Miracle-dz/UniFAR-FTUs huggingface dataset:
The Extracellular Matrix and Remyelination Strategies in Multiple Sclerosis

Remyelination therapy for multiple sclerosis (MS) is a rapidly emerging research area despite the fact that only limited success has been achieved so far in clinical trials. The extracellular matrix (ECM) is significantly altered in chronic MS lesions, which is believed to be an important remyelination-inhibiting factor. However, the ECM components have not been specifically targeted in current MS remyelinating trials. Qin et al. (2017) described the role of a major ECM protein, fibronectin, in de/remyelination. Exogenous ganglioside GD1a was demonstrated to overcome the remyelination-inhibiting effects of aggregated fibronectin during later stages of oligodendrocyte maturation. Thus, GD1a could potentially be used as a novel remyelinating compound or as combination therapy in conjunction with other drugs to enhance different stages of remyelination in MS. Multiple sclerosis (MS) is an autoimmune disorder of the central nervous system, characterized by inflammatory demyelination and progressive axonal loss. Demyelination has long been considered as the main pathologic feature of MS. Remyelination usually fails in chronic MS lesions despite the presence of oligodendrocyte precursor cells (OPCs; Kuhlmann et al., 2008). A major focus of current MS treatment is on immunomodulation and relapse control. However, it is increasingly believed that chronic demyelination can cause secondary axonal loss (Nave, 2010), which may lead to disease progression and clinical disability. Therefore, remyelinating therapy has become a rapidly emerging MS research area (Plemel et al., 2017). Some novel remyelinating compounds have been developed and progressed into clinical trials. Most of the remyelination clinical trials included patients with optic neuritis as study subjects, because de/remyelination in the visual pathways is more clinically measureable, which can be determined by the latency of visual evoked potentials (VEPs; You et al., 2011). However, only limited success in VEP latency improvement has been achieved to date in the clinical trials (Cadavid et al., 2017; …
Expectations influence treatment outcomes in patients with low back pain. A secondary analysis of data from a randomized clinical trial

Low back pain (LBP) is a global public health challenge, which causes high healthcare costs and the highest burden on society in terms of years lived with disability. While patients’ expectations for improvement may have effects on LBP treatment outcomes, it remains unclear if psychological profiles modify this relationship. Therefore, the objectives of this study were to investigate if (a) patients’ expectations predicted short‐term outcome, and (b) psychological profile, pain intensity and self‐rated health modified the relationship between expectations and outcome.
DADA-2000: Can Driving Accident be Predicted by Driver Attentionƒ Analyzed by A Benchmark

Driver attention prediction is currently becoming the focus in safe driving research community, such as the DR(eye)VE project and newly emerged Berkeley DeepDrive Attention (BDD-A) database in critical situations. In safe driving, an essential task is to predict the incoming accidents as early as possible. BDD-A was aware of this problem and collected the driver attention in laboratory because of the rarity of such scenes. Nevertheless, BDD-A focuses the critical situations which do not encounter actual accidents, and just faces the driver attention prediction task, without a close step for accident prediction. In contrast to this, we explore the view of drivers’ eyes for capturing multiple kinds of accidents, and construct a more diverse and larger video benchmark than ever before with the driver attention and the driving accident annotation simultaneously (named as DADA-2000), which has 2000 video clips owning about 658, 476 frames on 54 kinds of accidents. These clips are crowd-sourced and captured in various occasions (highway, urban, rural, and tunnel), weather (sunny, rainy and snowy) and light conditions (daytime and nighttime). For the driver attention representation, we collect the maps of fixations, saccade scan path and focusing time. The accidents are annotated by their categories, the accident window in clips and spatial locations of the crash-objects. Based on the analysis, we obtain a quantitative and positive answer for the question in this paper.
Predicting therapeutic response to fingolimod treatment in multiple sclerosis patients

Fingolimod, an orally active immunomodulatory drug for relapsing‐remitting multiple sclerosis (RRMS), sequesters T cells in lymph nodes through functional antagonism of the sphingosine‐1‐phosphate receptor, reducing the number of potential autoreactive cells that migrate to the central nervous system. However, not all RRMS patients respond to this therapy. Our aim was to test the hypothesis that by immune‐monitoring RRMS patient's leukocyte subpopulations it is possible to find biomarkers associated with clinical response to fingolimod.
Corrupt Bandits for Preserving Local Privacy

We study a variant of the stochastic multi-armed bandit (MAB) problem in which the rewards are corrupted. In this framework, motivated by privacy preservation in online recommender systems, the goal is to maximize the sum of the (unobserved) rewards, based on the observation of transformation of these rewards through a stochastic corruption process with known parameters. We provide a lower bound on the expected regret of any bandit algorithm in this corrupted setting. We devise a frequentist algoritthm, KLUCB-CF, and a Bayesian algorithm, TS-CF and give upper bounds on their regret. We also provide the appropriate corruption parameters to guarantee a desired level of local privacy and analyze how this impacts the regret. Finally, we present some experimental results that confirm our analysis.
A direct Primitive Variable Recovery Scheme for hyperbolic conservative equations: The case of relativistic hydrodynamics

In this article we develop a Primitive Variable Recovery Scheme (PVRS) to solve any system of coupled differential conservative equations. This method obtains directly the primitive variables applying the chain rule to the time term of the conservative equations. With this, a traditional finite volume method for the flux is applied in order avoid violation of both, the entropy and “Rankine-Hugoniot” jump conditions. The time evolution is then computed using a forward finite difference scheme. This numerical technique evades the recovery of the primitive vector by solving an algebraic system of equations as it is often used and so, it generalises standard techniques to solve these kind of coupled systems. The article is presented bearing in mind special relativistic hydrodynamic numerical schemes with an added pedagogical view in the appendix section in order to easily comprehend the PVRS. We present the convergence of the method for standard shock-tube problems of special relativistic hydrodynamics and a graphical visualisation of the errors using the fluctuations of the numerical values with respect to exact analytic solutions. The PVRS circumvents the sometimes arduous computation that arises from standard numerical methods techniques, which obtain the desired primitive vector solution through an algebraic polynomial of the charges.
Biologic Therapy For Ocular Inflammatory Diseases: An Update

Uveitis comprehends a wide and heterogeneous group of intraocular inflammatory conditions potentially sight-threatening and vari - able therapeutic strategies have been proposed. Classical treatment with steroids and conventional immunosuppressive agents is often used as first-step. However, a number of patients may not respond properly or tolerate these medications with well-known side ef - fects. Over the last two decades, advances in the understanding of the pathogenesis of autoimmune uveitis, as well as improved bio- technology, have enabled the development of a new class of drugs called biologics, which provide selective targeting of the immune mediators of the inflammation cascade. Biologic therapies were introduced as a new option for patients with autoimmune rheumatic conditions refractory to conventional therapy and due to their success have posteriorly been used in ophthalmology to treat ocular inflammatory disorders. These new agents may potentially provide more effective and less toxic treatment than conventional therapy. Biologic therapies include a wide variety of drugs with different mechanisms of action, including monoclonal antibodies against cell surface markers, cytokines and their receptors, or recombinant forms of natural inhibitory molecules. Although some results are based on investigations with insufficient clinical trials, the majority of biologics indicate preferable outcomes on refractory uveitis, with remarkable promise to increase the possibility of long-term remission. The development of these new drugs is one of the most revo- lutionary advances in recent years, and the promise of shifting paradigms makes it an exciting time for uveitis specialists worldwide.
CloudMF

While the number of cloud solutions is continuously increasing, the development and operation of large-scale and distributed cloud applications are still challenging. A major challenge is the lack of interoperability between the existing cloud solutions, which increases the complexity of maintaining and evolving complex applications potentially deployed across multiple cloud infrastructures and platforms. In this article, we show how the Cloud Modelling Framework leverages model-driven engineering and supports the DevOps ideas to tame this complexity by providing: (i) a domain-specific language for specifying the provisioning and deployment of multi-cloud applications, and (ii) a models@run-time environment for their continuous provisioning, deployment, and adaptation.
Zinc Absorption and Endogenous Fecal Zinc Losses in Bangladeshi Toddlers at Risk for Environmental Enteric Dysfunction

Objectives: Environmental enteric dysfunction (EED) impairs zinc absorption from food, and zinc deficiency may contribute to the poor growth associated with EED. We examined zinc absorption from a standardized aqueous zinc dose, and habitual daily endogenous fecal zinc excretion (EFZ) and compared these outcomes between children grouped by the lactulose to mannitol ratio (L:M). Methods: Bangladeshi toddlers (18–24 months) with low (<0.09) and high (≥0.09) L:M were administered isotope-labeled 3 mg aqueous zinc in the fasted state. Fractional absorption of zinc (FAZ) and EFZ were measured by dual stable isotope tracer method and an isotope dilution method, respectively. Secondary aims included examining relationships of biomarkers of systemic and intestinal inflammation and gut function with FAZ and EFZ. Results: Forty children completed the study; nearly all had evidence of EED. No differences in zinc homeostasis measurements (mean ± SD) were observed between high and low L:M groups: FAZ was 0.38 ± 0.19 and 0.31 ± 0.19, respectively; both figures were within estimated reference range. Means of EFZ were 0.73 ± 0.27 and 0.76 ± 0.20 mg/day for high and low L:M, respectively, and were 10% to 15% above estimated reference range. Regression analyses indicated that biomarkers of systemic inflammation were directly associated with increasing FAZ, consistent with increased gut permeability. Biomarkers of intestinal inflammation were negatively associated with EFZ, consistent with low-zinc intake and chronic deficiency. Conclusions: In these children at risk of EED, endogenous zinc losses were not markedly increased. Results suggest that efforts to improve zinc status in EED should focus on substantially improving zinc intakes.
TRPC1 stimulates calcium-sensing receptor-induced store-operated Ca2+ entry and nitric oxide production in endothelial cells

Store-operated Ca2+ entry (SOCE) via store-operated Ca2+ channels (SOCC), encoded by transient receptor potential canonical (TRPC) channel proteins, is an important underlying mechanism regulating intracellular Ca2+ concentration ([Ca2+]i) and various intracellular functions in endothelial cells (ECs). TRPC1, the probable candidate for SOCC, is expressed in ECs. Ca2+-sensing receptor (CaSR) is functionally expressed in vascular endothelium and is important in Ca2+ mobilization and cardiovascular functions. To date, there have been no reports demonstrating an association between CaSR and TRPC1 in ECs. The present study investigated the effects of TRPC1 on CaSR-induced Ca2+ influx and nitric oxide (NO) production in human umbilical vein ECs (HUVECs). TRPC1 and CaSR proteins in HUVECs were measured by immunostaining and western blot analysis. [Ca2+]i levels were measured using the Fura-2-acetoxymethyl ester method. The indicator 3-amino, 4-aminomethyl-2, 7-difluorescein diacetate was used to measure NO production in HUVECs. The expression of TRPC1 protein in HUVECs was silenced by transfecting HUVECs with small interfering RNA (siRNA) against TRPC1. Although changes in extracellular Ca2+ failed to alter [Ca2+]i in HUVECs, the CaSR agonist spermine increased [Ca2+]i and NO production in HUVECs. NO production in HUVECs was diminished in Ca2+-free medium or following treatment with a CaSR negative allosteric modulator (Calhex231), SOCC inhibitor (MRS1845) or TRPC inhibitor (SKF96365). The spermine-induced increases in [Ca2+]i and NO production were reduced in HUVECs transfected with TRPC1 siRNA. These results suggested that TRPC1 is a primary candidate in forming SOCC that stimulates CaSR-induced SOCE and NO production in HUVECs and is a potential therapeutic target for vascular diseases.
Analysis of Unstructured Text-Based Data Using Machine Learning Techniques: The Case of Pediatric Emergency Department Records in Nicaragua

Free-text information is still widely used in emergency department (ED) records. Machine learning techniques are useful for analyzing narratives, but they have been used mostly for English-language data sets. Considering such a framework, the performance of an ML classification task of a Spanish-language ED visits database was tested. ED visits collected in the EDs of nine hospitals in Nicaragua were analyzed. Spanish-language, free-text discharge diagnoses were considered in the analysis. Five-hundred random forests were trained on a set of bootstrap samples of the whole data set (1,789 ED visits) to perform the classification task. For each one, after having identified optimal parameter value, the final validated model was trained on the whole bootstrapped data set and tested. The classification accuracies had a median of 0.783 (95% CI [0.779, 0.796]). Machine learning techniques seemed to be a promising opportunity for the exploitation of unstructured information reported in ED records in low- and middle-income Spanish-speaking countries.
Human Pose Estimation Using Convolutional Neural Networks

Human pose estimation has always been a challenging problem that holds great attention, it has the widespread and extensive variety of uses from the classification of images to activity acknowledgment, main challenge is the detection and localization of the key points in the variation of several body poses. To resolve this issue, substantial research work have been done in this area. This paper discusses the issues in human pose estimation and gives the overview of considerable research work in pose estimation, including deep learning approach and customary image-based techniques. After analyzing several results and detecting the restrictions, the author has reconstructed a simple model using convolutional neural network that estimates the poses and demonstrates the potential of CNN’s. The author concludes with a few promising bearings and directions that have to be explored for future research.
Toxicity of adjuvant endocrine therapy in postmenopausal breast cancer patients: a systematic review and meta-analysis.

BACKGROUND Aromatase inhibitors are associated with consistent improvements in disease-free survival but not in overall survival. We conducted a literature-based meta-analysis of randomized trials to examine whether the relative toxicity of aromatase inhibitors compared with tamoxifen may explain this finding. METHODS We conducted a systematic review to identify randomized controlled trials that compared aromatase inhibitors and tamoxifen as primary adjuvant endocrine therapy in postmenopausal women by searching MEDLINE, EMBASE, and databases of the American Society of Clinical Oncology and San Antonio Breast Cancer Symposium. Odds ratios (ORs), 95% confidence intervals (CIs), absolute risks, and the number needed to harm associated with one adverse event were computed for prespecified serious adverse events including cardiovascular disease, cerebrovascular disease, bone fractures, thromboembolic events, endometrial carcinoma and other second cancers not including new breast cancer. All statistical tests were two-sided. RESULTS Seven trials enrolling 30,023 patients met the inclusion criteria. Longer duration of aromatase inhibitor use was associated with increased odds of developing cardiovascular disease (OR = 1.26, 95% CI = 1.10 to 1.43, P < .001; number needed to harm = 132) and bone fractures (OR = 1.47, 95% CI = 1.34 to 1.61, P < .001; number needed to harm = 46), but a decreased odds of venous thrombosis (OR = 0.55, 95% CI = 0.46 to 0.64, P < .001; number needed to harm = 79) and endometrial carcinoma (OR = 0.34, 95% CI = 0.22 to 0.53, P < .001; number needed to harm = 258). Five years of aromatase inhibitors was associated with a non-statistically significant increased odds of death without recurrence compared with 5 years of tamoxifen alone or tamoxifen for 2-3 years followed by an aromatase inhibitor for 2-3 years (OR = 1.11, 95% CI = 0.98 to 1.26, P = .09). CONCLUSIONS The cumulative toxicity of aromatase inhibitors when used as up-front treatment may explain the lack of overall survival benefit despite improvements in disease-free survival. Switching from tamoxifen to aromatase inhibitors reduces this toxicity and is likely the best balance between efficacy and toxicity.
Carbon Cloth Supported Nano-Mg(OH)2 for the Enrichment and Recovery of Rare Earth Element Eu(III) From Aqueous Solution

Nano-Mg(OH)2 is attracting great attention as adsorbent for pre-concentration and recovery of rare earth elements (REEs) from low-concentration solution, due to its superior removal efficiency for REEs and environmental friendliness. However, the nanoparticles also cause some severe problems during application, including aggregation, blockage in fixed-bed column, as well as the difficulties in separation and reuse. Herein, in order to avoid the mentioned problems, a carbon cloth (CC) supported nano-Mg(OH)2 (nano-Mg(OH)2@CC) was synthesized by electrodeposition. The X-ray diffraction and scanning electron microscopy analysis demonstrated that the interlaced nano-sheet of Mg(OH)2 grew firmly and uniformly on the surface of carbon cloth fibers. Batch adsorption experiments of Eu(III) indicated that the nano-Mg(OH)2@CC composite maintained the excellent adsorption performance of nano-Mg(OH)2 toward Eu(III). After adsorption, the Eu containing composite was calcined under nitrogen atmosphere. The content of Eu2O3 in the calcined material was as high as 99.66%. Fixed-bed column experiments indicated that no blockage for Mg(OH)2@CC composite was observed during the treatment, while the complete blockage of occurred to nano-Mg(OH)2 at an effluent volume of 240 mL. Moreover, the removal efficiency of Mg(OH)2@CC was still higher than 90% until 4,200 mL of effluent volume. This work provides a promising method for feasible application of nanoadsorbents in fixed-bed process to recycle low-concentration REEs from wastewater.
Steady-State Mean-Square Deviation Analysis of the Zero-Attracting CLMS Algorithm With Circular Gaussian Input

When the complex least mean-square (CLMS) algorithm is used to estimate a complex sparse system, its convergence rate is relatively slow. To make full use of the sparsity of the unknown system to improve convergence rate, a zero-attracting CLMS (ZA-CLMS) algorithm has recently been proposed. In order to predict the statistical behavior of the complex adaptive filter after converging, this paper analyzes the steady-state mean-square deviation (MSD) performance of ZA-CLMS with circular Gaussian input. For mathematical tractability, in the analysis, the unknown system weights are divided into two sets according to their values and some statistical assumptions are used. The simulation results are provided to show the superior performance of ZA-CLMS for complex sparse system identification and to verify the validity of the theoretical expressions for predicting the steady-state MSD performance.
Evolutionary trends in the flowers of Asteridae: is polyandry an alternative to zygomorphy?

BACKGROUND AND AIMS Floral symmetry presents two main states in angiosperms, actinomorphy (polysymmetry or radial symmetry) and zygomorphy (monosymmetry or bilateral symmetry). Transitions from actinomorphy to zygomorphy have occurred repeatedly among flowering plants, possibly in coadaptation with specialized pollinators. In this paper, the rules controlling the evolution of floral symmetry were investigated to determine in which architectural context zygomorphy can evolve. METHODS Floral traits potentially associated with perianth symmetry shifts in Asteridae, one of the major clades of the core eudicots, were selected: namely the perianth merism, the presence and number of spurs, and the androecium organ number. The evolution of these characters was optimized on a composite tree. Correlations between symmetry and the other morphological traits were then examined using a phylogenetic comparative method. KEY RESULTS The analyses reveal that the evolution of floral symmetry in Asteridae is conditioned by both androecium organ number and perianth merism and that zygomorphy is a prerequisite to the emergence of spurs. CONCLUSIONS The statistically significant correlation between perianth zygomorphy and oligandry suggests that the evolution of floral symmetry could be canalized by developmental or spatial constraint. Interestingly, the evolution of polyandry in an actinomorphic context appears as an alternative evolutionary pathway to zygomorphy in Asteridae. These results may be interpreted either in terms of plant-pollinator adaptation or in terms of developmental or physical constraints. The results are discussed in relation to current knowledge about the molecular bases underlying floral symmetry.
Conceptual Framework of Smart Device for Smart Home Management Based on RFID and IoT

World population is expanding continuously; the current world population is more than seven billion. And approximately 65–70% of the total population by 2050 will be in urban cities. This has also given a significant rise in the concept of Smart cities. To keep a pace with this fast moving life, Smart city provides equilibrium. With the fast moving world the life of human also became very fast which comes with lots of daily problems too. People forget where they placed their things. Daily life becomes a mess to many people nowadays. Our paper is an attempt to provide a design of a smart device which will help user for day to day memory management. A device, which will coordinate the help of RFID and IOT to recognize every second in a day. The methodology of the same paper talks about RFID and sensor-based object and one central device coordination. Once you put it on and it tracks everything, analyses everything and tells you where your object was kept last. This device will be very helpful especially for patients suffering from memory loss problems. Memory is a problem to all and the device can help out in this busy world.