Miracle-dz/UniFAR-FTUs huggingface dataset:
Deletion of caveolin‐1 attenuates LPS/GalN‐induced acute liver injury in mice

Acute hepatic injury caused by inflammatory liver disease is associated with high mortality. This study examined the role of caveolin‐1 (Cav‐1) in lipopolysaccharide (LPS) and D‐galactosamine (GalN)‐induced fulminant hepatic injury in wild type and Cav‐1‐null (Cav‐1−/−) mice. Hepatic Cav‐1 expression was induced post‐LPS/GalN treatment in wild‐type mice. LPS/GalN‐treated Cav‐1−/− mice showed reduced lethality and markedly attenuated liver damage, neutrophil infiltration and hepatocyte apoptosis as compared to wild‐type mice. Cav‐1 deletion significantly reduced LPS/GalN‐induced caspase‐3, caspase‐8 and caspase‐9 activation and pro‐inflammatory cytokine and chemokine expression. Additionally, Cav‐1−/− mice showed suppressed expression of Toll‐like receptor 4 (TLR4) and CD14 in Kupffer cells and reduced expression of vascular cell adhesion molecule 1 and intercellular adhesion molecule 1 in liver cells. Cav‐1 deletion impeded LPS/GalN‐induced inducible nitric oxide synthase expression and nitric oxide production and hindered nuclear factor‐κB (NF‐κB) activation. Taken together, Cav‐1 regulated the expression of mediators that govern LPS‐induced inflammatory signalling in mouse liver. Thus, deletion of Cav‐1 suppressed the inflammatory response mediated by the LPS‐CD14‐TLR4‐NF‐κb pathway and alleviated acute liver injury in mice.
Meta-analysis of ERP investigations of pain empathy underlines methodological issues in ERP research

Empathy has received considerable attention from the field of cognitive and social neuroscience. A significant portion of these studies used the event-related potential (ERP) technique to study the mechanisms of empathy for pain in others in different conditions and clinical populations. These show that specific ERP components measured during the observation of pain in others are modulated by several factors and altered in clinical populations. However, issues present in this literature such as analytical flexibility and lack of type 1 error control raise doubts regarding the validity and reliability of these conclusions. The current study compiled the results and methodological characteristics of 40 studies using ERP to study empathy of pain in others. The results of the meta-analysis suggest that the centro-parietal P3 and late positive potential component are sensitive to the observation of pain in others, while the early N1 and N2 components are not reliably associated with vicarious pain observation. The review of the methodological characteristics shows that the presence of selective reporting, analytical flexibility and lack of type 1 error control compromise the interpretation of these results. The implication of these results for the study of empathy and potential solutions to improve future investigations are discussed.
Relaxing the stability limit of adaptive control systems in the presence of unmodelled dynamics

ABSTRACT It is known that a closed-loop dynamical system subject to an adaptive controller remains stable either if there does not exist significant unmodelled dynamics or the effect of system uncertainties is negligible. This implies that these controllers cannot tolerate large system uncertainties even when the unmodelled dynamics satisfy a set of conditions. In this paper, we present an adaptive control architecture such that the proposed adaptive controller is augmented with an adaptive robustifying term. Unlike standard adaptive controllers, the proposed architecture allows the closed-loop dynamical system to remain stable in the presence of large system uncertainties when the unmodelled system dynamics satisfy a set of conditions. A numerical example is provided to demonstrate the efficacy of the proposed approach.
HER2 Basolateral versus Circumferential IHC Expression Is Dependent on Polarity and Differentiation of Epithelial Cells in Gastric/GE Adenocarcinoma

Aim Antigenic expression in epithelial cells can be heterogeneous which may pose a problem in immunohistochemical (IHC) analysis of tumor markers, in particular, predictive markers like HER2. Studies have shown that epithelial cells have distinct apical and basolateral domains which are separated by tight junctions. The cell membrane in these two domains has a different composition of macromolecules and hence can have variable antigen expression on immunohistochemistry. In our study, we aimed to investigate this phenomenon of basolateral versus circumferential IHC staining of HER2 in gastric/GE adenocarcinoma. Methods We selected 45 cases of gastric/GE adenocarcinoma and evaluated equal number of specimens (15 each) showing well-differentiated, moderately differentiated, and poorly differentiated morphology. All cases had 3+ HER2 score as per CAP guidelines. HER2-membrane staining pattern in all specimens was analyzed. Results Cases with well-differentiated morphology showed only basolateral or lateral membrane staining in most cases. Poorly differentiated adenocarcinoma samples showed circumferential staining (both basolateral and luminal) in all cases with highly significant p value. Mixed staining pattern was observed in moderately differentiated cases. Diffuse expression of E-cadherin in well-differentiated adenocarcinoma and loss in poorly differentiated tumors were also statistically significant. Conclusion These findings suggest that HER2 in gastric epithelium has a polarized distribution which is maintained by the fence function of tight junctions. With progression to high grade cancer, the glandular structural differentiation in gastric mucosa is lost, along with disruption of tight junctions. This leads to loss of cell polarity and migration of antigens across the membrane.
Sleep in children with epilepsy: the role of maternal knowledge of childhood sleep

Study Objectives To examine maternal knowledge of childhood sleep and its relation to sleep quantity, quality, and variability in a clinic sample of mothers of toddlers and preschool-age children with epilepsy. Methods A total of 112 epileptic children wore a wrist actigraphy to objectively assess daily sleep duration and its variability across 7 days. Mothers completed the Parents' Sleep Knowledge Inventory and Children's Sleep Habits Questionnaire (CSHQ). Multivariate linear regression models were performed to predict CSHQ sleep disturbance scores, daily sleep duration, and daily sleep duration variability in children with epilepsy. Results On average, mothers answered 30.5 per cent of the questions correctly about normal childhood sleep patterns. Only six (5.3%) of the mothers answered half or more of the questions correctly. Mothers more frequently answered "don't know" to questions about dreams, symptoms of sleep-disordered breathing, and adequate amounts of sleep required by children and adolescents. After adjusting for the child's age, gender, bed-sharing, and relevant clinical and epilepsy variables, poorer maternal sleep knowledge was the independent predictor of higher CSHQ sleep disturbance scores and greater intraindividual variability of daily sleep duration in epileptic children (p < 0.05). Conclusions Maternal knowledge about childhood sleep is inadequate and decreased maternal sleep knowledge is associated with poorer and more variable sleep in children with epilepsy. Findings from this study document the need to provide parental education about childhood sleep, particularly emphasizing the recommended sleep duration for children across different developmental stages and addressing the symptoms of sleep disorders commonly comorbid with epilepsy. Trial registration This trial has been registered at www.clinicaltrials. gov (trial name: Sleep Intervention for Pediatric Epilepsy; registration number: NCT02514291).
Scale-Out vs Scale-Up

ARM 64-bit processing has generated enthusiasm to develop ARM-based servers that are targeted for both data centers and supercomputers. In addition to the server-class components and hardware advancements, the ARM software environment has grown substantially over the past decade. Major development ecosystems and libraries have been ported and optimized to run on ARM, making ARM suitable for server-class workloads. There are two trends in available ARM SoCs: mobile-class ARM SoCs that rely on the heterogeneous integration of a mix of CPU cores, GPGPU streaming multiprocessors (SMs), and other accelerators, and the server-class SoCs that instead rely on integrating a larger number of CPU cores with no GPGPU support and a number of IO accelerators. For scaling the number of processing cores, there are two different paradigms: mobile-class SoCs that use scale-out architecture in the form of a cluster of simpler systems connected over a network, and server-class ARM SoCs that use the scale-up solution and leverage symmetric multiprocessing to pack a large number of cores on the chip. In this article, we present ScaleSoC cluster, which is a scale-out solution based on mobile class ARM SoCs. ScaleSoC leverages fast network connectivity and GPGPU acceleration to improve performance and energy efficiency compared to previous ARM scale-out clusters. We consider a wide range of modern server-class parallel workloads to study both scaling paradigms, including latency-sensitive transactional workloads, MPI-based CPU and GPGPU-accelerated scientific applications, and emerging artificial intelligence workloads. We study the performance and energy efficiency of ScaleSoC compared to server-class ARM SoCs and discrete GPGPUs in depth. We quantify the network overhead on the performance of ScaleSoC and show that packing a large number of ARM cores on a single chip does not necessarily guarantee better performance, due to the fact that shared resources, such as last-level cache, become performance bottlenecks. We characterize the GPGPU accelerated workloads and demonstrate that for applications that can leverage the better CPU-GPGPU balance of the ScaleSoC cluster, performance and energy efficiency improve compared to discrete GPGPUs.
Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks

Predicting the number of clock cycles a processor takes to execute a block of assembly instructions in steady state (the throughput) is important for both compiler designers and performance engineers. Building an analytical model to do so is especially complicated in modern x86-64 Complex Instruction Set Computer (CISC) machines with sophisticated processor microarchitectures in that it is tedious, error prone, and must be performed from scratch for each processor generation. In this paper we present Ithemal, the first tool which learns to predict the throughput of a set of instructions. Ithemal uses a hierarchical LSTM--based approach to predict throughput based on the opcodes and operands of instructions in a basic block. We show that Ithemal is more accurate than state-of-the-art hand-written tools currently used in compiler backends and static machine code analyzers. In particular, our model has less than half the error of state-of-the-art analytical models (LLVM's llvm-mca and Intel's IACA). Ithemal is also able to predict these throughput values just as fast as the aforementioned tools, and is easily ported across a variety of processor microarchitectures with minimal developer effort.
Supporting Resident Research Learning in the Workplace: A Rapid Realist Review

Purpose Residents are increasingly expected to engage in practice-based research; however, engagement in research whilst also fulfilling clinical duties is often challenging. Evidence suggests that residents require specific developmental experiences, along with clinical practice, to become effective researchers. The authors therefore conducted a rapid realist review to explore strategies and key mechanisms supporting effective resident research activities in clinical settings. They examined relationships amongst different clinical contexts, learning mechanisms, and research engagement outcomes to provide evidence-based, theory-informed recommendations for improving resident research engagement and extending understandings of workplace learning in health care settings. Method In 2015–2016, the authors used a rapid realist methodology informed by workplace learning theory to review international literature published between January 2005 and December 2015. The review drew upon sources from OVID Medline, ERIC, Embase, and AustHealth. The authors screened articles for eligibility using inclusion criteria and appraised articles using realist review quality criteria. Results The authors included 51 articles in the review. The review process identified three key mechanisms for effective integration and support of resident research engagement, as informed by workplace learning theory: (1) opportunities to engage in practice-informed research supported by longitudinal curricula, (2) guidance by clinician–researchers, and (3) assessing residents’ research readiness and promoting their intentionality for engagement. Conclusions This review extends existing literature and informs workplace-based research engagement strategies for residents whilst demonstrating the applicability of workplace learning theory to improving residents’ research engagement. The authors propose a learning model to support effective resident research engagement through clinical practice.
An overview of properties of Amphora (Acidform) contraceptive vaginal gel

ABSTRACT Introduction: Although only a minority of contracepting women rely solely on spermicides, they may soon be the only ongoing female method available without a prescription in the United States. Spermicides are also combined with other methods for additional pregnancy protection and/or lubrication. Nonoxynol-9 (N-9), the active ingredient in most spermicides, is cytotoxic and may increase risk of transmission of HIV and other sexually transmitted infections, especially in high-risk women. Amphora (previously called Acidform) is a noncytotoxic spermicide composed of a series of generally regarded as safe compounds, which maintains the acidity of the vagina following coitus to immobilize and kill sperm. Amphora is currently Food and Drug Administration-approved as a vaginal lubricant. Amphora is currently being tested in a multicenter Phase III contraceptive trial. Areas covered: This paper describes key properties of Amphora, including its acid-buffering abilities, viscosity, stability, bioadhesiveness, and tolerability. Expert opinion: Amphora is a nontoxic spermicide that maintains the pH within the vagina at levels less than 5.0 for hours, which immobilizes and kills sperm as well as many sexually transmitted pathogens. If the current clinical trial demonstrates safety, efficacy, and tolerability of Amphora as a contraceptive, it would represent a viable alternative to N-9. Its potential as a microbicide warrants further investigation.
Neural-Machine-Translation-Based Commit Message Generation: How Far Are We?

Commit messages can be regarded as the documentation of software changes. These messages describe the content and purposes of changes, hence are useful for program comprehension and software maintenance. However, due to the lack of time and direct motivation, commit messages sometimes are neglected by developers. To address this problem, Jiang et al. proposed an approach (we refer to it as NMT), which leverages a neural machine translation algorithm to automatically generate short commit messages from code. The reported performance of their approach is promising, however, they did not explore why their approach performs well. Thus, in this paper, we first perform an in-depth analysis of their experimental results. We find that (1) Most of the test diffs from which NMT can generate high-quality messages are similar to one or more training diffs at the token level. (2) About 16% of the commit messages in Jiang et al.'s dataset are noisy due to being automatically generated or due to them describing repetitive trivial changes. (3) The performance of NMT declines by a large amount after removing such noisy commit messages. In addition, NMT is complicated and time-consuming. Inspired by our first finding, we proposed a simpler and faster approach, named NNGen (Nearest Neighbor Generator), to generate concise commit messages using the nearest neighbor algorithm. Our experimental results show that NNGen is over 2,600 times faster than NMT, and outperforms NMT in terms of BLEU (an accuracy measure that is widely used to evaluate machine translation systems) by 21%. Finally, we also discuss some observations for the road ahead for automated commit message generation to inspire other researchers.
Spectrally resolved x-ray beam induced current in a single InGaP nanowire

We demonstrate x-ray absorption fine structure spectroscopy (XAFS) detected by x-ray beam induced current (XBIC) in single n+-i-n+ doped nanowire devices. Spatial scans with the 65 nm diameter beam show a peak of the XBIC signal in the middle segment of the nanowire. The XBIC and the x-ray fluorescence signals were detected simultaneously as a function of the excitation energy near the Ga K absorption edge at 10.37 keV. The spectra show similar oscillations around the edge, which shows that the XBIC is limited by the primary absorption. Our results reveal the feasibility of the XBIC detection mode for the XAFS investigation in nanostructured devices.
Do universal adhesives promote bonding to dentin? A systematic review and meta-analysis

Objectives The aims of this study were to conduct a systematic review of the microtensile bond strength (µTBS) of multi-mode adhesives to dentin and to perform a meta-analysis to assess the significance of differences in the µTBS of one of the most commonly used universal adhesives (Scotchbond Universal, 3M ESPE) depending on whether the etch-and-rinse or self-etch mode was used. Materials and Methods An electronic search was performed of MEDLINE/PubMed, ScienceDirect, and EBSCOhost. Laboratory studies that evaluated the µTBS of multi-mode adhesives to dentin using either the etch-and-rinse or self-etch mode were selected. A meta-analysis was conducted of the reviewed studies to quantify the differences in the µTBS of Scotchbond Universal adhesive. Results Only 10 studies fulfilled the inclusion criteria for the systematic review. Extensive variation was found in the restorative materials, testing methodologies, and failure mode in the reviewed articles. Furthermore, variation was also observed in the dimensions of the microtensile testing beams. The meta-analysis showed no statistically significant difference between the etch-and-rinse and self-etch modes for Scotchbond Universal adhesive (p > 0.05). Conclusions Multi-mode ‘universal’ adhesives can achieve substantial bonding to dentin, regardless of the used modes (either etch-and-rinse or self-etch).
MicroRNA‐mediated regulation of T helper type 17/regulatory T‐cell balance in autoimmune disease

T helper type 17 (Th17) cells and regulatory T (Treg) cells are two distinct T‐cell subsets with opposite effects on immune functions. While Th17 cells are a key effector in the immune response and play critical roles in the development of autoimmunity and inflammation, Treg cells orchestrate the overall immune response and maintain peripheral immune tolerance by regulating the activity of the effector T cells. However, the developmental pathways for Th17 and Treg cells are reciprocally interconnected and there is a significant amount of plasticity between them. Disturbed Th17/Treg balance contributes to the development of autoimmune diseases, like experimental autoimmune encephalomyelitis and multiple sclerosis. MicroRNAs (miRNAs) are small non‐coding RNA molecules that post‐transcriptionally regulate gene expression. Recently, emerging evidence demonstrates that miRNAs play an important role in regulating the pathogenesis of autoimmune diseases through the modulation of Th17/Treg balance. This review will provide an overview of the dysregulated miRNAs and their functions in modulating the Th17/Treg balance in autoimmune diseases.
Recreational freshwater fishing drives non-native aquatic species richness patterns at a continental scale

Mapping the geographic distribution of non‐native aquatic species is a critically important precursor to understanding the anthropogenic and environmental factors that drive freshwater biological invasions. Such efforts are often limited to local scales and/or to single species, due to the challenges of data acquisition at larger scales. Here, we map the distribution of non‐native freshwater species richness across the continental United States and investigate the role of human activity in driving macroscale patterns of aquatic invasion.
GATE, a game theory approach on traffic volume aware channel width adaptation for WBAN medical applications

Traditional single channel communication in Wireless Sensor Networks (WSN) offers limited network throughput due to frequent interferences and congestion caused by concurrent transmissions in the same neighborhood. On the one hand, successful packet delivery requires mostly multiple retransmissions because of frequent collisions which also uses much battery. On the other hand, concurrent transmissions over multiple channels not only offer better network throughput and delays, but also reduce power consumption as packet collisions are minimized or eliminated depending upon the efficiency of the concerned channel assignment scheme. This may ensure QoS requirements of transmissions demanding high bandwidth and those that are delay sensitive such as in the case of wireless body area networks. In this paper, we consider a multiple channel wireless body area networks and propose GATE, a theoretical game approach to adapt the channel bandwidth to the volume traffic requirement. In this way, medical video and audio traffics which are likely to be much bandwidth consumer are mainly considered using their priority classes. The simulation results show good performances of the proposed system in terms of increasing throughput and significantly reducing delay and energy consumption.
Decellularized sciatic nerve matrix as a biodegradable conduit for peripheral nerve regeneration

The use of autologous nerve grafts remains the gold standard for treating nerve defects, but current nerve repair techniques are limited by donor tissue availability and morbidity associated with tissue loss. Recently, the use of conduits in nerve injury repair, made possible by tissue engineering, has shown therapeutic potential. We manufactured a biodegradable, collagen-based nerve conduit containing decellularized sciatic nerve matrix and compared this with a silicone conduit for peripheral nerve regeneration using a rat model. The collagen-based conduit contains nerve growth factor, brain-derived neurotrophic factor, and laminin, as demonstrated by enzyme-linked immunosorbent assay. Scanning electron microscopy images showed that the collagen-based conduit had an outer wall to prevent scar tissue infiltration and a porous inner structure to allow axonal growth. Rats that were implanted with the collagen-based conduit to bridge a sciatic nerve defect experienced significantly improved motor and sensory nerve functions and greatly enhanced nerve regeneration compared with rats in the sham control group and the silicone conduit group. Our results suggest that the biodegradable collagen-based nerve conduit is more effective for peripheral nerve regeneration than the silicone conduit.