Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultrasound-mediated transdermal protein delivery

Transdermal drug delivery offers a potential method of drug administration. However, its application has been limited to a few low molecular weight compounds because of the extremely low permeability of human skin. Low-frequency ultrasound was shown to increase the permeability of human skin to many drugs, including high molecular weight proteins, by several orders of magnitude, thus making transdermal administration of these molecules potentially feasible. It was possible to deliver and control therapeutic doses of proteins such as insulin, interferon gamma, and erythropoeitin across human skin. Low-frequency ultrasound is thus a potential noninvasive substitute for traditional methods of drug delivery, such as injections.
Cloning of Clostridium cellulovorans endo-1,4-beta-glucanase genes.

A Clostridium cellulovorans lambda gt11 gene bank was screened for endo-1,4-beta-glucanase [EC 3.2. 1.4, EGase, Carboxy Methyl Cellulase (CMCase)] genes using a chromogenic substrate. Three genes (engA, engB, and engC) were isolated. The engB expressed the most active CMCase. The engA encoded a bifunctional enzyme that displayed endo-1,4-beta-glucanase and beta-glucosidase activities. The three recombinant glucanases, when expressed in Escherichia coli, were partially degraded into multiform active enzymes as evidenced by their SDS-PAGE-CMC zymograms. None of the clones could degrade crystalline cellulose, thus supporting the hypothesis that the integrity of the C. cellulovorans cellulase complex was essential for its 'true cellulase' activity.
MUF1, A Novel Elongin BC-interacting Leucine-rich Repeat Protein That Can Assemble with Cul5 and Rbx1 to Reconstitute a Ubiquitin Ligase*

The heterodimeric Elongin BC complex has been shown to interact in vitro and in mammalian cells with a conserved BC-box motif found in a growing number of proteins including RNA polymerase II elongation factor Elongin A, SOCS-box proteins, and the von Hippel-Lindau (VHL) tumor suppressor protein. Recently, the VHL-Elongin BC complex was found to interact with a module composed of Cullin family member Cul2 and RING-H2 finger protein Rbx1 to reconstitute a novel E3 ubiquitin ligase that activates ubiquitylation by the E2 ubiquitin-conjugating enzymes Ubc5 and Cdc34. In the context of the VHL ubiquitin ligase, Elongin BC functions as an adaptor that links the VHL protein to the Cul2/Rbx1 module, raising the possibility that the Elongin BC complex could function as an integral component of a larger family of E3 ubiquitin ligases by linking alternative BC-box proteins to Cullin/Rbx1 modules. In this report, we describe identification and purification from rat liver of a novel leucine-rich repeat-containing BC-box protein, MUF1, which we demonstrate is capable of assembling with a Cullin/Rbx1 module containing the Cullin family member Cul5 to reconstitute ubiquitin ligase activity. In addition, we show that the additional BC-box proteins Elongin A, SOCS1, and WSB1 are also capable of assembling with the Cul5/Rbx1 module to reconstitute potential ubiquitin ligases. Taken together, our findings identify MUF1 as a new member of the BC-box family of proteins, and they predict the existence of a larger family of Elongin BC-based E3 ubiquitin ligases.
Impact of Physical and Relational Peer Victimization on Depressive Cognitions in Children and Adolescents

The purpose of this study is to find longitudinal evidence of the effect of targeted peer victimization (TPV) on depressive cognitions as a function of victimization type and gender. Prospective relations of physical and relational peer victimization to positive and negative self-cognitions were examined in a 1-year, 2-wave longitudinal study. Self-reports of cognitions and both peer nomination and self-report measures of peer victimization experiences were obtained from 478 predominantly Caucasian children and young adolescents (Grades 3–6 at the beginning of the study) evenly split between genders. As a result, (a) peer victimization predicted increases in negative cognitions and decreases in positive cognitions over time; (b) relational victimization was more consistently related to changes in depressive cognitions than was physical victimization; (c) the prospective relation between victimization and depressive cognitions was stronger for boys than for girls; and (d) when the overlap between relational and physical TPV was statistically controlled, girls experienced more relational TPV than did boys, and boys experienced more physical TPV than did girls. Peer victimization, particularly relational TPV, has a significant impact on children's depressive cognitions. This relation seems particularly true for boys. Implications for future research, clinical work with victimized youth at risk for depression, and school policy to help both victims and bullies are discussed.
A semantic labeling strategy to reject unknown objects in large scale 3D point clouds

In recent years, there has been a growing interest in the research of semantic labeling of indoor scenes represented by 3D point clouds. A fundamental problem that has largely been oversighted in the current research is the way of dealing with the unknown class which collectively includes all the objects that are of no interest to the application developer. In the training stage, these objects are either completely removed or labeled as unknown, resulting in a trained model which is not fully and fairly exposed to the actual sample space. In the test stage, the unknown objects are naturally present and provided to the classifier, causing a significant drop of the classification accuracy-usually 20%~30%. Simply improving the features or the classifier will not address the root cause problem. In this paper, we propose a labeling framework combining both Conditional Random Field (CRF) and PI-SVM to specifically solve the problem caused by the unknown class. First, we use a CRF to model the contextual relations in the 3D space, for which the parameters for both node potential and edge potential are learned from training data. Then, we make use of the rejection strategy of the PI-SVM, which estimates an unnormalized probability for each class. Finally, we reinforce the result of CRF with the belief provided by the PI-SVM, and the labeling result is based on the agreement of the two classifiers. The proposed method takes advantage of the global optimization of CRF and the advantage of unknown rejection of PI-SVM. Experimental results on publicly available data set show that this method has improved the classification accuracy by 10.7% given the accuracy drop of 19.23% caused by the unknown.
A new method of Cloud-based Computation Model for Mobile Devices: Energy Consumption Optimization in Mobile-to-Mobile Computation Offloading

Today, cell phones have great important role in everyday lives. They are the most effective and achievable communication and computation devices that necessitate no exact time or location. Fast development of movable calculation created an energetic power to develop a synchronous technology in the markets. Anyhow movable devices are encountering with various challenges concerning available resources such as: battery, storage, bandwidth, security, and mobility. On the other side, limitation of resources in these phones has a great effect on the quality of the services. The most important limitation is the energy consuming that leads us to use the device for calculation, in spite of the accessibility of other sources. The best suggested solutions are getting rid of computation on the cloud and use of portable cloud for computation. But If there was no accessible cloud or an accurace of disconnection with the cloud, cell phones are the best to use. According to a mathematical algorithm based on Lyapunov optimization and regarding the requirement time for suitable program, we will try to introduce a dynamic way which its limitation analysis reveals that offlooding the computation considering the limitation of time leads to a less spending of power and energy resembled the current algorithm.
Cardiorespiratory fitness of post-stroke patients: as inpatients and as outpatients

The objective of this study was to determine the relationship between disuse weakness due to acute or subacute stroke and cardiorespiratory fitness. The participants were 15 men (average age 48.4 years) who were acute admissions to a hospital specializing in the management of stroke, 11 with cerebral infarction and four with intracerebral hemorrhage. All participants received physiotherapy (40 min/day, 5 days/week) at their bedside until leaving hospital. None of them received physiotherapy in an outpatient clinic. The anaerobic threshold (AT) was measured twice: during admission (an average of 37.3 days after onset) and after discharge (in an outpatient clinic, an average of 37 days after discharge and 42.7 days after the first test). The average AT was 12.5 ml/kg/min in the first test and 14.2 ml/kg/min in the second test (P<0.05). Because ATs in patients were lower after discharge than for healthy control individuals, physiotherapy during admission for stroke should be qualitatively and quantitatively reexamined for the prevention of disuse weakness. After discharge, it is important to give patients a more active rehabilitation program to improve their fitness.
Dynamic Structural Similarity on Graphs

One way of characterizing the topological and structural properties of vertices and edges in a graph is by using structural similarity measures. Measures like Cosine, Jaccard and Dice compute the similarities restricted to the immediate neighborhood of the vertices, bypassing important structural properties beyond the locality. Others measures, such as the generalized edge clustering coefficient, go beyond the locality but with high computational complexity, making them impractical in large-scale scenarios. In this paper we propose a novel similarity measure that determines the structural similarity by dynamically diffusing and capturing information beyond the locality. This new similarity is modeled as an iterated function that can be solved by fixed point iteration in super-linear time and memory complexity, so it is able to analyze large-scale graphs. In order to show the advantages of the proposed similarity in the community detection task, we replace the local structural similarity used in the SCAN algorithm with the proposed similarity measure, improving the quality of the detected community structure and also reducing the sensitivity to the parameter $\epsilon$ of the SCAN algorithm.
Assembly of TolC, a Structurally Unique and Multifunctional Outer Membrane Protein of Escherichia coli K-12

ABSTRACT TolC is a multifunctional outer membrane protein of Escherichia coli that folds into a novel α-β-barrel conformation absent in the other model outer membrane proteins used in assembly studies. The data presented in this work show that the unique folded structure of TolC reflects a unique assembly pathway. During its assembly, the newly translocated nascent TolC monomers are released in the periplasm. Maturation of these nascent monomers, and possibly their oligomerization, in the periplasm precedes their insertion in the outer membrane. The completion of the assembly process is signaled by the development of a characteristic proteinase K-resistant fragment generated by cleavage at a single, periplasmically exposed, protease-sensitive site of the membrane-anchored trimer. None of the assembly steps of TolC is affected by known folding factors, such as SurA, Skp, and lipopolysaccharide, which have profound effects on the assembly of other model trimeric outer membrane proteins. Two assembly-defective TolC mutants were isolated and characterized. One of the mutants (TolCI106N) was defective in the folding of nascent monomers, while the other (TolCS350F) was impaired in steps involving trimerization and membrane insertion of folded monomers.
WordNet Based Information Retrieval System for Assamese

Extracting the users expected information from a large text collection based on some query is the aim of a Information Retrieval (IR) system. Now a days Assamese Digital documents are increasing at a huge rate and to collect the information efficiently from them we are in need of an Assamese IR system for retrieving documents. Comparing query and document term on lexical level and the shorter length query implies the problem like word mismatch. Adding additional term with user's query means expanding the query can improve the IR system's performance. The electronic lexical database, WordNet can help identifying the synonymous expressions and linguistic entities that are semantically similar with the input query. Here we present an Assamese IR system based on vector space model and show our result by considering the query vector as the original user's query and the query is extended using the Assamese WordNet synsets.
SOPER: Discovering the Influence of Fashion and the Many Faces of User from Session Logs using Stick Breaking Process

Recommending lifestyle articles is of immediate interest to the e-commerce industry and is beginning to attract research attention. Often followed strategies, such as recommending popular items are inadequate for this vertical because of two reasons. Firstly, users have their own personal preference over items, referred to as personal styles, which lead to the long-tail phenomenon. Secondly, each user displays multiple personas, each persona has a preference over items which could be dictated by a particular occasion, e.g. dressing for a party would be different from dressing to go to office. Recommendation in this vertical is crucially dependent on discovering styles for each of the multiple personas. There is no literature which addresses this problem. We posit a generative model which describes each user by a Simplex Over PERsona, SOPER, where a persona is described as the individuals preferences over prevailing styles modelled as topics over items. The choice of simplex and the long-tail nature necessitates the use of stick-breaking process. The main technical contribution is an efficient collapsed Gibbs sampling based algorithm for solving the attendant inference problem. Trained on large-scale interaction logs spanning more than half-a-million sessions collected from an e-commerce portal, SOPER outperforms previous baselines such as [9] by a large margin of 35% in identifying persona. Consequently it outperforms several competitive baselines comprehensively on the task of recommending from a catalogue of roughly 150 thousand lifestyle articles, by improving the recommendation quality as measured by AUC by a staggering 12.23%, in addition to aiding the interpretability of uncovered personal and fashionable styles thus advancing our precise understanding of the underlying phenomena.
Unsupervised Anomaly Detection via Deep Metric Learning with End-to-End Optimization

We investigate unsupervised anomaly detection for high-dimensional data and introduce a deep metric learning (DML) based framework. In particular, we learn a distance metric through a deep neural network. Through this metric, we project the data into the metric space that better separates the anomalies from the normal data and reduces the effect of the curse of dimensionality for high-dimensional data. We present a novel data distillation method through self-supervision to remedy the conventional practice of assuming all data as normal. We also employ the hard mining technique from the DML literature. We show these components improve the performance of our model and significantly reduce the running time. Through an extensive set of experiments on the 14 real-world datasets, our method demonstrates significant performance gains compared to the state-of-the-art unsupervised anomaly detection methods, e.g., an absolute improvement between 4.44% and 11.74% on the average over the 14 datasets. Furthermore, we share the source code of our method on Github to facilitate further research.
Near-Complete Genome Sequence of a Fish Nervous Necrosis Virus Isolated from a Clinical Disease Outbreak in Farm-Reared Bream Sparus aurata in Spain

ABSTRACT Sparus aurata larvae infected by viral nervous necrosis were collected from an aquaculture fish farm. The isolated viral genome, composed of two segments (RNA1 and RNA2), was sequenced and analyzed comparatively. Phylogenetic tree analyses revealed that the isolated strain is a reassortant, exhibiting a red-spotted grouper nervous necrosis virus (RGNNV)-type RNA1 and a striped jack nervous necrosis virus (SJNNV)-type RNA2.
Hypoxia arising from concerted oxygen consumption by neutrophils and microorganisms in biofilms

Abstract Infections associated with microbial biofilms are often found to involve hypoxic or anoxic conditions within the biofilm or its vicinity. To shed light on the phenomenon of local oxygen depletion, mathematical reaction‐diffusion models were derived that integrated the two principal oxygen sinks, microbial respiration and neutrophil consumption. Three simple one‐dimensional problems were analyzed approximating biofilm near an air interface as in a dermal wound or mucus layer, biofilm on an implanted medical device, or biofilm aggregates dispersed in mucus or tissue. In all three geometries considered, hypoxia at the biofilm‐neutrophil interface or within the biofilm was predicted for a subset of plausible parameter values. The finding that oxygen concentration at the biofilm‐neutrophil juncture can be diminished to hypoxic levels is biologically relevant because oxygen depletion will reduce neutrophil killing ability. The finding that hypoxia can readily establish in the interior of the biofilm is biologically relevant because this change will alter microbial metabolism and persistence.
Influence of Nitrosative Stress on Fatigue During Childhood Leukemia Treatment

The focus on a cure for childhood leukemia over the last three decades has resulted in survival rates of more than 80%. However, efforts to manage leukemia-treatment symptoms have not kept pace with new therapies. Symptom toxicity during treatment can result in complications, treatment delays, and therapy dose reductions. Compromise in therapy can negatively influence the quality of life and, even more notably, jeopardize chances for long-term survival. This study examined biologic mechanisms that influence fatigue caused by increased reactive oxidative species (ROS) or actual failure of the antioxidant defense system due to genetic variation by investigating reactive nitrosative species, a “downstream” consequence of ROS. The specific aims of this study were to characterize the trajectory of nitrosative stress during acute lymphoblastic leukemia treatment and evaluate the influence of nitrosative stress on fatigue. A repeated measures design was used to evaluate the fatigue experienced by 186 children and adolescents, 3–18 years of age, with a diagnosis of leukemia during the most intense phase of treatment. An established biomarker of nitrosative stress, protein 3-nitrotyrosine (3NT) residues in the cerebral spinal fluid, was evaluated at diagnosis, postinduction, and consolidation phases of treatment. Higher fatigue was associated with higher 3NT levels at the beginning of treatment. Two distinct groups of children experienced either consistently high or consistently low 3NT levels across the treatment trajectory, from diagnosis to 12 months postinduction. Findings from this study support continued exploration into the phenotypic biochemical mechanisms that influence a reactive response to childhood cancer treatment.
An adaptive real time mechanism for IaaS cloud provider selection based on QoE aspects

Traditionally, companies host their own services, platforms and infrastructures on their own servers. This policy results in high costs in terms of material and human resources. It may also be inadequate to the real needs of the company. In this context, one solution is to use cloud computing to outsource their services. The latter is defined by making available to the customer high-performance servers and high bandwidth. The cloud is also defined by renting software and hardware infrastructure to customers according to their needs. Cloud computing is made possible by the improvement of computer networks infrastructures. Indeed, broadband connections have reduced latency and thus enabled the use of remote resources. The success of cloud computing has led to a significant increase in the providers number offering many and varied cloud services. While the access to these services is made possible through a simple subscription, no technique is currently available to select the cloud provider that best fits their needs. Selecting a provider is an optimization problem that has been studied in several areas. Given the large number of parameters and actors in the cloud, this problem is known as NP-complete one. In this work, we propose a new developed platform which plays the role of a broker between clients and cloud providers. Based on a set of benchmark tasks on provider services, it performs an adaptive cloud provider selection in accordance with the client needs. The experimental results show that the proposed approach gives benefits to subscribers in terms of QoE.
Carboxylate Transporter Gene JEN1 from the Entomopathogenic Fungus Beauveria bassiana Is Involved in Conidiation and Virulence

ABSTRACT Beauveria bassiana is an important entomopathogenic fungus widely used as a biological agent to control insect pests. A gene (B. bassiana JEN1 [BbJEN1]) homologous to JEN1 encoding a carboxylate transporter in Saccharomyces cerevisiae was identified in a B. bassiana transfer DNA (T-DNA) insertional mutant. Disruption of the gene decreased the carboxylate contents in hyphae, while increasing the conidial yield. However, overexpression of this transporter resulted in significant increases in carboxylates and decreased the conidial yield. BbJEN1 was strongly induced by insect cuticles and highly expressed in the hyphae penetrating insect cuticles not in hyphal bodies, suggesting that this gene is involved in the early stage of pathogenesis of B. bassiana. The bioassay results indicated that disruption of BbJEN1 significantly reduced the virulence of B. bassiana to aphids. Compared to the wild type, ΔBbJEN1 alkalinized the insect cuticle to a reduced extent. The alkalinization of the cuticle is a physiological signal triggering the production of pathogenicity. Therefore, we identified a new factor influencing virulence, which is responsible for the alkalinization of the insect cuticle and the initiation of fungal pathogenesis in insects.
[11C]PK11195 binding in Alzheimer disease and progressive supranuclear palsy

Objective We tested whether in vivo neuroinflammation relates to the distinctive distributions of pathology in Alzheimer disease (AD) and progressive supranuclear palsy (PSP). Methods Sixteen patients with symptomatic AD (including amnestic mild cognitive impairment with amyloid-positive PET scan), 16 patients with PSP–Richardson syndrome, and 13 age-, sex-, and education-matched healthy controls were included in this case-control study. Participants underwent [11C]PK11195 PET scanning, which was used as an in vivo index of neuroinflammation. Results [11C]PK11195 binding in the medial temporal lobe and occipital, temporal, and parietal cortices was increased in patients with AD, relative both to patients with PSP and to controls. Compared to controls, patients with PSP showed elevated [11C]PK11195 binding in the thalamus, putamen, and pallidum. [11C]PK11195 binding in the cuneus/precuneus correlated with episodic memory impairment in AD, while [11C]PK11195 binding in the pallidum, midbrain, and pons correlated with disease severity in PSP. Conclusions Together, our results suggest that neuroinflammation has an important pathogenic role in the 2 very different human neurodegenerative disorders of AD and PSP. The increase and distribution of microglial activation suggest that immunotherapeutic strategies may be useful in slowing the progression of both diseases.