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The establishment of an early pro-regenerative niche is crucial for tissue regeneration1,2. Gasdermin D (GSDMD)-dependent pyroptosis accounts for the release of inflammatory cytokines upon various insults3–5. However, little is known about its role in tissue regeneration followed by homeostatic maintenance. Here we show that macrophage GSDMD deficiency delays tissue recovery but has little effect on the local inflammatory milieu or the lytic pyroptosis process. Profiling of the metabolite secretome of hyperactivated macrophages revealed a non-canonical metabolite-secreting function of GSDMD. We further identified 11,12-epoxyeicosatrienoic acid (11,12-EET) as a bioactive, pro-healing oxylipin that is secreted from hyperactive macrophages in a GSDMD-dependent manner. Accumulation of 11,12-EET by direct supplementation or deletion of Ephx2, which encodes a 11,12-EET-hydrolytic enzyme, accelerated muscle regeneration. We further demonstrated that EPHX2 accumulated within aged muscle, and that consecutive 11,12-EET treatment rejuvenated aged muscle. Mechanistically, 11,12-EET amplifies fibroblast growth factor signalling by modulating liquid–liquid phase separation of fibroblast growth factors, thereby boosting the activation and proliferation of muscle stem cells. These data depict a GSDMD-guided metabolite crosstalk between macrophages and muscle stem cells that governs the repair process, which offers insights with therapeutic implications for the regeneration of injured or aged tissues.Untargeted metabolomics reveals that 11,12-epoxyeicosatrienoic acid released from macrophages via gasdermin G pores has a key role in promoting fibroblast growth factor-dependent muscle regeneration following injury. [ABSTRACT FROM AUTHOR]

An effective strategy to enhance the pressure sensitivity in flexible capacitive sensors is altering the microstructure of the dielectric layer surface. The common sensitized structures are cylindrical, hemispherical, and pyramidal. Limited by the common processes, such as replication and direct-writing technology, it has rarely been investigated that the effect of asymmetric structures on the sensitization of flexible capacitive sensors. Hence, we propose a method based on two-photon polymerization to process tilted micropillar to enhance the pressure sensitivity. When subjected to external pressure, these tilted micropillar structures can undergo compressive and bending deformation, which endows the sensor with excellent response capability. The sensor exhibits a sensitivity of 0.1021 kPa−1, a detection limit of 8 Pa, a fast response/recovery time of 60/50 ms, a stability of 6000 cycles, and a wide detection range (at least 160 kPa). The process combines the high precision of 3D printing with the flexibility of molding to process more complex sensitized structures. This technology can be used not only to prepare flexible capacitive pressure sensors but also to provide important support in the field of micro- and nano-manufacturing, such as electronic skin and microfluidic chips. [ABSTRACT FROM AUTHOR]

The rapid growth of the Internet of Things and wearable sensors has led to advancements in monitoring technology in the field of health. One such advancement is the development of wearable respiratory sensors, which offer a new approach to real‐time respiratory monitoring compared to traditional methods. However, the energy consumption of these sensors raises concerns about environmental pollution. To address the issue, this study proposes the use of a triboelectric nanogenerator (TENG) as a sustainable energy source. The electrical conductivity of the TENG is improved by incorporating chitosan and carbon nanotubes, with the added benefit of chitosan's biodegradability reducing negative environmental impact. A wireless intelligent respiratory monitoring system (WIRMS) is then introduced, which utilizes a degradable triboelectric nanogenerator for real‐time respiratory monitoring, diagnosis, and prevention of obstructive respiratory diseases. WIRMS offers stable and highly accurate respiratory information monitoring, while enabling real‐time and nondestructive transmission of information. In addition, machine learning technology is used for sleep respiration state analysis. The potential applications of WIRMS extend to wearables, medical monitoring and sports monitoring, thereby presenting innovative ideas for modern medical and sports monitoring. [ABSTRACT FROM AUTHOR]

The adoption and growth of functional magnetic resonance imaging (fMRI) technology, especially through the use of Pearson's correlation (PC) for constructing brain functional networks (BFN), has significantly advanced brain disease diagnostics by uncovering the brain's operational mechanisms and offering biomarkers for early detection. However, the PC always tends to make for a dense BFN, which violates the biological prior. Therefore, in practice, researchers use hard-threshold to remove weak connection edges or introduce l1-norm as a regularization term to obtain sparse BFNs. However, these approaches neglect the spatial neighborhood information between regions of interest (ROIs), and ROI with closer distances has higher connectivity prospects than ROI with farther distances due to the principle of simple wiring costs in resent studies. Thus, we propose a neighborhood structure-guided BFN estimation method in this article. In detail, we figure the ROIs' Euclidean distances and sort them. Then, we apply the K-nearest neighbor (KNN) to find out the top K neighbors closest to the current ROIs, where each ROI's K neighbors are independent of each other. We establish the connection relationship between the ROIs and these K neighbors and construct the global topology adjacency matrix according to the binary network. Connect ROI nodes with k nearest neighbors using edges to generate an adjacency graph, forming an adjacency matrix. Based on adjacency matrix, PC calculates the correlation coefficient between ROIs connected by edges, and generates the BFN. With the purpose of evaluating the performance of the introduced method, we utilize the estimated BFN for distinguishing individuals with mild cognitive impairment (MCI) from the healthy ones. Experimental outcomes imply this method attains better classification performance than the baselines. Additionally, we compared it with the most commonly used time series methods in deep learning. Results of the performance of K-nearest neighbor-Pearson's correlation (K-PC) has some advantage over deep learning. [ABSTRACT FROM AUTHOR]

α-Cembrenediol displays a diverse array of biological activities, encompassing antibacterial, antitumor, and neuroprotective effects. To comprehensively understand the in vivo transport, distribution, and elimination mechanisms associated with α-cembrenediol, its interaction with bovine serum albumin (BSA) was investigated. In this study, the interaction between α-cembrenediol and BSA was explored using various techniques, including UV absorption, steady-state fluorescence, circular dichroism spectrum, molecular docking, and molecular dynamics simulation. The results showed that there was a clear interaction between BSA and α-cembrenediol. Specifically, the KSV and Kb decreased with increasing temperature at 293, 303, and 310 K, indicating that α-cembrenediol interacted with BSA through a static quenching mechanism. Furthermore, the number of binding sites was approximately 1 at the three temperatures, suggesting the presence of a single specific binding site for α-cembrenediol on BSA. Moreover, the binding process occurred spontaneously (ΔG<0), primarily driven by hydrogen bonds and van der Waals forces (ΔH<0 and ΔS<0). α-Cembrenediol bound to the Sudlow site I of BSA. Binding of BSA to α-cembrenediol also caused its conformation to change. This study provides essential insights into the interaction between α-cembrenediol and BSA, contributing to a better understanding of the pharmacokinetic properties of the compound. [ABSTRACT FROM AUTHOR]

Objective: A convenient strategy was developed to recycle selectable markers using Cre/loxP system for constructing Komagataella phaffii strains co-expressing multiple proteins. Results: A plasmid in this strategy was generated from pPICZαA with integration of lox71-Sh ble-lox66. Firstly, the plasmid was inserted with one target protein gene and then transformed into K. phaffii KM71. Secondly, the auxiliary plasmid pPICZαA/cre/his4 containing CRE recombinase gene was further chromosomally inserted to Sh ble gene therein. Finally, methanol induction was conducted to produce CRE for Cre/loxP-mediated recombination, and consequently, the sequence between lox71 and lox66 was deleted, leading to recycling of ZeoR and His− markers. Then the resulted strain expressing the one target protein was used as the host to which another target protein gene could be inserted by the same procedures. Conclusions: With easy manipulation, the method was effective in recycling of the selectable markers, and consequently two protein genes were sequential integrated chromosomally and successfully co-expressed in the yeast. [ABSTRACT FROM AUTHOR]

In the new era of artificial intelligence (AI) and the Internet of Things (IoT), big data collection and analysis for intelligent sports are of great importance in monitoring human health. Herein, naturally, biodegradable triboelectric nanogenerators (NB‐TENGs) are developed based on low‐cost, recyclable, and environmentally friendly corn bracts, which are further applied in neck motion recognition. Three NB‐TENGs are integrated into an elastic collar to create a neck‐condition monitoring triboelectric sensor (NCM‐TS). An intelligent behavioral monitoring system is achieved by combining NCM‐TS with a deep learning model, which allows the recognition of four types of neck motion with an average accuracy of 94%. The developed neck motion monitoring sensor has broad potential applications in sports health monitoring, rehabilitation training, and healthcare. [ABSTRACT FROM AUTHOR]

Multifunctional groups diarylamines, an innovative product, efficiently produced from arylamines and p‐nitrosoanisole derivatives by intermolecular SNAr under weak acid conditions. This SNAr proceeds under mild reaction conditions, and more significantly, the substrates involved do not necessarily require strong electron‐withdrawing groups. Moreover, this SNAr is characterized by resistance to space crowding, tolerance to halogen and nitroso functional groups, and high regioselectivity. Mechanistic observations suggest that the SNAr is the result of the transfer of the positive charge center of the protonated nitroso group to the p‐methoxy group. [ABSTRACT FROM AUTHOR]

Flexible pressure sensors based on micro‐/nanostructures can be integrated into robots to achieve sensitive tactile perception. However, conventional symmetric structures, such as pyramids or hemispheres, can sense only the magnitude of a force and not its direction. In this study, a capacitive flexible tactile sensor inspired by skin structures and based on an asymmetric microhair structure array to perceive directional shear force is designed. Asymmetric microhair structures are obtained by two‐photon polymerization (TPP) and replication. Owing to the features of asymmetric microhair structures, different shear force directions result in different deformations. The designed device can determine the directions of both static and dynamic shear forces. Additionally, it exhibits large response scales ranging from 30 Pa to 300 kPa and maintains high stability even after 5000 cycles; the final relative capacitive change (ΔC/C0) is <2.5%. This flexible tactile sensor has the potential to improve the perception and manipulation ability of dexterous hands and enhance the intelligence of robots. [ABSTRACT FROM AUTHOR]

Lindera communis is a medicinal and aromatic plant widely distributed in China. Its leaves are rich in essential oil (EO), but the reports on biological activities of the leaf EO are limited. This study aimed to analyze the chemical composition of L. communis leaf EO and evaluate its different biological activities. The leaf EO was obtained by hydro-distillation and analyzed by GC-MS and GC-FID. 53 compounds were identified, representing 96.80% of the total composition. The major compounds included germacrene D (28.34%), bicyclogermacrene (21.07%), germacrene B (6.14%) and spathulenol (5.73%). SC50 values of L. communis leaf EO in DPPH and ABTS assays were 252.36 and 34.25 mg/mL, respectively, indicating inactivity in antioxidant effect. MICs of L. communis leaf EO against Bacillus cereus, Listeria monocytogenes, Staphylococcus aureus and Staphylococcus epidermidis were 25 mg/mL. Of four enzymes, inhibitory effects on tyrosinase and butyrylcholinesterase were observed, with kojic acid equivalent (KAE) and galanthamine equivalent (GE) values as 22.89 ± 1.38 mg KAE/g of EO and 67.13 ± 0.99 mg GE/g of EO, respectively. L. communis leaf EO also demonstrated strong antiproliferative effects on MCF-7 and HepG2 cells. At the concentration of 500 μg/mL, the cell viability of MCF-7 cells was only 4.86%. L. communis leaf EO could find its possible use in cosmetic and pharmaceutical industries. [ABSTRACT FROM AUTHOR]

In the pursuit of discovering new active metabolites from helicosporous hyphomycetes, rice fermentation products of Neohelicosporium griseum were examined. Eight compounds were isolated from this saprophytic fungus, namely vertixanthone (1), diaportheone A (2), 1,3,6,8-tetrahydroxyanthraquinone (3), lecanoric acid (4), decarboxycitrinone (5), 6,8-dihydroxy-4-hydroxymethyl-3,5-dimethyl-isochromen-1-one (6), decarboxyhydroxycitrinone (7), and ergosterin (8). The 1D and 2D NMR characteristics of compound 1 in DMSO-d6 were detailed for the first time. Antimicrobial testing indicated that compounds 1–4 exhibited moderate activity against Pseudomonas aeruginosa, with compound 3 also showing weak activity against Staphylococcus aureus. In-vitro cytotoxicity assays revealed that compounds 1, 3, and 4 displayed cytotoxic activity against HELA cell lines, with respective IC50 values of 30.8, 13.7, and 14.1 µM. Compounds 1, 3, and 4 also showed significant cytotoxicity against A549 cell lines, with respective IC50 values of 24.7, 7.4, and 10.3 µM. [ABSTRACT FROM AUTHOR]

It is essential to further characterize liver injury aimed at developing novel therapeutic approaches. This study investigated the mechanistic basis of genipin against carbon tetrachloride (CCl4)-triggered acute liver injury concerning ferroptosis, a novel discovered modality of regulated cell death. All experiments were performed using hepatotoxic models upon CCl4 exposure in mice and human hepatocytes in vitro. Immunohistochemistry, immunoblotting, molecular docking, RNA-sequencing and ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) were conducted. CCl4 intoxication was manifested with lipid peroxidation-dictated ferroptotic cell death, together with changes in a cascade of ferroptosis-associated events and several regulatory pathways. Both the administration of genipin and ferrostatin-1 (Fer-1) significantly prevented this hepatotoxicity in response to CCl4 intoxication via upregulating GPX4 and xCT (i.e., critical regulators of ferroptosis). RNA-sequencing unraveled that arachidonic acid metabolism was considerably influenced upon genipin treatment. Accordingly, genipin treatment attenuated arachidonate 15-lipoxygenase (ALOX15)-launched lipid peroxidation in terms of UHPLC-MS/MS analysis and inflammation. In vitro, genipin supplementation rescued erastin-induced hepatocellular inviability and lipid ROS accumulation. The siRNA knockdown of GPX4 partially abrogated the protective effects of genipin on erastin-induced cytotoxicity, whereas the cytotoxicity was less severe in the presence of diminished ALOX15 expression in L-O2 cells. In conclusion, our findings uncovered that genipin treatment protects against CCl4-triggered acute liver injury by abrogating hepatocyte ferroptosis, wherein the pharmacological modification of dysregulated GPX4 and ALOX15-launched lipid peroxidation was responsible for underlying medicinal effects as molecular basis. [ABSTRACT FROM AUTHOR]

Background. Aspiration pneumonia (AP) is difficult to diagnose and has poor outcomes. This case-control study aimed to explore the risk factors and delineate the antibiotic usage for AP. Methods. Inpatients diagnosed with community-acquired pneumonia (CAP) from 2013 to 2017, enrolled in the urban employee basic medical insurance program in Beijing, were included and classified into the AP (N = 2,885) and non-AP (N = 53,825) groups. Risk factors were identified by logistic regression. Results. Older age (compared to 18–64 years, OR for 65–79 years: 4.3, 95% CI: 3.8–4.9; OR for >80 years: 6.3, 95% CI: 5.6–7.2), male (OR: 1.4, 95% CI: 1.3–1.5), cerebrovascular disease (OR: 3.1, 95% CI: 2.8–3.5), dementia (OR: 2.0, 95% CI: 1.8–2.1), vomiting (OR: 1.4, 95% CI: 1.2–1.7), Parkinson's disease (OR: 2.1, 95% CI: 1.8–2.4), and epilepsy (OR: 3.2, 95% CI: 2.8–3.7) were associated with an increased risk of AP. 92.8% of the AP patients received antibiotic therapy. Among them, patients treated with broad-spectrum antibiotics, antibiotics for injection, and combined antibiotics accounted for 93.3%, 97.9%, and 81.7%, respectively. Conclusions. Older age, male, and several comorbidities were independent risk factors for AP, and combined antibiotics treatments are common, which merits attention in accurate detection of AP in a high-risk population. [ABSTRACT FROM AUTHOR]

This study aimed to explore the association between family function and sleep disturbances in preschool children in rural areas of China. Caregivers of preschool children completed sociodemographic questionnaires, the Children's Sleep Habits Questionnaire (CSHQ), the Self-rating Anxiety Scale (SAS) and the Family APGAR scale. Using sleep disturbances in children as the dependent variable, family function and other related factors as independent variables, binary logistic regression analyses were performed to examine associations between family function and sleep disturbances in children. A total of 3,636 caregivers of preschool children were enrolled in our study, and the prevalence of sleep disturbances among their preschool children was 89.4%. In our study, lower family function was associated with higher risk of sleep disturbances among preschool children. After adjusting for age (years), education level of mother, discipline attitudes of father and mother, only child status and caregivers' anxiety, the associations were statistically significant both in families of which caregivers of children are their parents or other relatives. (AOR for parents = 1.487, 95% CI:1.152–1.919, P = 0.002; AOR for other relatives = 1.963, 95% CI:1.302–2.958, P = 0.001). Our study results indicated that family function was associated with sleep disturbances in preschool children, and future high-quality cohort studies are needed to explore this topic in more detail. [ABSTRACT FROM AUTHOR]

Lindera glauca is a shrub or small tree mostly distributed in China, Japan and Korea. However, reports on the biological activities of Lindera glauca fruit essential oil (LGFEO) are limited. The study on its chemical composition, and antioxidant and cholinesterase inhibitory activities were performed, along with molecular docking of six selected compounds. The LGFEO was extracted by hydro distillation and analyzed by GC-MS and GC-FID. Antioxidant activities of LGFEO were evaluated by three methods with different mechanisms. Acetylcholinesterase and butyrylcholinesterase inhibitory activities of LGFEO were tested. A total of 48 components were identified representing 95.74% of the total composition of LGFEO in which the major compounds were (E)-β-ocimene (41.53%), α-copaene (13.17%), δ-cadinene (6.20%), 3-carene (5.89%) and eucalyptol (3.57%). Weak antioxidant activities of LGFEO in three assays (9.52, 11.36 and 38.98 μmol TE/g, respectively) were observed. LGFEO showed obvious cholinesterase inhibitory activities at the final concentrations of 50 and 20 μg/mL. IC50 values for acetylcholinesterase and butyrylcholinesterase were 46.48 and 34.85 μg/mL, respectively. Molecular docking revealed that geranyl acetate, β-caryophyllene and limonene had lower binding affinities in the range of −7.1 to −6.1 kcal/mol through hydrophobic interactions and hydrogen bond. Six compounds including 3-carene, limonene, eucalyptol, (E)-β-ocimene, geranyl acetate and β-caryophyllene could contribute together to cholinesterase inhibitory activities of LGFEO. This essential oil indicated low potential as natural antioxidant, but it could be potentially used as cholinesterase inhibitor with possible application in food, aromatherapy and pharmaceutical industries. [ABSTRACT FROM AUTHOR]

Progress in science and technology drives the continuous innovation of energy collection and utilization. In the field of sports, the information collection and analysis based on Internet of things have attracted particular attention. Moreover, triboelectric nanogenerator (TENG) has promising applications in the field of sports. Here, we introduce the working principle of the TENG then the progress of the TENG as a wearable energy sensor is examined in the two fields of basic human activities and sports, especially competitive sports. On this basis, it is considered that the stability of devices, the universality of materials, and the scientificity of application of the TENG in the future need to be improved. We provide a direction for further upgrading energy collection technology to promote the high-quality development of human mechanical energy sensing in the field of sports. [ABSTRACT FROM AUTHOR]

Vehicles are important targets in the remote sensing applications and nighttime vehicle detection has been a hot study topic in recent years. Vehicles in the visible images at nighttime have inadequate features for object detection. Infrared images retain the contours of vehicles while they lose the color information. Thus, it is valuable to fuse infrared and visible images to improve the vehicle detection performance at nighttime. However, it is still a challenge to design effective fusion models due to the complexity of visible and infrared images. In order to improve vehicle detection performance at nighttime, this paper proposes a fusion model of infrared and visible images with Generative Adversarial Networks (GAN) for vehicle detection named GF-detection. GAN is utilized in the image reconstruction and introduced in the image fusion recently. To be specific, to exploit more features for the fusion, GAN is utilized to fuse the infrared and visible images via the image reconstruction. The generator fuses the image features and detection features, and then generates the reconstructed images for the discriminator to classify. Two branches, visible and infrared branches, are designed in the GF-detection model. Different feature extraction strategies are conducted according to the variance of the visible and infrared images. Detection features and self-attention mechanism are added to the fusion model aiming to build a detection task-driven fusion model of infrared and visible images. Extensive experiments based on nighttime images are conducted to demonstrate the effectiveness of the proposed fusion model in night vehicle detection. [ABSTRACT FROM AUTHOR]

As it is urgently needed to address the energy consumption and health care problems caused by population growth, the field of sustainable energy collection and storage equipment as well as intelligent health care for monitoring human motion behavior has received wide attention and achieved rapid development. However, the portable intelligent systems that integrate them have not been widely discussed. In this work, we propose a design of a nanogenerator-based wireless intelligent motion correction system, combining triboelectric nanogenerator technology with wireless intelligent host computer signal processing and visualization systems. Under the condition of no external power supply, a noninvasive triboelectric nanogenerator (FL-TENG) sensor integrated system stores the mechanical energy due to human movement behavior and drives wireless micro-electronic devices to realize the human–computer interaction application of the intelligent system. In the conducted test, the reported instantaneous output of an ordinary clap action was around 241V. For a variety of physical exercise types being monitored, it can accurately determine human movement behavior and perform error correction and scoring for movement techniques. Additionally, using hydrogel as an electrode improves the service life and stability of the device. Therefore, this flexible and convenient design concept is beneficial to the development and utilization of sustainable energy and sports activities. In addition, it extends the application prospects of FL-TENG in self-powered sensing systems. [ABSTRACT FROM AUTHOR]

Nowadays, the applications of the triboelectric nanogenerator in sensing and monitoring sports experience a blooming prosperity. Here, we report a flexible and lightweight triboelectric nanogenerator (FL-TENG) made of hydrogel electrodes, polytetrafluoroethylene (PTFE), PDMS, and polyurethane (PU). Based on the triboelectric effect, the FL-TENG can work as a self-powered sensor attaching to taekwondo protective gear, which can be used to monitor athletes' competition performance and improve the fairness of the competition. In addition, the FL-TENG can drive micro-wireless devices for wireless transmitting sports data during the competition in real time. This kind of sustainable green self-powered sensor provides a new path for the field of sports competition monitoring. [ABSTRACT FROM AUTHOR]

Wearable motion-monitoring systems have been widely used in recent years. However, the battery energy storage problem of traditional wearable devices limits the development of human sports training applications. In this paper, a self-powered and portable micro-structure triboelectric nanogenerator (MS-TENG) has been made. It consists of micro-structure polydimethylsiloxane (PDMS) film, fluorinated ethylene propylene (FEP) film, and lithium chloride polyacrylamide (LiCl-PAAM) hydrogel. Through the micro-structure, the voltage of the MS-TENG can be improved by 7 times. The MS-TENG provides outstanding sensing properties: maximum output voltage of 74 V, angular sensitivity of 1.016 V/degree, high signal-to-noise ratio, and excellent long-term service stability. We used it to monitor the running skills of speed skaters. It can also store the biomechanical energy which is generated in the process of speed skating through capacitors. It demonstrates capability of sensor to power electronic calculator and electronic watch. In addition, as a flexible electrode hydrogel, it can readily stretch over 1300%, which can help improve the service life and work stability of MS-TENG. Therefore, MS-TENG has great application potential in human sports training monitoring and big data analysis. [ABSTRACT FROM AUTHOR]

We aimed to explore factors associated with prognosis in patients with metastatic small bowel adenocarcinoma (SBA) as well as to develop and validate nomograms to predict overall survival (OS) and cancer-specific survival (CSS). Relevant information of patients diagnosed between 2004 and 2016 was extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Nomograms for predicting 1- and 3-year OS and CSS were established with potential risk factors screened from multivariate cox regression analysis. The discrimination and accuracy of the nomograms were assessed by concordance index (C-index), calibration plots, and the area under receiver operating characteristic curve (AUC). In total, 373 SBA patients with M1 category were enrolled. Multivariate analysis revealed that age, size and grade of primary tumor, primary tumor surgery, and chemotherapy were significant variables associated with OS and CSS. The C-index values of the nomogram for OS were 0.715 and 0.687 in the training and validation cohorts, respectively. For CSS, it was 0.711 and 0.690, respectively. Through AUC, decision curve analysis (DCA) and calibration plots, the nomograms displayed satisfactory prognostic predicted ability and clinical application both in the OS and CSS. Our models could be served as a reliable tool for prognostic evaluation of patients with metastatic SBA, which are favorable in facilitating individualized survival predictions and clinical decision-making. [ABSTRACT FROM AUTHOR]

Deep learning (DL) has demonstrated great performance in various applications on powerful computers and servers. Recently, with the advancement of more powerful mobile devices (e.g., smartphones and touch pads), researchers are seeking DL solutions that could be deployed on mobile devices. Compared to traditional DL solutions using cloud servers, deploying DL on mobile devices have unique advantages in data privacy, communication overhead, and system cost. This article provides a comprehensive survey for the current studies of adopting and deploying DL on mobile devices. Specifically, we summarize and compare the state-of-the-art DL techniques on mobile devices in various application domains involving vision, speech/speaker recognition, human activity recognition, transportation mode detection, and security. We generalize an optimization pipeline for bringing DL to mobile devices, including model-oriented optimization mechanisms (e.g., pruning and quantization) and nonmodel-oriented optimization mechanisms (e.g., software accelerator and hardware design). Moreover, we summarize popular DL libraries regarding their support to state-of-the-art models (software) and processors (hardware). Based on our summarization, we further provide insights into potential research opportunities for developing DL for mobile devices. [ABSTRACT FROM AUTHOR]

Background: Liver cirrhosis is characterized by immune dysfunction, contributing to malnutrition. We previously revealed neutrophil‐to‐lymphocyte ratio (NLR) as an indicator of disordered immune system. Herein we aimed to (1) determine the optimal NLR cutoff that best predicts malnutrition risk and (2) clarify the association between NLR and nutrition status. Methods: A total of 135 hospitalized patients with cirrhosis were included. Immune dysfunction was evaluated by levels of serum C‐reactive protein (CRP), NLR, and other parameters. Malnutrition was screened by a risk score referring to the Royal Free Hospital–Nutritional Prioritizing Tool (RFH‐NPT). Receiver operating characteristic (ROC) curve was implemented to determine the best NLR cutoff that predicts malnutrition risk. Correlation between NLR and indicators of hepatic and physical function (handgrip strength) were also examined. Multivariable logistic regression was used to assess the association between NLR and malnutrition risk. Results: ROC curve revealed that the optimum cutoff to predict malnutrition risk was NLR > 4.2, with a sensitivity of 47.2%, specificity of 81.0%, negative predictive value of 58.0%, and positive predictive value of 74.5%, respectively. Patients with NLR > 4.2 exhibited a higher RFH‐NPT score, serum platelet‐to‐lymphocyte ratio, and CRP. A positive correlation was found between NLR values and Child‐Turcotte‐Pugh (r = 0.22; P =.010), model for end‐stage liver disease (r = 0.36; P <.001), and RFH‐NPT scores (r = 0.31; P <.001). NLR was a risk factor for malnutrition independently of alcoholic liver disease and presence of ascites. Conclusions: Immune dysfunction measured by NLR was associated with malnutrition risk estimated by RFH‐NPT in cirrhosis. [ABSTRACT FROM AUTHOR]

Spontaneous parametric down-conversion ( SPDC) is a primary method for preparing quantum light sources. In this paper, the central technical schemes of different types of SPDC ( type-0, type-1, type-) were introduced, and the research progress and applications of quantum light sources to prepare multi-photon quantum entangled states and high- dimensional quantum entangled states were discusseed. At the same time, the preparation and application of narrow linewidth entangled states from cavity-enhanced SPDC were also introduced. Finally, the existing problems and future development direction of various schemes were analyzed and prospected. [ABSTRACT FROM AUTHOR]

This study aimed to explore the prevalence of sleep disturbances among preschool children in rural areas of China and identify the underlying associated factors. A cross-sectional study was conducted in rural areas of Anhui Province, China, from September 2019 to January 2020. The caregivers of children from 26 kindergartens completed the demographic questionnaire, the Children's Sleep Habits Questionnaire (CSHQ), the Strengths and Difficulties Questionnaire (SDQ), the Self-rating Anxiety Scale (SAS), and the adapted Identification and Management of Feeding Difficulties (IMFeD) tool. One-way analysis of variance, independent-samples t-test, and hierarchical multiple linear regression were conducted to explore the potential influencing factors of sleep disturbances in preschool children. For the specific sleep disturbances based on each subscale of the CSHQ, bedtime resistance (54.9%) and sleep anxiety (47.9%) were the most common types of sleep disturbances, followed by daytime sleepiness (21.3%), sleep duration (20.8%), parasomnias (16.5%), sleep-onset delay (12.6%), night wakings (12.2%) and sleep-disordered breathing (10.3%). The ages of children, children's emotional/behavioral problems, children's feeding difficulties, inconsistent parenting attitudes of parents, poor parenting styles, non-parent caregivers, and caregiver anxiety contributed significantly to the CSHQ total score, accounting for approximately 27.1% (R2 = 0.271) of the variance. Our study indicates that the prevalence of sleep disturbances among preschool children in rural areas of China is quite high. Furthermore, the potential risk factors are complicated, including factors related to both children and their caregivers. [ABSTRACT FROM AUTHOR]

Acorus macrospadiceus is an aromatic herb that is widely distributed in southwest China. However, reports on the biological activities of its essential oil (EO) are limited. In the present study, the chemical composition, antioxidant, antimicrobial and cholinesterase inhibitory activities were determined for essential oils extracted from the leaves and rhizomes of this species. The essential oils were extracted by hydrodistillation and analysed by gas chromatography/mass spectrometry (GC/MS) and gas chromatography with a flame ionization detector (GC/FID). Antioxidant activity was examined using DPPH, ABTS and FRAP assays. Antimicrobial activity was evaluated by determining the minimum inhibitory concentrations (MICs) and minimum microbiocidal concentrations (MMCs). Acetylcholinesterase and butyrylcholinesterase inhibitory activities of the essential oils were also tested to evaluate the potential effect of the EOs on neurodegenerative disease. A total of 15 and 19 components were identified in the leaf and rhizome EOs, representing 99.24% and 98.35% of the total composition, respectively. Estragole was found to be the most abundant compound at 98.14% and 94.69% of the leaf and rhizome EOs, respectively. The essential oils displayed weak antioxidant and acetylcholinesterase inhibitory activities. The essential oils showed higher inhibitory effects against Candida albicans than other strains, with a MIC of 3.13 mg/mL, indicating possible use in the treatment of Candida infections. [ABSTRACT FROM AUTHOR]

No tailored model incorporating physical frailty for 2-year mortality in cirrhosis is available for practitioners in general practice. Thus we aimed to develop a model based on laboratory results and physical frailty allowing clinicians for stratifying cirrhotics by using individual estimate. One hundred and thirteen cases were assigned to the primary cohort, and all other 76 patients were regarded as the validation cohort. Multivariate Cox regression was performed, and a nomogram including five-meter gait speed (5MGS) were generated. The performance of the proposed model was assessed by C-index, calibration curve, and decision curve analysis (DCA). On multivariate analysis, the Model for End-Stage Liver Disease-Sodium, albumin and 5MGS were independent predictors for 2-year mortality in cirrhosis. A nomogram incorporating all these parameters achieved a C-index of 0.804 (95%CI, 0.731–0.877). The calibration curve implied optimal correspondence between the predicted survival and actual outcomes. Our model is useful in the clinical settings based on DCA. Similar results were observed in the validation cohort with a C-index of 0.796 (95%CI, 0.689–0.899). Moreover, 5MGS, as a surrogate of physical performance, significantly correlated with multiple domains of general frailty according to Frailty Index (our published data), including instrumental activities of daily living, self-reported health, social activity and falls. In conclusion, the nomogram incorporating 5MGS may represent an individualized tool for predicting mortality in cirrhosis for primary care physicians. [ABSTRACT FROM AUTHOR]

To evaluate the relationship between resilience and emotion regulation among preschool left-behind children (LBC) in rural China. A total of 620 preschool LBC were enrolled from rural areas in Anhui province, China. Multivariate logistic regression was used to evaluate the associations between resilience and variables. The results showed that 20.2% of LBC had higher resilience. Emotion regulation was correlated with resilience among preschool LBC. Children with higher cognitive reconstruction (adjusted OR (AOR) = 0.349,95%CI:0.249–0.489), passive dealing (AOR = 0.577, 95%CI:0.411–0.810), alternative action (AOR = 0.369, 95%CI:0.267–0.510) and self-comforting (AOR = 0.441, 95%CI:0.315–0.619) would have lower risk of low resilience. Our findings suggest that strengthening emotion regulation could promote psychological resilience and prevent adverse developments in LBC. [ABSTRACT FROM AUTHOR]

Only when we understand how hackers think, can we defend against their attacks. Towards this end, this paper studies the cyber-attacks that aim to remove nodes or links from network topologies. We particularly focus on one type of such attacks called Maximum Vertex Coverage Attacks under Knapsack constraint (MVCAK), in which a hacker has a fixed budget to remove nodes from a network with the nodes involving different costs for removal, and the hacker’s goal is to maximize the number of links incident to the nodes removed. Since the MVCAK problem is NP-hard, we firstly propose an optimal solution by Integer Linear Program formulation. Secondly, we give an approximate solution by Linear Programming relaxation that achieves an approximation ratio of 3/4, outperforming the existing 1 - 1√(e) (about 0.39). Thirdly, since the straightforward implementation of our approximate solution has a high time complexity, we propose two heuristics to significantly reduce its complexity while preserving the approximation ratio. We formally prove the correctness and the effectiveness of these two heuristics. Finally, we conduct extensive experiments on both artificial and real-world networks, showing that our approximate solution produces almost the same results as the optimal solution in practice and has an acceptable running time. [ABSTRACT FROM AUTHOR]

Different from traditional gestures, sign language gestures involve a lot of finger-level gestures without wrist or arm movements. They are hard to detect using existing motion sensors-based approaches. We introduce the first low-cost sign language gesture recognition system that can differentiate fine-grained finger movements using the Photoplethysmography (PPG) and motion sensors in commodity wearables. By leveraging the motion artifacts in PPG, our system can accurately recognize sign language gestures when there are large body movements, which cannot be handled by the traditional motion sensor-based approaches. We further explore the feasibility of using both PPG and motion sensors in wearables to improve the sign language gesture recognition accuracy when there are limited body movements. We develop a gradient boost tree (GBT) model and deep neural network-based model (i.e., ResNet) for classification. The transfer learning technique is applied to ResNet-based model to reduce the training effort. We develop a prototype using low-cost PPG and motions sensors and conduct extensive experiments and collect over 7000 gestures from 10 adults in the static and body-motion scenarios. Results demonstrate that our system can differentiate nine finger-level gestures from the American Sign Language with an average recognition accuracy over 98 percent. [ABSTRACT FROM AUTHOR]

Background: Alterations in body compositions are related to poor outcomes and the presence of complications in cirrhosis. However, no predictive tools combining all these anthropometric parameters are applicable in the clinical setting. We aimed to clarify the potential utility of body compositions and develop a nomogram incorporating any independent factor for prognosticating long-term mortality in cirrhosis.Methods: A total of 414 patients were randomized into primary (n = 274) and validation (n = 140) cohorts. X-tile was performed to identify optimal cut points for stratifying participants. Multivariate Cox regression was performed, and nomogram incorporating body compositions were generated. The utility of developed models was evaluated by Harrell concordance index (C-index), calibration curve, and decision curve analysis (DCA).Results: Stratifying by X-tilederived cut points, low skeletal muscle index (myopenia), high intramuscular adipose tissue content (myosteatosis), and the ratio of high visceral to subcutaneous adipose tissue area (adiposity) was independently associated with 3-year mortality. A sex-stratified nomogram incorporating anthropometric indices and clinical factors resulted in moderate discriminative accuracy, with a C-index of 0.787 (95% CI, 0.736-0.838) and 0.789 (95% CI, 0.727-0.851) in males and females, respectively. The calibration curve showed predictive survival corresponding optimally with the actual outcomes. Our models were feasible in the clinical settings based on DCA. Similar results were observed in the validation cohort. Additionally, participants could be classified into 3 distinct risk groups by the nomogram.Conclusions: Our proposed nomogram embedding body compositions rendered an individualized predictive tool for long-term mortality in cirrhosis. [ABSTRACT FROM AUTHOR]

Objective: Colorectal cancer (CRC) is a commonly diagnosed cancer. Previous studies investigating the relationship between periodontal disease (PD) and CRC showed controversial conclusions. This meta‐analysis is to explore the association between PD and CRC. Methods: Observational studies that explore the association between CRC and PD were included in this meta‐analysis. A comprehensive literature search in 7 electronic databases to identify all relevant studies published prior to February 2020. The Newcastle‐Ottawa Quality Assessment Scale was used to evaluate the quality each study. The pooled relative risk (RR) and 95% confidence interval (CI) were used to estimate the association between the PD and CRC risk. Results: A total of 838 articles were obtained from database searching and 4 articles were obtained from other sources, and 13 articles with 14 studies involving 634,744 participants were included. An association between PD and increased CRC incidence was found, periodontal disease patients were 21% (95%CI, [1.06, 1.38], I2=83.9%) more likely to develop colorectal cancer than people with healthy oral cavity. But there is no significant association between PD and CRC mortality. The heterogeneity of this meta‐analysis was relatively high, I2 was 83.9% (95%CI, [72.7%, 90.5%]), chi‐squared of Q test was 62.18, but sensitivity analysis confirmed the stability of the result. Funnel plot, Eggerʼs test and Beggʼs test found no publication bias of analysis. Conclusion: The current meta‐analysis demonstrates an association between PD and CRC, indicating that early CRC screening is necessary for people with poor oral health, and oral health improvement might be beneficial for reducing CRC risk. [ABSTRACT FROM AUTHOR]

Objective: Alzheimer's disease (AD) is a common type of dementia, which has caused heavy global economic and health burden, and the using of statins to treat AD has caused widely debated. The purpose of this meta-analysis is to explore the effect of statins in the treatment of Alzheimer's disease.Methods: Studies were retrieved by searching PubMed, Embase, Cochrane library, OvisdSP, Web of Science, Chinese Nation Knowledge Infrastructure (CNKI) and Chinese Biomedical Database (CBM) databases before March 31, 2019. We extracted the Mini-Mental State Examination (MMSE), Alzheimer's Disease Assessment Scale-cognitive (ADAS-Cog), Neuropsychiatric Inventory (NPI), Activities of Daily Living (ADL) scale score, and other information. The pooled Weighted Mean Difference (WMD) and their 95% confidence intervals (95% CI) were calculated with random effect model or fixed random effect model.Results: A total of nine randomized controlled trials were included that contained 1489 patients; of them, 742 patients in the statins group, 747 patients in the control group. There were nine studies used the MMSE scale, five studies used the ADAS-Cog scale, four studies used the NPI scale, and six studies used the ADL scale. Meta-analysis of the nine studies that reported the MMSE scale scores indicated that there is no significant effect of statins as compared with control group (the pooled WMD = 1.09, 95% CI, - 0.00, 2.18, p = 0.05, I2 = 87.9%). Meta-analysis of the five studies that reported the ADAS-Cog scale scores also indicated that there is no significant effect of statins as compared with control group (the pooled WMD = - 0.16, 95% CI, - 2.67, 2.36, p = 0.90, I2 = 80.1%). Meta-analysis of the four studies that reported the NPI scale scores indicated that treatment with statins could slow the rise in the NPI scale scores (the pooled WMD = - 1.16, 95% CI, - 1.88, - 0.44, p = 0.002, I2 = 45.4%). Meta-analysis of the six studies that reported the ADL scale scores indicated that treatment with statins could improve patients' daily living ability (the pooled WMD = - 4.06, 95% CI, - 6.88, - 1.24, p = 0.005, I2 = 86.7%). Results of subgroup analysis indicated that the use of statins in the short term (≤ 12 months) associated with the change of the MMSE scale scores (the pooled WMD = 1.78, 95% CI, 0.53, 3.04, p = 0.005, I2 = 79.6%). Sensitivity analysis and publication bias test were both negative, and the results were relatively reliable and stable.Conclusion: Statins used in AD patients had beneficial effects on the scores of MMSE scale in the short term (≤ 12 months), and statins could slow the deterioration of neuropsychiatric status and significantly improve activities of daily living ability in AD patients, but statins did not show an advantage in the change of the ADAS-Cog scale scores. [ABSTRACT FROM AUTHOR]

Aim: It is well known that the use of proton pump inhibitor (PPI) is widespread in patients with liver cirrhosis. PPI counteracts H2 receptor inhibitor (H2RA) with its strong acid suppression effect. However, there is always a concern that PPI use may increase spontaneous bacteria peritonitis (SBP) development in cirrhotic patients. We aimed to investigate the association between acid suppression therapy (i.e. PPI or H2RA) and SBP through meta‐analysis. Methods: We searched PubMed, Medline, Web of Science, Cochrane library, and Embase for relevant studies published up to April 2019. Pooled OR and 95% CI were calculated by a random‐effects model. Funnel plots and Egger's tests were performed for the evaluation of publication bias. Non‐parametric "trim‐and‐fill" tests were conducted for sensitivity analysis. Results: A total of 20 original articles including 9566 cirrhotic patients were analyzed. The overall meta‐analysis highlighted that PPI use was associated with the risk of SBP (pooled OR 1.77, 95% CI 1.49–2.11). The conclusion was irrespective of study methods, whereas the result was inconsistent only in South America. However, the conclusion might not be stable enough and should be extrapolated with caution. Unlike PPI, we found H2RA was not associated with SBP (pooled OR 1.06, 95% CI 0.75–1.48). Conclusions: In conclusion, PPI use, but not H2RA, will increase the incidence of SBP in cirrhotic patients. In addition, H2RA might be beneficial for patients who require long‐term acid suppression therapy. [ABSTRACT FROM AUTHOR]

Highlights: Wearable battery-free perspiration analyzing sites based on sweat flowing on ZnO nanoarrays was fabricated. Coupling of hydrovoltaic effect and enzymatic reaction were analyzed. The wearable wireless physiological status monitoring system has potential application in constructing sports big data.We fabricated wearable perspiration analyzing sites for actively monitoring physiological status during exercises without any batteries or other power supply. The device mainly consists of ZnO nanowire (NW) arrays and flexible polydimethylsiloxane substrate. Sweat on the skin can flow into the flow channels of the device through capillary action and flow along the channels to ZnO NWs. The sweat flowing on the NWs (with lactate oxidase modification) can output a DC electrical signal, and the outputting voltage is dependent on the lactate concentration in the sweat as the biosensing signal. ZnO NWs generate electric double layer (EDL) in sweat, which causes a potential difference between the upper and lower ends (hydrovoltaic effect). The product of the enzymatic reaction can adjust the EDL and influence the output. This device can be integrated with wireless transmitter and may have potential application in constructing sports big data. This work promotes the development of next generation of biosensors and expands the scope of self-powered physiological monitoring system. [ABSTRACT FROM AUTHOR]

Background & Aims: An elevated neutrophil‐to‐lymphocyte ratio (NLR) has received attention as a prognostic surrogate across chronic liver diseases. However, an exact threshold has not been fully elucidated. Methods: A total number of 589 patients with cirrhosis (LC) were included. The value of NLR was calculated and its optimal cut‐off was initially determined by X‐tile program. Independent predictors of 90‐day mortality were identified with Cox regression model. The Kaplan‐Meier method was used to generate survival curves. To reduce influences of selection bias and possible confounders, a 1:2 propensity score matching (PSM) was performed. Results: The X‐tile indicated that the difference in survival was most significant for NLR more than 8.9. Serum NLR > 8.9 was an independent indicator in the entire cohort and PSM subset (HR 4.268, 95% CI 2.211‐8.238, P < .001; HR 4.209, 95% CI 1.448‐12.238, P = .008 respectively). Subgroup analysis showed that NLR > 8.9 was an independent risk factor of 90‐day mortality regardless of age, gender, CTP or MELD score. Conclusions: The value of NLR more than 8.9 is a feasible cut‐off across clinical settings among applicable population. The adding of NLR to other conventional predictive systems has the potential to provide incremental value without extra economic cost. [ABSTRACT FROM AUTHOR]