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Edge computing (EC) can overcome several limitations of cloud computing. In the EC environment, a service provider can deploy its application instances on edge servers to serve users with low latency. Given a limited budget K for deploying applications in a particular geographical area, some approaches have been proposed to achieves various optimization objectives, e.g., to maximize the servers' coverage, to minimize the average network latency, etc. However, the robustness of the services collectively delivered by the service provider's applications deployed on the edge servers has not been considered at all. This is a critical issue, especially in the highly distributed, dynamic and volatile EC environment. We make the first attempt to tackle this challenge. Specifically, we formulate this Robustness-oriented Edge Application Deployment(READ) problem as a constrained optimization problem and prove its NP-hardness. Then, we provide an integer programming based approach READ-O for solving it precisely, and an approximation algorithm READ-A for efficiently finding near-optimal solutions to large-scale problems. READ-A's approximation ratio is not worse than K/2, which is constant regardless of the total number of edge servers. Evaluation of the widely-used real-world dataset against five representative approaches demonstrates that our approaches can solve the READ problem effectively and efficiently.

Influenza A viruses possess a high antigenic shift, and the approved anti-influenza drugs are extremely limited, which makes the development of novel anti-influenza drugs for the clinical treatment and prevention of influenza outbreaks imperative. Herein, we report a series of novel aryl benzoyl hydrazide analogs as potent anti-influenza agents. Particularly, analogs

The rapid growth of mobile apps has significantly promoted the use of third-party libraries in mobile app development. However, mobile app developers are now facing the challenge of finding useful third-party libraries for improving their apps, e.g., to enhance user interfaces, to add social features, etc. An effective approach is to leverage collaborative filtering (CF) to predict useful third-party libraries for developers. We employed Matrix Factorization (MF) approaches - the classic CF-based prediction approaches - to make the predictions based on a total of 31,432 Android apps from Google Play. However, our investigation shows that there is a significant lack of diversity in the prediction results - a small fraction of popular third-party libraries dominate the prediction results while most other libraries are ill-served. The low diversity in the prediction results limits the usefulness of the prediction because it lacks novelty and serendipity which are much appreciated by mobile app developers. In order to increase the diversity in the prediction results, we designed an innovative MF-based approach, namely LibSeek, specifically for predicting useful third-party libraries for mobile apps. It employs an adaptive weighting mechanism to neutralize the bias caused by the popularity of third-party libraries. In addition, it introduces neighborhood information, i.e., information about similar apps and similar third-party libraries, to personalize the predictions for individual apps. The experimental results show that LibSeek can significantly diversify the prediction results, and in the meantime, increase the prediction accuracy.

The Late Ordovician-Early Silurian period witnessed the second largest Phanerozoic mass extinction, Hirnantian glaciation and volcanic events. Wufeng, Guanyinqiao and Longmaxi formations were developed in South China across the Ordovician-Silurian transition.To infer the weathering conditions, provenance, tectonic setting of the source area in western South China during this period, we measured the mineralogical and geochemical characteristics of 42 samples of Wufeng-Longmaxi formations taken from Xindi No. 1 well, south west of Sichuan Basin. These shales and argillaceous limestones mainly consist of quartz, clay mineral, carbonate, feldspar, and minor amounts of pyrite. Geochemically, the rocks from three formations are enriched in CaO and MgO and slightly depleted in SiO2, Al2O3 and K2O. Chondrite-normalized rare earth elements (REE) patterns display a negative Eu anomaly, a slight enrichment in LREE and a flat HREE. Paleoweathering indices (CIA and PIA) and Th/U ratios indicate that the sediments experienced moderate-intense to weak chemical weathering in the source area. CIA values of the lower Wufeng Formation range from 64.88 to 70.88, indicating a warm and humid climate. Upward the CIA values on the top of Wufeng Formation decrease from 62.56 to 62.93, the CIA values of the Guanyinqiao and lowest Longmaxi formation are consistently low values (58.48-67.12) , suggesting a cold and dry climate which is consistent with Gondwana glaciation in Hirnantian period. Geochemical discrimination diagrams revealed that the rocks of the three formations were derived from felsic igneous source rocks and deposited in an active continental margin setting.

The spectrum and size controllable synthesis of gold nanorods is of great value for their widely applicable aspect ratio dependence of anisotropic surface plasmon resonance. Herein, 1,7-dihydroxynaphthalene with a relatively strong reducibility is proposed as a reducing agent for the controllable synthesis of gold nanorods. The result indicated that gold nanorods with high monodispersity, high shape yield, relatively small diameters, and maximum plasmon resonance wavelength of above 1000 nm can be acquired. More importantly, by virtue of the reducing agent used, fine and precise controls over the plasmon wavelength and diameter of the rod can be achieved

This study aims to develop a systematic overview and meta-analysis protocol to evaluate the efficacy and safety of oral traditional Chinese medicine decoction for chronic rhinosinusitis undergoing endoscopic sinus surgery.

The inherent compliance of soft materials imbues robots, generally referred to as soft robots, with particular advantages in producing adaptive and safe interactions. However, the mainstream design paradigms of soft robots have been focused on pursuing large free motions only, usually at the expense of greatly decreased stiffness, leading to limited capability of withstanding external loads in interactive scenarios. There is a pressing need to incorporate the interaction specifications at the design stage to embody soft robots with not only proper deformability but equally importantly, considerable stiffness to perform complex tasks in practical applications. Here, inspired by the dexterity of human hands, we propose a computational design framework for soft grippers with a focus on improving their interaction performance in power grasping or precision grasping mode. The design paradigm rests on attaching a relatively stiffer skeleton layer to the parametric pneumatic networks based actuator which is widely used due to the geometric advantage, and the skeleton layout is designed for customized interaction conditions by a level set based topology optimization approach. As expected, the optimized skeleton layouts exhibit specified structural features highly relevant to the predefined concentrated loads for precision grip or distributed loads for power grip, which physically implies the compromise between deformability and stiffness. Since the interaction forces are difficult to measure in situ, we devise power and precision grasping scenarios and evaluate the critical actuation pressure of the object’s falling instead. The experiments qualitatively demonstrate the superiority of each specified design. This work represents an initial step toward the rational design for interaction in soft robots.

The nutritional selenium (Se) has been demonstrated to have health-boosting effects on fish. However, its effect on fish energy metabolism remains unclear. This study explores the effect and underlying mechanism of the action of nutritional Se on energy metabolism in fish. Rainbow trout (Oncorhynchus mykiss) were fed a basal diet (0 mg Se/kg diet) and a diet containing an already established nutritional Se level (2 mg Se/kg diet, based on Se-yeast) for 30 days. After the feeding experiment, the plasma and liver biochemical profiles and liver transcriptome were analyzed. The results showed that the present nutritional level of Se significantly increased liver triglyceride, total cholesterol, and plasma total cholesterol contents (P < 0.05) compared with the control. Transcriptome analysis showed that 336 and 219 genes were significantly upregulated and downregulated, respectively. Gene enrichment analysis showed that many differentially expressed genes (DEGs) were associated with lipid metabolism pathways (fatty acid biosynthesis, fatty acid elongation, and unsaturated fatty acid biosynthesis), carbohydrate metabolism pathways (glycolysis, the pentose phosphate pathway, and the citrate cycle), and the oxidative phosphorylation pathway. Real-time quantitative PCR (Q-PCR) validation results showed that the expression profiles of 15 genes exhibited similar trends both in RNA sequencing (RNA-seq) and Q-PCR analysis. These results reveal that optimum dietary Se activates glucose catabolic processes, fatty acid biosynthetic processes, and energy production and hence produces higher liver lipid content. This study concludes that the previously established level of nutritional Se (Se-yeast) (2 mg/kg diet, fed basis) for rainbow trout promotes energy storage in the liver, which may benefit fish growth to some extent.

Macrocyclic peptides have the potential to address intracellular protein–protein interactions (PPIs) of high value therapeutic targets that have proven largely intractable to small molecules. Here, we report broadly applicable lessons for applying this modality to intracellular targets and specifically for advancing chemical matter to address KRAS, a protein that represents the most common oncogene in human lung, colorectal and pancreatic cancers yet is one of the most challenging targets in human disease. Specifically, we focused on KRpep-2d, an arginine-rich KRAS-binding peptide with a disulfide-mediated macrocyclic linkage and a protease-sensitive backbone. These latter redox and proteolytic labilities obviated cellular activity. Extensive structure–activity relationship studies involving macrocyclic linker replacement, stereochemical inversion, and backbone α-methylation, gave a peptide with on-target cellular activity. However, we uncovered an important generic insight – the arginine-dependent cell entry mechanism limited its therapeutic potential. In particular, we observed a strong correlation between net positive charge and histamine release in an ex vivo assay, thus making this series unsuitable for advancement due to the potentially fatal consequences of mast cell degranulation. This observation should signal to researchers that cationic-mediated cell entry – an approach that has yet to succeed in the clinic despite a long history of attempts – carries significant therapy-limiting safety liabilities. Nonetheless, the cell-active molecules identified here validate a unique inhibitory epitope on KRAS and thus provide valuable molecular templates for the development of therapeutics that are desperately needed to address KRAS-driven cancers – some of the most treatment-resistant human malignancies., Targeting undruggable intracellular proteins with peptides: novel on-target macrocyclic peptide inhibitors of KRAS with broad inhibition of proliferation of multiple KRAS-dependent cancer cell lines.

The cultural heritage (CH) sector has always been looking for preeminent ways to improve visitors’ interactions with their collections through interactive technologies such as applications and webs...

Dielectric elastomers (DEs) are promising soft actuators for use in soft material robots, due to their considerable voltage-induced strain. The actuator's behavior is highly nonlinear due to the complex interplay between the DE, the support structure, and the input electric field, making it a big challenge to automatically design dielectric elastomer actuators (DEAs). Here, in this article, we present an integrated design strategy for planar DEAs, aiming to realize their full potential. To endow the actuator module with the maximal actuation strain, we carry out dimensionless analysis to identify the key design variables, develop a fast finite element analysis model, and thoroughly investigate how the geometric structuring and the material prestretch tailor the voltage-induced deformation. We also provide a fabrication strategy by patterning the compliant electrodes on the DE membrane and then directly printing the support structure made of thermoplastic polyurethane. The experiments show that the optimized actuator obtains a remarkable nominal strain up to 38.6%. We also characterize the dynamic performance of the optimized actuator, evaluate its energy density and power density, and develop a soft locomotion robot that can crawl through a confined tunnel, at a fast moving speed up to 0.17 body length/s.

Aims There is an emerging interest in elucidating the natural history and prognosis for patients with heart failure with reduced ejection fraction (HFrEF) in whom left ventricular ejection fraction (LVEF) subsequently improves. The characteristics and outcomes were compared between heart failure with recovered ejection fraction (HFrecEF) and persistent HFrEF. Methods and results This is a retrospective study of adults who underwent at least two echocardiograms 3 months apart between 1 November 2015 and 31 October 2019 with an initial diagnosis of HFrEF. The subjects were divided into HFrecEF group (second LVEF > 40%, ≥10% absolute improvement in LVEF) and persistent HFrEF group (20% subgroups. The primary outcomes were all‐cause mortality and rehospitalization. A total of 1160 HFrEF patients were included [70.2% male, mean (standard deviation) age: 62 ± 13 years]. On the second echocardiogram, 284 patients (24.5%) showed HFrecEF and 876 patients (75.5%) showed persistent HFrEF. All‐cause mortality was identified in 23 (8.10%) HFrecEF and 165 (18.84%) persistent HFrEF, whilst 76 (26.76%) and 426 (48.63%) showed rehospitalizations, respectively. Survival analysis showed that the persistent HFrEF subgroup experienced a significantly higher mortality at 12 and 24 months and a higher hospitalization at 12, 24, 48, and more than 48 months following discharge. Multivariate Cox regression showed that persistent HFrEF had a higher risk of all‐cause mortality [hazard ratio (HR) 2.30, 95% confidence interval (CI) 1.49–3.56, P = 0.000] and rehospitalization (HR 1.85, 95% CI 1.45–2.36, P = 0.000) than the HFrecEF group. Subgroup analysis showed that the LVEF ≥ 20% improvement subgroup had lower rates of adverse outcomes compared with those with less improvement of 10–20%. Conclusions Heart failure with recovered ejection fraction is a distinct HF phenotype with better clinical outcomes compared with those with persistent HFrEF. HFrecEF patients have a relatively better short‐term mortality at 24 months but not thereafter.

The number of Web services on the Internet has been growing rapidly. This has made it increasingly difficult for users to find the right services from a large number of functionally equivalent candidate services. Inspecting every Web service for their quality value is impractical because it is very resource consuming. Therefore, the problem of quality prediction for Web services has attracted a lot of attention in the past several years, with a focus on the application of the Matrix Factorization (MF) technique. Recently, researchers have started to employ user similarity to improve MF-based prediction methods for Web services. However, none of the existing methods has properly and systematically addressed two of the major issues: 1) retrieving appropriate neighborhood information, i.e., similar users and services; 2) utilizing full neighborhood information, i.e., both users’ and services’ neighborhood information. In this paper, we propose CNMF, a c overing-based quality prediction method for Web services via n eighborhood-aware m atrix f actorization. The novelty of CNMF is twofold. First, it employs a covering-based clustering method to find similar users and services, which does not require the number of clusters and cluster centroids to be prespecified. Second, it utilizes neighborhood information on both users and services to improve the prediction accuracy. The results of experiments conducted on a real-world dataset containing 1,974,675 Web service invocation records demonstrate that CNMF significantly outperforms eight existing quality prediction methods, including two state-of-the-art methods that also utilize neighborhood information with MF.

The nonlinear optical properties of emerging metal halide perovskites (MHP) materials are sufficiently intriguing that this topic has become the hotspots in the realm of material science. Hence, we investigate the third-order nonlinear optical properties of CsPbBrx/I

NiMoS supported on ZSM-5 with different Si/Al ratio, crystallite size and pore structure was prepared by incipient impregnation method and applied in 1, 3, 5-trimethylbenzene (1, 3, 5-TMB) hydrodealkylation (HDAK). The physicochemical properties of samples were characterized by XRD, FTIR, SEM, N2 adsorption–desorption, NH3-TPD, Py-FTIR, H2-TPR, HRTEM and TGA. It is demonstrated that for microporous NiMoS/ZSM-5, acid amount and crystallite size of HZSM-5 are key factors affecting HDAK performance. The larger acid amount and smaller crystallite size can promote the conversion of 1, 3, 5-TMB, especially the dealkylation reaction, resulting in higher BTX yield. Compared to NiMoZ-3, mesopores in micro-mesoporous NiMoAKZ-3 are beneficial to accessibility of 1, 3, 5-TMB to NiMoS and acid sites in close proximity, and the diffusion of reactant and product molecules inside pores, thus resulting in superior HDAK performance of NiMoAKZ-3. Moreover, the reaction network of 1, 3, 5-TMB HDAK was revealed according to product distribution. NiMoS supported on ZSM-5 was developed for heavy aromatic hydrodealkylation (HDAK). Acid amount and crystallite size of microporous ZSM-5 are key factors affecting 1,3,5-trimethylbenzene (1,3,5-TMB) HDAK. Mesopores inside ZSM-5 facilitate accessibility of 1,3,5-TMB to NiMoS and acid sites in close proximity and improve HDAK performance.

In big data query processing, there is a trade-off between query accuracy and query efficiency, for example, sampling query approaches trade-off query completeness for efficiency. In this article, we argue that query performance can be significantly improved by slightly losing the possibility of query completeness, that is, the chance that a query is complete. To quantify the possibility, we define a new concept, Probability of query Completeness (hereinafter referred to as PC). For example, If a query is executed 100 times, PC = 0.95 guarantees that there are no more than 5 incomplete results among 100 results. Leveraging the probabilistic data placement and scanning, we trade off PC for query performance. In the article, we propose PoBery (POssibly-complete Big data quERY), a method that supports neither complete queries nor incomplete queries, but possibly-complete queries. The experimental results conducted on HiBench prove that PoBery can significantly accelerate queries while ensuring the PC. Specifically, it is guaranteed that the percentage of complete queries is larger than the given PC confidence. Through comparison with state-of-the-art key-value stores, we show that while Drill-based PoBery performs as fast as Drill on complete queries, it is 1.7 ×, 1.1 ×, and 1.5 × faster on average than Drill, Impala, and Hive, respectively, on possibly-complete queries.

Multimaterials with different modulus can endow soft robots with embodied intelligence that deliver spatially varying deformation upon actuation. There is an increasing need for design tools that can rigorously and efficiently generate material layouts for desired motions. Here, we present a design paradigm for soft pneumatic multimaterial actuators by attaching a stiffer material layer as skeleton to softer inflated rubber, and develop a topology optimization based framework to automatically generate the skeleton layout that leads the actuator to achieve desired motions such as bending or twisting. Our method is enabled by a dynamic level set function to describe and track the topological change of the skeleton, large-deformation analysis compatible with the varying skeleton layout, and a gradient-based optimizer to govern the evolution of material layout, with the geometric and material nonlinearities taken into account. A forward geometric mapping and a backward design velocity mapping are constructed to allow manipulating the level sets on the planar space. We show that the design methodology is capable of generating high-performance bending and twisting actuators of cylindrical or customized cone shape. The simulation and experiment results show that, the bending actuator achieves a free bending angle 73 $^\circ$ and blocking force 2.05 N, and the twisting actuator achieves a large rotation angle of 143 $^\circ$ .

Twisting motion plays an important role in kinematics of soft robots. However, current twisting actuators usually suffer from complex mechanical design with multiple materials and undesired coupling with bending and stretching motions. In this letter, we propose a new class of soft twisting pneumatic actuators that purely rely on the freeform chamber geometry to achieve large bi-directional twisting rotations. The freeform chamber surface integrates geometric flexibility in the cross section, lateral profile, and axial chirality, which are parameterized as design variables. We develop a finite element analysis model and investigate the effect of the geometry parameters on the actuators’ mechanical behavior. The actuator naturally undergoes combined twisting and axial motions, and achieves a bi-directional twisting rotation of 116.7 $^\circ$ , blocking torque of 0.81 N $\cdot$ m, and energy density of 1907 J/m $^3$ , well in line with the theoretical prediction. When it is constrained from axial motions, the actuator delivers pure twisting motion, achieving a bi-directional twisting rotation of 72.5 $^\circ$ , blocking torque of 0.56 N $\cdot$ m, and energy density of 925 J/m $^3$ . This letter represents an important step toward leveraging the full potential of the freeform geometry design to create novel compact soft-bodied actuators and robots.

Ivosidenib (AG-120) is an unlisted, but estimated to be valid, oral inhibitor for isocitrate dehydrogenase 1 (IDH1) in the phase Ⅰ study of IDH1-mutated acute myeloid leukemia (AML) patients. This paper presents the investigation and validation of a rapid, effective, qualitative and quantitative determination method of ivosidenib in rat plasma by ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). The samples were treated using acetonitrile precipitation to remove protein influence. Then, the supernatant was extracted to analyze plasma concentration traits. In the UPLC system, acetonitrile and water containing 0.1% formic acid were selected as a cosolvent mobile phase, applying a gradient elution to isolate compounds in a C18 column. Mass detections were performed on a triple quadruple mass spectrometer in positive ion mode. Electroshock characteristic fragment ionization was used for m/z 583.95→214.53 for ivosidenib for quantitative determination, m/z 583.95→186.6 for qualitative determination, and m/z 492.06→354.55 for IS. The selectivity, linearity, stability, accuracy and precision were verified by reaching the guideline criteria from European Medicine Agency (EMA) and the Food and Drug Administration (FDA). The calibration curve was linear over the concentration range of 2–2,000 ng mL−1 for ivosidenib in rat plasma with a lower limit of quantification (LLOQ) of at least 2 ng mL−1. Additionally, there was no distinct matrix effect or carry-over phenomenon. The method was successfully established and applied to separate ivosidenib from plasma, with the entire analytical process being performed within 3 min for each sample, which shows high-efficiency and convenience for further studies of ivosidenib.

To examine the perceived professional benefits (PPB) and associated factors among nurses during the coronavirus disease 2019 (COVID-19) pandemic in China.Cross-sectional study.Using the snowball sampling method, 492 nurses (478 females, 14 males) were recruited. Data were collected using an online survey, including participants' socio-demographic and working characteristics, psychological distress related to the COVID-19 pandemic, dealing with professional frustration, professional self-reflection and PPB from 1-30 April 2020.Nurses experienced high levels of PPB. In linear regression analysis, self-perceived concerns about COVID-19, emotional shock caused by it, risk perception towards their occupations, dealing with professional frustration and professional self-reflection were positively associated with PPB among nurses. These factors explained 84% variance in PPB.This study highlighted that although the nurses experienced psychological distress, they gained high PPB during the COVID-19 pandemic. Additionally, to facilitate nurses' efforts to achieve professional growth, more educational resources and opportunities for engaging in reflective practices could be provided.

Nerve root injury and dural tears are important complications in current endoscopic spine techniques. Whether Kambin's Triangle is safe or not is unknown for percutaneous endoscopic transforaminal oblique fixation from posterior corner (PETOFPC) in lumbar spine. The aims of this study were to verify neural safety of PETOFPC and to define and evaluate the ideal operating target and actual safe working area in Kambin's triangle for PETOFPC.Sixty outpatients underwent lumbar magnetic resonance examination. The distances from the working targets to exiting nerve roots and dural sac/traversing nerve roots in the coronal and sagittal planes (c1-6, s1-6), and the distances from the exiting roots to the dural sac/traversing nerve roots in the upper and lower endplate planes (d1-2) were measured and statistically analyzed.The c1, c2, c3, c4, c5 and c6 all first increased and then decreased; they gradually increased from L1/2, maximized in L4/5, and decreased slightly in L5/S1. In L1/2-L5/S1, d1 and d2 gradually increased (F=249.7, P0.0001; F=511.7, P0.0001) and d2d1 (P0.05). The values of d1 and d2 were the smallest in L1/2 (6.71±2.10, 11.89±2.55) mm and the largest in L5/S1 (13.37±4.09, 22.05±3.96) mm. With the outward shift of the targets in the sagittal plane, both s1, s3, s5 and s2, s4, s6 gradually decreased (s1s3s5, s2s4s6).In this study, we calculate the ideal operating target and actual safe area and further proved that Kambin's triangle is safe enough for PETOFPC. PETOFPC may be a very promising technology and have great clinical significance.

Phenol-soluble modulins (PSMs) and Staphylococcal protein A (SpA) are key virulence determinants for community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA). Here, using chemical and genetic approaches, we show that inhibition of TarO, the first enzyme in the wall teichoic acid (WTA) biosynthetic pathway, decreases the expression of genes encoding PSMs and SpA in the prototypical CA-MRSA strain USA300 LAC. Mechanistically, these effects are linked to the activation of VraRS two-component system that directly represses the expression of accessory gene regulator (agr) locus and spa. The activation of VraRS was due, at least in part, to the loss of the functional integrity of penicillin-binding protein 2 (PBP2) in a PBP2a-dependent manner. We provide multiple lines of evidence that the accumulation of lipid-linked peptidoglycan precursors is a trigger for the activation of VraRS. In sum, our data reveal an unprecedented and important role for WTA biosynthesis in the regulation of virulence gene expression in CA-MRSA, underlining that acquisition of PBP2a-encoding mecA gene can impart an additional regulatory layer for the modulation of key signaling pathways (e.g., VraRS and agr) in S. aureus.

Mobile Edge computing (MEC) is a new distributed computing paradigm where edge servers are deployed at, or near cellular base stations in close proximity to end-users. This offers computing resources at the edge of the network, facilitating a highly accessible platform for real-time, latency-sensitive services. A typical MEC environment is highly stochastic with random user arrivals and departures over time. Here, we address the user allocation problem from a service provider's perspective, who needs to allocate its users to the cloud or edge servers in a specific area. A user, who has a multi-dimensional resource requirement, can be allocated to either the remote cloud, which incurs a high latency, or an edge server, which results in a low latency but might require the user to wait in a queue. This study aims to achieve a controllable trade-off between performance (throughput) and several associated costs such as queuing delay and latency costs. We model this problem as a stochastic optimization problem, propose SUAC (Stochastic User AlloCation) -- an online Lyapunov optimization-based algorithm, and prove its performance bounds. The experimental results demonstrate that SUAC outperforms existing approaches, effectively allocating users with a desired trade-off while keeping the system strongly stable.

Background Alcohol can cause neuroinflammation, leading to neuron damage and further memory and cognitive impairment. Recent animal studies have shown that the exposure to chronic alcohol consumption induces robust inflammatory microglial activation in the brain. However, as a novel anti-inflammation approach, the impact of sodium butyrate on chronic alcohol-induced neuroinflammation still remains unclear. Methods Sixty female C57BL/6J mice were randomly divided into 4 groups: pair-fed (PF) group (PF/CON), alcohol-fed (AF) group (AF/CON), PF with sodium butyrate (NaB) group (PF/NaB) and AF with NaB group (AF/NaB). Each group was fed a modified Lieber-DeCarli liquid diet with or without alcohol. Mice were subjected to different behavioral tests to assess aberrant behaviours (deficits in cognitive functions, depression and anxiety). Pathological changes were further investigated by Hematoxylin and eosin staining (HE) and Nissl staining. The microglial activation and microglial polarization were observed by immunohistochemistry (IHC), immunofluorescence (IF) and flow cytometry. Enzyme-linked immunosorbent assay (ELISA) was used to determine the levels of inflammatory factors. G-protein coupled receptor 109A (GPR109A), peroxisome proliferator-activated receptor γ (PPAR-γ) and nuclear factor-κB (NF-κB) mRNA and protein levels were evaluated by reverse transcription‑quantitative (RT‑q) PCR and western blot (WB). Results As indicated by the behavioural tests, inflammatory indicators, microglial activation (M1/M2 microglia polarization) and brain morphology, sodium butyrate administration ameliorated aberrant behaviours (locomotor hypoactivity, anxiety disorders and depressive behaviours, impaired learning and spatial recognition memory), effectively reduced neuroinflammation and neuronal damage. The effectiveness of sodium butyrate may attribute to the GPR109A receptor in microglia by up-regulating the expression of PPAR-γ and inhibiting the activation of NF-κB. Conclusion Sodium butyrate ameliorates neuroinflammation induced by chronic alcohol exposure and improves memory and cognitive functions in mice via modulating microglia-mediated GPR109A / PPAR-γ / NF-κB signaling pathway.

This study aimed to explore the correlations of Lnc-UCA1/miR-138 axis with gestational diabetes mellitus (GDM) risk and neonatal prognosis.First, the blood samples from sixty GDM patients and 60 healthy pregnant women were collected to detect the change of Lnc-UCA1/miR-138 axis by using real-time polymerase chain reaction (RT-qPCR). The clinical characteristics of GDM patients, healthy controls, and neonates were recorded. Then, the correlation analysis of Lnc-UCA1, miR-138, and Lnc-UCA1/miR-138 axis levels with clinicopathological characteristics was performed to explore the clinical value of Lnc-UCA1/miR-138 axis in GDM. Finally, the specificity and sensitivity of Lnc-UCA1, miR-138, and Lnc-UCA1/miR-138 axis for GDM diagnosis was evaluated using receiver operating characteristic (ROC) curves.Our present study found that, when compared with healthy pregnancies, the expression levels of Lnc-UCA1 and miR-138 were increased and decreased, respectively, and Lnc-UCA1/miR-138 axis profile was elevated. Second, Lnc-UCA1 and Lnc-UCA1/miR-138 axis were positively correlated with fasting glucose, one-hour glucose, and two-hour glucose, while miR-138 showed the opposite trend. Furthermore, the area under the ROC curve (AUC) were 0.8196, 0.8021, and 0.8901 for diagnostic efficiencies of Lnc-UCA1, miR-138, and Lnc-UCA1/miR-138, respectively. In addition, higher profiles of Lnc-UCA1 were correlated with birth asphyxia of neonate.Circulating Lnc-UCA1/miR-138 axis might be involved in the pathogenesis of GDM and could function as a novel and effective biomarker for GDM risk and neonatal prognosis.

The ever-increasing popularity of web APIs allows app developers to leverage a set of existing APIs to achieve their sophisticated objectives. The heavily fragmented distribution of web APIs makes it challenging for an app developer to find appropriate and compatible web APIs. Currently, app developers usually have to manually discover candidate web APIs, verify their compatibility and select appropriate and compatible ones. This process is cumbersome and requires detailed knowledge of web APIs which is often too demanding. It has become a major obstacle to further and broader applications of web APIs. To address this issue, we first propose a web API correlation graph built on extensive data about the compatibility between web APIs. Then, we propose WAR (Web APIs Recommendation), the first data-driven approach for web APIs recommendation that integrates API discovery, verification and selection operations based on keywords search over the web API correlation graph. WAR assists app developers without detailed knowledge of web APIs in searching for appropriate and compatible APIs by typing a few keywords that represent the tasks required to achieve app developers’ objectives. We conducted large-scale experiments on 18,478 real-world APIs and 6,146 real-world apps to demonstrate the usefulness and efficiency of WAR.