Search

Although social participation has been reported to be associated with significantly lower risks of mortality and disability, to our knowledge, no study has estimated its impact on disability-free life expectancy (DFLE). Therefore, this study aimed to investigate the association between social participation and DFLE in community-dwelling older people.We analyzed 11-year follow-up data from a cohort study of 11,982 Japanese older adults (age ≥65 years) in 2006. We collected information on the number of social participations using a questionnaire. Using this information, we categorized the participants into four groups. DFLE was defined as the average number of years a person could expect to live without disability. The multistate life table method using a Markov model was employed for calculating DFLE.The results revealed that DFLE according to the number of social participations was 17.8 years (95% confidence interval [CI], 17.3-18.2) for no activities, 20.9 (95% CI, 20.4-21.5) for one activity, 21.5 (95% CI, 20.9-22.0) for two activities, and 22.7 (95% CI, 22.1-23.2) for three activities in men, and 21.8 (95% CI, 21.5-22.2), 25.1 (95% CI, 24.6-25.6), 25.3 (95% CI, 24.7-25.9), and 26.7 years (95% CI, 26.1-27.4), respectively, in women. This difference in DFLE did not change after the participants were stratified for smoking, body mass index, physical activity, and depression.Social participation is associated with longer DFLE among Japanese older people; therefore, encouraging social participation at the population level could increase life-years lived in good health.

Introduction Sepsis is an infection-induced severe inflammatory disorder leading to multiple organ dysfunction. It remains a highly lethal condition for which early diagnosis and therapy achieve unsatisfactory results. Circulating exosomes containing biomarkers and mediators of sepsis have recently received attention, but the progress has been far from optimal. Objectives The present study focuses on the profiles of molecular dynamics in serum exosomes and explores the potential molecular mechanisms on serum exosomes during the process of sepsis. Methods We used high-performance liquid chromatography-tandem mass spectrometry and RNA-seq to detect the dynamic profiles of exosome proteins and RNAs (including mRNAs, lncRNAs and miRNAs) in serum exosomes from 3 healthy individuals and 9 septic patients at the different stages. Then integrative multiomics analyses were performed and the results were validated by qRT-PCR, LiquiChip assay and metabolomics analysis on mice subjected to cecal ligation and puncture (CLP) modeling. Results A total of 354 proteins, 195 mRNAs, 82 lncRNAs and 55 miRNAs were identified as differentially expressed molecules in serum exosomes from septic patients. Integrative multiomics analysis showed that exosome components were associated with cytokine storm, complement and clotting cascades, the endothelial barrier, 20S proteasome-dependent protein degradation and vitamin metabolism. Importantly, pretreatment with serum exosomes derived from mice subjected to CLP significantly restrained proinflammatory cytokine expression and alleviated tissue injury in septic mice. Further metabolomics analysis demonstrated that pretreatment with septic serum exosomes significantly affected the metabolites associated with vitamin digestion and absorption in CLP mice. Conclusion Our study for the first time describes the landscape of the molecular dynamics of serum exosomes during the development of sepsis and proposes some hypothetical molecular mechanisms by integrative multiomics analysis, which may provide helpful diagnostic and therapeutic insights for the ongoing battle against sepsis.

The accurate segmentation of cerebral vessels from time-of-flight magnetic resonance angiography (TOF-MRA) data is crucial for the diagnosis and treatment of cerebrovascular diseases. However, cerebrovascular segmentation remains challenging due to the tiny and complex structure of the vessels. This paper proposed a GAN-based deep-based method that maps the TOF-MRA data to 3D cerebral vessels. To improve the capability of feature expression, the proposed network integrates squeeze-and-excite blocks into a Vnet structure to extract and accumulate features at different scales. In addition, we introduce adversarial loss for network training, which can help the model to learn the distribution of the cerebral vessels. Besides, we introduce island number and minimum diameter to evaluate the spatial consistency and recognized minimal vessel of the cerebrovascular segmentation results. The proposed method is validated on 102 TOF-MRA cases with manually annotated labels. The experimental results indicate that our method can identify more tiny cerebral vessels meanwhile maintaining the spatial consistency of the cerebral vessel structure. Besides, our GAN-based cerebrovascular segmentation method reaches an average dice similar coefficient of 89.89 % , outperforming other state-of-the-art segmentation methods.

Background: The peculiarity and the lack of clinical studies of dual primary lung cancer (DPLC) led to limited knowledge about its clinical characteristics and prognosis. The current study performed a retrospective analysis and established a prognostic nomogram to assess the prognostic factors and clinical characteristics of DPLC.Methods: A total of 1419 DPLC patients with pathological confirmation from SEER were selected and analyzed by univariate and multivariable Cox regression analyses. The independent prognostic factors were included to establish a nomogram. The accuracy and reliability of prognostic model were evaluated by C-indexes, calibration plots, receiver operating characteristic (ROC) curves, decision curve analyses (DCA) and integrated discrimination improvement (IDI) scores. Chi-square test was used to assess the differences between DPLC and single primary lung cancer (SPLC) or synchronous DPLC (sDPLC) and metachronous DPLC (mDPLC).Results: Cox regression analysis showed that age, sex, histological type, stage, LN metastasis, surgery, chemotherapy were independent prognostic factors, we included these factors to establish a prognostic model. In the training cohort, the C-index was 0.690, and the area under curves (AUC) of 3- and 5-year survival time were 0.720 and 0.723. The calibration plots in training cohort and validation cohort were in excellent agreement. DCA and IDI showed that the predictive effect of the novel prognostic model was better than the model based on 8th AJCC TNM system. Chi-square test indicated that DPLC and SPLC had statistical differences on pathological and clinical features.Conclusions: The clinical and pathological characteristics of DPLC were different from the SPLC. The nomogram based on significant factors could provide accurate and individualized survival predictions for DPLC.

In this paper, we propose a portrait relighting method based on deep reinforcement learning (called PR-RL). Our PR-RL model could conduct portrait relighting by sequentially predicting local light editing strokes, and use strokes to conduct dodge and burn operations on the image lightness, simulating image editing by artists using brush strokes. Reinforcement learning with Deep Deterministic Policy Gradient is introduced to design our PR-RL model, defining the action (stroke parameters) in a continuous space, through which a reward can be designed to guide the agent to learn and relight a portrait image like an artist. To optimize the relighting effect, we further enable the reward to be location relevant and hence a coarse-to-fine strategy can be applied to select corresponding actions and maximize the performance of the proposed method. In comparison with the existing efforts, our proposed PR-RL method is locally effective, scale-invariant and interpretable. We apply the proposed method to tasks of portrait relighting based on both SH-lighting and reference images. The experiments show that our PR-RL method outperforms state-of-the-art methods in generating locally effective and interpretable high resolution relighting results for wild portrait images.

In order to evaluate the importance of pain in systemic sclerosis (SSc), the characteristics of pain reported by patients with SSc were analyzed and compared with the characteristics of pain reported by patients with primary Sjőgren’s syndrome (pSS). Pain was reported by 56 patients (80%) in a group of 70 patients with SSc and by 25 patients (78%) in a group of 32 patients with pSS. Pain severity was assessed by the Pain Rating Index (PRI) and the Present Pain Intensity (PPI) of the McGill Pain Questionnaire (MPQ) and by values obtained by a visual analog scale (VAS) indicating the intensity of pain felt in the moment of the examination and the intensity of pain felt in the week preceding the moment of the examination. No significant difference was detected in the comparison of mean values of pain indices between patients with SSc and patients with pSS and in the comparison among subgroups of patients with SSc. The data indicate that pain is a frequent and important cause of suffering in SSc as in other chronic diseases. The association of different methods may be especially useful to obtain a careful evaluation of pain in clinical research.

AIM Maintaining ≥20 teeth is a public health goal worldwide. Healthy aging, which includes psychological and social well-being, as well as physical indicators, has attracted a great deal of attention with the progression of aging societies. However, no studies have examined the association between the number of remaining teeth and healthy aging. This study aimed to investigate the association between the number of remaining teeth and healthy aging. METHODS This community-based longitudinal cohort study included 8300 Japanese people aged ≥65 years who were free of disability and depression in the baseline survey in 2006. The participants were categorized into four groups according to the number of remaining teeth at baseline: 0-9, 10-19, 20-24 and ≥25. The primary outcome was healthy aging (defined as meeting all four of the following criteria: free of disability, free of depression, high health-related quality of life and high life satisfaction), as assessed by a questionnaire survey carried out in 2017. Multiple logistic regression was used to calculate the corresponding odds ratios and 95% confidence intervals. RESULTS During about 11 years of follow-up, 621 (7.5%) participants attained healthy aging. Participants with ≥20 remaining teeth showed a higher healthy aging rate. Compared with participants with 0-9 teeth, the multivariate-adjusted odds ratios (95% confidence intervals) for 10-19, 20-24 and ≥25 teeth were 0.98 (0.77-1.26), 1.28 (1.01-1.63) and 1.59 (1.24-2.03), respectively. CONCLUSIONS These findings suggest that maintaining ≥20 teeth was associated with healthy aging. Geriatr Gerontol Int 2021; ••: ••-••.

Brain degeneration and damage is difficult to cure due to the limited endogenous repair capability of the central nervous system. Furthermore, drug development for treatment of diseases of the central nervous system remains a major challenge. However, it now appears that using human pluripotent stem cell-derived neural cells to replace degenerating cells provides a promising cell-based medicine for rejuvenation of brain function. Accordingly, a large number of studies have carried out preclinical assessments, which have involved different neural cell types in several neurological diseases. Recent advances in animal models identify the transplantation of neural derivatives from pluripotent stem cells as a promising path toward the clinical application of cell therapies [Stem Cells Transl Med 2019;8:681-693; Drug Discov Today 2019;24:992-999; Nat Med 2019;25:1045-1053]. Some groups are moving toward clinical testing in humans. However, the difficulty in selection of valuable critical quality criteria for cell products and the lack of functional assays that could indicate suitability for clinical effect continue to hinder neural cell-based medicine development [Biologicals 2019;59:68-71]. In this review, we summarize the current status of preclinical studies progress in this area and outline the biological characteristics of neural cells that have been used in new developing clinical studies. We also discuss the requirements for translation of stem cell-derived neural cells in examples of stem cell-based clinical therapy.

For a practical engineering system, disturbances usually have a negative impact on system performance. Especially, when the system physical constraints (e.g., actuator amplitude saturation and input channel constraint) are present, the study for antidisturbance controllability (ADC) is of paramount importance. This article presents the concepts of disturbance estimability, disturbance compensability, and an enhanced antidisturbance control (EADC). From the viewpoint of control system design, an example of spacecraft attitude control is given. The control constraints and multiple disturbances are explicitly analyzed for the sake of attitude control system design of flexible spacecraft. Subsequently, an EADC approach with integration of the disturbance observer-based control (DOBC) and active disturbance rejection control (ADRC) is proposed, based on the characteristics of disturbances exposed. Moreover, prescribed performance approach is incorporated into the spacecraft attitude tracking control. In consequence, the presented control can not only achieve superior antidisturbance capability than DOBC or ADRC, but also quantify the control performances. Numerical simulations and hardware-in-the-loop tests exemplify the applicability of the proposed scheme.

Background Intravenous iron sucrose is becoming a prevailing treatment for individuals undergoing maintenance haemodialysis, but comparisons of dosing regimens are lacking. The aim of this retrospective review was to evaluate the safety and efficacy of proactively administered high-dose iron sucrose versus reactively administered low-dose iron sucrose in patients undergoing maintenance haemodialysis. Methods We analysed the data of 1500 individuals with maintenance haemodialysis who were treated with either high-dose iron sucrose that was proactively administered (Group HD) or low-dose iron sucrose that was reactively administered (Group LD) at the First Affiliated Hospital of Chongqing Medical University from Jan 1, 2008, to Dec 31, 2020. The primary endpoints were the cumulative doses of iron and erythropoiesis-stimulating agent; the secondary endpoints were the events of nonfatal myocardial infarction, nonfatal stroke, hospitalization for heart failure, infection rate, and death from any cause. Results Of the 2124 individuals, 624 individuals were excluded because they met one or more of the exclusion criteria, thus resulting in 1500 individuals who were eligible for inclusion in the study (Group HD, n = 760 and Group LD, n = 740). The median follow-up for the two cohorts was 32 months (range: 25–36). A significant median difference was detected in the monthly iron dose between the groups (1121 mg [range: 800–1274] in the HD group vs. 366 mg [range: 310–690] in the LD group; p p = 0.000). A significant difference was detected in the secondary endpoints (266 events in 320 cases in the HD group vs. 344 events in 385 cases in the LD group) (HR: 0.62; 95% CI: 0.51–0.79; p p = 0.361). Conclusions For individuals undergoing maintenance haemodialysis, high-dose iron sucrose that was proactively administered may be superior to low-dose iron sucrose that was reactively administered with low doses of erythropoiesis-stimulating agent.

In this paper, the Zn-CuInS2 and CuInS2 quantum dots (QDs) were synthesized by heat injection method and were explored as photosensitizers for quantum dot sensitized solar cells (QDSCs). The X-ray diffraction (XRD) analyses indicate that the synthesized Zn-CuInS2 QDs with chalcopyrite structures have a slight shift towards large angle direction with the increase of doping concentrations. The UV–vis absorption and photoluminescence (PL) emission spectra show that Zn doping expands the range of optical absorption and enhances the luminescence intensity. The Zn-CuInS2 QDs with the particle size of around 6.5 nm and homogeneous size distribution are observed by transmission electron microscope (TEM). The current density–voltage curves show that Zn-CuInS2 QDSCs exhibit a conversion efficiency of 2.90%, 17.17 mA/cm2 of short circuit current density (Jsc), 0.42 V of open circuit voltage (Voc), 30.9% of fill factor (FF) at 100 mW/cm2 AM 1.5G illumination. The ZnS coating reduces the recombination of electron–hole pairs and improves the electron injection efficiency. The short-circuit current and power conversion efficiency (PCE) are improved with the increase of pH value and Mercaptopropionic acid (MPA) concentrations. The response range of photocurrent and IPCE of photoanode are improved by Zn doping and ZnS coating strategy.

Photocatalytic technology offers a practical way to solve the energy crisis by producing hydrogen under sunlight but its performance is encumbered by the fast recombination of photoinduced electron-hole pairs. Constructing heterojunctions to form built-in electric fields could separate these electrons and holes, finally enhancing the photocatalytic efficiency. Herein, a Mn0.5Cd0.5Se/g-C3N4 (MCS/CN) heterojunction was fabricated by a facile method to tap into this advantage. 2%MCS/CN shows a hydrogen evolution rate of up to 354.5 μmol in 3 h, which is 4.49 and 126.6 times that of pure g-C3N4 and Mn0.5Cd0.5Se, respectively. Its photocatalytic stability is proved by six cycling tests. Photocurrent, EIS, along with PL spectra, prove that the recombination of photoinduced electron-hole pairs is inhibited by constructing a heterojunction between Mn0.5Cd0.5Se and g-C3N4. In summary, this work demonstrates the enhancement of photocatalysis by constructing a S-scheme heterojunction and offers a feasible way to develop other effective photocatalysts.

ObjectivesRheumatoid arthritis (RA), systemic lupus erythematosus (SLE) and primary Sjögren’s syndrome (pSS) share many clinical manifestations and serological features. The aim of this study was to identify the common transcriptional profiling and composition of immune cells in peripheral blood in these autoimmune diseases (ADs).MethodsWe analysed bulk RNA-seq data for enrichment of biological processes, transcription factors (TFs) and deconvolution-based immune cell types from peripheral blood mononuclear cells (PBMCs) in 119 treatment-naive patients (41 RA, 38 pSS, 28 SLE and 12 polyautoimmunity) and 20 healthy controls. The single-cell RNA-seq (scRNA-seq) and flow cytometry had been performed to further define the immune cell subsets on PBMCs.ResultsSimilar transcriptional profiles and common gene expression signatures associated with nucleosome assembly and haemostasis were identified across RA, SLE, pSS and polyautoimmunity. Distinct TF ensembles and gene regulatory network were mainly enriched in haematopoiesis. The upregulated cell-lineage-specific TFsPBX1,GATA1,TAL1andGFI1Bdemonstrated a strong gene expression signature of megakaryocyte (MK) expansion. Gene expression-based cell type enrichment revealed elevated MK composition, specifically, CD41b+CD42b+and CD41b+CD61+MKs were expanded, further confirmed by flow cytometry in these ADs. In scRNA-seq data, MKs were defined by TFsPBX1/GATA1/TAL1and pre-T-cell antigen receptor gene,PTCRA. Cellular heterogeneity and a distinct immune subpopulation with functional enrichment of antigen presentation were observed in MKs.ConclusionsThe identification of MK expansion provided new insights into the peripheral immune cell atlas across RA, SLE, pSS and polyautoimmunity. Aberrant regulation of the MK expansion might contribute to the pathogenesis of these ADs.

Background Pancreaticobiliary reflux (PBR) causes chronic inflammation of the gallbladder mucosa and changes in the bile components, which are known to promote gallstone formation. This study aimed to investigate the bile biochemistry changes in gallstone patients with PBR and provide new clues for research on the involvement of PBR in gallstone formation. Methods Patients undergoing surgery for gallstones between December 2020 and May 2021 were eligible for inclusion. The bile biochemistry (including amylase, lipase, triglyceride, cholesterol, free fatty acids [FFAs], alanine aminotransferase [ALT], aspartate aminotransferase [AST], alkaline phosphatase [ALP], and γ-glutamyl transferase [γ-GT]) of the included gallstone patients was analysed to determine correlations with PBR. Results In this study, 144 gallstone patients who underwent surgery were enrolled. Overall, 15.97 % of the patients had an increased bile amylase level, which was associated with older age and significantly higher bile levels of ALP, lipase, triglyceride, and FFAs. Positive correlations were observed between amylase and lipase, triglyceride, FFAs levels in the gallbladder bile. However, the bile levels of triglyceride, FFAs, and lipase were positively correlated with each other only in the PBR group and showed no significant correlation in the control (N) group. In addition, elevated bile FFAs levels were found to be an independent risk factor for gallbladder wall thickening. Conclusions In conclusion, PBR-induced increase in FFAs and triglyceride in the gallbladder bile is a cause of gallstone formation, and an increase in bile ALP suggests the presence of cholestasis in PBR.

Screening and follow-up of interstitial lung disease associated with rheumatoid arthritis (RA-ILD) is a challenge in clinical practice. In fact, the majority of RA-ILD patients are asymptomatic and optimal tools for early screening and regular follow-up are lacking. Furthermore, some patients may remain oligosymptomatic despite significant radiological abnormalities. In RA-ILD, usual interstitial pneumonia (UIP) is the most frequent radiological and pathological pattern, associated with a poor prognosis and a high risk to develop acute exacerbations and infections. If RA-ILD can be identified early, there may be an opportunity for an early treatment and close follow-up that might delay ILD progression and improve the long-term outcome.In connective tissue disease–associated interstitial lung disease (CTD-ILD), lung ultrasound (LUS) with the assessment of B-lines and serum Krebs von den Lungen-6 antigen (KL-6) has been recognized as sensitive biomarkers for the early detection of ILD. B-line number and serum KL-6 level were found to correlate with high-resolution computed tomography (HRCT), pulmonary function tests (PFTs), and other clinical parameters in systemic sclerosis–associated ILD (SSc-ILD). Recently, the significant correlation between B-lines and KL-6, two non-ionizing and non-invasive biomarkers, was demonstrated. Hence, the combined use of LUS and KL-6 to screen and follow up ILD in RA patients might be useful in clinical practice in addition to existing tools. Herein, we review relevant literature to support this concept, propose a preliminary screening algorithm, and present 2 cases where the algorithm was used.

Two-dimensional van der Waals (vdW) ferromagnetic materials have attached a significant attention for developing miniaturized electronic devices. Fe3GeTe2 (FGT) as two-dimensional vdW materials with intrinsic ferromagnetism has high Curie temperature, which have potential applications in overcoming microwave pollution and radiation. Herein, a single-crystal FGT is synthesized using a self-flux method and then dissociated into nanosheets via the liquid-phase exfoliation technique. Curie temperature of FGT nanosheets powder is approximately 230 K, which is close to room temperature. FGT nanosheets as microwave absorber exhibit low reflection loss (RL) due to poor impedance matching. The microwave absorption properties of FGT nanosheets are improved by introducing graphene nanosheets (GNS). FGT@GNS 1–2 composites exhibit excellent microwave absorption performance. The minimum RL of FGT@GNS 1–2 reach − 44.43 dB at a microwave frequency of 9.9 GHz, when thickness is only 1.45 mm. This meets the requirements of strong RL and thin thickness of microwave absorption materials, indicating that FGT@GNS composites have a potential application for overcoming microwave pollution and radiation.

Immune checkpoint inhibitors can cause immune-related toxicity in various systems, and myocarditis is the most serious life-threatening toxicity. This report introduces diagnosis and treatment of two cases which developed myocarditis after receiving PD-1 inhibitors therapy. The first case was a 77-year-old male with chordoma, who was treated by third-line sintilimab combined with anlotinib, and presented with symptoms of chest tightness, shortness of breath and upper eyelid ptosis three weeks later. He was diagnosed as immune-checkpoint-inhibitors-related myocarditis and myositis-myasthenia-gravis overlap syndrome based on his clinical symptoms, serum biomarkers, electrocardiogram, echocardiogram, and characteristic findings on cardiac 18F-FDG PET-MRI. Methylprednisolone was given 480 mg/d initially and was gradually reduced to 40 mg/d in 4 weeks, with the myocardial injury biomarkers declined in the same time. The second case was a 69-year-old female with advanced non-small cell lung cancer, who was treated by pemetrexed combined with bevacizumab and camrelizumab, and presented with palpitations 20 days later. She was diagnosed as immune-checkpoint-inhibitors-related myocarditis based on her clinical symptoms, serum biomarkers, electrocardiogram and echocardiogram. Methylprednisolone was given 240 mg/d initially and was gradually reduced to 40 mg/d with good response of myocardial injury biomarkers decline. However, the patient developed fatal myasthenia gravis afterwards, with little response to all treatments. These two cases revealed that, early detection and timely intervention, including discontinuation of immune checkpoint inhibitors and initiation of adequate steroid therapy, can reduce morbidity and mortality and improve prognosis.

BACKGROUND: Coronavirus Disease 2019 (COVID-19) was outbreaking in late 2019 and a proportion of patients developed to pneumonia. Although chest CT is a pivotal diagnostic tool for COVID-19 pneumonia, CT is expensive and also radiological burden for patients. There is urgent to investigate the role of lung ultrasound (LUS) in diagnosing and monitoring COVID-19 pneumonia. METHODS: A total of 8 patients with confirmed cases of COVID-19 pneumonia in Shantou Central Hospital from January 2020 to February 2020 were retrospectively studied. All participants underwent chest HRCT and LUS examination; both were independently performed within 1 day of the other. The radiological patterns were reviewed by 2 radiologists who were blind to the clinical information. A senior ultrasound physician, blind to HRCT results and clinical data, performed bedside LUS in the isolation ward. The CT score was used (a semi-quantitative scoring system) to assess radiographic severity and extent. A B-lines score denoting the extent and severity of sonographic lesion was calculated by summing the number of B-lines on 18 scanning sites. RESULTS: B-lines (100%), pleural irregularities (25%), consolidation (25%), and pleural effusion (25%) were the main findings of LUS examination. Interstitial abnormalities, ground-glass opacities (GGO), consolidations and local or bilateral patchy shadowing were the main findings of HRCT examination. The findings of LUS and HRCT were compared point to point and high consistency was found between the 2 measurements. A significant correlation was also found between the B-lines score and CT score [r=0.96, 95% confidence interval (CI): 0.81 to 0.99, P=0.0001]. CONCLUSIONS: Both LUS patterns and B-lines score are significantly correlated with HRCT findings and score, respectively, supporting its role in assessing COVID-19 pneumonia severity, screening, and following up dynamic changes of pneumonia.

Non-parallel text style transfer has attracted increasing research interests in recent years. Despite successes in transferring the style based on the encoder-decoder framework, current approaches still lack the ability to preserve the content and even logic of original sentences, mainly due to the large unconstrained model space or too simplified assumptions on latent embedding space. Since language itself is an intelligent product of humans with certain grammars and has a limited rule-based model space by its nature, relieving this problem requires reconciling the model capacity of deep neural networks with the intrinsic model constraints from human linguistic rules. To this end, we propose a method called Graph Transformer–based Auto-Encoder, which models a sentence as a linguistic graph and performs feature extraction and style transfer at the graph level, to maximally retain the content and the linguistic structure of original sentences. Quantitative experiment results on three non-parallel text style transfer tasks show that our model outperforms state-of-the-art methods in content preservation, while achieving comparable performance on transfer accuracy and sentence naturalness.

Background. The C-reactive protein (CRP) to albumin (ALB) ratio (CAR) has emerged as a novel inflammatory biomarker. This study was designed to investigate the role of CAR in the disease activity of axial spondyloarthritis (axSpA). Methods. A total of 241 patients and 61 healthy controls were retrospectively enrolled in this study. AxSpA patients were further divided into the inactive group ( n = 176 ) and active group ( n = 65 ) according to Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) cutoff value of 4. Laboratory data and clinical assessment indices were recorded. Spearman’s correlation analysis, receiver operation characteristic (ROC) curve analysis, and binary logistic regression analysis were performed. Results. In axSpA patients, CAR was significantly higher than the healthy group ( P < 0.001 ). Similarly, axSpA patients in the active group had higher CAR than the inactive group ( P < 0.001 ). Besides, CAR was positively correlated with erythrocyte sedimentation rate (ESR) ( r = 0.704 , P < 0.001 ), CRP ( r = 0.996 , P < 0.001 ), BASDAI ( r = 0.329 , P < 0.001 ), and Bath Ankylosing Spondylitis Functional Index (BASFI) ( r = 0.330 , P < 0.001 ). ROC curve analysis suggested that the area under the curve (AUC) of CAR for axSpA of the active group was 0.701, which was higher than that of CRP and ESR. The optimal cutoff point of CAR for axSpA of the active group was 0.3644, with a sensitivity and specificity of 58.5% and 79.0%. Binary logistic analysis results revealed that CAR was an independent predictive factor for axSpA disease activity ( odds ratio = 4.673 , 95% CI: 1.423-15.348, P = 0.011 ). Conclusions. CAR was increased in axSpA and axSpA of the active group. CAR may be a novel and reliable indicator for axSpA disease activity.

Purpose C5α receptor 1 (C5ΑR1) is associated with the development of various human cancers. However, whether it is involved in the development of hepatitis B virus (HBV)–related hepatocellular carcinoma (HCC) is poorly understood. We explored the expression, biological role, and associated mechanisms of C5AR1 in HBV-related hepatoma cells. Materials and Methods The expression of C5ΑR1 mediated by HBV and HBV core protein (HBc) was detected in hepatoma cells. The function of nuclear factor кB (NF-κB) pathway in HBc-induced C5AR1 expression was assessed. The roles of C5ΑR1 in the activation of intracellular signal pathways, the upregulation of inflammatory cytokines, and the growth and migration of hepatoma cells mediated by HBc, were investigated. The effect of C5α in the development of HCC mediated by C5AR1 was also measured. Results C5ΑR1 expression was increased in HBV-positive hepatoma cells. Dependent on HBc, HBV enhanced the expression of C5ΑR1 at the mRNA and protein levels. Besides, HBc could promote C5ΑR1 expression via the NF-κB pathway. Based on the C5ΑR1, HBc facilitated the activation of JNK and ERK pathways and the expression and secretion of interleukin-6 in hepatoma cells. Furthermore, C5ΑR1 was responsible for enhancing the growth and migration of hepatoma cells mediated by HBc. Except these, C5α could promote the malignant development of HBc-positive HCC via C5AR1. Conclusion We provide new insight into the mechanisms of hepatocarcinogenesis mediated by HBc. C5ΑR1 has a significant role in the functional abnormality of hepatoma cells mediated by HBc, and might be utilized as a potential therapeutic target for HBV-related HCC.

Background Our study examined the association between social participation and healthy aging using a community-based cohort study among Japanese older adults. Methods This prospective study was conducted in Ohsaki City, Japan, and included 7226 participants aged ≥65 years at the baseline survey in 2006. We obtained information on frequency of participation in 3 types of community activities (ie, neighborhood activities, hobbies, and volunteer activities) at baseline. Exposure was measured by the number of types of community activities participated in and participants were categorized into 4 groups (ie, none, 1 type, 2 types, and 3 types). The primary outcome was healthy aging as assessed by a questionnaire survey conducted in 2017, and was defined as meeting the following 4 criteria: free of disability, free of depression, high health-related quality of life, and high life satisfaction. We used multiple logistic regression models to calculate the corresponding odds ratios and 95% confidence intervals. Results During 11 years of follow-up, 574 (7.9%) participants attained healthy aging. Compared with participants not participating in any activity, the multivariable-adjusted odds ratios (95% confidence intervals) were 1.90 (1.40, 2.59) for those participating in 1 type, 2.49 (1.84, 3.38) for 2 types, and 3.06 (2.30, 4.07) for 3 types (p for trend < .0001). Furthermore, for each type of community activity, a higher frequency of participation was related to higher probability of healthy aging. Conclusions Our study suggests that social participation is associated with the promotion of healthy aging, and that the benefits were observed across different types of community activities.

Electroencephalography (EEG) signal classification is a crucial part in motor imagery brain–computer interface (BCI) system. Traditional supervised learning methods have performed well pleasing in EEG classification. Unfortunately, the unlabeled samples are easier to collect than labeled samples. In addition, recent studies have shown that it may degenerate performance of semi-supervised learning by exploiting unlabeled samples without selection. To address these issues, a novel semi-supervised broad learning system with transfer learning (TSS-BLS) is proposed in this paper. First, the pseudo-labels of unlabeled samples are obtained using the joint distribution adaptation algorithm. TSS-BLS is then constructed by an improved manifold regularization framework containing both labeled and pseudo-label information. Finally, the effectiveness of the proposed TSS-BLS is evaluated on three BCI competition datasets and four benchmark datasets from UCI repository and compared with seven state-of-the-art algorithms, including ELM, SS-ELM, HELM, SVM, LapSVM, BLS and GSS-BLS. Experimental results show that the performance of TSS-BLS is superior to BLS and GSS-BLS on average. It is thereby shown that TSS-BLS is safe and efficient for EEG classification.

Background The unclear mechanisms and severity of injuries in the injury pyramids for Chinese children and adolescents prevent the prioritization of interventions. This study aimed to describe the injury mechanisms and injury pyramids in this population to provide a priority for injury prevention strategies. Methods Death, hospitalization, and outpatient/emergency department visit data from patients aged 0 ~ 17 years with injuries were obtained from January 1, 2013, to December 31, 2017, in Zhuhai City, China. The injury mechanism ratios were calculated, and the injury pyramid ratios were drawn in proportion using injury mortality and the incidence of both injury hospitalizations and outpatient/emergency department injury visits. Results The top three mechanisms for injuries in children and adolescents treated in outpatient/emergency departments were falls (52.02%), animal bites (14.57%), and blunt injuries (10.60%). The top three mechanisms for injury hospitalizations were falls (37.33%), road traffic injuries (17.87%), and fire/burns (14.29%), while the top three mechanisms for injury deaths were drowning (32.91%), road traffic injuries (20.25%) and falls (13.92%). The incidence rate of outpatient/emergency department injury visits for children and adolescents was 11,210.87/100,000; the incidence rate of injury hospitalization was 627.09/100,000, and the injury death rate was 10.70/100,000. For each injury death, there were 59 injury hospitalizations and 1048 outpatient/emergency injury visits. Conclusions The injury mechanisms were different for injury-related outpatient/emergency department visits, hospitalizations, and deaths among children and adolescents. The injury mechanisms by sex at different stages of child development, and interventions should be formulated based on this finding. The ratios of the injury pyramids varied by age, sex, region, and injury mechanisms; minor nonfatal injuries were more common in children and adolescents. The differences in the severity and extent of the injuries suggested that injury interventions in children and adolescents still have a long way to go.

Background Lung cancer remains the leading cause of cancer death globally. In 2015, the cancer classification guidelines of the World Health Organization were updated. The term “invasive mucinous adenocarcinoma (IMA)” aroused people’s attention, while the clinicopathological factors that may influence survival were unclear. Methods Data of IMA patients was downloaded from SEER database. Kaplan-Meier methods and log-rank tests were used to compare the differences in OS and LCSS. The nomogram was developed based on the result of the multivariable analysis. The discrimination and accuracy were tested by Harrell’s concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve and decision curve analyses (DCA). Integrated discrimination improvement (IDI) index was used to evaluate the clinical efficacy. Results According to multivariate analysis, the prognosis of IMAs was associated with age, differentiation grade, TNM stage and treatments. Surgery might be the only way that would improve survival. Area under the curve (AUC) of the training cohort was 0.834and 0.830 for3-and 5-year OS, respectively. AUC for 3-and 5-year LCSS were separately 0.839 and 0.839. The new model was then evaluated by calibration curve, DCA and IDI index. Conclusion Based on this study, prognosis of IMAs was systematically reviewed, and a new nomogram was developed and validated. This model helps us understand IMA in depth and provides new ideas for IMA treatment.

Owing to its photonic band gap (PBG) and slow light effects, aniline black (AB)-poly(vinylidene fluoride) (PVDF) inverse opal (IO) photonic crystal (PC) was constructed to promote the utility of light and realize photothermal synergetic catalysis. As a highly efficient reaction platform with the capability of restricting heat, a microreactor was introduced to further amplify the photothermal effects of near infrared (NIR) radiation. The photocatalytic efficiency of ZnO/0.5AB-PVDF IO (Z0.5A) increases 1.63-fold compared to that of pure ZnO film under a full solar spectrum, indicating the effectiveness of synergetic promotion by slow light and photothermal effects. Moreover, a 5.85-fold increase is achieved by combining Z0.5A with a microreactor compared to the film in a beaker. The photon localization effect of PVDF IO was further exemplified by finite-difference time-domain (FDTD) calculations. In conclusion, photonic crystal-microreactor enhanced photothermal catalysis has immense potential for alleviating the deteriorating water environment.

Biliary tract cancer (BTC) comprises infrequently occurring neoplasms with poor prognoses. Red blood cell-related parameters are commonly reported prognostic factors. We aimed to compare and evaluate the clinical value of red blood cell-related parameters and develop a prognostic nomogram. The analysis involved 418 patients with BTC who underwent surgery from December 2003 to April 2017. Patients were divided into training and validation cohorts. Red blood cell-related parameters were compared using Kaplan-Meier analysis, the area under receiver-operating characteristic curve (AUC), and C-index. Predictive abilities were evaluated using Cox regression. We developed a nomogram incorporating superior parameters verified using calibration curves, internal validation, and subgroup analysis. The nomogram was compared with the tumour-node-metastasis staging system through ROC, C-index, and Kaplan-Meier analysis. A combined parameter comprising haemoglobin, albumin, lymphocytes, and platelets (HALP), which was superior to other red blood cell-related parameters, indicated a high risk of worse overall survival when low. Univariate analysis revealed that HALP together with other clinical characteristics was associated with overall survival. Multivariate analysis revealed that HALP, tumour-node-metastasis staging, and operative outcome were independent predictors of poor overall survival. Internal validation proved the predictive value of the nomogram. Additional statistical analyses established the advantages of the nomogram vs. tumour-node-metastasis staging. HALP was a superior red blood cell-related parameter and an independent predictor of prognosis. Our nomogram based on HALP, tumour-node-metastasis staging, and operative outcome is a promising model for predicting overall survival.

Background The patterns and risk factors of intentional injuries compared to unintentional injuries among Chinese children and adolescents have not been examined in depth. This work comprehensively describes patterns of intentional injuries in China, for which little information has been previously published. Methods All cases involving individuals 0-17 years old registered at emergency rooms and outpatient clinics were examined using data submitted to the National Injury Surveillance System from 2006 through 2017. A logistic regression model was performed to explore the risk factors related to intentional injuries compared to unintentional injuries. Results A total of 81,459 (95.1%) unintentional injuries, 4,218 (4.9%) intentional injuries (4,013 violent attacks and 205 self-mutilation/suicide) cases were identified. Blunt injuries accounted for 59.4% of violent attacks, while cuts and poisoning accounted for 37.1% and 23.4% of injuries involving self-mutilation/suicide, respectively. For unintentional injuries, falls (50.4%) ranked first. Additional risk factors for intentional injuries included being male (odds ratio [OR] 1.6), coming from rural areas (OR 1.9), being staff or workers (OR 2.2), and being a student (OR 1.8). As the age of the patients increased, so did the risk of intentional injuries (OR 5.0 in the 15-17 age group). Intentional injuries were more likely to occur at 00:00-03:00 am (OR 2.0). Conclusions Intentional injuries affected more males, rural and older children, school students, and staff or workers. The mechanisms and occurrence times differed according to age group. Preventive measures should be taken to reduce the dropout of rural students, strengthen the school's violence prevention plan, and reduce self-harm.

In this paper, we explore the potential of using the multivoxel proton magnetic resonance spectroscopy (1H-MRS) to diagnose neuropsychiatric systemic lupus erythematosus (NPSLE) with the assistance of a support vector machine broad learning system (BL-SVM). We retrospectively analysed 23 confirmed patients and 16 healthy controls, who underwent a 3.0 T magnetic resonance imaging (MRI) sequence with multivoxel 1H-MRS in our hospitals. One hundred and seventeen metabolic features were extracted from the multivoxel 1H-MRS image. Thirty-three metabolic features selected by the Mann-Whitney U test were considered to have a statistically significant difference ( p < 0.05 ). However, the best accuracy achieved by conventional statistical methods using these 33 metabolic features was only 77%. We turned to develop a support vector machine broad learning system (BL-SVM) to quantitatively analyse the metabolic features from 1H-MRS. Although not all the individual features manifested statistics significantly, the BL-SVM could still learn to distinguish the NPSLE from the healthy controls. The area under the receiver operating characteristic curve (AUC), the sensitivity, and the specificity of our BL-SVM in predicting NPSLE were 95%, 95.8%, and 93%, respectively, by 3-fold cross-validation. We consequently conclude that the proposed system effectively and efficiently working on limited and noisy samples may brighten a noinvasive in vivo instrument for early diagnosis of NPSLE.

A deep learning-based inversion algorithm is developed to solve the inhomogeneous background inverse scattering problem (ISP). To alleviate the burden of nonlinearity and ill-posedness of the ISP, a noniterative method called the distorted-Born backpropagation scheme is introduced to quantitatively reconstruct a rough image of the unknown object in inhomogeneous background. The roughly reconstructed result serves as the input of the designed generative adversarial network (GAN), which outputs the fine reconstructed image of the relative permittivity. The generator network of the GAN is well designed as an encoder–decoder structure configured with the attention scheme. The discriminator network is taken to supervise the generator to learn the features of target scatterers through an adversarial training process. The proposed method is proven to be effective in reconstructing objects embedded in inhomogeneous background, which promises a real-time application future of the ISP.

Gout is an inflammatory disease characterized by the deposition of monosodium urate (MSU) in synovial fluid and other tissues. Many studies have shown that the activation of coagulation system had been proposed correlated with systemic inflammation. The concentrations of plasma fibrinogen and D-dimer are increased in abnormal coagulation, emerging as available indicators to predict systemic inflammation. The aim of this study is to reveal the predictive value of plasma fibrinogen, D-dimer in the disease activity of gout patients.This retrospective study included 334 gout patients and 101 age- and gender- matched healthy controls. The gout patients were divided into two groups according to the gout activity score (GAS = 0.09 × last 12 month attacks + 1.01 × sUA + 0.34 × VAS patient + 0.53 × ln(1 + tophi number). The remission group included 46 patients with GAS of lower than 2.5 and the active group included 288 patients with GAS of 2.5 or higher. Clinical and laboratory data were recorded. The correlations between plasma fibrinogen, D-dimer and GAS were analyzed by Spearman's correlation analysis and Partial correlation analysis. Receiver operating characteristic (ROC) was used to evaluate the diagnostic value for the active group compared with remission group. The predictive value of fibrinogen, D-dimer to the disease activity of gout patients was tested by Binary logistic regression analysis.Plasma fibrinogen and D-dimer in gout patients (3.66 (2.88, 5.20), 0.29 (0.22, 0.80)) were increased as compared with the control group (2.88 (2.51, 3.24), 0.22 (0.22, 0.32), both P 0.001). Fibrinogen and D-dimer in active group (3.91 (3.00, 5.53), 0.34 (0.22, 0.86)) were higher than those in remission group (2.88 (2.34, 3.22), 0.22 (0.22, 0.26), both P 0.001)). Plasma fibrinogen, D-dimer, ESR and CRP were positively correlated with GAS (r = 0.606, r = 0.419, r = 0.570, r = 0.440, all P 0.001). ROC curve showed fibrinogen yielded a highest AUC than D-dimer, ESR, CRP. In addition, the optimal cutoff value of fibrinogen for active group was 3.60, with a specificity of 89.1% and sensitivity of 58.3%. Binary logistic regression analysis showed fibrinogen (odds ratio = 2.71, 95% confidence interval: 1.28-5.74, p = 0.011) was a predictor for gout disease activity.Fibrinogen was increased in active gout group. Fibrinogen can serve as a reliable inflammatory marker for monitoring inflammatory response and disease activity in gout patients.

Purpose The immune prognostic index (IPI) has been used as a prognostic biomarker in various cancers. However, the prognostic value of the IPI in gallbladder cancer remains to be determined. Patients and Methods This study included 139 patients who were diagnosed with gallbladder cancer after surgical resection from 2003 to 2017. We used a Kaplan-Meier curve analysis to evaluate the overall survival (OS). Cox proportional hazards regression methodology was used to identify significant independent prognostic factors. Prognostic nomograms for predicting OS were established to achieve superior discriminatory abilities. The prognostic nomograms were verified according to the concordance index, calibration curves, and decision curve analyses in the training cohort and validation cohort. Results Of all 139 patients, 87 (62.6%) patients accepted R0 resection, 32% and 68% were stratified into the good and poor IPI group, respectively. The median OS was 55.9 (range, 5.93-182.7) months in the good IPI group and 15.47 (range, 0.29-190.37) months in the poor IPI group (P < 0.001). In the multivariate Cox model, the IPI was an independent predictor of OS along with the CA19-9, curative resection, and postoperative chemoradiotherapy. A nomogram based on these factors was efficient in predicting 1-, 3-, and 5-year survival probabilities. The nomogram showed higher sensitivity and specificity than the current cancer TNM staging system in the training cohort and validation cohort. Conclusion The IPI is an independent prognostic factor in gallbladder cancer. Our IPI-based nomogram can serve as a useful and convenient prognostic tool for gallbladder cancer.

In the last decades lung ultrasound (LUS) has become of crucial importance in the evaluation and monitoring of a widely range of pulmonary diseases. One of the major benefits which favours this examination, is that this is a non-invasive, low-cost and radiation-free imaging modality which allows repeated imaging. LUS plays an important role in a wide range of pathologies, including cardiogenic oedema, acute respiratory distress syndrome and fibrosis. Specific LUS findings have proved useful and predictive of acute respiratory distress syndrome which is of particular relevance in the suspicion and monitoring of patients with lung disease. Furthermore, several studies have confirmed the role of LUS in the screening of interstitial lung diseases in connective tissue diseases. Given these data, LUS will likely play an important role in the management of COVID-19 patients from identification of specific abnormalities corresponding to definite pneumonia phases and CT scans findings. In addition, LUS could allow reduction in the exposure of health-care workers to potential infection. Herein, we provide a summary on emerging role of lung ultrasound in COVID-19 pneumonia.

Modeling interpretable artificial intelligence (AI) for flood forecasting represents a serious challenge: both accuracy and interpretability are indispensable. Because of the uncertainty and nonlinearity of flood, existing hydrological solutions always achieve low prediction robustness while machine learning (ML) approaches neglect the physical interpretability of models. In this paper, we focus on the need for flood forecasting and propose an interpretable Spatio-Temporal Attention Long Short Term Memory model (STA-LSTM) based on LSTM and attention mechanism. We use dynamic attention mechanism and LSTM to build model, Max-Min method to normalize data, variable control method to select hyperparameters, and Adam algorithm to train the model. Emphasis is placed on the visualization and interpretation of attention weights. Experiment results on three small and medium basins in China suggest that the proposed STA-LSTM model outperforms Historical Average (HA), Fully Connected Network (FCN), Convolutional Neural Networks (CNN), Graph Convolutional Networks (GCN), original LSTM (LSTM), spatial attention LSTM (SA-LSTM), and temporal attention LSTM (TA-LSTM) in most cases. Visualization and interpretation of spatial and temporal attention weights reflect the reasonability of the proposed attention-based model.

COVID-19 is a world health emergency which may inevitably affect the management of a complex autoimmune disease such as systemic sclerosis (SSc). Several SSc patients are frail and, in this pandemic, need a careful protection. The COVID-19 infection might complicate the clinical scenario of interstitial lung disease (ILD) in SSc because it determines a severe pneumonia characterized by radiological features similar to SSc-ILD. The striking CT similarities between the 2 diseases make it difficult to distinguish a worsening of SSc-ILD from COVID-19-ILD superinfection. Moreover, other aspects, like isolation during lock down, may cause a significant psychological stress which will pile up on the already difficult contact with the patients for a routine check-up. Moreover, the drug shortage is a real problem in these times. For these reasons, the rheumatologist in daily clinical practice should carefully differentiate the possible COVID-19 infection in order to optimize the patient management. Therefore, the challenge in everyday life will be to achieve in due time the differential diagnosis as well as the long-term psychological impact.Key Points• SSc patients should be encouraged to continue their chronic therapy; in case of immunosuppressive therapy it must be discontinued for safety in case of COVID-19 infection.• Psychological support must be guaranteed to every SSc patients.• COVID-19 pneuminia is hard to distinguish from an interstitial lung disease due to SSc lung involvment.• Data sharing is fundamental for an optimal managment of SSc patients during COVID-19 pandemia.

This study aimed to assess the role of fibrinogen (Fib) to albumin (ALB) ratio (FAR) in ankylosing spondylitis (AS) and its association with disease activity.135 AS patients and 76 age - and gender - matched healthy controls were collected in this retrospective study. Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) score was used to divide the AS patients into remission group (BASDAI 4) and active group (BASDAI ≥ 4). The association between FAR and BASDAI was evaluated by Spearman correlation. Receiver operating characteristic (ROC) curve was made to determine the area under curve (AUC) value. The prognostic value of FAR in the AS disease activity was tested by multivariate logistical regression analyses.AS patients showed higher FAR levels than the controls (P 0.001). FAR was also increased in active group of AS patients than those in inactive group (P 0.001). Spearman analyses showed that FAR was positively related with BASDAI (r = 0.594, P 0.001) in AS patients. ROC curve analyses revealed that the AUC of FAR was higher than ALB and Fib. In addition, the optimal cutoff value of FAR for AS diagnosis was 78.84, with a specificity of 88.2% and sensitivity of 77.0%. Logistical regression analyses showed that FAR (odds ratio = 13.091, 95% confidence interval: 4.686-36.571, P 0.001) was a predictor for AS disease activity.FAR was increased in AS and may act as a novel inflammatory parameter for mirroring disease activity in AS.

PURPOSE It remains unknown whether allergen-specific immunotherapy (AIT) could attenuate airway inflammatory response triggered by allergen exposure. METHODS We performed Dermatophagoides pteronyssinus (Der-p) nasal provocation tests (NPTs) in allergic rhinitis (AR) and/or asthma patients without AIT (non-AIT), or at 16, 52, 104, or 156 weeks after Der-p AIT. Rhinitis and asthma visual analog scale (VAS; VAS of nasal symptoms [VAS-NS], VAS of asthma symptoms), the rhinoconjunctivitis quality of life questionnaire (RQLQ), nasal lavage, sputum induction, fractional exhaled nitric oxide (FeNO), nasal airway resistance, pulmonary function, and airway hyperresponsiveness were performed before and after NPT. RESULTS Non-AIT subjects demonstrated significantly higher VAS-NS before and after NPT compared to AIT subjects (P < 0.05). NPT response was positive in 14 (100%) non-AIT, 7 (70%) 16 weeks-AIT, 6 (60%) 52 weeks-AIT, 6 (60%) 104 weeks-AIT, and 2 (20%) 156 weeks-AIT subjects. The NPT grade significantly correlated with AIT duration and baseline RQLQ score (r =- 0.561, P < 0.001 and r = 0.525, P < 0.001, respectively). Sputum and nasal lavage eosinophil count, and FeNO in non-AIT subjects were significantly increased 6 hours after NPT (P < 0.05). AIT subjects did not change their sputum or nasal lavage eosinophil count before and after NPT. Subjects with 156 weeks-AIT demonstrated significantly lower levels of sputum and nasal lavage eosinophil count before and after NPT when compared with non-AIT patients (P < 0.05). Sputum eosinophil counts positively correlated with nasal lavage eosinophil counts at baseline and 6 hours after NPT (r = 0.719, P = 0.006 and r = 0.823, P < 0.001, respectively) in non-AIT patients. CONCLUSION Our results show that AIT can attenuate both upper and lower airway immune response to nasal allergen exposure in patients with AR and/or asthma.

The vast amount of web data enables us to build knowledge bases with unprecedented quality and coverage. Named Entity Disambiguation (NED) is an important task that automatically resolves ambiguous mentions in free text to correct target entries in the knowledge base. Traditional machine learning based methods for NED were outperformed and made obsolete by the state-of-the-art deep learning based models. However, deep learning models are more complex, requiring large amount of training data and lengthy training and parameter tuning time. In this paper, we revisit traditional machine learning techniques and propose a light-weight, tuneable and time-efficient method without using deep learning or deep learning generated features. We propose novel adaptive features that focus on extracting discriminative features to better model similarities between candidate entities and the mention's context. We learn a local ranking model based on traditional and the new adaptive features based on the learning-to-rank framework. While arriving at linking decisions individually via the local model, our method also takes into consideration the correlation between decisions by running multiple recurrent global models, which can be deemed as a learned local search method. Our method attains performances comparable to the state-of-the-art deep learning-based methods on NED benchmark datasets while being significantly faster to train.

With a significant development of big data analysis and cloud-fog-edge computing, human-centered computing (HCC) has been a hot research topic worldwide. Essentially, HCC is a cross-disciplinary research domain, in which the core idea is to build an efficient interaction among persons, cyber space, and real world. Inspired by the improvement of HCC on big data analysis, we intend to involve related core and technologies to help solve one of the most important issues in the real world, i.e., flood prediction. To minimize the negative impacts brought by floods, researchers pay special attention to improve the accuracy of flood forecasting with quantity of technologies including HCC. However, historical flood data is essentially imbalanced. Imbalanced data causes machine learning classifiers to be more biased towards patterns with majority samples, resulting in poor classification of pattern with minority samples. In this paper, we propose a novel Synthetic Minority Over-sampling Technique (SMOTE)-Boost-based sparse Bayesian model to perform flood prediction with both high accuracy and robustness. The proposed model consists of three modules, namely, SMOTE-based data enhancement, AdaBoost training strategy, and sparse Bayes model construction. In SMOTE-based data enhancement, we adopt a SMOTE algorithm to effectively cover diverse data modes and generate more samples for prediction pattern with minority samples, which greatly alleviates the problem of imbalanced data by involving experts’ analysis and users’ intentions. During AdaBoost training strategy, we propose a specifically designed AdaBoost training strategy for sparse Bayesian model, which not only adaptively and inclemently increases prediction ability of Bayesian model, but also prevents its over-fitting performance. Essentially, the design of AdaBoost strategy helps keep balance between prediction ability and model complexity, which offers different but effective models over diverse rivers and users. Finally, we construct a sparse Bayesian model based on AdaBoost training strategy, which could offer flood prediction results with high rationality and robustness. We demonstrate the accuracy and effectiveness of the proposed model for flood prediction by conducting experiments on a collected dataset with several comparative methods.

With significant development of sensors and Internet of things, researchers nowadays can easily know what happens in physical space by acquiring time-varying values of various factors. Essentially, growing data category and size greatly contribute to solve problems happened in physical space. In this paper, we aim to solve a complex problem that affects both cities and villages, i.e., flood. To reduce impacts induced by floods, hydrological factors acquired from physical space and data-driven models in cyber space have been adopted to accurately forecast floods. Considering the significance of modeling attention capability among hydrology factors, we believe extraction of discriminative hydrology factors not only reflect natural rules in physical space, but also optimally model iterations of factors to forecast run-off values in cyber space. Therefore, we propose a novel data-driven model named as STA-LSTM by integrating Long Short-Term Memory (LSTM) structure and spatiotemporal attention module, which is capable of forecasting floods for small- and medium-sized rivers. The proposed spatiotemporal attention module firstly explores spatial relationship between input hydrological factors from different locations and run-off outputs, which assigns time-varying weights to various factors. Afterwards, the proposed attention module allocates temporal-dependent weights to hidden output of each LSTM cell, which describes significance of state output for final forecasting results. Taking Lech and Changhua river basins as cases of physical space, several groups of comparative experiments show that STA-LSTM is capable to optimize complexity of mathematically modeling floods in cyber space.

To investigate the association of smoking status and years since smoking cessation with the risk of incident dementia among elderly Japanese. We conducted a longitudinal analysis of smoking status and smoking cessation with dementia in prospective cohort study of 12,489 Japanese individuals aged ≥ 65 years who were followed up for 5.7 years. Information on smoking status and other lifestyle factors was collected via a questionnaire in 2006. Data on incident dementia were retrieved from the public Long-term Care Insurance Database. The Cox proportional hazards model was used to estimate the multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (95% CIs) for incident dementia. During 61,613 person-years of follow-up, 1110 cases (8.9%) of incident dementia were documented. Compared with individuals who had never smoked, current smokers showed a higher risk of dementia (HR 1.46, 95% CI 1.17, 1.80). Among ex-smokers, the risk for those who had stopped smoking for ≤ 2 years was still high (HR 1.39, 95% CI 0.96, 2.01), however, quitting smoking for 3 years or longer mitigated the increased risk incurred by smokers; the multivariable HRs (95% CIs) were 1.03 (0.70, 1.53) for those who had stopped smoking for 3–5 years, 1.04 (0.74, 1.45) for 6–10 years, 1.19 (0.84, 1.69) for 11–15 years, and 0.92 (0.73, 1.15) for > 15 years. Our study suggests that the risk of incident dementia among ex-smokers becomes the same level as that of never smokers if they maintain abstinence from smoking for at least 3 years. Electronic supplementary material The online version of this article (10.1007/s10654-020-00612-9) contains supplementary material, which is available to authorized users.

With population aging, an increasing attention has been paid to quality of life rather than mere longevity. Now, it is urgently needed to clarify predictors of well-being in later life, i.e., "successful aging (SA)." The aim of this study is to investigate whether the number of remaining teeth impacts on maintenance of SA among Japanese older people. The present study was conducted in Tsurugaya district, a suburban area of Sendai, in northern Japan, and included older people aged ≥ 70 years who had met the criteria for SA at a 2003 baseline survey. At the baseline survey, dentists obtained data for the number of remaining teeth. We obtained information about Long-term Care Insurance certification, including the dates of incident functional disability and death between 2003 and 2012. Data pertaining to health-related quality of life (HRQOL) were collected at the 2003 baseline survey and the 2012 follow-up survey. Maintenance of SA was defined in terms of survival, disability-free status and high HRQOL in both 2003 and 2012. Among 450 participants, 108 (24.0%) were considered to have maintained a state of SA. When participants were classified into three groups according to previous studies, in comparison with participants who retained 0-9 teeth, the multivariate prevalence ratios (95% confidence intervals) were 1.39 (0.81-2.36) for those who retained 10-19 teeth and 1.58 (1.002-2.50) for those who retained ≥ 20 teeth (p trend = 0.046). The present results suggest that retaining ≥ 20 teeth is associated with maintenance of SA among Japanese older people.

GOALS This study aimed to explore whether quantitative surface antigen [hepatitis B surface antigen (HBsAg)] can be used as a surrogate marker of hepatitis B virus (HBV) DNA to predict hepatitis B transmission before the first hepatitis vaccine dose in infants born to hepatitis B e antigen (HBeAg)-positive pregnant women. BACKGROUND Currently, HBV transmission persistently occurs worldwide, especially in infants born to e antigen (HBeAg)-positive highly viremic mothers. However, due to high cost, the extensive use of viral load testing to identify these high-risk mothers is limited. MATERIALS AND METHODS In total of 275 HBeAg-positive pregnant women paired with 280 infants were enrolled in this study. Quantitative HBsAg and HBV DNA levels were measured in the third trimester. Spearman rank correlation was used to assess the correlation between HBsAg levels and viral load, and multivariate logistic regression to identify factors related to HBV transmission in infants. RESULTS Among 280 infants included, 15 (5.4%) infants were infected with HBV. In this study, we observed that quantitative HBsAg was positively correlated with maternal viral load (r=0.70, P

Strong upconversion luminescence is significant for effective photocatalytic technology. In this work, photonic crystals and Au nanoparticles (AuNPs) were introduced together to enhance triplet–triplet annihilation upconversion (TTA-UC) luminescence intensity. Photonic crystal films have been fabricated by demolding a polydimethylsiloxane film containing platinum(II)-octaethylporphyrin & 9,10-diphenylanthracene and AuNPs from V-shape anodic aluminum oxide templates. The blue light intensity of the photonic crystal film with AuNPs has gained a 3.69-fold enhancement under green light excitation. After coupling the photonic crystal structure with AuNP plasma resonance, the green-to-blue TTA-UC intensity of the composite film has been enhanced 7.68 times compared with the planar upconversion film without AuNPs. The pseudo-first-order rate constant of the composite film system with g-C3N4@CdS has been increased 3.88 times compared with that of the planar upconversion film system without AuNPs under visible light. This work presents a new route to enhance the TTA-UC luminescence via a hybrid effect, which is useful for photocatalysis.

Utilizing genomic data to predict cancer prognosis was insufficient. Proteomics can improve our understanding of the etiology and progression of cancer and improve the assessment of cancer prognosis. And the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has generated extensive proteomics data of the vast majority of tumors. Based on CPTAC, we can perform a proteomic pan-carcinoma analysis. We collected the proteomics data and clinical features of cancer patients from CPTAC. Then, we screened 69 differentially expressed proteins (DEPs) with R software in five cancers: hepatocellular carcinoma (HCC), children’s brain tumor tissue consortium (CBTTC), clear cell renal cell carcinoma (CCRC), lung adenocarcinoma (LUAD) and uterine corpus endometrial carcinoma (UCEC). GO and KEGG analysis were performed to clarify the function of these proteins. We also identified their interactions. The DEPs-based prognostic model for predicting over survival was identified by least absolute shrinkage and selection operator (LASSO)-Cox regression model in training cohort. Then, we used the time-dependent receiver operating characteristics analysis to evaluate the ability of the prognostic model to predict overall survival and validated it in validation cohort. The results showed that the DEPs-based prognostic model could accurately and effectively predict the survival rate of most cancers.

A piezoelectric built-in electric field is believed to be an effective way to separate photoinduced carriers and enhance photocatalytic performance. The ubiquitous and inexhaustible water wave energy might be a good choice for the extra energy needed to actuate the deformation of piezoelectric materials to create an internal electric field. Thus, in order to harness the piezoelectric effect and the water flow energy, seaweed bio-inspired ZnO piezoelectric cilia arrays were fabricated and a microreactor was applied to further enhance their photocatalytic ability owing to its fast mass transfer. By means of the light localization effect, the reflectance of the cilia arrays was reduced by 41% and hence the absorbance increased correspondingly. By comparison with a P1Z0.5 film (P3U7 : ZnO = 1 : 0.5), P1Z0.5 cilia gain a 261% improvement of photocatalytic degradation of tetracycline (TC). In addition, the P1Z0.5 cilia in the microreactor show a 222% increase against those in the bulk reactor when degrading 50 mL of TC. An 83% increase can be seen for ZnO cilia between P3U7 and PDMS substrates, indicating the significant role of the piezoelectric field in photocatalysis. By combining piezoelectric field enhanced ZnO cilia arrays with microreactors, a huge improvement can be observed in photocatalytic degradation results. This work demonstrates a new avenue for taking advantage of the piezoelectric effect to enhance photocatalytic performance by harnessing ubiquitous water flow energy, pointing out another horizon for practical application of photocatalytic technology.

Background Few studies have investigated whether maternal age and education level modify the association of chronic hepatitis B virus (HBV) infection with preterm labor. We hypothesized that the association of HBV infection with preterm labor is modified by maternal age and education level. Methods A retrospective cohort study was conducted on the HBsAg-positive and HBsAg-negative pregnant women delivered from June 2012 to August 2017 at Wuhan Medical Care Center for Women and Children, Wuhan, China. A multivariate regression model was used in this study. Results This study included 2050 HBsAg-positive pregnant women and 2050 HBsAg negative women. In the stratified analyses, positive HBsAg status was associated with the increased risk of preterm labor in women aged p = 0.023), educational level (p = 0.002). After adjusting other co-variables, we observed maternal HBV infection (OR 1.60, 95% CI 1.03–2.49) was still associated with risk of preterm labor in pregnancy women with age Conclusions Our results indicated that HBV infection was associated with high risk of preterm labor, but maternal age and educational level could modify the association between HBV infection and preterm labor.

ObjectivesFamilial aggregation of primary Sjögren’s syndrome (pSS), systemic lupus erythematosus (SLE), rheumatoid arthritis (RA) and co-aggregation of these autoimmune diseases (ADs) (also called familial autoimmunity) is well recognised. However, the genetic predisposition variants that explain this clustering remains poorly defined.MethodsWe used whole-exome sequencing on 31 families (9 pSS, 11 SLE, 6 RA and 5 mixed autoimmunity), followed by heterozygous filtering and cosegregation analysis of a family-focused approach to document rare variants predicted to be pathogenic byin silicoanalysis. Potential importance in immune-related processes, gene ontology, pathway enrichment and overlap analyses were performed to prioritise gene sets.ResultsA range from 1 to 50 rare possible pathogenic variants, including 39 variants in immune-related genes across SLE, RA and pSS families, were identified. Among this gene set, regulation of T cell activation (p=4.06×10−7) and T cell receptor (TCR) signalling pathway (p=1.73×10−6) were particularly concentrated, includingPTPRC(CD45),LCK,LAT–SLP76complex genes (THEMIS,LAT,ITK,TEC,TESPA1,PLCL1),DGKD,PRKD1,PAK2andNFAT5, shared across 14 SLE, RA and pSS families. TCR-interactive genesP2RX7,LAG3,PTPN3andLAX1were also detected. Overlap analysis demonstrated that the antiviral immunity geneDUS2variant cosegregated with SLE, RA and pSS phenotypes in an extended family, that variants in the TCR-pathway genesCD45,LCKandPRKD1occurred independently in three mixed autoimmunity families, and that variants inCD36andVWA8occurred in both RA-pSS and SLE-pSS families.ConclusionsOur preliminary results define common genetic characteristics linked to familial pSS, SLE and RA and highlight rare genetic variations in TCR signalling pathway genes which might provide innovative molecular targets for therapeutic interventions for those three ADs.

Objective Idiopathic inflammatory myositis-associated interstitial lung disease (IIM-ILD) significantly increases morbidity and mortality. Lung ultrasound B-lines and Krebs von den Lungen-6 (KL-6) are identified as new sonographic and serum markers of ILD, respectively. The aim of our work was to assess the role of B-lines and KL-6 as markers of the severity of IIM-ILD. For this purpose, the correlation among B-lines score, serum KL-6 levels, high-resolution CT (HRCT) score, and pulmonary function tests were investigated in IIM-ILD patients. Methods Thirty-eight patients with IIM-ILD underwent chest HRCT scans, lung ultrasound and pulmonary function tests (independently performed within 1 week) examination. To assess severity and extent of ILD at HRCT, the Warrick score was used. The B-lines score denoting the extension of ILD was calculated by summing the number of B-lines on a total of 50 scanning sites. Serum KL-6 levels (U/ml) was measured by chemiluminescent enzyme immunoassay. Results A significant correlation was found between the B-lines score and serum KL-6 levels (r = 0.43, P Conclusion B-lines score and serum KL-6 levels correlate with HRCT findings and pulmonary function tests, supporting their use as measures of IIM-ILD severity.

Hyperdense middle cerebral artery sign (HMCAS) on admitting to neuroimaging is reported to have prognostic value for poor outcomes after thrombolysis, while evidence from studies comprising a sufficiently large sample size is limited. To detect prognostic predictors after thrombolysis could help improve therapeutic clinical strategies for acute ischemic stroke. We included prospective and retrospective studies of stroke patients that were treated with intravenous thrombolysis, in which functional outcomes (ie, a modified Rankin scale [mRS]) and systematic intracranial hemorrhage (sICH) were assessed in relation to HMCAS during pretreatment head CT. Random-effects models were used to calculate pooled risk ratios (RR) of poor outcomes and sICH for HMCAS patients as compared to patients without HMCAS. Eleven studies permitted identification of 11 818 patients. The risk of poor outcome at 3 months in the HMCAS-positive group was 1.56-fold the negative group (RR, 1.56; 95% CI 1.50-1.62; P < .001). The sICH risk when comparing both groups was found to be non-significant. Sensitivity analysis regarding studies performing thrombolysis within 3 hours also exhibited significant differences in their functional outcomes (RR, 1.56, 95% CI 1.49-1.62; P < .001) in patients with HMCAS as compared to non-HMCAS patients, although this was true for sICH risk. The presence of HMCAS on pretreatment CT predicts a poor outcome at 3 months after intravenous thrombolysis, while its relationship with the incidence of sICH was found to have no statistic value. Our study implies that more aggressive treatment should be considered for HMCAS patients.