Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of self-efficacy in pain intensity, function, psychological factors, health behaviors, and quality of life in people with rheumatoid arthritis: A systematic review

ABSTRACT Objective: The aim of this study was to systematically review and critically appraise the role of self-efficacy in pain intensity, function, psychological factors, health behaviors, and quality of life in people with rheumatoid arthritis, based on the analyses of longitudinal studies. Methods: An electronic search of PubMed, AMED, CINAHL, PsycINFO, and PubPsych was carried out from inception to July 2017. Study selection was based on longitudinal studies which have explored the role of self-efficacy in rheumatoid arthritis. The Newcastle-Ottawa Scale adapted version was used to evaluate the risk of bias, whereas the Grading of Recommendations Assessment, Development and Evaluation evaluated the quality of the evidence per outcome. Results: A total of 11 articles met the inclusion criteria. Our results suggest an association between higher self-efficacy and greater goal achievement, positive affect, acceptance of illness, problem-solving coping, physical function, physical activity participation, and quality of life. Inversely, there was also an association between higher self-efficacy and lower pain intensity, depressive symptoms, and anxiety. Conclusions: The findings of this systematic review suggest that self-efficacy might have a positive effect on the prognosis of this condition, although further longitudinal studies are needed.
NEDD9 stimulated MMP9 secretion is required for invadopodia formation in oral squamous cell carcinoma

Neural precursor cell expressed developmentally downregulated 9 (NEDD9) is a component of the metastatic signatures of melanoma, breast cancer, glioblastoma, lung cancer and head and neck squamous cell carcinoma (HNSCC). Here we tested the efficacy of NEDD9's domains in stimulating matrix metalloproteinase (MMP) secretion and invadopodia formation in cells stably expressing various NEDD9 mutants. Replacement of the 13 YxxP motif substrate domain (SD) tyrosines and the C-terminal Y629 with phenylalanines (F14NEDD9) eliminated tyrosine phosphorylation, MMP9 secretion and loss of invadopodia formation. Mutation of the N-terminal SH3 domain Y12 to glutamic acid (Y12ENEDD9) or phenylalanine (Y12FNEDD9) reduced MMP9 secretion and inhibited invadopodia formation. SH3 domain deletion (∆SH3NEDD9) resulted in the loss of MMP9 secretion and a lack of invadopodia formation. The SH3–SD domain (SSNEDD9) construct exhibited tyrosine phosphorylation and stimulated MMP9 secretion, as did ∆CTNEDD9 which lacked the C-terminus (∆C-terminal; ∆CT). E13NEDD9 expression blocked MMP9 secretion and invadopodia formation. MICAL1 (molecule interacting with Cas-L1) silencing with a short hairpin RNA reduced MMP9 secretion, vimentin and E-cadherin levels while increasing N-cadherin and Rab6 levels, consistent with reduced invasive behavior. These findings indicate that NEDD9 SD phosphorylation and SH3 domain interactions are necessary for increasing MMP9 secretion and invadopodia formation.
EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signals

Generative adversarial networks (GANs) are recently highly successful in generative applications involving images and start being applied to time series data. Here we describe EEG-GAN as a framework to generate electroencephalographic (EEG) brain signals. We introduce a modification to the improved training of Wasserstein GANs to stabilize training and investigate a range of architectural choices critical for time series generation (most notably up- and down-sampling). For evaluation we consider and compare different metrics such as Inception score, Frechet inception distance and sliced Wasserstein distance, together showing that our EEG-GAN framework generated naturalistic EEG examples. It thus opens up a range of new generative application scenarios in the neuroscientific and neurological context, such as data augmentation in brain-computer interfacing tasks, EEG super-sampling, or restoration of corrupted data segments. The possibility to generate signals of a certain class and/or with specific properties may also open a new avenue for research into the underlying structure of brain signals.
Counting Human Flow with Deep Neural Network

Human flow counting has many applications in space management. This study applied channel state information (CSI) available in IEEE 802.11n networks to characterize the flow count. Raw inputs including mean, standard deviation and five-number summary were extracted from windowed CSI data. Due to the large number of raw inputs, stacked denoising autoencoders were used to extract hierarchical features from raw inputs and a final layer of softmax regression was used to model the flow counting problem. It is found that this deep neural network structure beats other popular classification algorithms including random forest, logistic regression, support vector machine and multilayer perceptron in predicting the flow count with attractive speed performance.
Variations in physiotherapy practice in neurological rehabilitation trajectories –an explorative interview and observational study

ABSTRACT Rehabilitation following acquired brain injury requires multidisciplinary efforts, including physiotherapy, across health care levels. Recent changes in the organization of health care services in western societies have led to earlier hospital discharge and increased responsibility for rehabilitation in primary care. The aim of this study was to describe and increase knowledge on the variations in physiotherapy practice for people with acquired brain injury across health care levels in Norway. We performed qualitative interviews with physiotherapists and field observations of physiotherapy treatments for 10 rehabilitation trajectories. We also performed systematic analyses using data from field observations, interviews, and hospital discharge records related to perspectives on social practices. The institutionalized rehabilitation context in hospitals promoted a more uniform approach by physiotherapists, emphasizing quality of movement and reacquisition of function. Physiotherapists in primary health care had to balance between interventions aiming to improve quality of movement versus interventions enabling patients to identify coping strategies. The informants highlighted the relevance of contextual surroundings when patients were discharged earlier from the hospital, as these patients’ level of function was perceived to be lower. Moreover, the preconditions for providing rehabilitation in primary care challenged physiotherapists to practice and use their knowledge base in novel ways.
The translational landscape of Arabidopsis mitochondria

Abstract Messenger RNA translation is a complex process that is still poorly understood in eukaryotic organelles like mitochondria. Growing evidence indicates though that mitochondrial translation differs from its bacterial counterpart in many key aspects. In this analysis, we have used ribosome profiling technology to generate a genome-wide snapshot view of mitochondrial translation in Arabidopsis. We show that, unlike in humans, most Arabidopsis mitochondrial ribosome footprints measure 27 and 28 bases. We also reveal that respiratory subunits encoding mRNAs show much higher ribosome association than other mitochondrial mRNAs, implying that they are translated at higher levels. Homogenous ribosome densities were generally detected within each respiratory complex except for complex V, where higher ribosome coverage corroborated with higher requirements for specific subunits. In complex I respiratory mutants, a reorganization of mitochondrial mRNAs ribosome association was detected involving increased ribosome densities for certain ribosomal protein encoding transcripts and a reduction in translation of a few complex V mRNAs. Taken together, our observations reveal that plant mitochondrial translation is a dynamic process and that translational control is important for gene expression in plant mitochondria. This study paves the way for future advances in the understanding translation in higher plant mitochondria.
EWS‐FLI1 reprograms the metabolism of Ewing sarcoma cells via positive regulation of glutamine import and serine‐glycine biosynthesis

Ewing sarcoma (EWS) is a soft tissue and bone tumor that occurs primarily in adolescents and young adults. In most cases of EWS, the chimeric transcription factor, EWS‐FLI1 is the primary oncogenic driver. The epigenome of EWS cells reflects EWS‐FLI1 binding and activation or repression of transcription. Here, we demonstrate that EWS‐FLI1 positively regulates the expression of proteins required for serine‐glycine biosynthesis and uptake of the alternative nutrient source glutamine. Specifically, we show that EWS‐FLI1 activates expression of PHGDH, PSAT1, PSPH, and SHMT2. Using cell‐based studies, we also establish that EWS cells are dependent on glutamine for cell survival and that EWS‐FLI1 positively regulates expression of the glutamine transporter, SLC1A5 and two enzymes involved in the one‐carbon cycle, MTHFD2 and MTHFD1L. Inhibition of serine‐glycine biosynthesis in EWS cells impacts their redox state leading to an accumulation of reactive oxygen species, DNA damage, and apoptosis. Importantly, analysis of EWS primary tumor transcriptome data confirmed that the aforementioned genes we identified as regulated by EWS‐FLI1 exhibit increased expression compared with normal tissues. Furthermore, retrospective analysis of an independent data set generated a significant stratification of the overall survival of EWS patients into low‐ and high‐risk groups based on the expression of PHGDH, PSAT1, PSPH, SHMT2, SLC1A5, MTHFD2, and MTHFD1L. In summary, our study demonstrates that EWS‐FLI1 reprograms the metabolism of EWS cells and that serine‐glycine metabolism or glutamine uptake are potential targetable vulnerabilities in this tumor type.
Physical, chemical, and sensory properties of biscuits prepared from flour blends of unripe cooking banana, pigeon pea, and sweet potato

Abstract Biscuits were produced from 14 flour blends of cooking banana (UBF), pigeon pea (PPF), and sweet potato (SPF). The physical properties, nutrient composition, and sensory characteristics of the biscuits were evaluated using standard methods. Data obtained were subjected to analysis of variance, and mean values were separated using Duncan's multiple range test. The hardness of the biscuit samples decreased as PPF increased, while the fracturability decreased with increase in UBF. Biscuits were significantly (p < .05) different in their nutrient composition, with the crude protein, crude fiber, ash contents, and dietary fiber content increasing as the PPF level increased. Cookies were rich in magnesium (576.54–735.06 mg/100 g) with favorable Na/K ratio (<1.0). The antinutritional factors in the biscuit samples were within permissible levels. Biscuits prepared from flour blend of 21.67% unripe cooking banana, 21.67% pigeon pea, and 56.67% sweet potato were the most preferred in terms of shape, mouthfeel, taste, crunchiness, and overall acceptability. Flour blends of unripe cooking banana, pigeon pea, and sweet potato could therefore be used as raw materials for the production of biscuits, with high protein, total dietary, and energy content.
Probabilistic Deep Learning using Random Sum-Product Networks

The need for consistent treatment of uncertainty has recently triggered increased interest in probabilistic deep learning methods. However, most current approaches have severe limitations when it comes to inference, since many of these models do not even permit to evaluate exact data likelihoods. Sum-product networks (SPNs), on the other hand, are an excellent architecture in that regard, as they allow to efficiently evaluate likelihoods, as well as arbitrary marginalization and conditioning tasks. Nevertheless, SPNs have not been fully explored as serious deep learning models, likely due to their special structural requirements, which complicate learning. In this paper, we make a drastic simplification and use random SPN structures which are trained in a "classical deep learning manner", i.e. employing automatic differentiation, SGD, and GPU support. The resulting models, called RAT-SPNs, yield prediction results comparable to deep neural networks, while still being interpretable as generative model and maintaining well-calibrated uncertainties. This property makes them highly robust under missing input features and enables them to naturally detect outliers and peculiar samples.
Quantification times 16 : When decentralization stands in the way of markets

In the German prison sector, quantification – the institutionalized production and consumption of numbers – has been widely practised over the past decades. However, the absence of comparison and benchmarking amongst the 16 federal Länder (states) precludes wider marketization and competition. This is in clear contrast to the UK, where since the 1980s private sector accounting instruments have transformed the prison from a ‘rules-based, bureaucratic institution to a calculating, economically minded organisation’ (Mennicken, 2013, p. 207). We trace here the role of quantified data in the German prison sector and explore how quantification, benchmarking and competition are linked therein. The context of the German federal system plays an ambiguous role. While the federal structure should be expected to encourage competition between the Länder’s penal systems, it actually precluded national comparisons across Germany.
Sequential combined Treatment of Pifithrin-α and Posiphen Enhances Neurogenesis and Functional Recovery After Stroke

Objective: Although cerebral ischemia can activate endogenous reparative processes, such as proliferation of endogenous neural stem cells (NSCs) in the subventricular zone (SVZ) and subgranular zone (SGZ), the majority of these new cells die shortly after injury and do not appropriately differentiate into neurons, or migrate and functionally integrate into the brain. The purpose of this study was to examine a novel strategy for treatment of stroke after injury by optimizing the survival of ischemia-induced endogenous NSCs in the SVZ and SGZ. Methods: Adult SVZ and SGZ NSCs were grown as neurospheres in culture and treated with a p53 inactivator, pifithrin-α (PFT-α), and an amyloid precursor protein (APP)-lowering drug, posiphen, and effects on neurosphere number, size and neuronal differentiation were evaluated. This combined sequential treatment approach was then evaluated in mice challenged with middle cerebral artery occlusion (MCAo). Locomotor behavior and cognition were evaluated at 4 weeks, and the number of new surviving neurons was quantified in nestin creERT2-YFP mice. Results: PFT-α and posiphen enhanced the self-renewal, proliferation rate and neuronal differentiation of adult SVZ and SGZ NSCs in culture. Their sequential combination in mice challenged with MCAo-induced stroke mitigated locomotor and cognitive impairments and increased the survival of SVZ and SGZ NSCs cells. PFT-α and the combined posiphen+PFT-α treatment similarly improved locomotion behavior in stroke challenged mice. Notably, however, the combined treatment provided significantly more potent cognitive function enhancement in stroke mice, as compared with PFT-α single treatment. Interpretation: Delayed combined sequential treatment with an inhibitor of p53 dependent apoptosis (PFT-α) and APP synthesis (posiphen) proved able to enhance stroke-induced endogenous neurogenesis and improve the functional recovery in stroke animals. Whereas the combined sequential treatment provided no further improvement in locomotor function, as compared with PFT-α alone treatment, suggesting a potential ceiling in the locomotion behavioral outcome in stroke animals, combined treatment more potently augmented cognitive function recovery after stroke.
Could Nearby Pokéstops Improve Restaurants' Online Reputation?

PokemonGo, 2016’s most popular and profitable mobile game, promoted people’s physical activities and impacted local business by bring new-foot-traffic. Many restaurant managers used it as a marketing tool to improve their traffic, reputation and sales. PokemonGo seems to serve as a positive externality to sales performance and reputation of restaurants with Pokestops nearby and seems to bring positive spill-over to these restaurants. However, windfall is not always there. It is necessary to examine the effectiveness of PokemonGo as marketing tool for restaurants through the information platform Yelp. Our objective is to examine how PokemonGo impacts restaurants’ reputation on Yelp.com. By focusing on “Pokestop”, we conducted difference-in-difference estimation to investigate the change of restaurants’ online-reputation before and after the launch of PokemonGo and with and without Pokestop nearby in both long and short term. We found that in short-run, PokemonGo significantly boosted onlinereputation for restaurants with Pokestop nearby by increasing their review volume, checkin, Elite review number and rating. In long-run, the impacts faded out with PokemonGo’s fading populairty. Yet surprisingly, rating in long-run are still significantly improved by the game. Additionally, Restaurant’s heterogeneity also influences PokemonGos’ effectiveness.
Role of IT Management and the Dynamics Behind IT Business Value Creation - A Longitudinal Assessment

In this study, we investigated how “good” IT management with its linkages to other factors influence IT business value (ITBV). First, we identified potential model constructs, then hypothesized about the relationships between the constructs and finally integrated the hypotheses into a research model. We empirically probed the hypotheses and our dynamic research model. We used survey data of 642 responses collected with annual surveys from CxOs during the years 2013, 2014 and 2015. Empirical results confirmed that the research model factors affected IT business value positively. The perceived importance of IT was discovered to be an antecedent to IT management. Both these constructs were detected to influence IT business value indirectly through the other model constructs. As a feedback, the perceived importance of IT depends strongly on IT business value.
The Notch Signaling Pathway Is Balancing Type 1 Innate Lymphoid Cell Immune Functions

The Notch pathway is one of the canonical signaling pathways implicated in the development of various solid tumors. During carcinogenesis, the Notch pathway dysregulation induces tumor expression of Notch receptor ligands participating to escape the immune surveillance. The Notch pathway conditions both the development and the functional regulation of lymphoid subsets. Its importance on T cell subset polarization has been documented contrary to its action on innate lymphoid cells (ILC). We aim to analyze the effect of the Notch pathway on type 1 ILC polarization and functions after disruption of the RBPJk-dependent Notch signaling cascade. Indeed, type 1 ILC comprises conventional NK (cNK) cells and type 1 helper innate lymphoid cells (ILC1) that share Notch-related functional characteristics such as the IFNg secretion downstream of T-bet expression. cNK cells have strong antitumor properties. However, data are controversial concerning ILC1 functions during carcinogenesis with models showing antitumoral capacities and others reporting ILC1 inability to control tumor growth. Using various mouse models of Notch signaling pathway depletion, we analyze the effects of its absence on type 1 ILC differentiation and cytotoxic functions. We also provide clues into its role in the maintenance of immune homeostasis in tissues. We show that modulating the Notch pathway is not only acting on tumor-specific T cell activity but also on ILC immune subset functions. Hence, our study uncovers the intrinsic Notch signaling pathway in ILC1/cNK populations and their response in case of abnormal Notch ligand expression. This study help evaluating the possible side effects mediated by immune cells different from T cells, in case of multivalent forms of the Notch receptor ligand delta 1 treatments. In definitive, it should help determining the best novel combination of therapeutic strategies in case of solid tumors.
Extracting Causal Claims from Information Systems Papers with Natural Language Processing for Theory Ontology Learning

The number of scientific papers published each year is growing exponentially. How can computational tools support scientists to better understand and process this data? This paper presents a softwareprototype that automatically extracts causes, effects, signs, moderators, mediators, conditions, and interaction signs from propositions and hypotheses of full-text scientific papers. This prototype uses natural language processing methods and a set of linguistic rules for causal information extraction. The prototype is evaluated on a manually annotated corpus of 270 Information Systems papers containing 723 hypotheses and propositions from the AIS basket of eight. F1results for the detection and extraction of different causal variables range between 0.71 and 0.90. The presented automatic causal theory extraction allows for the analysis of scientific papers based on a theory ontology and therefore contributes to the creation and comparison of inter-nomological networks.
Effect of Diode Laser-assisted Flap Surgery on Postoperative Healing and Clinical Parameters: A Randomized Controlled Clinical Trial

Background and Objectives: Lasers have been widely used because of several potential benefits such as antibacterial effect and stimulation of wound healing. In addition, lasers help in hemostasis and delaying epithelial migration which may facilitate the outcome of flap surgery. Hence, this study is aimed to investigate the adjunctive effect of diode laser irradiation on conventional access flap surgery in the treatment of periodontal disease. Materials and Methods: A total of 23 patients requiring periodontal flap surgery in two sextants with probing pocket depth ≥5 mm in at least three teeth post-phase I therapy were selected for a split-mouth study. Flap surgery with adjunctive diode laser irradiation was performed in the test quadrant while conventional access flap surgery was done in the control quadrant. Procedural pain and tissue response of the patients were evaluated at 3, 7, and 14 days postoperatively. Clinical parameters including probing depth, clinical attachment level, plaque index, and gingival index were recorded at baseline, 3 months, and 6 months following treatment. Results: There is no significant difference between the groups with respect to healing response of tissues; however, patients experienced more pain in test sites compared to control sites. Intragroup comparisons showed a statistically significant reduction of all clinical parameters from baseline to 6 months without any significant difference between the groups. Conclusion: Overall within the limitations of the study, diode lasers did not show any significant added benefits over conventional access flap surgery.