Miracle-dz/UniFAR-FTUs huggingface dataset:
Cholesterol crystallization within hepatocyte lipid droplets and its role in murine NASH[S]

We recently reported that cholesterol crystals form in hepatocyte lipid droplets (LDs) in human and experimental nonalcoholic steatohepatitis. Herein, we assigned WT C57BL/6J mice to a high-fat (15%) diet for 6 months, supplemented with 0%, 0.25%, 0.5%, 0.75%, or 1% dietary cholesterol. Increasing dietary cholesterol led to cholesterol loading of the liver, but not of adipose tissue, resulting in fibrosing steatohepatitis at a dietary cholesterol concentration of ≥0.5%, whereas mice on lower-cholesterol diets developed only simple steatosis. Hepatic cholesterol crystals and crown-like structures also developed at a dietary cholesterol concentration ≥0.5%. Crown-like structures consisted of activated Kupffer cells (KCs) staining positive for NLRP3 and activated caspase 1, which surrounded and processed cholesterol crystal-containing remnant LDs of dead hepatocytes. The KCs processed LDs at the center of crown-like structures in the extracellular space by lysosomal enzymes, ultimately transforming into lipid-laden foam cells. When HepG2 cells were exposed to LDL cholesterol, they developed cholesterol crystals in LD membranes, which caused activation of THP1 cells (macrophages) grown in coculture; upregulation of TNF-alpha, NLRP3, and interleukin 1beta (IL1β) mRNA; and secretion of IL-1beta. In conclusion, cholesterol crystals form on the LD membrane of hepatocytes and cause activation and cholesterol loading of KCs that surround and process these LDs by lysosomal enzymes.
Translational autoregulation of BZW1 and BZW2 expression by modulating the stringency of start codon selection

The efficiency of start codon selection during ribosomal scanning in eukaryotic translation initiation is influenced by the context or flanking nucleotides surrounding the AUG codon. The levels of eukaryotic translation initiation factors 1 (eIF1) and 5 (eIF5) play critical roles in controlling the stringency of translation start site selection. The basic leucine zipper and W2 domain-containing proteins 1 and 2 (BZW1 and BZW2), also known as eIF5-mimic proteins, are paralogous human proteins containing C-terminal HEAT domains that resemble the HEAT domain of eIF5. We show that translation of mRNAs encoding BZW1 and BZW2 homologs in fungi, plants and metazoans is initiated by AUG codons in conserved unfavorable initiation contexts. This conservation is reminiscent of the conserved unfavorable initiation context that enables autoregulation of EIF1. We show that overexpression of BZW1 and BZW2 proteins enhances the stringency of start site selection, and that their poor initiation codons confer autoregulation on BZW1 and BZW2 mRNA translation. We also show that overexpression of these two proteins significantly diminishes the effect of overexpressing eIF5 on stringency of start codon selection, suggesting they antagonize this function of eIF5. These results reveal a surprising role for BZW1 and BZW2 in maintaining homeostatic stringency of start codon selection, and taking into account recent biochemical, genetic and structural insights into eukaryotic initiation, suggest a model for BZW1 and BZW2 function.
Associations between self‐reported sleep measures and dietary behaviours in a large sample of Australian school students (n = 28,010)

This study examined the associations between self‐reported sleep timing and quality, and the frequency of breakfast and junk food consumption in 28,010 Australian school students (mean ± SD age = 13.3 ± 1.2 years, 51% male). After controlling for age, sex and socioeconomic status, regression analyses revealed that the odds of missing breakfast were significantly higher in children who reported poor sleep or later bedtimes, while the odds of junk food consumption were significantly higher in children reporting later weeknight bedtimes (p < 0.001). These findings suggest that sleep timing and quality influence the dietary choices of adolescents.
How users’ Internet experience affects the adoption of mobile payment: a mediation model

ABSTRACT Mobile payment becomes a convenient way to complete transactions due to the increasing popularity of mobile devices and the maturity of related technologies. Users’ experience of using computers and the Internet in financial activities largely affects their intention to use mobile payment. Combining the Technology Acceptance Model and Innovation Diffusion Theory, we examined the mediating effect of five factors, that is, perceived usefulness, perceived ease of use, compatibility, risk, and privacy concern, in the relationship between Internet experience and the adoption of mobile payment. Data from 922 mobile users supported the partial mediating effects of the five factors.
Auto-categorization of medical concepts and contexts

In healthcare, information extraction is important in order to identify conceptual knowledge as a category of medical concepts from a large number of unstructured and semi-structured corpora. Category describes how medical concepts are fundamentally separated from each other to represent their conceptual knowledge in the corpus. In this paper, we focus on identifying the category of medical concepts and contexts which describe the subjective and the conceptual information of the medical corpus. To recognize the medical concept and assign their category, we employ our previously developed WordNet of Medical Event (WME 2.0) domain-specific lexicon. The lexicon provides medical concepts and their affinity, gravity, polarity scores, similar sentiment words, and sentiment features, help to develop the category assignment system. The identified categories for the concepts are diseases, drugs, symptoms, human_anatomy, and miscellaneous medical terms (MMT), which all refer the broadest fundamental classes of medical concepts. Therefore, the assigned categories of medical concepts used to build the category assignment system for the medical context. The proposed system allows extracting eleven types of pairbased categories as disease-symptom, disease-drug, and disease-MMT of contexts. To validate the categorization system for medical concepts and contexts, we have employed widely used supervised machine learning classifiers namely Naïve Bayes and Logistic Regression in the presence of WME 2.0 lexicon. The two classifiers provide F-scores of 0.81 and 0.86 for the concepts and contexts categorization systems, respectively.
A comparison of attitudes towards stuttering of non-stuttering preschoolers in the United States and Turkey

Background and objectives Extensive research documents ubiquitous negative attitudes towards stuttering, but when and how they develop is unclear. This non-experimental, comparative study examined US and Turkish preschoolers to explore the origin of stuttering attitudes cross-culturally. Method The authors compared stuttering attitudes of 28 US and 31 Turkish non-stuttering preschoolers on English and Turkish versions of experimental prototypes of the newly developed Public Opinion Survey on Human Attributes–Stuttering/Child (POSHA–S/Child). Children first watched a short video of two stuttering avatar characters and then answered oral questions about stuttering. Parents completed a demographic questionnaire. Differences in the US and Turkish POSHA–S/Child means were calculated using the Mann–Whitney U test. Results Attitudes of the US and Turkish children were remarkably similar. Children rated most of the items negatively but also rated some items as neutral or positive. They held relatively more negative attitudes towards traits and personalities of children who stutter yet relatively more positive attitudes towards stuttering children’s potential. Conclusion Stuttering attitudes in children appear to be partly independent of culture.
Direct interaction of Ikaros and Foxp1 modulates expression of the G protein-coupled receptor G2A in B-lymphocytes and acute lymphoblastic leukemia

Ikaros and Foxp1 are transcription factors that play key roles in normal lymphopoiesis and lymphoid malignancies. We describe a novel physical and functional interaction between the proteins, which requires the central zinc finger domain of Ikaros. The Ikaros-Foxp1 interaction is abolished by deletion of this region, which corresponds to the IK6 isoform that is commonly associated with high-risk acute lymphoblastic leukemia (ALL). We also identify the Gpr132 gene, which encodes the orphan G protein-coupled receptor G2A, as a novel target for Foxp1. Increased expression of Foxp1 enhanced Gpr132 transcription and caused cell cycle changes, including G2 arrest. Co-expression of wild-type Ikaros, but not IK6, displaced Foxp1 binding from the Gpr132 gene, reversed the increase in Gpr132 expression and inhibited G2 arrest. Analysis of primary ALL samples revealed a significant increase in GPR132 expression in IKZF1-deleted BCR-ABL negative patients, suggesting that levels of wild-type Ikaros may influence the regulation of G2A in B-ALL. Our results reveal a novel effect of Ikaros haploinsufficiency on Foxp1 functioning, and identify G2A as a potential modulator of the cell cycle in Ikaros-deleted B-ALL.
Magnetic resonance imaging connectivity for the prediction of seizure outcome in temporal lobe epilepsy

Currently, approximately 60–70% of patients with unilateral temporal lobe epilepsy (TLE) remain seizure‐free 3 years after surgery. The goal of this work was to develop a presurgical connectivity‐based biomarker to identify those patients who will have an unfavorable seizure outcome 1‐year postsurgery.
One-Bit compressive sampling with time-varying thresholds for multiple sinusoids

Wide-band spectral sensing is a challenging task that will be required in future cognitive radio and radar applications. Recent research has shown that sampling using only one-bit of amplitude precision can be realized at an extremely high rate [1] in an affordable manner. In this work, one-bit sampling using time-varying thresholds is considered for line spectral estimation. The time-varying thresholds allow for amplitude estimation. A novel one-bit RELAX algorithm is developed for multi-tone parameter estimation. This algorithm is shown to have excellent performance via a numerical example.
The Impact of Memory T Cells on Rejection and the Induction of Tolerance

Accumulating evidence suggests that alloreactive memory T cells (Tm) may be generated in transplant recipients that have not previously been exposed to alloantigen through mechanisms such as cross-reactivity and homeostatic proliferation. The presence of Tm correlates with both acute and chronic rejection episodes and, furthermore, may be responsible for the failure to induce tolerance in large animal and clinical settings. A clearer understanding of how Tm function and their requirements to mount an effective response to alloantigen will be key to further attempts to translate tolerance induction protocols from the experimental setting to the clinic.
Device-to-Device Communications Enabled Energy Efficient Multicast Scheduling in mmWave Small Cells

To keep pace with the rapid growth of mobile traffic demands, dense deployment of small cells in millimeter wave (mmWave) bands has become a promising candidate for next-generation wireless communication systems. With a greatly increased data rate from huge bandwidth of mmWave communications, energy consumption should be mitigated for higher energy efficiency. Due to content popularity, many content-based mobile applications can be supported by the multicast service. mmWave communications exploit directional antennas to overcome high path loss, and concurrent transmissions can be enabled for better multicast service. On the other hand, device-to-device (D2D) communications in physical proximity should be exploited to improve multicast performance. In this paper, we propose an energy-efficient multicast scheduling scheme, referred to as EMS, which utilizes both D2D communications and concurrent transmissions to achieve high energy efficiency. In EMS, a D2D path planning algorithm establishes multi-hop D2D transmission paths, and a concurrent scheduling algorithm allocates the links on the D2D paths into different pairings. Then, the transmission power of links is adjusted by the power control algorithm. Furthermore, we theoretically analyze the roles of D2D communications and concurrent transmissions in reducing energy consumption. Extensive simulations under various system parameters demonstrate the superior performance of EMS in terms of energy consumption compared with the state-of-the-art schemes. Furthermore, we also investigate the choice of the interference threshold to optimize network performance.
Design of Service Net based Correctness Verification Approach for Multimedia Conferencing Service Orchestration

Multimedia conferencing is increasingly becoming a very important and popular application over Internet. Due to the complexity of asynchronous communications and handle large and dynamically concurrent processes for multimedia conferencing, which confront relevant challenge to achieve sufficient correctness guarantees, and supporting the effective verification methods for multimedia conferencing services orchestration is an extremely difficult and challenging problem. In this paper, we firstly present the Business Process Execution Language (BPEL) based conferencing service orchestration, and mainly focus on the service net based correction verification approach for multimedia conferencing services orchestration, which can automatically translated the BPEL based service orchestration into a corresponding Petri net model with the Petri Net Markup Language (PNML), and also present the BPEL service net reduction rules and multimedia conferencing service orchestration correction verification algorithms. We perform the correctness analysis and verification using the service net properties as safeness, reachability and deadlocks, and also provide an automated support tool for the formal analysis and soundness verification for the multimedia conferencing services orchestration scenarios. Finally, we give the comparison and evaluations.
The advanced glycation end‐product Nϵ‐carboxymethyllysine promotes progression of pancreatic cancer: implications for diabetes‐associated risk and its prevention

Diabetes is an established risk factor for pancreatic cancer (PaC), together with obesity, a Western diet, and tobacco smoking. The common mechanistic link might be the accumulation of advanced glycation end‐products (AGEs), which characterizes all of the above disease conditions and unhealthy habits. Surprisingly, however, the role of AGEs in PaC has not been examined yet, despite the evidence of a tumour‐promoting role of receptor for advanced glycation end‐products (RAGE), the receptor for AGEs. Here, we tested the hypothesis that AGEs promote PaC through RAGE activation. To this end, we investigated the effects of the AGE Nϵ‐carboxymethyllysine (CML) in human pancreatic ductal adenocarcinoma (PDA) cell lines and in a mouse model of Kras‐driven PaC interbred with a bioluminescent model of proliferation. Tumour growth was monitored in vivo by bioluminescence imaging and confirmed by histology. CML promoted PDA cell growth and RAGE expression, in a concentration‐dependent and time‐dependent manner, and activated downstream tumourigenic signalling pathways. These effects were counteracted by RAGE antagonist peptide (RAP). Exogenous AGE administration to PaC‐prone mice induced RAGE upregulation in pancreatic intraepithelial neoplasias (PanINs) and markedly accelerated progression to invasive PaC. At 11 weeks of age (6 weeks of CML treatment), PaC was observed in eight of 11 (72.7%) CML‐treated versus one of 11 (9.1%) vehicle‐treated [control (Ctr)] mice. RAP delayed PanIN development in Ctr mice but failed to prevent PaC promotion in CML‐treated mice, probably because of competition with soluble RAGE for binding to AGEs and/or compensatory upregulation of the RAGE homologue CD166/ activated leukocyte cell adhesion molecule, which also favoured tumour spread. These findings indicate that AGEs modulate the development and progression of PaC through receptor‐mediated mechanisms, and might be responsible for the additional risk conferred by diabetes and other conditions characterized by increased AGE accumulation. Finally, our data suggest that an AGE reduction strategy, instead of RAGE inhibition, might be suitable for the risk management and prevention of PaC. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Modified Classification of Posterior Malleolus Fracture of Ankle

1.Introduction Objective : Our study aims to classify posterior malleolar fractures (PMF) based on preoperative computed tomography (CT), initial injury radiographs, and intraoperative image intensifier screening. Design: Retrospective study Setting: Two hospitals: (1) Level I trauma cent re and (2) Level II rural trauma center. Patients : Between June 2013 and March 2015, 50 consecutive patients with bi-or trimalleolar ankle fractures with one or more posterior fragments or a posterior inferior tibiofibular ligament (PITFL) injury who underwent operative fixation were selected for the study. 2.Material and Methods : Preoperative and intraoperative image intensifier screening and CT were reviewed to determine stability of the ankle joint and classify the PMF. Of 50 patients, 34 underwent CT. We also noted the type of operative fixation and whether the PMF was fixed. 3.Results: The 34 fractures with CT scans were categorised into the following: Type I fracture is an isolated PMF. Type II fracture is either a bi- or trimalleolar fracture associated with a Weber B or C fracture pattern. These are further classified depending on the presence or absence of syndesmotic injury. Type III PMF is associated with an ipsilateral tibial diaphyseal fracture. This is further subdivided based on sagittal or coronal plane instability. All the above categories are further subdivided, as per our CT-guided classification mentioned in the text. 4.Conclusion: The ankle stability on initial injury radiographs, intraoperative image intensifier screening, and preoperative CT is critical for classification and management of PMF, regardless of the fragment size.
Behavioural State Machines: Programming Modular Agents

Different application domains require different knowledge representation techniques. Agent designers should therefore be able to easily exploit benefits of various knowledge representation technologies in a single agent system. I describe here an agent programming framework of Behavioural State Machines, with Jazzyk, an implemented programming language interpreter for BSM. The presented framework draws a strict distinction between a knowledge representational and a behavioural level of an agent program. It supports a high degree of modularity w.r. t. employed KR technologies and at the same time provides a clear and concise semantics.
Study of wavelet-based performance enhancement for motor imagery brain-computer interface

To enhance the reliability of motor imagery based brain-computer interface, we present a study that considers subject-based optimization of feature extraction and classification. In particular, wavelet-based feature extraction performed on different bands was optimized over available selections of wavelet family, length and number of decomposition levels. Likewise, the classification step considers three general families of classifiers whose parameters are optimized in a similar manner. Such optimization was performed for each subject whereby processing parameters are selected based on the best performance obtained in the training session. We report the results obtained from applying this approach to the BCI competition 2008 dataset 2b (Graz) and demonstrate that such optimization provides results that outperform previous methods.
MAP–Based Framework for Segmentation of MR Brain Images Based on Visual Appearance and Prior Shape

We propose a new MAP-based technique for the unsupervised segmentation of different brain structures (white matter, gray matter, etc.) from T1-weighted MR brain images. In this paper, we follow a procedure like most conventional approaches, in which T1-weighted MR brain images and desired maps of regions (white matter, gray matter, etc.) are modeled by a joint Markov-Gibbs Random Field model (MGRF) of independent image signals and interdependent region labels. However, we specifically focus on the most accurate model identification that can be achieved. The proposed joint MGRF model accounts for the following three descriptors: i) a 1st-order visual appearance descriptor(empirical distribution of signal intensity), ii) a 3D probabilistic shape prior, and iii) a 3D spatially invariant 2nd-order homogeneity descriptor. To better specify the 1st-order visual appearance descriptor, each empirical distribution of signals is precisely approximated by a Linear Combination of Discrete Gaussians (LCDG) having both positive and negative components. The 3D probabilistic shape prior is learned using a subset of 3D co-aligned training T1-weighted MR brain images. The 2nd-order homogeneity descriptor is modeled by a 2nd-order translation and rotation invariant MGRF of 3D T1-weighted MR brain region labels with analytically estimated potentials. The initial segmentation, based on a 1st-order visual appearance and 3D probabilistic shape, is then iteratively refined using a 3D MGRF model with analytically estimated potentials. Experiments on twelve 3D T1-weighted MR brain images confirm the high accuracy of the proposed approach.
Optical limiting phenomena of carbon nanoparticles prepared by laser ablation in liquids

We report optical limiting properties of carbon nanoparticles, which were made in liquids by laser ablation of a bulk carbon target. The carbon nanoparticles were analyzed with micro-Raman spectroscopy, UV-Vis spectroscopy and Electron microscopy. Optical limiting responses towards 532-nm wavelength were measured with a 7-ns Nd:YAG laser. Nanoparticle size and laser pulse repetition rate effects on optical limiting behaviour were studied. A model was proposed to explain the physical origin of this nonlinear optical process. This work can provide useful information for designing carbon nanoparticle based optical limiters.
Distorted Replicas: Intelligent Replication Schemes to Boost I/O Throughput in Document-Stores

NoSQL databases commonly use an aggregate data model, where data that is expected to be accessed together is packed in a single clump and stored in a single node. This aggregate-orientation is essential to running on a cluster as it avoids cross-nodes joins and writes. An important downside of the aggregate data model is that it severely limits the ways data can be efficiently explored and processed, especially as NoSQL systems are being increasingly used by complex datadriven applications, mixing heterogeneous data access patterns.Replication is ubiquitous in NoSQL systems. In this work we propose a new replication scheme termed distorted replicas. Rather than being physically identical, distorted replicas are logically identical: they restructure replicated data in different ways, but keep the fundamental property of being constructible from one another. By doing so, distorted replicas provide new ways for exploring data, while still ensuring high availability. Experiments conducted in this paper show that even basic distortion schemes allow substantial performance improvements.