Miracle-dz/UniFAR-FTUs huggingface dataset:
Down-regulation of GAP-43 by inhibition of caspases-3 in a rat model of neuropathic pain.

BACKGROUND Neuropathic pain remains a prevalent and persistent clinical problem due to incomplete understanding of its pathogenesis. OBJECTIVE The present study aimed to investigate the role of caspase-3 in the neuropathic pain in rats with chronic constriction injury (CCI). METHODS SD rats were randomly assigned four groups (n=18 per group): sham group, normal saline group (NS group), Z-DEVD-FMK group (DEVD group) and RNA interference group (siRNA group). Z-DEVD-FMK (1 U/30 μl), siRNA targeting caspase-3 (10 μg/30 μl) and NS of equal volume were intrathecally administered once daily for 5 days starting 1 day before surgery in the DEVD, siRNA and NS group, respectively. Thermal hyperalgesia was assessed at one day before and 1, 2, 4, 5, 6, 7 and 10 days after surgery. The mRNA and protein expressions of caspase-3 were measured by real time PCR and immunofluorescence assay. Apoptosis was detected by TUNEL staining. GAP-43 expression was measured by immunofluorescence and western blot assays. RESULTS The right paw withdrawal latency (PWL) was decreased after CCI (P<0.05). TUNEL-positive neurons and the mRNA and protein expressions of caspase-3 in the spinal cord were increased significantly. After Z-DEVD-FMK or siRNA treatment, TUNEL-positive neurons were decreased, PWLs increased (P<0.05) and the mRNA and protein expressions of caspase-3 decreased. The expression of GAP-43, a sprouting related protein, was decreased in the DEVD and siRNA group as compared to NS group (P<0.05). Up-regulation of GAP-43 following CCI was decreased following caspase-3 inhibition. Following sciatic nerve ligation, the gene expression, translation and transcription are significantly changed in the neurons which finally results in neuron apoptosis. The neuron apoptosis induce the up-regulation of GAP-43 expression leading to hyperalgesia. CONCLUSION Caspase-3 mediated neuron apoptosis is probably responsible for the neuropathic pain in CCI rats. Inhibition of caspase-3 may serve as a treatment of neuropathic pain.
Using Brain-Computer Interface to understand and decode neural processes associated with imagined speech

—Imagined speech plays a central role in human consciousness, and its understanding is of great importance for the construction of a speech-like Brain-Computer Interface (BCI). Such BCIs would considerably beneﬁt patients suffering from severe conditions where they are unable to verbally communicate, despite being fully conscious. The goal of this study was to build a non-invasive closed-loop BCI for a vowel task. To this end, an ofﬂine vowel / syllable / word task was designed to better understand neural processes underlying imagined speech and evaluate binary classiﬁcation ability. We recorded six subjects brain activities using electroencephalography (EEG) during the ofﬂine task (listening to auditory stimuli and subsequently imagining saying them) and performed a comparative analysis between different classiﬁcation approaches. The best method consisted of a semi-automatic feature selection from a list of 41 EEG sub-band spectral features, followed by principal component analysis and nearest centroid classiﬁcation. Using this method, vowel vs rest average classiﬁcation accuracies were 68 . 9 ± 12 . 4% s.d. (best subject 85 . 5% ) and 71 . 1 ± 12 . 7% ( 90 . 6% ) for imag-ined speech and auditory stimulation conditions, respectively ( p < 0 . 05 ). For the best pairs, vowel vs vowel corresponding average classiﬁcation accuracies were 58 . 7 ± 6 . 0% ( 63 . 5% ) and 60 . 4 ± 3 . 9% ( 65 . 9% ). The online task, where users generated vowel speech imagery signals to control a ball on a screen, resulted in 67 . 7 ± 10 . 9% ( 83 . 9% ) classiﬁcation accuracy for the best pair. We conclude non-invasive speech imagery BCIs are within reach, but their applicability still requires efforts in signal acquisition, processing and classiﬁcation improvement, and in investigating the neural principles behind imagined speech.
Correlation Between the Interval of Influenza Virus Infectivity and Results of Diagnostic Assays in a Ferret Model.

BACKGROUND The relationship between influenza virus infectivity and virus shedding, based on different diagnostic methods, has not been defined. METHODS Three donor ferrets infected with 2009 pandemic influenza A(H1N1) underwent daily quantitative culture, antigen-detection testing, and real-time reverse transcription-polymerase chain reaction (RT-PCR). Eight contacts were sequentially cohoused with each of the donors for 24 hours during days 3-10 after inoculation. RESULTS Transmission was observed until day 5 after inoculation, corresponding to high culture titers and positive results of antigen-detection tests. Real-time RT-PCR showed no relation to the cessation of transmission. CONCLUSIONS Antigen-detection testing and virus culture but not real-time RT-PCR identified the end of the infectious period.
Contextual synchronization for efficient social collaborations in enterprise computing: A case study on TweetPulse

It is important to be aware of user contexts for supporting efficient collaborations among them. The goal of this article is to present a social collaboration platform where we can understand (1) how the user contexts are dynamically changing over time and (2) how the user contexts are mixed with multiple sub-contexts together. Therefore, we have implemented TweetPulse, which is a Twitter-based tool for context monitoring and propagation system in a given social network. TweetPulse can match contexts of the users (and integrate them) to find the most relevant users. Eventually, collaborations among users are contextually synchronized by dynamically organizing a number of communities. A set of users in each community can share their skills and core competencies with each other. We have shown the experimental results collected from a collaborative information searching system in terms of (1) setting thresholds, (2) searching performance, and (3) robustness testing.
Sentiment analysis for Arabic e-commerce websites

Sentiment analysis is a research area where studies focus on the analysis and the processing of opinions found on the web content. It is about finding the polarity of sentiment expressed by internet user in their interaction about a giving subject in order to classify them on positive or negative. In this paper, we propose the implementation of a tool for sentiment analysis able to find the polarity of opinions in reviews extracted from e-commerce magazines and blogs in Arabic language. To do this, we conducted various experiments like testing different techniques of stemming and the performance of some classification algorithms to have the combination that gives us satisfactory results. In spite of the huge difficulties that we found in this research area like the lack of resources in data collection and the complexity of processing the Arabic language dialects, the results were hopeful and satisfying.
A Double-Inactivated Severe Acute Respiratory Syndrome Coronavirus Vaccine Provides Incomplete Protection in Mice and Induces Increased Eosinophilic Proinflammatory Pulmonary Response upon Challenge

ABSTRACT Severe acute respiratory syndrome coronavirus (SARS-CoV) is an important emerging virus that is highly pathogenic in aged populations and is maintained with great diversity in zoonotic reservoirs. While a variety of vaccine platforms have shown efficacy in young-animal models and against homologous viral strains, vaccine efficacy has not been thoroughly evaluated using highly pathogenic variants that replicate the acute end stage lung disease phenotypes seen during the human epidemic. Using an adjuvanted and an unadjuvanted double-inactivated SARS-CoV (DIV) vaccine, we demonstrate an eosinophilic immunopathology in aged mice comparable to that seen in mice immunized with the SARS nucleocapsid protein, and poor protection against a nonlethal heterologous challenge. In young and 1-year-old animals, we demonstrate that adjuvanted DIV vaccine provides protection against lethal disease in young animals following homologous and heterologous challenge, although enhanced immune pathology and eosinophilia are evident following heterologous challenge. In the absence of alum, DIV vaccine performed poorly in young animals challenged with lethal homologous or heterologous strains. In contrast, DIV vaccines (both adjuvanted and unadjuvanted) performed poorly in aged-animal models. Importantly, aged animals displayed increased eosinophilic immune pathology in the lungs and were not protected against significant virus replication. These data raise significant concerns regarding DIV vaccine safety and highlight the need for additional studies of the molecular mechanisms governing DIV-induced eosinophilia and vaccine failure, especially in the more vulnerable aged-animal models of human disease.
Collaborative Visual Analysis on the Web with RCloud

Consider the emerging role of data science teams embedded in larger organizations. Individual analysts work on loosely related problems, and must share their findings with each other and the organization at large, moving results from exploratory data analyses (EDA) into automated visualizations, diagnostics and reports deployed for wider consumption. There are two problems with the current practice. First, there are gaps in this workflow: EDA is performed with one set of tools, and automated reports and deployments with another. Second, these environments often assume a single-developer perspective, while data scientist teams could get much benefit from easier sharing of scripts and data feeds, experiments, annotations, and automated recommendations, which are well beyond what traditional version control systems provide. We contribute and justify the following three requirements for systems built to support current data science teams and users: technology transfer, coexistence, and discoverability. In addition, we contribute the design and implementation of RCloud, a system that supports the requirements of collaborative data analysis, visualization and web deployment. The biggest deployment of RCloud has been in active use for more than two years, and has about fifty active users. We report on interviews with some of these users, and discuss the design decisions, tradeoffs and limitations, comparing RCloud to other current proposals.
Modelling the time course of antimalarial parasite killing: a tour of animal and human models, translation and challenges

Malaria remains a global public health concern and current treatment options are suboptimal in some clinical settings. For effective chemotherapy, antimalarial drug concentrations must be sufficient to remove completely all of the parasites in the infected host. Optimized dosing therefore requires a detailed understanding of the time course of antimalarial response, whilst simultaneously considering the parasite life cycle and host immune elimination. Recently, the World Health Organization (WHO) has recommended the development of mathematical models for understanding better antimalarial drug resistance and management. Other international groups have also suggested that mechanistic pharmacokinetic (PK) and pharmacodynamic (PD) models can support the rationalization of antimalarial dosing strategies. At present, artemisinin‐based combination therapy (ACT) is recommended as first line treatment of falciparum malaria for all patient groups. This review summarizes the PK–PD characterization of artemisinin derivatives and other partner drugs from both preclinical studies and human clinical trials. We outline the continuous and discrete time models that have been proposed to describe antimalarial activity on specific stages of the parasite life cycle. The translation of PK–PD predictions from animals to humans is considered, because preclinical studies can provide rich data for detailed mechanism‐based modelling. While similar sampling techniques are limited in clinical studies, PK–PD models can be used to optimize the design of experiments to improve estimation of the parameters of interest. Ultimately, we propose that fully developed mechanistic models can simulate and rationalize ACT or other treatment strategies in antimalarial chemotherapy.
The Compound Effect of Boosting and Stratified Sampling on Decision Tree Accuracy

It is generally recognized that recursive partitioning, as used in the construction of classification trees, is inherently unstable, particularly for small data sets. Classification accuracy and, by implication, tree structure, are sensitive to changes in the training data. Successful approaches to counteract this effect include multiple classifiers, e.g. boosting, bagging or windowing. The downside of these multiple classification models, however, is the plethora of trees that result, often making it difficult to extract the classifier in a meaningful manner. We show that, by using some very weak knowledge in the sampling stage, when the data set is partitioned into the training and test sets, a more consistent and improved performance is achieved by a single decision tree classifier. The reductions in error rate attained are comparable with those attained using boosting. In addition, we demonstrate that the combination of such sampling, combined with boosting, yields significant reductions in error rates
On models and algorithms for dynamic communication networks : the case for evolving graphs †

New technologies and the deployment of mobile and nomadic se rvices are driving the emergence of complex communications networks, that have a highly dynamic behavior. Modeling such dynamics, and designing algorithms that take it into account, received considerable attention rece ntly. In this paper, we introduce the evolving graphs , a simple model which aims at harnessing the complexity of an evolving setting as yielded by dynamic communication networks. We exemplify its use through the computation of shortest pat hs under different hypotheses in fixed-schedule dynamic networks.
Cell cycle dependent expression of Plk1 in synchronized porcine fetal fibroblasts

Enzymes of the Polo‐like kinase (Plk) family are active in the pathways controlling mitosis in several species. We have cloned cDNA fragments of the porcine homologues of Plk1, Plk2, and Plk3 employing fetal fibroblasts as source. All three partial cDNAs showed high sequence homology with their mouse and human counterparts and contained the Polo box, a domain characteristic for all Polo kinases. The expression levels of Plk1 mRNA at various points of the cell cycle in synchronized porcine fetal fibroblasts were analyzed by both RT‐PCR and the ribonuclease protection assay. Plk1 mRNA was barely detectable in G0 and G1, increased during S phase and peaked after the G2/M transition. A monoclonal antibody was generated against an in vitro expressed porcine Plk1‐protein fragment and used to detect changes in Plk1 expression at the protein level. Plk1 protein was first detected by immunoblotting at the beginning of S phase and was highest after the G2/M transition. In summary, the Plk1 expression pattern in the pig is similar to that reported for other species. The absence of Plk1 mRNA and protein appears to be a good marker for G0/G1 and thus for the selection of donor cells for nuclear transfer based somatic cloning. Mol. Reprod. Dev. 65: 245–253, 2003. © 2003 Wiley‐Liss, Inc.
Parallel iterative solvers in computational electronics

This work investigates parallel iterativesolvers for large sparse linear Systems of equations that arise in semiconduetordevice Simulation, an important area of computational electronics. The sparse linear Sys¬ tems in this field are unsymmetric, highly ill-conditioned, thus posing large demands on the linear solver. For the iterative Solution of sparse linear Systems many ingredi-ents are required. A state-of-the-artiterativesolver consists of various parts, such as algorithms to compute permutations, preconditioners and, of course, methods that iteratively compute an approximation of the Solution. For each category of algorithms, there are several possible choiees. In the first part of this work the most important ingredients are presented. The optimal set of these algorithms is then evaluated for realistic applications through an extensive number of numerical experiments. It is shown that algorithms that place large entries on the diagonal using unsymmetric permutations and scalings play an important role and greatly enhance the reliability of iterative solvers in this field. Incomplete LU-factorisations
The Role of Topical Antibiotic Prophylaxis in Patients Undergoing Contaminated Head and Neck Surgery With Flap Reconstruction

Objectives/Hypothesis Patients undergoing contaminated head and neck surgery with flap reconstruction have wound infection rates of 20% to 25% with parenteral antibiotic prophylaxis. Studies suggest that perioperative antimicrobial mouthwash reduces oropharyngeal flora and may prevent wound infections. We hypothesized that the addition of topical antibiotics to a parenteral prophylactic regimen would reduce the incidence of wound infection in these high‐risk patients.
Preserved priming effect in individuals with schizophrenia: cues towards rehabilitation

Introduction. Individuals with schizophrenia and affective disorders show relatively intact implicit memory as compared to declarative memory. Implicit memory is usually assessed with skill learning and priming tasks. Whereas priming is thought to involve storage changes in the posterior neocortex, skill learning is thought to rely more on the corticostriatal pathway. Since frontostriatal and frontotemporal dysfunctions are, respectively, found in schizophrenia and affective disorders, we hypothesised that individuals with schizophrenia and first-episode psychosis would exhibit disturbances in skill learning, but not priming. Methods. Thirty-five patients (11 first-episode psychosis; 11 schizophrenia; 13 affective disorders) and 10 controls completed a procedural learning and priming task. Participants had to identify fragmented images throughout five training sessions. The improvement of the threshold at which the images could be identified between the first and last session was used as an index of procedural learning. In a final session, the identification thresholds for old and new images were compared to assess the priming effect. Results. Whereas individuals with schizophrenia and first-episode psychosis showed impaired skill learning, the priming effect was similar in all groups. Conclusion. Even though some aspects of learning and memory are affected in schizophrenia, our results suggest that the posterior cortical pathway remains efficient at modulating the priming effect. This intact ability could be used to guide the elaboration of new rehabilitation programmes.
TBC1D24 regulates neuronal migration and maturation through modulation of the ARF6-dependent pathway

Significance The six-layered cerebral cortex forms through tightly regulated steps including neuronal proliferation, migration, and circuitry formation. Alterations of cortical development are associated with several neurological conditions, but the underlying pathogenetic mechanisms remain largely unknown. Here, we describe the role of TBC1 domain family member 24 (TBC1D24), a gene associated with syndromes combining epilepsy and cognitive deficits, in cortical development. Using an in vivo approach, we found that TBC1D24 regulates neuronal polarity, thus promoting neuronal migration and maturation. We further show that TBC1D24 exerts its function through the modulation of the activity of ADP ribosylation factor 6, a GTPase involved in membrane trafficking. Collectively, our data disclose a previously uncharacterized molecular mechanism involved in cortical development and underline how appropriate and timely neuronal positioning is essential for brain function. Alterations in the formation of brain networks are associated with several neurodevelopmental disorders. Mutations in TBC1 domain family member 24 (TBC1D24) are responsible for syndromes that combine cortical malformations, intellectual disability, and epilepsy, but the function of TBC1D24 in the brain remains unknown. We report here that in utero TBC1D24 knockdown in the rat developing neocortex affects the multipolar-bipolar transition of neurons leading to delayed radial migration. Furthermore, we find that TBC1D24-knockdown neurons display an abnormal maturation and retain immature morphofunctional properties. TBC1D24 interacts with ADP ribosylation factor (ARF)6, a small GTPase crucial for membrane trafficking. We show that in vivo, overexpression of the dominant-negative form of ARF6 rescues the neuronal migration and dendritic outgrowth defects induced by TBC1D24 knockdown, suggesting that TBC1D24 prevents ARF6 activation. Overall, our findings demonstrate an essential role of TBC1D24 in neuronal migration and maturation and highlight the physiological relevance of the ARF6-dependent membrane-trafficking pathway in brain development.
Low stress PECVD amorphous silicon carbide for MEMS applications

We present a characterization of PECVD (plasma-enhanced chemical vapour deposition) amorphous silicon carbide films for MEMS/BioMEMS applications. For this applications a high deposition rate and a controllable value of the residual stress is required. The influence of the main parameters is analyzed. Due to annealing effect, the temperature can decrease the compressive value of the stress. The RF frequency mode presents a major influence on residual stress: in low frequency mode a relatively high compressive stress is achieved due to ion bombardment and, as a result, densification of the layer achieved. The PECVD amorphous silicon carbide layers presents a low etching rate in alkaline solutions (around 13 A/min in KOH 30% at 80°C) while in HF 49% the layer is practically inert. Amorphous silicon carbide can be used as masking layer for dry etching in XeF2 reactors (etching rate of 7 A/min). Finally, applications of PECVD amorphous silicon carbide layers for MEMS/BioMEMS applications are presented.
Differential Roles of Two Homologous Cyclin-Dependent Kinase Inhibitor Genes in Regulating Cell Cycle and Innate Immunity in Arabidopsis1[OPEN]

Two homologous kinase inhibitor proteins play differential roles in regulating plant cell cycle and defense. Precise cell-cycle control is critical for plant development and responses to pathogen invasion. Two homologous cyclin-dependent kinase inhibitor genes, SIAMESE (SIM) and SIM-RELATED 1 (SMR1), were recently shown to regulate Arabidopsis (Arabidopsis thaliana) defense based on phenotypes conferred by a sim smr1 double mutant. However, whether these two genes play differential roles in cell-cycle and defense control is unknown. In this report, we show that while acting synergistically to promote endoreplication, SIM and SMR1 play different roles in affecting the ploidy of trichome and leaf cells, respectively. In addition, we found that the smr1-1 mutant, but not sim-1, was more susceptible to a virulent Pseudomonas syringae strain, and this susceptibility could be rescued by activating salicylic acid (SA)-mediated defense. Consistent with these results, smr1-1 partially suppressed the dwarfism, high SA levels, and cell death phenotypes in acd6-1, a mutant used to gauge the change of defense levels. Thus, SMR1 functions partly through SA in defense control. The differential roles of SIM and SMR1 are due to differences in temporal and spatial expression of these two genes in Arabidopsis tissues and in response to P. syringae infection. In addition, flow-cytometry analysis of plants with altered SA signaling revealed that SA is necessary, but not sufficient, to change cell-cycle progression. We further found that a mutant with three CYCD3 genes disrupted also compromised disease resistance to P. syringae. Together, this study reveals differential roles of two homologous cyclin-dependent kinase inhibitors in regulating cell-cycle progression and innate immunity in Arabidopsis and provides insights into the importance of cell-cycle control during host-pathogen interactions.