This work was motivated by the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), data from 2006 to 2011, for which relationships between several outcomes and diet, an error-prone self-reported exposure, are of interest. We assessed the relative performance of these variance estimation strategies in an extensive simulation study built on the HCHS/SOL data. We further illustrate the proposed estimators with an analysis of the cross-sectional association of dietary sodium intake with hypertension-related outcomes in a subsample of the HCHS/SOL cohort. We provide investigators guidelines for the application of regression models with regression-calibrated exposures. Practical considerations for implementation of these two variance estimators in the setting of a large multi-center study are also discussed. Code to replicate the presented results is available online.
Mitotic spindle: lessons from theoretical modeling

Cell biology is immensely complex. To understand how cells work, we try to find patterns and suggest hypotheses to identify underlying mechanisms. However, it is not always easy to create a coherent picture from a huge amount of experimental data on biological systems, where the main players have multiple interactions or act in redundant pathways. In such situations, when a hypothesis does not lead to a conclusion in a direct way, theoretical modeling is a powerful tool because it allows us to formulate hypotheses in a quantitative manner and understand their consequences. A successful model should not only reproduce the basic features of the system but also provide exciting predictions, motivating new experiments. Much is learned when a model based on generally accepted knowledge cannot explain experiments of interest, as this indicates that the original hypothesis needs to be revised. In this Perspective, we discuss these points using our experiences in combining experiments with theory in the field of mitotic spindle mechanics.
Comparison of therapeutic effects of budesonide and ambroxol combined with bovine pulmonary surfactant on neonatal respiratory distress syndrome

Objective: To explore the role of budesonide (BUD)/ambroxol (AMB) with bovine pulmonary surfactant (PS) on neonatal respiratory distress syndrome (NRDS). Methods: Altogether 90 cases of children with NRDS treated in our hospital from September 2019 to May 2020 were collected. Among them, 45 cases were treated with BUD combined with PS as the control group (CG), and the other 45 cases were treated with AMB combined with PS as the observation group (OG). The curative effect, arterial blood gas index (PaO2, PaCO2, PaO2/FiO2), treatment time (CPAP usage time, oxygen time, length of stay), symptom recovery time (pulmonary rales disappearance time, cough disappearance time, antipyretic disappearance time), complications and death, repeated medication, inflammatory index (TNF-α, IL-6, IL-10), oxidative stress index (GSH-Px, SOD, MDA) were observed and compared. Results: The total effective rate of the OG was higher than that of the CG. Arterial blood gas index, inflammatory index and oxidative stress index were better in the OG. CPAP usage time, oxygen time, length of stay, pulmonary rales disappearance time, cough disappearance time and antipyretic disappearance time were shorter in the OG. Complications, deaths and repeated medication were lower in the OG. Conclusion: AMB with PS is superior to BUD with PS in NRDS, which is useful for clinical treatment.
Preoperative Immunonutrition vs. Standard Dietary Advice in Normo-Nourished Patients Undergoing Fast-Track Laparoscopic Colorectal Surgery

Immunonutrition (IN) appears to reduce infective complications and in-hospital length of stay (LOS) after major gastrointestinal surgery, but its use in normo-nourished patients is still controversial. The primary aim of this comparative observational study was to evaluate if pre-operative IN reduces in-hospital stay in patients undergoing laparoscopic colorectal resection for cancer under an enhanced recovery after surgery (ERAS) program. The influence of IN on time to first bowel movements, time to full oral diet tolerance, number and type of complications, reasons of prolonged LOS and readmission rate was evaluated as secondary outcome. Patients undergoing ERAS laparoscopic colorectal resection between December 2016 and December 2019 were reviewed. Patients who have received preoperative IN (group A) were compared to those receiving standard dietary advice (group B). Mean in-hospital LOS was significantly shorter in patients receiving preoperative IN than standard dietary advice (4.85 ± 2.25 days vs. 6.06 ± 3.95 days; p < 0.0492). No differences in secondary outcomes were observed. Preoperative IN associated with ERAS protocol in normo-nourished patients undergoing laparoscopic colorectal cancer resection seems to reduce LOS.
Hepatokines as a Molecular Transducer of Exercise

Exercise has health benefits and prevents a range of chronic diseases caused by physiological and biological changes in the whole body. Generally, the metabolic regulation of skeletal muscle through exercise is known to have a protective effect on the pathogenesis of metabolic syndrome, non-alcoholic fatty liver disease (NAFLD), type 2 diabetes (T2D), and cardiovascular disease (CVD). Besides this, the importance of the liver as an endocrine organ is a hot research topic. Hepatocytes also secrete many hepatokines in response to nutritional conditions and/or physical activity. In particular, certain hepatokines play a major role in the regulation of whole-body metabolic homeostasis. In this review, we summarize the recent research findings on the exercise-mediated regulation of hepatokines, including fibroblast growth factor 21, fetuin-A, angiopoietin-like protein 4, and follistatin. These hepatokines serve as molecular transducers of the metabolic benefits of physical activity in chronic metabolic diseases, including NAFLD, T2D, and CVDs, in various tissues.
Solution Structure, Dynamics, and New Antifungal Aspects of the Cysteine-Rich Miniprotein PAFC

The genome of Penicillium chrysogenum Q176 contains a gene coding for the 88-amino-acid (aa)-long glycine- and cysteine-rich P. chrysogenum antifungal protein C (PAFC). After maturation, the secreted antifungal miniprotein (MP) comprises 64 aa and shares 80% aa identity with the bubble protein (BP) from Penicillium brevicompactum, which has a published X-ray structure. Our team expressed isotope (15N, 13C)-labeled, recombinant PAFC in high yields, which allowed us to determine the solution structure and molecular dynamics by nuclear magnetic resonance (NMR) experiments. The primary structure of PAFC is dominated by 14 glycines, and therefore, whether the four disulfide bonds can stabilize the fold is challenging. Indeed, unlike the few published solution structures of other antifungal MPs from filamentous ascomycetes, the NMR data indicate that PAFC has shorter secondary structure elements and lacks the typical β-barrel structure, though it has a positively charged cavity and a hydrophobic core around the disulfide bonds. Some parts within the two putative γ-core motifs exhibited enhanced dynamics according to a new disorder index presentation of 15N-NMR relaxation data. Furthermore, we also provided a more detailed insight into the antifungal spectrum of PAFC, with specific emphasis on fungal plant pathogens. Our results suggest that PAFC could be an effective candidate for the development of new antifungal strategies in agriculture.
Cadmium and lead in livestock feed and cattle manure from four agricultural areas of Bursa, Turkey

The cadmium and lead contents in cattle manure taken from four agricultural areas exposed to different degrees of environmental pollution and in the livestock feeds grown in those places were measured by Atomic Absorption Spectrophotometer (AAS). The levels of cadmium and lead contamination in the manures of the cattle, which were fed in the areas far from industries, traffic or urbanization, were less than those that were closer to heavy traffic and industrial activities. The highest heavy metal content was found in cattle manure collected from the region with heavy traffic, followed by the industrial region and the rural region. Among the live stock feeds used in the present study, the highest levels of lead were found in grass; and the lowest levels were obtained from the samples of straw.
Image Processing for Industrial Structure Analysis

—As the world becomes increasingly more dependent on industrial infrastructures, structures like electrical power towers are very important for society to function properly, as the failure of these kinds of structure could affect thousands of people. This makes the inspection and maintenance of these structures a necessity. The most common way of analysing structures, like electrical towers, is by a human inspector visually assessing the state of the structure, which is time consuming, expensive and potentially dangerous. However, with the increased usage of robotic systems, such as drones, which are unmanned areal vehicles, and high resolution cameras, it is possible to acquire images from structures in a faster and safer way. With this information it is possible to further analyse the images obtained from these structures in order to detect which images contain a signiﬁcant amount of rust and should be evaluated by an expert. This thesis proposes the construction of two different methodologies for detecting the amount of rust in structures, the ﬁrst is an adaptation of a technique based on a sliding window and utilizing a convolution neural network for detecting rust regions, and the second is a methodology based on semantic segmentation for detecting how many pixels in an image are detected as ”rust” and how many are detected as ”structure”. These two approaches will then be compared in order to determine their advantages and limitations, when trying to achieve a good performance for the desired task.
Only Integer Multiplication Neural Networks for On Device AI

—Recently, training aware quantization using learnable quantization parameters is emerging. The above method is drawing attention because the accuracy of the 4bit quantization model is almost similar to that of the full-precision model. In addition, when the batch normalization layer, which plays an important role in the convolutional neural network, is folded with the convolution layer, it is possible to increase the inference speed because batch-related operations are unnecessary in model inference. This paper proposes a method of folding the convolution layer and the batch normalization layer into one module, and quantizing the weight and activation of the folded module with learnable quantization parameters. It was confirmed that the result of the proposed method was higher than Asymmetric Uniform quantization(IAO), which is a beta version of library provided by Pytorch, as VGG16: +0.2, ResNet18: +0.07, MobileNetv2: +3.32. In addition, it was confirmed that MovileNetv2 was impossible with the Pytorch library. The proposed method can be used for IoT (Internet of Things), Edge, etc. that require real-time inference.
Is there a Burnout Among Medical Interns - A cross-sectional study among Medical Interns in a Tertiary care Hospital in Tamil Nadu

Background: Burnout is a psychological syndrome comprising three dimensions: emotional exhaustion (EE), depersonalization (DP) and a perceived lack of personal accomplishment. Objectives: To estimate the proportion of burnout syndrome and the factors affecting the same in a private tertiary care hospital in South India. Methods: A cross-sectional study was done among internswho have been in the training for at least 6 monthsusing the Maslach Burnout inventory -Human Services Survey (MBI-HSS) which assesses the burnout among Health care workers. Therewas a total of 22 items in 3 sub-scales: A high score on EE and DP combined low PA was taken to diagnose burnout among the individuals. Results: The average age of the interns was 23.1 in which more than half (54.6%) of the respondents were female. The proportion of Burnout syndrome in our study was 27%. In the Burnout subcomponent score, it was found that more than 2/3 rd (77%) of the subjects reported high scores in the Emotional exhaustion component, while more than half (52.8%) score high in the depersonalization component. About 1/3 rd (33.3%) of the respondents reported low scores in the personal accomplishment segment. Conclusion: There should also be a support system for the interns to overcome the challenges that they face and also on the interns' part, there should be acceptance for the task ahead and the medical field requires a tremendous amount of mental and physical strength, a lot of hard work, and constant learning throughout life [1]. Medical training and Internship is considered to be a particularly stressful period as it is characterized by long working hours, unsatisfactory pay, poor work-life balance and in recent times they are also facing a lot of violence from the patient end [2]. In spite of certain regulations in practice with regards to the working hours for the residents, most often one end up working more than 48 hours per week. In addition, because of a lack of hospital staff (ranging from nurses to patient transport personnel), medical interns may have to take on extra responsibilities to replace or support other roles to guarantee patient care. This means medical students have even less time to sleep and may be unable to attend educational sessions or, in some cases they Ganesan et al (2020): Burn out syndrome and associated factors among interns Dec, 2020 Vol. 23 Issue 23 Annals of Tropical Medicine & Public Health http://doi.org/10.36295/ASRO.2020. 232387 may have to skip their meals to fill their duties [3]. Often these results in highly stressful conditions resulting in a Burnout of the individuals.
COMPARATIVE ANALYSIS OF PSO-DERIVED WORKFLOW SCHEDULING ALGORITHMS IN CLOUD COMPUTING BASED ON QOS REQUIREMENTS

Cloud computing is an advanced technique involving networks of servers that run on a huge amount of data. These servers and other sources of the cloud can be located in wide remote areas. Different scientific and web applications are representing by using Workflow models in the cloud. Scheduling different workflows in multi-cloud environment is a major issue of concern since they are quite huge and follow specific scientific standards. The need to meet user’s Quality of service (QoS) requirements are the other issues in public cloud computing, such as scalability and reliability and as well maximize the rate of resource utilization to end-users. This paper makes a comparison between three Particle Swarm Optimization (PSO) based algorithms in terms of makespan and cost. These algorithms were tested with the same number of virtual machines (VMs) and workflows
Packing R-trees with Space-filling Curves

The massive amount of data and large variety of data distributions in the big data era call for access methods that are efficient in both query processing and index management, and over both practical and worst-case workloads. To address this need, we revisit two classic multidimensional access methods—the R-tree and the space-filling curve. We propose a novel R-tree packing strategy based on space-filling curves. This strategy produces R-trees with an asymptotically optimal I/O complexity for window queries in the worst case. Experiments show that our R-trees are highly efficient in querying both real and synthetic data of different distributions. The proposed strategy is also simple to parallelize, since it relies only on sorting. We propose a parallel algorithm for R-tree bulk-loading based on the proposed packing strategy and analyze its performance under the massively parallel communication model. To handle dynamic data updates, we further propose index update algorithms that process data insertions and deletions without compromising the optimal query I/O complexity. Experimental results confirm the effectiveness and efficiency of the proposed R-tree bulk-loading and updating algorithms over large data sets.
Mechanism Design for Boolean Constraint Satisfaction Problems ´A kos Lukovics

In this thesis, we explore mechanism design without money for boolean constraint satisfaction problems. We present three main results. First, we show that for every boolean constraint satisfaction problem there is an optimal deterministic strategy proof mechanism. Second, we prove that there does not exist a deterministic group-strategy proof mechanism with a non-zero constant approximation ratio for Max-SAT, Max-Cut and Max-DiCut. Third, we describe a randomized group-strategy proof mechanism providing an approximation ratio of 1 − ε (for every constant ε > 0) for boolean constraint satisfaction problems without tautologies and contradictions. We also present some additional results not listed here, and describe and analyze mechanisms for Max-SAT, Max-Cut and Max-DiCut.