Miracle-dz/UniFAR-FTUs huggingface dataset:
Plexin-Semaphorin Signaling Modifies Neuromuscular Defects in a Drosophila Model of Peripheral Neuropathy

Dominant mutations in GARS, encoding the ubiquitous enzyme glycyl-tRNA synthetase (GlyRS), cause peripheral nerve degeneration and Charcot-Marie-Tooth disease type 2D (CMT2D). This genetic disorder exemplifies a recurring paradigm in neurodegeneration, in which mutations in essential genes cause selective degeneration of the nervous system. Recent evidence suggests that the mechanism underlying CMT2D involves extracellular neomorphic binding of mutant GlyRS to neuronally-expressed proteins. Consistent with this, our previous studies indicate a non-cell autonomous mechanism, whereby mutant GlyRS is secreted and interacts with the neuromuscular junction (NMJ). In this Drosophila model for CMT2D, we have previously shown that mutant gars expression decreases viability and larval motor function, and causes a concurrent build-up of mutant GlyRS at the larval neuromuscular presynapse. Here, we report additional phenotypes that closely mimic the axonal branching defects of Drosophila plexin transmembrane receptor mutants, implying interference of plexin signaling in gars mutants. Individual dosage reduction of two Drosophila Plexins, plexin A (plexA) and B (plexB) enhances and represses the viability and larval motor defects caused by mutant GlyRS, respectively. However, we find plexB levels, but not plexA levels, modify mutant GlyRS association with the presynaptic membrane. Furthermore, increasing availability of the plexB ligand, Semaphorin-2a (Sema2a), alleviates the pathology and the build-up of mutant GlyRS, suggesting competition for plexB binding may be occurring between these two ligands. This toxic gain-of-function and subversion of neurodevelopmental processes indicate that signaling pathways governing axonal guidance could be integral to neuropathology and may underlie the non-cell autonomous CMT2D mechanism.
Bioactivity‐guided Isolation of Cytotoxic Sesquiterpene Lactones of Gochnatia polymorpha ssp. floccosa

Phytochemical study of Gochnatia polymorpha (Less) Cabr. ssp. floccosa Cabr. trunk bark, guided by antiproliferative assays on 10 human cancer cell lines and the VERO cell line, yielded six known compounds identified as the triterpene bauerenyl acetate, the guaianolide 11α,13‐dihydrozaluzanin C and the dimeric guaianolides 10‐desoxygochnatiolide A, gochnatiolide A, 8‐hydroxi‐10‐desoxygochnatiolide A and 8‐hydroxigochnatiolide A. Extracts, fractions of extracts and isolated compounds were tested in vitro against a panel of human cancer cell lines, including U251 (glioma, CNS), UACC‐62 (melanoma), MCF‐7 (breast), NCI‐ADR/RES (drug‐resistant ovarian), 786.0 (kidney), NCI‐H460 (lung, no small cells), PC‐3 (prostate), OVCAR‐3 (ovarian), HT‐29 (colon), K562 (leukemia) and against the VERO no cancer cell line. Bauerenyl acetate was inactive, while 11α,13‐dihydrozaluzanin C showed weak activity against UACC62 and the VERO cell line. The most active compounds were 10‐desoxygochnatiolide A and gochnatiolide A, which inhibited the growth of kidney, melanoma, ovarian‐resistant and glioma cell lines with values of TGI (total growth inhibition) varying 0.21–1.09 µg/mL. This is the first report about cytotoxic activity of dimeric lactones against cell lines. Copyright © 2011 John Wiley & Sons, Ltd.
Are quality improvement collaboratives effective? A systematic review

Background Quality improvement collaboratives (QIC) have proliferated internationally, but there is little empirical evidence for their effectiveness. Method We searched Medline, Embase, CINAHL, PsycINFO and the Cochrane Library databases from January 1995 to December 2014. Studies were included if they met the criteria for a QIC intervention and the Cochrane Effective Practice and Organisation of Care (EPOC) minimum study design characteristics for inclusion in a review. We assessed study bias using the EPOC checklist and the quality of the reported intervention using a subset of SQUIRE 1.0 standards. Results Of the 220 studies meeting QIC criteria, 64 met EPOC study design standards for inclusion. There were 10 cluster randomised controlled trials, 24 controlled before-after studies and 30 interrupted time series studies. QICs encompassed a broad range of clinical settings, topics and populations ranging from neonates to the elderly. Few reports fully described QIC implementation and methods, intensity of activities, degree of site engagement and important contextual factors. By care setting, an improvement was reported for one or more of the study’s primary effect measures in 83% of the studies (32/39 (82%) hospital based, 17/20 (85%) ambulatory care, 3/4 nursing home and a sole ambulance QIC). Eight studies described persistence of the intervention effect 6 months to 2 years after the end of the collaborative. Collaboratives reporting success generally addressed relatively straightforward aspects of care, had a strong evidence base and noted a clear evidence-practice gap in an accepted clinical pathway or guideline. Conclusions QICs have been adopted widely as an approach to shared learning and improvement in healthcare. Overall, the QICs included in this review reported significant improvements in targeted clinical processes and patient outcomes. These reports are encouraging, but most be interpreted cautiously since fewer than a third met established quality and reporting criteria, and publication bias is likely.
A three-dimensional collagen scaffold cell culture system for screening anti-glioma therapeutics

Three-dimensional (3D) culture, which can simulate in vivo microenvironments, has been increasingly used to study tumor cell biology. Since most preclinical anti-glioma drug tests still rely on conventional 2D cell culture, we established a collagen scaffold for 3D glioma cell culture. Glioma cells cultured on these 3D scaffolds showed greater degree of dedifferentiation and quiescence than cells in 2D culture. 3D-cultured cells also exhibited enhanced resistance to chemotherapeutic alkylating agents, with a much higher proportion of glioma stem cells and upregulation of O6-methylguanine DNA methyltransferase (MGMT). Importantly, tumor cells in 3D culture showed chemotherapy resistance patterns similar to those observed in glioma patients. Our results suggest that 3D collagen scaffolds are promising in vitro research platforms for screening new anti-glioma therapeutics.
Ukiyo-e recommender system using restricted boltzmann machine

In this study, we implement an Ukiyo-e recommender system based on a restricted Boltzmann machine (RBM) for recommending Ukiyo-e prints to Ukiyo-e novices. This system can solve the problem of searching Ukiyo-e prints using keywords that are known only to Ukiyo-e experts. This system thus enables even an Ukiyo-e novice to obtain appropriate Ukiyo-e prints based on his interests. The user selects his interests amongst the few prints that are displayed initially. Then, with the use of an RBM, the system can find prints that match the user's interests. It can reconstruct the content information before making any recommendations.
Synchronization of master-slave neural networks with sampled-data control and actuator saturation

This paper focuses on synchronization of the master-slave neural networks. Under the constraint of sampleddata control and actuator saturation, synchronization criterion of master-slave neural network-based systems has been derived through the dynamic output feedback controller(DOFC). The error signals of master-slave systems are sampled and then transmitted to dynamic output-feedback controller, and an augmented system is modeled as an interval time-varying delay control system with nonlinear items. Through constructing discontinuous Lyapunov function and employing linear matrix inequality approach, sufficient conditions are derived, which guarantee asymptotical stability and accordingly synchronization master-slave systems; on the other hand, under the above synchronization and stability condition, a dynamic outputfeedback controller is designed. A numerical example has proved the effectiveness of this method.
Classifiers Accuracy Improvement Based on Missing Data Imputation

Abstract In this paper we investigate further and extend our previous work on radar signal identification and classification based on a data set which comprises continuous, discrete and categorical data that represent radar pulse train characteristics such as signal frequencies, pulse repetition, type of modulation, intervals, scan period, scanning type, etc. As the most of the real world datasets, it also contains high percentage of missing values and to deal with this problem we investigate three imputation techniques: Multiple Imputation (MI); K-Nearest Neighbour Imputation (KNNI); and Bagged Tree Imputation (BTI). We apply these methods to data samples with up to 60% missingness, this way doubling the number of instances with complete values in the resulting dataset. The imputation models performance is assessed with Wilcoxon’s test for statistical significance and Cohen’s effect size metrics. To solve the classification task, we employ three intelligent approaches: Neural Networks (NN); Support Vector Machines (SVM); and Random Forests (RF). Subsequently, we critically analyse which imputation method influences most the classifiers’ performance, using a multiclass classification accuracy metric, based on the area under the ROC curves. We consider two superclasses (‘military’ and ‘civil’), each containing several ‘subclasses’, and introduce and propose two new metrics: inner class accuracy (IA); and outer class accuracy (OA), in addition to the overall classification accuracy (OCA) metric. We conclude that they can be used as complementary to the OCA when choosing the best classifier for the problem at hand.
Visual Working Memory Is Independent of the Cortical Spacing Between Memoranda

The sensory recruitment hypothesis states that visual short-term memory is maintained in the same visual cortical areas that initially encode a stimulus' features. Although it is well established that the distance between features in visual cortex determines their visibility, a limitation known as crowding, it is unknown whether short-term memory is similarly constrained by the cortical spacing of memory items. Here, we investigated whether the cortical spacing between sequentially presented memoranda affects the fidelity of memory in humans (of both sexes). In a first experiment, we varied cortical spacing by taking advantage of the log-scaling of visual cortex with eccentricity, presenting memoranda in peripheral vision sequentially along either the radial or tangential visual axis with respect to the fovea. In a second experiment, we presented memoranda sequentially either within or beyond the critical spacing of visual crowding, a distance within which visual features cannot be perceptually distinguished due to their nearby cortical representations. In both experiments and across multiple measures, we found strong evidence that the ability to maintain visual features in memory is unaffected by cortical spacing. These results indicate that the neural architecture underpinning working memory has properties inconsistent with the known behavior of sensory neurons in visual cortex. Instead, the dissociation between perceptual and memory representations supports a role of higher cortical areas such as posterior parietal or prefrontal regions or may involve an as yet unspecified mechanism in visual cortex in which stimulus features are bound to their temporal order. SIGNIFICANCE STATEMENT Although much is known about the resolution with which we can remember visual objects, the cortical representation of items held in short-term memory remains contentious. A popular hypothesis suggests that memory of visual features is maintained via the recruitment of the same neural architecture in sensory cortex that encodes stimuli. We investigated this claim by manipulating the spacing in visual cortex between sequentially presented memoranda such that some items shared cortical representations more than others while preventing perceptual interference between stimuli. We found clear evidence that short-term memory is independent of the intracortical spacing of memoranda, revealing a dissociation between perceptual and memory representations. Our data indicate that working memory relies on different neural mechanisms from sensory perception.
SparseX

The Sparse Matrix-Vector Multiplication (SpMV) kernel ranks among the most important and thoroughly studied linear algebra operations, as it lies at the heart of many iterative methods for the solution of sparse linear systems, and often constitutes a severe performance bottleneck. Its optimization, which is intimately associated with the data structures used to store the sparse matrix, has always been of particular interest to the applied mathematics and computer science communities and has attracted further attention since the advent of multicore architectures. In this article, we present SparseX, an open source software package for SpMV targeting multicore platforms, that employs the state-of-the-art Compressed Sparse eXtended (CSX) sparse matrix storage format to deliver high efficiency through a highly usable “BLAS-like” interface that requires limited or no tuning. Performance results indicate that our library achieves superior performance over competitive libraries on large-scale problems.
Does independent component analysis perform well for iris recognition?

This paper is concerned with an application of ICA for a possible improvement of iris recognition by replying to the question: does ICA perform well for such purpose? To achieve this, the hypotheses and the theoretical concepts of ICA methods used are handled so that coherence with iris authentication application is guaranteed. Our contribution is not in the development of new theoretical concepts of ICA but it is in adapting its basic ideas for our application. Also, it consists of deploying its powerful and its efficiency for iris recognition, and consequently; it's potential to embed it on smart cards for increasing application domains of secure biometric-based individual identification systems. We have developed a comparative study between the implemented ICA algorithms and other recent and popular methods of iris recognition. We have demonstrated our experimental results using some mathematical criteria. Three different subsets of international certified CASIA iris image databases are used for testing the different implemented methods. The conclusion of such comparative study is that the ICA-based approaches are more effective and more practical than other existing methods.
A facile template-free route for synthesis of hollow hexagonal ZnS nano- and submicro-spheres

In the current paper, we report a facile template-free route for ‘mass production’ of ZnS hollow spheres with nano- and submicro-sizes, employing thiocarbamide, (CH3COO)2Zn·2H2O and water as the raw materials. ZnS hollow spheres were obtained via hydrothermal reaction at 140 °C for 5 h. XRD analysis showed that the as-prepared ZnS hollow spheres were of hexagonal phase structure. To the best of our knowledge, there were few reports on the preparation of hexagonal ZnS crystals under low temperature (<300 °C) in the literature. Furthermore, there is no report on the hollow structure of hexagonal phase ZnS under such low temperature (140 °C). Experimental results showed that the amount of thiocarbamide in the reaction system had a great impact on the size, shape, and structure of the final product. On the basis of the experimental results and our previous work, a possible formation mechanism was suggested.
Coordinated control of a four-area power system under structural perturbation

This paper discusses the procedure of coordinated controller design under system structural perturbation when new interconnections are adding into the overall system. With the concept of pair-wise decomposition, a group of adding matrices is defined to obtain the structure-changed transformation matrices used in permuted inclusion principle. By adjusting the former controllers structure corresponding to the information structure constraints variation, the new coordinated controller is capable of achieving high performance after this structural perturbation. A numerical simulation of automatic generation control (AGC) for a four-area power system under information structure constraints addition is provided by coordinated control.
Interleukin-10 Gene Transfer in Rat Limbal Transplantation

ABSTRACT Purpose: To evaluate the gene transfer of the interleukin (IL)-10 cytokine as a treatment modality for prolonging limbal allograft survival in a rat model. Materials and methods: Adenoviral (AV) and lentiviral (LV) vectors were produced for ex vivo gene transfer into limbal graft tissue prior to orthotopic transplantation. Experimental groups comprised unmodified isografts, unmodified allografts, allografts transfected with a reporter gene, and allografts transfected with IL-10. The functional effects of the transgenes were determined by clinical assessment and by following donor cell survival in the recipient animal. Group comparisons were made using survival analysis and tested with the log-rank test. Differences in mean rejection times between groups were tested using the Wilcoxon rank-sum test. Results: Isografts survived during the entire observation period of 56 days. Allografts underwent clinical rejection at a mean of 6.7 days (standard deviation 2.0) postoperatively, irrespective of the presence of transgenes (p < 0.001 for difference in rejection times). For both the AV and LV vector systems, Kaplan–Meier analysis showed a statistically significant difference with respect to time-to-graft failure when comparing allografts transfected with IL-10 with allografts transfected with reporter gene alone (p = 0.011 and p < 0.001, respectively). In the isografts, donor cells could be detected during the complete observation period. In all the allograft groups, however, donor cell detection declined after 1 week and was lost after 4 weeks. Conclusions: Under the conditions tested in the present model, both the AV and the LV vector systems were able to transfect limbal graft tissue ex vivo with biologically active IL-10, leading to delayed rejection compared to the controls.
Optimization of regularization parameter for sparse reconstruction based on predictive risk estimate

Recently, ℓ1-based sparse reconstruction has shown its superior performance in terms of accuracy and interpretation. The reconstruction quality is generally sensitive to the value of regularization parameter. In this work, we develop two data-driven optimization schemes based on minimization of predicted Stein's unbiased risk estimate (p-SURE) — statistically equivalent to predicted mean squared error (p-MSE). First, we propose a recursive evaluation of p-SURE for any given regularization parameter, where the optimal value is identified by the minimum p-SURE. Second, for fast optimization, we perform alternating optimization between regularization parameter and solution during the ℓ1-based iterative algorithms. We exemplify the proposed methods with a typical alternating direction method of multipliers (ADMM) for both analysis and synthesis formulations. Numerical experiments show that the proposed methods lead to highly accurate estimate of regularization parameter and nearly optimal reconstruction.
Effect of psychotherapy for depression on quality of life: meta-analysis

Background Several meta-analyses have shown that psychotherapy is effective for reducing depressive symptom severity. However, the impact on quality of life (QoL) is as yet unknown. Aims To investigate the effectiveness of psychotherapy for depression on global QoL and on the mental health and physical health components of QoL. Method We conducted a meta-analysis of 44 randomised clinical trials comparing psychotherapy for adults experiencing clinical depression or elevated depressive symptoms with a control group. We used subgroup analyses to explore the influence of various study characteristics on the effectiveness of treatment. Results We detected a small to moderate effect size (Hedges' g = 0.33, 95% CI 0.24–0.42) for global QoL, a moderate effect size for the mental health component (g = 0.42, 95% CI 0.33–0.51) and, after removing an outlier, a small but statistically significant effect size for the physical health component (g = 0.16, 95% CI 0.05–0.27). Multivariate meta-regression analyses showed that the effect size of depressive symptoms was significantly related to the effect size of the mental health component of QoL. The effect size of depressive symptoms was not related to global QoL or the physical health component. Conclusions Psychotherapy for depression has a positive impact on the QoL of patients with depression. Improvements in QoL are not fully explained by improvements in depressive symptom severity.
Behavior of the E–E’ Bonds (E, E’ = S and Se) in Glutathione Disulfide and Derivatives Elucidated by Quantum Chemical Calculations with the Quantum Theory of Atoms-In-Molecules Approach

The nature of the E–E’ bonds (E, E’ = S and Se) in glutathione disulfide (1) and derivatives 2–3, respectively, was elucidated by applying quantum theory of atoms-in-molecules (QTAIM) dual functional analysis (QTAIM-DFA), to clarify the basic contribution of E–E’ in the biological redox process, such as the glutathione peroxidase process. Five most stable conformers a–e were obtained, after applying the Monte-Carlo method then structural optimizations. In QTAIM-DFA, total electron energy densities Hb(rc) are plotted versus Hb(rc) − Vb(rc)/2 at bond critical points (BCPs), where Vb(rc) are potential energy densities at BCPs. Data from the fully optimized structures correspond to the static nature. Those containing perturbed structures around the fully optimized one in the plot represent the dynamic nature of interactions. The behavior of E–E’ was examined carefully. Whereas E–E’ in 1a–3e were all predicted to have the weak covalent nature of the shared shell interactions, two different types of S–S were detected in 1, depending on the conformational properties. Contributions from the intramolecular non-covalent interactions to stabilize the conformers were evaluated. An inverse relationship was observed between the stability of a conformer and the strength of E–E’ in the conformer, of which reason was discussed.
Variance-Based Global Sensitivity Analysis for Power Systems

Knowledge of the impact of uncertain inputs is valuable, especially in power systems with large amounts of stochastic renewable generations. A global sensitivity analysis (GSA) can determine the impact of input uncertainties on the output quantity of interest in a certain physical or mathematical model. The GSA has not been widely employed in power systems due to the prohibitively computational burden. In this paper, it is demonstrated that, via the implementation of a basis-adaptive sparse polynomial chaos expansion, a GSA can be applied to the power system with numerous uncertain inputs. The performance of the proposed method is tested on both the IEEE 13-bus test feeder and the IEEE 123-node test system, in presence of a large amount of independent or correlated uncertain inputs. The possible application of a GSA on the basis of the basis-adaptive sparse polynomial chaos expansion in power systems are discussed in terms of various sensitivities. The findings cannot only be used to rank the most influential input uncertainties with respect to a specific output, such as variances of the nodal power, but also to identify the most sensitive or robust electrical variables such as the bus voltage with respect to input uncertainties.