Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of HEXACO Personality Factors on Consumer Video Game Engagement: A Study on eSports

This article aims to uncover novel insights into personality factors and consumer video game engagement modeling. This research empirically validates the role of specific HEXACO personality factors that foster consumer engagement (CE) in electronic sports (eSports) users. Using a survey-based approach, we incorporated the HEXACO 60 items and consumer video game engagement scales for data collection. Data were collected from eSports users, with 250 valid responses. WarpPLS 6.0 was used for partial least squares–structural equation modeling analyses comprising measurement and structural model assessment. The results showed that the reflective measurement model is reliable and sound, whereas the second-order formative measurement model also meets the criteria of indicator weights and collinearity values variance inflation factor (VIF). The results based on the structural model indicate that openness to experience, extraversion, agreeableness, and conscientiousness positively predict CE in eSports. This article is first among others that conceptualizes and validates the HEXACO personality traits as a reflective formative model using the hierarchical component model approach. The research model carries the explanatory capacity for CE in eSports concerning personality dimensions as indicated by the HEXACO model. It highlights the potential benefits of such research especially to marketers who could potentially employ personality modeling to develop tailored strategies to increase CE in video games.
Deep learning based segmentation of brain tissue from diffusion MRI

Segmentation of brain tissue types from diffusion MRI (dMRI) is an important task, required for quantification of brain microstructure and for improving tractography. Current dMRI segmentation is mostly based on anatomical MRI (e.g., T1- and T2-weighted) segmentation that is registered to the dMRI space. However, such inter-modality registration is challenging due to more image distortions and lower image resolution in the dMRI data as compared with the anatomical MRI data. In this study, we present a deep learning method that learns tissue segmentation from high-quality imaging datasets from the Human Connectome Project (HCP), where registration of anatomical data to dMRI is more precise. The method is then able to predict a tissue segmentation directly from new dMRI data, including data collected with a different acquisition protocol, without requiring anatomical data and inter-modality registration. We train a convolutional neural network (CNN) to learn a tissue segmentation model using a novel augmented target loss function designed to improve accuracy in regions of tissue boundary. To further improve accuracy, our method adds diffusion kurtosis imaging (DKI) parameters that characterize non-Gaussian water molecule diffusion to the conventional diffusion tensor imaging parameters. The DKI parameters are calculated from the recently proposed mean-kurtosis-curve method that corrects implausible DKI parameter values and provides additional features that discriminate between tissue types. We demonstrate high tissue segmentation accuracy on HCP data, and also when applying the HCP-trained model on dMRI data from a clinical acquisition with lower resolution and fewer gradient directions.
Sesquiterpene Lactones Specifically Inhibit Activation of NF-κB by Preventing the Degradation of IκB-α and IκB-β*

Extracts from certain Mexican Indian medicinal plants used in traditional indigenous medicine for the treatment of inflammations contain sequiterpene lactones (SLs), which specifically inhibit the transcription factor NF-κB (Bork, P. M., Schmitz, M. L., Kuhnt, M., Escher, C., and Heinrich, M. (1997) FEBS Lett. 402, 85–90). Here we show that SLs prevented the activation of NF-κB by different stimuli such as phorbol esters, tumor necrosis factor-α, ligation of the T-cell receptor, and hydrogen peroxide in various cell types. Treatment of cells with SLs prevented the induced degradation of IκB-α and IκB-β by all these stimuli, suggesting that they interfere with a rather common step in the activation of NF-κB. SLs did neither interfere with DNA binding activity of activated NF-κB nor with the activity of the protein tyrosine kinases p59 fyn and p60 src . Micromolar amounts of SLs prevented the induced expression of the NF-κB target gene intracellular adhesion molecule 1. Inhibition of NF-κB by SLs resulted in an enhanced cell killing of murine fibroblast cells by tumor necrosis factor-α. SLs lacking an exomethylene group in conjugation with the lactone function displayed no inhibitory activity on NF-κB. The analysis of the cellular redox state by fluorescence-activated cell sorter showed that the SLs had no direct or indirect anti-oxidant properties.
Current Insights on Early Life Nutrition and Prevention of Allergy

The incidence of allergic diseases in childhood appears to have significantly increased over the last decades. Since environmental factors, including diet, have been thought to play a significant role in the development of these diseases, there is great interest in identifying prevention strategies related to early nutritional interventions. Breastfeeding is critical for the immune development of newborns and infants through immune-modulating properties and it impacts the establishment of a healthy gut microbiota. However, the evidence for a protective role of breastfeeding against the development of food allergy in childhood is controversial, and there is little evidence to support the benefits of an antigen avoidance diet during lactation. Although it is not possible to draw a definitive conclusion about the protective role of breast milk against allergic diseases, exclusive breastfeeding is still recommended throughout the first 6 months of life due to associated health benefits. Furthermore, recommendations regarding complementary feeding in infancy have been significantly modified over the last few decades. Several studies have shown that delayed exposure to allergenic foods does not have a role in allergy prevention and recent guidelines recommend against delaying the introduction of complementary foods after 6 months of age, both in high- and low-risk infants. However, trials investigating this dietary approach have reported equivocal results so far. This review summarizes the available high-quality evidence regarding the efficacy of the principal dietary interventions proposed in early life to prevent allergic diseases in children.
The genetic architecture of host response reveals the importance of arbuscular mycorrhizae to maize cultivation

Arbuscular mycorrhizal fungi (AMF) are ubiquitous in cultivated soils, forming symbiotic relationships with the roots of major crop species. Although studies in controlled conditions have demonstrated the potential of the symbiosis to enhance host plant nutrition and alleviate environmental stress, practical difficulties make it hard to estimate the actual benefit in cultivated fields, not least because of the lack of availability of suitable AMF-free controls. Furthermore, the response can vary depending on the plant variety in a manner which is not fully understood. Here, we implemented a novel strategy based on the selective incorporation of AMF-resistance into a genetic mapping population to evaluate maize response in the field. We found AMF to account for about one third of the grain production in a rain-fed medium input field, as well as to impact the relative performance of plant varieties. Characterization of the genetic architecture of host response allowed us to distinguish mycorrhizal benefit from dependence and indicated a trade-off between mycorrhizal and non-mycorrhizal performance, both at the level of individual QTL and genomewide. This approach is applicable to other crop species, permits further mechanistic analysis and is scalable to full yield trials.
Effective Context-Aware Recommendations Based on Context Weighting Using Genetic Algorithm and Alleviating Data Sparsity

ABSTRACT Context-aware collaborative filtering (CACF) is an effective approach for adapting recommendations under users’ specific contextual situations and aims to improve predictive accuracy for Context-aware recommender systems (CARSs). Incorporating context in recommender systems (RSs) considering the equal importance to all contextual dimensions is not appropriate for seeking an intelligent and useful recommendation. In this paper, we propose a Real-coded Genetic Algorithm (RCGA) based CARS framework that exploits contextual pre-filtering and contextual modeling paradigms into CACF with appropriate context feature weights for enhancing accuracy as well as the diversity of the recommendation list. Further to alleviate the data sparsity, an effective missing value prediction (EMVP) algorithm is applied into proposed framework. The accuracy based on RCGA is compared with other two schemes: Support Vector Machine (SVM) and Particle Swarm Optimization (PSO), and RCGA has shown better results. Experimental results based on real-world datasets have clearly established the effectiveness of our proposed CARS schemes.
MacaquePose: A Novel “In the Wild” Macaque Monkey Pose Dataset for Markerless Motion Capture

Video-based markerless motion capture permits quantification of an animal’s pose and motion, with a high spatiotemporal resolution in a naturalistic context, and is a powerful tool for analyzing the relationship between the animal’s behaviors and its brain functions. Macaque monkeys are excellent non-human primate models, especially for studying neuroscience. Due to the lack of a dataset allowing training of a deep neural network for the macaque’s markerless motion capture in the naturalistic context, it has been challenging to apply this technology for macaques-based studies. In this study, we created MacaquePose, a novel open dataset with manually labeled body part positions for macaques in naturalistic scenes, consisting of >13,000 images, refined by researchers. We show that the pose estimation performance of an artificial neural network trained with the dataset is close to that of a human-level. The MacaquePose will provide a platform for innovative behavior analysis for non-human primate.
Modeling Dynamics with Deep Transition-Learning Networks

Markov processes, both classical and higher order, are often used to model dynamic processes, such as stock prices, molecular dynamics, and Monte Carlo methods. Previous works have shown that an autoencoder can be formulated as a specific type of Markov chain. Here, we propose a generative neural network known as a transition encoder, or \emph{transcoder}, which learns such continuous-state dynamic processes. We show that the transcoder is able to learn both deterministic and stochastic dynamic processes on several systems. We explore a number of applications of the transcoder including generating unseen trajectories and examining the propensity for chaos in a dynamic system. Further, we show that the transcoder can speed up Markov Chain Monte Carlo (MCMC) sampling to a convergent distribution by training it to make several steps at a time. Finally, we show that the hidden layers of a transcoder are useful for visualization and salient feature extraction of the transition process itself.
Developing an Unbiased Multiplex PCR System to Enrich the TRB Repertoire Toward Accurate Detection in Leukemia

Accurate T cell receptor repertoire profiling has provided novel biological and clinical insights in widespread immunological settings; however, there is a lack of reference materials in the community that can be used to calibrate and optimize the various experimental systems in different laboratories. In this study, we designed and synthesized 611 T cell receptor (TCR) beta chain (TRB) templates and used them as reference materials to optimize the multiplex PCR experimental system to enrich the TRB repertoire. We assessed the stability of the optimized system by repeating the experiments in different batches and by remixing the TRB templates in different ratios. These TRB reference materials could be used as independent positive controls to assess the accuracy of the experimental system, and they can also be used as spike-in materials to calibrate the residual biases of the experimental system. We then used the optimized system to detect the minimal residual disease of T cell acute lymphoblastic leukemia and showed a higher sensitivity compared with flow cytometry. We also interrogated how chemotherapy affected the TCR repertoire of patients with B-cell acute lymphoblastic leukemia. Our result shows that high-avidity T cells, such as those targeting known pathogens, are largely selected during chemotherapy, despite the global immunosuppression. These T cells were stimulated and emerged at the time of induction treatment and further expanded during consolidation treatment, possibly to fight against infections. These data demonstrate that accurate immune repertoire information can improve our understanding of the adaptive immunity in leukemia and lead to better treatment management of the patients.
Practical and economic advantages of choice feeding systems for laying poultry

Poultry can be managed under different feeding systems, depending on the husbandry skills and the feed available. These systems include the following: (1) a complete dry feed offered as a mash ad libitum; (2) the same feed offered as pellets or crumbles ad libitum; (3) a complete feed with added whole grain; (4) a complete wet feed given once or twice a day; (5) a complete feed offered on a restricted basis; (6) choice feeding. Of all these, an interesting alternative to offering complete diets is choice feeding which can be applied on both a small or large commercial scale. Under choice feeding or “free-choice feeding” birds are usually offered a choice between three types of feedstuffs: (a) an energy source (e.g. maize, rice bran, sorghum or wheat); (b) a protein source (e.g. soyabean meal, meat meal, fish meal or coconut meal) plus vitamins and minerals and (c), in the case of laying hens, calcium in granular form (i.e. oyster-shell grit). This system differs from the modern commercial practice of offering a complete diet comprising energy and protein sources, ground and mixed together. Under the complete diet system, birds are mainly only able to exercise their appetite for energy. When the environmental temperature varies, the birds either over- or under-consume protein and calcium. The basic principle behind practising choice feeding with laying hens is that individual hens are able to select from the various feed ingredients on offer and compose their own diet, according to their actual needs and production capacity. A choice-feeding system is of particular importance to small poultry producers in developing countries, such as Indonesia, because it can substantially reduce the cost of feed. The system is flexible and can be constructed in such a way that the various needs of a flock of different breeds, including village chickens, under different climates can be met. The system also offers a more effective way to use home-produced grain, such as maize, and by-products, such as rice bran, in developing countries. Because oyster-shell grit is readily available in developing countries at lower cost than limestone, the use of cheaper oyster-shell grit can further benefit small-holders in these countries. These benefits apart, simpler equipment suffices when designing and building a feed mixer on the farm, and transport costs are lower. If whole (unground) grain is used, the intake of which is accompanied by increased efficiency of feed utilisation, the costs of grinding, mixing and many of the handling procedures associated with mash and pellet preparation are eliminated. The choice feedstuffs can all be offered in the current feed distribution systems, either by mixing the ingredients first or by using a bulk bin divided into three compartments.
New tyrosinases with a broad spectrum of action against contaminants of emerging concern: Insights from in silico analyses

Tyrosinases (EC 1.14.18.1) are type-3 copper metalloenzymes with strong oxidative capacities and low allosteric selectivity to phenolic and non-phenolic aromatic compounds that have been used as biosensors and biocatalysts to mitigate the impacts of environmental contaminants over aquatic ecosystems. However, the widespread use of these polyphenol oxidases is limited by elevated production costs and restricted knowledge on their spectrum of action. Here, six tyrosinase homologs were identified and characterized from the genomes of 4 widespread freshwater ciliates using bioinformatics. Binding energies between 3D models of these homologs and ~1000 contaminants of emerging concern (CECs), including fine chemicals, pharmaceuticals, personal care products, illicit drugs, natural toxins, and pesticides were estimated through virtual screening, suggesting their spectrum of action and potential uses in environmental biotechnology might be considerably broader than previously thought. Moreover, considering that many ciliates, including those caring tyrosinase genes within their genomes are fast-growing unicellular microeukaryotes that can be efficiently culturable at large-scales under in vitro conditions, should be regarded as potential low-cost sources for the production of relevant biotechnological molecules.
Increasing temperature threatens an already endangered coastal dune plant

Climate change has the potential to reduce the abundance and distribution of species and threaten global biodiversity, but it is typically not listed as a threat in classifying species conservation status. This likely occurs because demonstrating climate change as a threat requires data-intensive demographic information. Moreover, the threat from climate change is often studied in specific biomes, such as polar or arid ones. Other biomes, such as coastal ones, have received little attention, despite being currently exposed to substantial climate change effects. We forecast the effect of climate change on the demography and population size of a federally endangered coastal dune plant (Lupinus tidestromii). We use data from a 14-year demographic study across seven extant populations of this endangered plant. Using model selection, we found that survival and fertility measures responded negatively to temperature anomalies. We then produced forecasts based on stochastic individual based population models that account for uncertainty in demographic outcomes. Despite large uncertainties, we predict that all populations will decline if temperatures increase by 1° Celsius. Considering the total number of individuals across all seven populations, the most likely outcome is a population decline of 90%. Moreover, we predict extinction is certain for one of our seven populations. These results demonstrate that climate change will profoundly decrease the current and future population growth rates of this plant, and its chance of persistence. Thus, our study provides the first evidence that climate change is an extinction threat for a plant species classified as endangered under the USA Endangered Species Act.
Glucose clearance and uptake is increased in the SOD1G93A mouse model of amyotrophic lateral sclerosis through an insulin-independent mechanism

Metabolic disturbances are associated with the progression of the neurodegenerative disorder, amyotrophic lateral sclerosis (ALS), however the molecular events that drive energy imbalances in ALS are not completely understood. In this study we aimed to elucidate deficits in energy homeostasis in the SOD1G93A mouse model of ALS. We identified that SOD1G93A mice at mid-symptomatic disease stage have increased oxygen consumption and faster exogenous glucose uptake, despite presenting with normal insulin tolerance. Fasting glucose homeostasis was also disturbed, along with increased liver glycogen stores, despite elevated circulating glucagon, suggesting that glucagon signalling is impaired. Metabolic gene expression profiling of livers indicated that glucose cannot be utilised efficiently in SOD1G93A mice. Overall, we demonstrate that glucose homeostasis and uptake are altered in SOD1G93A mice, which is linked to an increase in insulin-independent glucose uptake and a disturbance in glucagon sensitivity, suggesting glucagon secretion and signalling could be potential therapeutic targets for ALS.
Notes on the genus Aphistogoniulus Silvestri (Diplopoda, Spirobolida, Trigoniulidae)

In this paper the species referable to the genus Aphistogoniulus Silvestri, 1897, are enumerated and their status is briefly discussed. Mystalides Attems, 1910, is a junior subjective synonym. Two species from Madagascar, A. quadridentatus (Attems, 1910) and A. polleni nov. spec. , are described after material in the collection of the Zoological Museum, Amsterdam. The gonopods of a male from the type series of A. hova (De Saussure & Zehntner, 1897) are depicted. The name A. brolemanni nov. spec. is proposed for the material referred to A. hova by Brolemann, 1922.
MiR-124 synergism with ELAVL3 enhances target gene expression to promote neuronal maturity

Neuron-enriched microRNAs (miRNAs), miR-9/9* and miR-124 (miR-9/9*-124), direct cell fate switching of human fibroblasts to neurons when ectopically expressed by repressing anti-neurogenic genes. How these miRNAs function after the onset of the transcriptome switch to a neuronal fate remains unclear. Here, we identified direct targets of miRNAs by Argonaute (AGO) HITS-CLIP as reprogramming cells activate the neuronal program and reveal the role of miR-124 that directly promotes the expression of its target genes associated with neuronal development and function. The mode of miR-124 as a positive regulator is determined by a neuron-enriched RNA-binding protein, ELAVL3, that interacts with AGO and binds target transcripts, whereas the non-neuronal ELAVL1 counterpart fails to elevate the miRNA-target gene expression. Although existing literature indicate that miRNA-ELAVL1 interaction can result in either target gene upregulation or downregulation in a context-dependent manner, we specifically identified neuronal ELAVL3 as the driver for miRNA target gene upregulation in neurons. In primary human neurons, repressing miR-124 and ELAVL3 led to the downregulation of genes involved in neuronal function and process outgrowth, and cellular phenotypes of reduced inward currents and neurite outgrowth. Results from our study support the role of miR-124 promoting neuronal function through positive regulation of its target genes.
Comparison of ultrasonic pachymetry, with a new optical biometry and tono-pachymetry -

The aim of this study was to compare the measurements of central corneal thickness (CCT) using the CT-1P tonopachymetry and AL-Scan optical biometry with those obtained with ultrasound (US) pachymetry. In this prospective study, CCTs were measured in 100 eyes of healthy subjects with the CT-1P tonopachymetry, AL-Scan optical biometry and US pachymetry, and the results were compared. The mean CCT taken with the CT-1P, AL-Scan optical biometry and US pachymetry were 514.1±34.96 µm, 540.00±29.57 µm and 542.53±31.2 µm, respectively. There were high correlations between CCT readings using US pachymetry and AL-Scan optical biometry (r=0.949, p= 0.001), between US pachymetry and CT-1P tonopachymetry (r=0.851, p< 0.001) and between AL-Scan optical biometry and CT-1P tonopachymetry (r=0.859, p< 0.001). Both AL-Scan optical biometry and CT-1P tonopachymetry are quick, non-contact devices that are easy to use and are reliable alternatives to US pachymetry for measuring CCTs.