Search

The Baveno VII consensus recommends that spleen stiffness measurement (SSM) ≤40 kPa is safe for ruling out high-risk varices (HRVs) and avoiding endoscopic screening in patients who do not meet the Baveno VI criteria. This study aimed to validate the performance of the Baveno VII algorithm in individuals with HBV-related cirrhosis.Consecutive individuals with HBV-related cirrhosis who underwent liver stiffness measurement (LSM) and SSM - using a 50 Hz shear wave frequency, spleen diameter measurement, and esophagogastroduodenoscopy (EGD) were prospectively enrolled from June 2020. A 100 Hz probe has been adopted for additional SSM assessment since July 2021.From June 2020 to January 2022, 996 patients were screened and 504 were enrolled for analysis. Among the 504 patients in whom SSM was assessed using a 50 Hz probe, the Baveno VII algorithm avoided more EGDs (56.7% vs. 39.1%, p 0.001) than Baveno VI criteria, with a comparable missed HRV rate (3.8% vs. 2.5%). Missed HRV rates were5% for all other measures: 11.3% for LSM-longitudinal spleen diameter to platelet ratio score, 20.0% for platelet count/longitudinal spleen diameter ratio, and 8.8% for Rete Sicilia Selezione Terapia-hepatitis. SSM@100 Hz was assessed in 232 patients, and the Baveno VII algorithm with SSM@100 Hz spared more EGDs (75.4% vs. 59.5%, p 0.001) than that with SSM@50 Hz, both with a missed HRV rate of 3.0% (1/33).We validated the Baveno VII algorithm, demonstrating the excellent performance of SSM@50 Hz and SSM@100 Hz in ruling out HRV in individuals with HBV-related cirrhosis. Furthermore, the Baveno VII algorithm with SSM@100 Hz could safely rule out more EGDs than that with SSM@50 Hz.NCT04890730.The Baveno VII guideline proposed that for patients who do not meet the Baveno VI criteria, SSM ≤40 kPa could avoid further unnecessary endoscopic screening. The current study validated the Baveno VII algorithm using 50 Hz and 100 Hz probes, which both exhibited excellent performance in ruling out HRVs in individuals with HBV-related cirrhosis. Compared with the Baveno VII algorithm with SSM@50 Hz, SSM@100 Hz had a better capability to safely rule out unnecessary EGDs. Baveno VII algorithm will be a practical tool to triage individuals with cirrhosis in future clinical practice.

The accuracy of model for end-stage liver disease (MELD) and MELD with sodium (MELD-Na) scores in reflecting the clinical outcomes of patients with cirrhosis and portal vein thrombosis (PVT) remains unclear. This study aimed to evaluate the performance of scores in predicting 90-day mortality in patients with cirrhosis and PVT.Post hoc analysis was performed in two prospective cohorts (NCT02457637 and NCT03641872). The correlation between the MELD/MELD-Na score and 90-day liver transplantation (LT)-free mortality was investigated in patients with cirrhosis with and without PVT.In this study, 2826 patients with cirrhosis were included, and 255 (9.02%) had PVT. The cumulative incidence of 90-day LT-free mortality did not significantly differ between patients with and without PVT (log-rank P = 0.0854). MELD [area under the receiver operating curve (AUROC), 0.649 vs. 0.842; P = 0.0036] and MELD-Na scores (AUROC, 0.691 vs. 0.851; P = 0.0108) were compared in patients with and without PVT, regarding the prediction of 90-day LT-free mortality. In MELD 15 and MELD-Na 20 subgroups, patients with PVT had a higher 90-day LT-free mortality than those without PVT (7.91% vs. 2.64%, log-rank P = 0.0011; 7.14% vs. 3.43%, log-rank P = 0.0223), whereas in MELD ≥ 15 and MELD-Na ≥ 20 subgroups, no significant difference was observed between patients with and without PVT.The performance of MELD and MELD-Na scores in predicting 90-day LT-free mortality of patients with cirrhosis was compromised by PVT. MELD 15 or MELD-Na 20 may underestimate the 90-day LT-free mortality in patients with PVT.

Industrial cyber-physical-social systems (CPSSs), a prominent data-driven paradigm, tightly couple and coordinat social space into cyber-physical systems (CPSs) within industrial environments. With the proliferation of cloud-fog computing, cloud-fog computing becomes the most prominent computing paradigm used to implement industrial data analysis. However, the open environment of cloud-fog computing and the limited control of industrial CPSSs users make industrial data analysis without compromising users' privacy one great research challenge in practical cloud-fog-based industrial applications. High-order Bi-Lanczos (HOBI-Lanczos) approach has shown remarkable success in heterogeneous data analysis in industrial applications. In this paper, a novel privacy preserving HOBILanczos approach using tensor train in cloud-fog computing is proposed for industrial data applications. Specifically, a privacy preserving industrial data analysis model using cloud-fog computing and tensor train is firstly proposed. The proposed model enables fogs and clouds to securely carry out industrial data analysis for large-scale tensors given in a tensor train format. In addition, by using this model, a privacy preserving HOBILanczos approach is provided. Last but not least, by using a brain-controlled robot system case study, the proposed approach is theoretically and empirically analyzed. Our proposed approach is proven to be secure. A series of experiments corroborate the superiority of the proposed approach in cloud-fog computing for industrial applications.

Xiuhua Jiang,1,* Shiqi Chai,1,* Yan Huang,2,* Zuxiong Huang,3,* Wenting Tan,4,* Yanhang Gao,5,* Xiaobo Lu,6,* Zhongji Meng,7,* Huayou Zhou,8 Wenbing Kong,8 Xiaoting Tang,1 Yujun Tang,1 Tingting Qi,1 Chengjin Liao,2 Qiaorong Gan,3 Xiaomei Xiang,4 Yanan Zhang,5 Shuai Wang,6 Yuanyuan Chen,7 Jinjun Chen1,9 1Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 2Department of Infectious Diseases, Hunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, People’s Republic of China; 3Department of Hepatology, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, People’s Republic of China; 4Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, People’s Republic of China; 5Department of Hepatology, the First Hospital of Jilin University, Changchun, People’s Republic of China; 6Infectious Disease Center, the First Affiliated Hospital of Xinjiang Medical University, Urumqi, People’s Republic of China; 7Department of Infectious Diseases, Hubei Clinical Research Center for Precise Diagnosis and Treatment of Liver Cancer, Taihe Hospital, Hubei University of Medicine, Shiyan, People’s Republic of China; 8Department of Blood Transfusion, Nanfang Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 9Hepatology Unit, Zengcheng Branch, Nanfang Hospital, Southern Medical University, Guangzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jinjun Chen, Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Dadao Bei, Guangzhou, 510515, People’s Republic of China, Email chjj@smu.edu.cnBackground: Acute-on-chronic liver failure (ACLF) has high short-term mortality and lacks sufficient medical therapy. Available algorithms are unable to precisely predict short-term outcomes or safely stratify patients with ACLF as emergent liver transplantation candidates. Therefore, a personalized prognostic tool is urgently needed.Purpose: Platelet function and its clinical significance in ACLF patients with chronic hepatitis B virus (HBV) infection have not been investigated. This study aimed to assess changes in platelet function using thromboelastography (TEG) and platelet mapping (TEG-PM) in HBV-related ACLF patients.Methods: Chronic liver disease patients with acute decompensation or acute hepatic injury were recruited. The derivation cohort enrolled HBV-related patients at Nanfang Hospital. HBV-related and non-HBV-related patients were both enrolled in internal and external validation cohorts at seven university hospitals. TEG and TEG-PM were performed at baseline in the derivation cohort and baseline, day 7, and day 14 in the validation cohorts. The primary outcome was all-cause 28-day mortality. Status check and new-onset complications were recorded during the 3-month follow-up, but status check will extend to 5 years.Conclusion and Future Plans: In this study, 586 participants were enrolled, including 100 in derivation cohort, 133 in internal validation cohort, and 353 in external validation cohort. Biomaterials, including plasma, serum, urine, and some explanted liver tissues, were collected from these patients. A 3-month follow-up with survival status was completed. The baseline characteristics indicated that 51% of the patients had adenosine diphosphate (ADP)-hyporesponsive circulating platelets. The prognostic potential of platelet function will be explored in the derivation cohort (HBV-related ACLF patients) and further substantiated in the validation cohorts (HBV-related and non-HBV-related ACLF patients). Biosamples are currently used to explore the underlying mechanisms related to ADP-hyporesponsive platelets. The ongoing proteomic and metabolic analyses will provide new insights into the pathogenesis of extrahepatic organ failures in ACLF patients.Keywords: acute-on-chronic liver failure, coagulopathy failure, platelet function, thromboelastography, prognosis, study design

Background There is growing recognition of natural history, complications, and outcomes of patients who develop non-acetaminophen (APAP) drug-induced acute liver failure (ALF). To clarify high-risk factors and develop a nomogram model to predict transplant-free survival (TFS) in patients with non-APAP drug-induced ALF. Methods Patients with non-APAP drug-induced ALF from 5 participating centers were retrospectively analyzed. The primary endpoint was 21-day TFS. Total sample size was 482 patients. Results Regarding causative agents, the most common implicated drugs were herbal and dietary supplements (HDS) (57.0%). The hepatocellular type (R ≥ 5) was the main liver injury pattern (69.0%). International normalized ratio, hepatic encephalopathy grades, the use of vasopressor, N-acetylcysteine, or artificial liver support system were associated with TFS and incorporated to construct a nomogram model (drug-induced acute liver failure-5, DIALF-5). The AUROC of DIALF-5 for 7-day, 21-day, 60-day, and 90-day TFS in the internal cohort were 0.886, 0.915, 0.920, and 0.912, respectively. Moreover, the AUROC of DIALF-5 for 21-day TFS had the highest AUROC, which was significantly higher than 0.725 of MELD and 0.519 of KCC (p p > 0.05). These results were successfully validated in the external cohort (147 patients). Conclusions Based on easily identifiable clinical data, the novel DIALF-5 model was developed to predict transplant-free survival in non-APAP drug-induced ALF, which was superior to KCC, MELD and had a similar prediction performance to ALFSG-PI but is more convenient, which can directly calculate TFS at multiple time points.

IntroductionInflammatory bowel disease (IBD) and irritable bowel syndrome (IBS) are lifelong digestive diseases that severely impact patients’ quality of life. The existence of a causal association between IBS and IBD remains unclear. This study aimed to determine the direction of causality between IBD and IBS by quantifying their genome-wide genetic associations and performing bidirectional two-sample Mendelian randomization (MR) analyses.MethodsGenome-wide association studies (GWAS) among a predominantly European patient cohort identified independent genetic variants associated with IBS and IBD. Two separate databases (a large GWAS meta-analysis and the FinnGen cohort) for both IBS and IBD were consulted to retrieve statistics on instrument-outcome associations. MR analyses included inverse-variance-weighted, weighted-median, MR-Egger regression, MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) methods, and sensitivity analyses were performed. The MR analyses were carried out for each outcome data, followed by a fixed-effect meta-analysis.ResultsGenetically predicted IBD was associated with an increased risk of IBS. Odds ratios (95% confidence intervals) for samples of 211,551 (17,302 individuals with IBD), 192,789 (7,476 Crohn’s disease cases), and 201,143 (10,293 ulcerative colitis cases) individuals were 1.20 (1.00, 1.04), 1.02 (1.01, 1.03), and 1.01 (0.99, 1.03), respectively. After outlier correction using MR-PRESSO, the odds ratio for ulcerative colitis was 1.03 (1.02, 1.05) (p = 0.001). However, an association between genetically influenced IBS and IBD was not identified.DiscussionThis study confirms that IBD is causally related to IBS, which may interfere with the diagnosis and treatment of both diseases.

Background Bacterial resistance leads to the dilemma in the treatment with synthetic antibiotics. A new alternative strategy is to develop some safe and non-toxic natural antibiotics as alternative therapeutic drugs. The aims of this research were to determine the saponins extracted from fresh fruit of Luffa acutangula, to evaluate their antibacterial property by inhibiting the formation of biofilm, and to reveal the mechanism in ultrastructural surface. Methods the saponin components were extracted and isolated from Fresh Fruit of Luffa acutangula by organic solvents extraction; their chemical structures were identified by HPLC-MS/MS. The growth inhibition curves and the 50% inhibitory concentrations (IC50) were used to evaluate the antibacterial activity of the extract. Then, crystal violet staining method was accepted to investigate the capacity of the saponins to inhibit biofilm formation. Anti-biofilm activity was assessed with minimum biofilm inhibitory concentration (MBIC). The interaction of the chemical compounds with saponins and biofilm were observed by SEM in ultrastructural surface. Results the extract by n-butanol was mainly saponins and the total content of saponins in the extract was 322.58 mg/g. nine saponin compounds were identified in n-butanol extract and the saponin compounds were mainly triterpene aglycone and triterpene glucosides. The extracted saponins have great bacteriostasis with IC50 value 3mg/ml, and the saponins can also inhibite the biofilm formation with MBIC value 16mg/ml. Conclusions the saponins extracted from fresh fruit of Luffa acutangula could inhibit multidrug resistance Staphylococcus aureus and substantially eradicate biofilm, it may be a potential to be developed as antibacterial agent.

Huge amounts of unstructured data including image, video, audio, and text are ubiquitously generated and shared, and it is a challenge to protect sensitive personal information in them, such as human faces, voiceprints, and authorships. Differential privacy is the standard privacy protection technology that provides rigorous privacy guarantees for various data. This survey summarizes and analyzes differential privacy solutions to protect unstructured data content before it is shared with untrusted parties. These differential privacy methods obfuscate unstructured data after they are represented with vectors and then reconstruct them with obfuscated vectors. We summarize specific privacy models and mechanisms together with possible challenges in them. We also discuss their privacy guarantees against AI attacks and utility losses. Finally, we discuss several possible directions for future research.

Background the incidence of acute-on-chronic liver disease (AoCLD) is increasing. Objective to investigate the clinical features and risk factors of AoCLD and construct an effective prognostic nomogram model for older patients with AoCLD. Methods data from 3,970 patients included in the CATCH-LIFE study were used, including 2,600 and 1,370 patients in the training and validation sets, respectively. Multivariate Cox regression analyses were performed to identify predictive risk factors in older individuals, and an easy-to-use nomogram was established. Performance was assessed using area under the curve, calibration plots and decision curve analysis (DCA). Results of the 3,949 patients with AoCLD, 809 were older with a higher proportion of autoimmune-related abnormalities, hepatitis C viral infection and schistosomiasis. In the older patient group, the incidence of cirrhosis, hepatic encephalopathy (HE), infection, ascites and gastrointestinal bleeding; neutrophil-to-lymphocyte ratio (NLR), aspartate-to-alanine transaminase ratio (AST/ALT), creatinine and blood urea nitrogen levels were higher, whereas incidence of acute-on-chronic liver failure, white blood cell, platelet and haemoglobin levels; albumin, total bilirubin (TB), AST and ALT levels; international normalised ratio (INR), estimated glomerular filtration rate and blood potassium levels were lower than in the younger group. The final nomogram was developed based on the multivariate Cox analysis in training cohort using six risk factors: ascites, HE grades, NLR, TB, INR and AST/ALT. Liver transplantation-free mortality predictions were comparable between the training and validation sets. DCA showed higher net benefit for the nomograph than the treat-all or treat-none strategies, with wider threshold probabilities ranges. Conclusions our analysis will assist clinical predictions and prognoses in older patients with AoCLD.

BackgroundThe accurate prediction of the outcome of hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is impeded by population heterogeneity. The study aimed to assess the impact of underlying cirrhosis on the performance of clinical prediction models (CPMs).MethodsUsing data from two multicenter, prospective cohorts of patients with HBV-ACLF, the discrimination, calibration, and clinical benefit were assessed for CPMs predicting 28-day and 90-day outcomes in patients with cirrhosis and those without, respectively.ResultsA total of 919 patients with HBV-ACLF were identified by Chinese Group on the Study of Severe Hepatitis B (COSSH) criteria, including 675 with cirrhosis and 244 without. COSSH-ACLF IIs, COSSH-ACLFs, Chronic Liver Failure-Consortium Acute-on-Chronic Liver Failure score (CLIF-C ACLFs), Tongji Prognostic Predictor Model score (TPPMs), Model for End-Stage Liver Disease score (MELDs), and MELD-Sodium score (MELD-Nas) were all strong predictors of short-term mortality in patients with HBV-ACLF. In contrast to a high model discriminative capacity in ACLF without cirrhosis, each prognostic model represents a marked decline of C-index, net reclassification index (NRI), and integrated discrimination improvement (IDI) in predicting either 28-day or 90-day prognosis of patients with cirrhosis. The hazard analysis identified largely overlapping risk factors of poor outcomes in both subgroups, while serum bilirubin was specifically associated with short-term mortality in patients with cirrhosis and blood urea nitrogen in patients without cirrhosis. A subgroup analysis in patients with cirrhosis showed a decline of discrimination of CPMS in those with ascites or infections compared to that in those without.ConclusionPredicting the short-term outcome of HBV-ACLF by CPMs is optimal in patients without cirrhosis but limited in those with cirrhosis, at least partially due to the complicated ascites or infections.

Empirical antibiotic therapy in patients with spontaneous bacterial peritonitis (SBP) is common as pathogen(s) are identified in only 5%-20% patients using conventional culture-based techniques. Metagenome next-generation sequencing (mNGS) test is a promising approach for the diagnosis of infectious disease. The clinical application of mNGS for infected ascites in cirrhotic patients is rarely reported. Here, we describe three cases to preliminarily explore the potential role of mNGS for microbiological diagnosis of ascites infection in an exploratory manner. The clinical performance of ascites mNGS in cirrhotic patients remains to be further evaluated.

As the application scenarios of recommendation algorithms are becoming increasingly complex, the efficiency of traditional recommendation algorithm based on accuracy is no longer satisfied. To solve this problem, an improved matrix factorization based model for many-objective optimization recommendation is proposed to simultaneously optimize the four recommendation objectives of novelty, diversity, accuracy, and recall. As a novel double-layer recommendation model, two improved algorithms are composed: 1) For the bottom layer, an improved matrix factorization algorithm with additional regularization constraints is used to predict unknown item ratings; 2) For the top layer, the recommendation list is optimized by a many-objective evolutionary algorithm . Comprehensive experiments demonstrate that the proposed model can effectively improve the four recommended evaluation metrics . And a recommended list with novel and diverse items is provided for users in a more efficient way while maintaining accuracy.

While the industrial Internet of Things (IIoT) can support efficient control of the physical world through large amounts of industrial data, data security has been a challenge due to various interconnections and accesses. Blockchain technology can support security and privacy preservation in IIoT data with its trusted and reliable security mechanism. Sharding technology can help improve the overall throughput and scalability of blockchain networks. However, the effectiveness of sharding is still challenging due to the uneven distribution of malicious nodes. By aiming to improve the performance of blockchain networks and reduce the possibility of malicious node aggregation, in this article, we propose a many-objective optimization algorithm based on the dynamic reward and penalty mechanism (MaOEA-DRP) to optimize the shard validation validity model. Then, an optimal blockchain sharding scheme is obtained. Compared with other state-of-the-art many-objective optimization algorithms, MaOEA-DRP performs better on the DTLZ test suite. The simulation results demonstrate that our proposed algorithm can significantly improve the throughput and validity of sharding for better security in the blockchain-enabled IIoT.

Background This study aimed to assess the association between metabolic syndrome (MetS) and severity of nonalcoholic fatty liver disease (NAFLD), and to discuss the pathological relevance of the diagnostic criteria in metabolic (dysfunction) associated fatty liver disease (MAFLD). Methods This was a multicenter, cross-sectional study. Patients with NAFLD confirmed by liver biopsy were enrolled between July 2016 and December 2018 from 14 centers across the mainland of China. Anthropometric and metabolic parameters were collected to assess the pathological relevance. Results Of 246 enrolled patients with NAFLD, 150 (61.0%) had the comorbidity of MetS. With the increase of metabolic components, the proportions of nonalcoholic steatohepatitis (NASH) and significant fibrosis were notably increased. The comorbid three metabolic components significantly increased the proportion of NASH, and further increase of metabolic components did not increase the proportion of NASH. However, the increase of metabolic components was parallel to the increase of the proportion of liver fibrosis. Among the 246 patients, 239 (97.2%) met the diagnostic criteria of MAFLD. Although non-MAFLD patients had less NASH, they present with similar proportion of significant fibrosis and cirrhosis. In the diagnostic criteria of MAFLD, BMI ≥ 23 kg/m2 was related to NASH (Mantel-Haenszel Common Estimate OR: 2.975; 95% CI: 1.037–8.538; P = 0.043), and T2DM was related to significant fibrosis (Mantel-Haenszel Common Estimate OR: 2.531; 95% CI: 1.388–4.613; P = 0.002). The homeostasis model assessment of insulin resistance (HOMA-IR) ≥ 2.5 was the most significant factor for NASH (OR: 4.100; 95% CI: 1.772–9.487; P = 0.001) and significant factor for liver fibrosis (OR: 2.947; 95% CI: 1.398–6.210; P = 0.004) after the adjustments of the BMI and diabetes. Conclusions Metabolic dysregulations are important risk factors in NAFLD progression. The insulin resistance status may play a predominant role in the progression in MAFLD patients.

Introduction Acute-on-chronic liver failure (ACLF) patients are susceptible to invasive fungal infections. We evaluated the prognosis and antifungal options in ACLF patients with invasive pulmonary aspergillosis (IPA). Methods ACLF patients with IPA from 15 hospitals were retrospectively screened from 2011 to 2018, and 383 ACLF patients without lung infections were included from a prospective cohort (NCT02457637). Demographic, laboratory, clinical data, and 28-day outcomes were documented in the two cohorts. Results ACLF patients with probable IPA (n = 145) had greater 28-day mortality (33.6% vs. 15.7%, p

BACKGROUND Chronic liver diseases (CLD), including cirrhosis and non-cirrhotic liver diseases, are globally widespread and create a serious disease burden. Platelet count is a clinically accessible and affordable prognostic indicator of liver disease. We investigated the relationship between platelet count and 90-day prognosis in patients with acute-on-chronic liver diseases (AoCLD). METHODS A total of 3,970 patients with AoCLD from the Chinese Acute-on-Chronic Liver Failure (CATCH-LIFE) study, which included two prospective multi-center cohorts, were included in the study. We grouped the patients according to the platelet count and analyzed the 90-day adverse outcome (death or liver transplantation). RESULTS In the final analysis, 3,939 patients with AoCLD were included, of whom 2,802 had definite liver cirrhosis. The cumulative incidence of 90-day adverse outcomes in patients increased with the change of platelet group (log-rank P

Innate immunity is an ancient and evolutionarily conserved system that constitutes the first line of host defense against invading microbes. We previously determined that the GABAergic neuromuscular junction (NMJ) suppresses intestinal innate immunity via muscular insulin signaling. Here, we found that a muscular mitochondrial oxidative phosphorylation pathway of

The Internet-of-Things (IoT) technology is widely used in various fields. In the Earth observation system, hyperspectral images (HSIs) are acquired by hyperspectral sensors and always transmitted to the cloud for analysis. In order to reduce cost and reply promptly, we deploy artificial intelligence (AI) models for data analysis on edge servers. Subspace clustering, the core of the AI model, is employed to analyze high-dimensional image data such as HSIs. However, most traditional subspace clustering algorithms construct a single model, which can be affected by noise more easily. It hardly balances the sparsity and connectivity of the representation coefficient matrix. Therefore, we proposed a postprocess strategy of subspace clustering for taking account of sparsity and connectivity. First, we define close neighbors as having more common neighbors and higher coefficients neighbors, where the close neighbors are selected according to the nondominated sorting algorithm. Second, the coefficients between the sample and close neighbors are reserved, incorrect, or useless connections are pruned. Then, the postprocess strategy can reserve the intrasubspace connection and prune the intersubspace connection. In experiments, we verified the universality and effectiveness of postprocessing strategies in the traditional image recognition field and IoT field, respectively. The experiment results demonstrate that the proposed strategy can process noise data in the IoT to improve clustering accuracy.

Background Obesity is typically associated with metabolic dysfunction, but its impact on hepatocellular carcinoma (HCC) remains unclear in patients with chronic hepatitis B (CHB). Aim To study the effect of obesity on HCC development in patients with CHB receiving antiviral therapy. Methods We included patients from a Chinese multicentre, prospective, observational, treated CHB cohort in this study. General obesity was evaluated by body-mass index (BMI). Central obesity was evaluated by waist circumference, waist-to-hip ratio and waist-to-height ratio. Results A total of 5754 nucleos(t)ide analogue treated patients were enrolled in the analysis. The 5-year cumulative incidence of HCC was 2.9%. Waist-to-height ratio performed better in predicting HCC development than BMI, waist circumference or waist-to-hip ratio. Patients with central obesity (defined as waist-to-height ratio >0.5) had significantly higher 5-year incidence of HCC than those without central obesity in the overall population (3.9% vs 2.1%, hazard ratio [HR]: 2.06, P = 0.0001) and 745 propensity score matched pairs (4.7% vs 2.3%, HR: 2.04, P = 0.026), respectively. Besides cirrhosis status and aMAP HCC risk score, central obesity was also independently associated with HCC risk (HR: 1.63, P = 0.013). Waist-to-height ratio gain within 1 year was associated with a significantly higher HCC risk with an adjusted HR value of 1.88 (95% confidence interval: 1.12-3.13, P = 0.017). Conclusions Central obesity, evaluated by the waist-to-height ratio, was associated with a twofold increase in HCC risk among CHB patients receiving antiviral treatment, highlighting the important role of abnormal metabolic function in the progression of liver disease.

Internet of Things (IoT) is a huge network and establishes ubiquitous connections between smart devices and objects. The flourishing of IoT leads to an unprecedented data explosion, traditional data storing or processing techniques have the problem of low efficiency, and if the data are used maliciously, the security loss may be further caused. Multicloud is a high-performance secure computing platform, which combines multiple cloud providers for data processing, and the distributed multicloud platform ensures the security of data to some extent. Based on multicloud and task scheduling in IoT, this article constructs a many-objective distributed scheduling model, which includes six objectives of total time, cost, cloud throughput, energy consumption, resource utilization, and balancing load. Furthermore, this article presents a many-objective intelligent algorithm with sine function to implement the model, which considers the variation tendency of diversity strategy in the population is similar to the sine function. The experimental results demonstrate excellent scheduling efficiency and hence enhancing the security. This work provides a new idea for addressing the difficult problem of data processing in IoT.

With accelerated ensemble of the Internet of Things technology and automotive industry, vehicular network has been established as powerful tools. However, it is a significant challenge for dynamic and heterogeneous vehicular network to meet high requirements of the sixth-generation (6G) network such as high reliability and high security. To address this challenge, we design a novel weight-based ensemble machine learning algorithm (WBELA) to identify abnormal messages of vehicular Controller Area Network (CAN) bus network. Then, we establish a model based on many-objective optimization for intrusion detection of CAN bus network. To support this model, a many-objective optimization algorithm based on balance convergence and diversity (MaOEA-BCD) is designed. Open-source CAN bus message data sets and tamper attack scenarios are used to evaluate the effectiveness of proposed algorithm for different ID data frames. Experimental results revealed that proposed methods significantly enhance precision, reduce the false positive rate and have better performance than other methods so as to enhance security of vehicular networks in 6G.

The acute-on-chronic liver failure (ACLF) development is highly dynamic. Currently, no satisfactory algorithm identifies patients with HBV at risk of this complication. The aim of the study was to characterize ACLF development in hospitalized HBV-related patients without previous decompensation and to test the performance of traditional prognostic models in ruling out ACLF development within 28 days on admission we conducted a cohort study. Two multi-center cohorts with hospitalized HBV-related previous compensated patients were analyzed. Performances of MELD, MELD-Na, CLIF-C AD, and CLIF-C ACLF-D in ruling out ACLF development within 28 days were compared and further validated by ROC analyses. In the derivation cohort (n = 892), there were 102 patients developed ACLF within 28 days, with profound systemic inflammatory levels and higher 28-day mortality rate (31.4% vs. 1.0%) than those without ACLF development. The MELD score (cut-off = 18) achieved acceptable missing rate (missed/total ACLF development) at 2.9%. In the validation cohort (n = 1656), the MELD score (18) was able to rule out ACLF development within 28 days with missing rate at 3.0%. ACLF development within 28 days were both lower than 1% (0.6%, derivation cohort; 0.5%, validation cohort) in patients with MELD 18. While in patients with MELD ≥ 18, 26.6% (99/372, derivation cohort) and 17.8% (130/732, validation cohort) developed into ACLF within 28 days, respectively. While MELD-Na score cut-off at 20 and CLIF-AD score cut-off at 42 did not have consistent performance in our two cohorts. MELD 18 was able to safely rule out patients with ACLF development within 28 days in HBV-related patients without previous decompensation, which had a high 28-day mortality.

Background and AimsHepatitis B virus (HBV) reactivation is a serious condition and has been extensively described in chemotherapeutic immunosuppressive population. However, little is known about HBV reactivation in immunocompetent patients with chronic hepatitis B (CHB). In this study, we evaluated the prevalence and the clinical significance of HBV reactivation in CHB patients with acute exacerbations.MethodPatients were screened from two prospective multicenter observational cohorts (CATCH-LIFE cohort). A total of 1,020 CHB patients with previous antiviral treatment history were included to assess the prevalence, risk factors, clinical characteristics of HBV reactivation, and its influence on the progression of chronic liver disease.ResultsThe prevalence of HBV reactivation was 51.9% in CHB patients with acute exacerbations who had antiviral treatment history in our study. Among the 529 patients with HBV reactivation, 70.9% of them were triggered by discontinued antiviral treatment and 5.9% by nucleos(t)ide analogs (NUCs) resistance. The prevalence of antiviral treatment disruption and NUCs resistance in patients with HBV reactivation is much higher than that in the patients without (70.9% vs. 0.2%, and 5.9% vs. 0, respectively, both p p p p = 0.005), and short-term death (14.0% vs. 5.9% for 28-day, and 23.3% vs. 12.4% for 90-day, both p p = 0.005), as well as hepatic encephalopathy, ascites, and bacterial infection.ConclusionThis study clearly demonstrated that there was a high prevalence of HBV reactivation in CHB patients, which was mainly triggered by discontinued antiviral treatment. The HBV reactivation strongly increased the risk of developing hepatic failure, ACLF and short-term death in HBV-related cirrhotic patients, which may suggest that HBV reactivation would be a new challenge in achieving the WHO target of 65% reduction in mortality from hepatitis B by 2030.

Background Budd-Chiari syndrome (BCS), especially BCS-hepatic vein occlusion type (BCS-HV), and Pyrrolizidine alkaloids-induced hepatic sinusoidal obstructive syndrome (PA-HSOS) share many clinical characteristics. In this study, we comprehensively compare the two diseases to identify key characteristics. Methods 139 patients with BCS-HV and 257 PA-HSOS patients admitted to six hospitals between January 2014 and October 2021 were retrospectively analyzed. The two groups were then comprehensively compared and analyzed clinically. Results Among the 139 BCS-HV and 257 PA-HSOS patients, the mean age and the median time from symptom onset to the first visit have a statistical difference. 257 PA-HSOS patients all had a history of taking PA-containing plants, while no patients in the BCS-HV group were exposed to PA-containing plants (p

Grass carp hemorrhagic disease is a fatal disease caused by the grass carp reovirus (GCRV). The aberrant regulation of transcripts has been implicated in many types of diseases. In the present study, we characterized mRNA and miRNA transcriptomes of different virulent GCRVs using RNA sequencing (RNA-Seq). One hundred eighteen miRNAs were identified as being differentially expressed between different virulent viruses in grass carp fibroblasts. Eight miRNAs were selected to verify the RNA-Seq results using RT-PCR and mRNA methods. In total, 996 differentially expressed mRNA genes were identified in grass carp fibroblasts, while 901 miRNA-mRNA target pairs were observed to be inversely regulated in grass carp fibroblasts. Integrated mRNA/miRNA expression profiling analysis results showed that the most influenced processes were the immune response and cell death. Three miRNAs were shown to exhibit the same expression patterns when two different methods were used and had important functions during viral infection. These results provide insights into the miRNA-mediated regulation of mRNA and valuable resources on transcript variation and regulation during GCRV infection, which are potentially useful for mechanistic and drug studies.

Recommendation system is a technology that can mine user's preference for items. Explainable recommendation is to produce recommendations for target users and give reasons at the same time to reveal reasons for recommendations. The explainability of recommendations that can improve the transparency of recommendations and the probability of users choosing the recommended items. The merits about explainability of recommendations are obvious, but it is not enough to focus solely on explainability of recommendations in field of explainable recommendations. Therefore, it is essential to construct an explainable recommendation framework to improve the explainability of recommended items while maintaining accuracy and diversity. An explainable recommendation framework based on knowledge graph and multi-objective optimization is proposed that can optimize the precision, diversity and explainability about recommendations at the same time. Knowledge graph connects users and items through different relationships to obtain an explainable candidate list for target user, and the path between target user and recommended item is used as an explanation basis. The explainable candidate list is optimized through multi-objective optimization algorithm to obtain the final recommendation list. It is concluded from the results about experiments that presented explainable recommendation framework provides high-quality recommendations that contains high accuracy, diversity and explainability.

The fifth generation (5G) mobile communication technology brings people a higher perceived rate experience, the high-quality service of high-density user connection, and other commercial applications. As an important means of data processing in 5G heterogeneous networks (HetNets), data fusion technology is faced with a large number of malicious code attacks. Thus, it is particularly important to find an efficient malicious code detection method. However, in the traditional research, due to dataset imbalance, the complexity of the deep learning network model, the use of a single-objective algorithm, and other factors, it brings greater loss and lower detection accuracy. Therefore, how to choose a suitable network model and improve the data classification accuracy in HetNets is a big challenge. To enhance the model's robustness, a multi-objective restricted Boltzmann machine (RBM) model is designed for training. In this article, evaluation indices are used to comprehensively measure the effect of data classification, introducing a strategy pool to improve the effect of data fusion and using non-dominated sorting genetic algorithms (NSGA-II) to deal with the imbalanced malware family. Experimental results demonstrate that the proposed multi-objective RBM model combined with NSGA-II can effectively enhance the data classification accuracy of HetNets and reduce the loss in the process of data fusion.

There exist communication barriers between the deaf people and the listeners. Sign language translation is a reasonable and effective way to break these barriers. Recognition of sign language symbols is an essential part of sign language translation. Sign language digits of (0–9) and alphabetic letters of (A–Z) are elementary but important symbols of sign languages of different countries or regions. Capsule networks (CapsNet) are promising alternative to convolutional neural networks (CNN), which take into account of the spatial relationships and orientations of the features of an entity. For sign language digits and alphabets recognition tasks, the proposed SLR-CapsNet architecture achieves a start-of-the-art test accuracy of 99.52% with 100*100 RGB input size and 99.94% with 32*32 RGB input size on Sign Language Digits Dataset and 99.60% with 28*28 Gray-scale input on Sign Language MNIST Dataset. The experimental results also prove that CapsNet has higher generalization and expressiveness capacity on unseen data than CNN dose. Another important finding in our work is that SLR-CapsNet is robust to routing iterations, i.e., its performance will not be affected by various routing iterations.

To date, several studies have investigated the influence of micoplastics (MPs) on scleractinian coral. However, research of MPs on button polyps (Protopalythoa sp.) is still in its infancy. This st...

Leaves and flowers of Amorphophallus konjac do not develop simultaneously thus unique features can be elucidated through study of flowering transformation in A. konjac. In this study, transcriptome libraries of A. konjac leaf buds (LB) and flower buds (FB) were constructed followed by high-throughput sequencing. A total of 68,906 unigenes with an average length of 920 bp were obtained after library assembly. Out of these genes, 24,622 unigenes had annotation information. A total of 6859 differentially expressed genes (DEGs) were identified through differential expression analysis using LB as control. Notably, 2415 DEGs were upregulated whereas 4444 DEGs were downregulated in the two transcriptomes. Go and KEGG analysis showed that the DEGs belonged to 44 functional categories and were implicated in 98 metabolic pathways and 38 DEGs involved in plant hormone signal transduction. Several genes were mined that may be involved in A. konjac flower bud differentiation and flower organ development. Eight DEGs were selected for verification of RNA-seq results using qRT-PCR analysis. Two FLOWERING LOCUS T (FT) genes named AkFT1 and AkFT2 were identified though homologous analysis may be the florigen gene implicated in modulation of A. konjac flowering. These genes were significantly upregulated in flower buds compared with the expression levels on leaf buds. Overexpression of AkFT genes though heterologous expression in Arabidopsis showed that the transgenics flowered at a very early stage relative to wild type plants. These findings indicate that AkFT1 and AkFT2 function as regulation genes in A. konjac flowering development and the two genes may present similar functions during flowering transition.

Although the effect of bacterial infection on cirrhosis has been well-described, the effect of non-hepatotropic virus (NHV) infection is unknown. This study evaluated the genome fragments of circulating microorganisms using metagenomic next-generation sequencing (mNGS) in individuals with acute decompensation (AD) of cirrhosis, focusing on NHVs, and related the findings to clinical outcomes.Plasma mNGS was performed in 129 individuals with AD of cirrhosis in the study cohort. Ten healthy volunteers and 20, 39, and 81 individuals with stable cirrhosis, severe sepsis and hematological malignancies, respectively, were enrolled as controls. Validation assays for human cytomegalovirus (CMV) reactivation were performed in a validation cohort (n = 58) and exploratory treatment was instituted.In the study cohort, 188 microorganisms were detected in 74.4% (96/129) of patients, including viruses (58.0%), bacteria (34.1%), fungi (7.4%) and chlamydia (0.5%). A NHV signature was identified in individuals with AD, and CMV was the most frequent NHV, which correlated with the clinical effect of empirical antibiotic treatment, progression to acute-on-chronic liver failure, and 90-day mortality. The NHV signature in individuals with acute-on-chronic liver failure was similar to that in those with sepsis and hematological malignancies. CMV was detected in 24.1% (14/58) of patients in the validation cohort. Of the 14 cases with detectable CMV by mNGS, nine were further validated by real-time PCR or pp65 antigenemia testing. Three patients with CMV reactivation received ganciclovir therapy in an exploratory manner and experienced clinical resolutions.The results of this study suggest that NHVs may play a pathogenic role in complicating the course of AD. Further validation is needed to define whether this should be incorporated into the routine management of individuals with AD of cirrhosis.A non-hepatotropic virus (NHV) signature, which was similar to that in individuals with sepsis and hematological malignancies, was identified in individuals with acute decompensation of cirrhosis. The detected viral signature had clinical correlates, including clinical efficacy of empirical antibiotic treatment, progression to acute-on-chronic liver failure and short-term mortality. Cytomegalovirus reactivation, which is treatable, may adversely affect clinical outcomes in some individuals with decompensated cirrhosis. Routine screening for NHVs, especially cytomegalovirus, may be useful for the management of individuals with acute decompensation of cirrhosis.

The α2δ-1 protein coded by

Introduction Sepsis is a complication in acute-on-chronic liver failure (ACLF) patients associated with high rates of mortality and morbidity. Early diagnosis of sepsis in ACLF patients can improve prognosis. This study aimed to explore potential effective biomarkers for the early diagnosis of sepsis in ACLF patients. Methods Ninety-four ACLF patients with sepsis were enrolled from 10 hospitals across China from January 2015 to June 2016 as well as 49 ACLF patients without infection from Xiangya Hospital. The first-day admission data and SOFA score and CLIF-SOFA score were collected. The differences of indicators between groups were compared with Kruskal-Wallis test. The receiver-operating characteristic (ROC) curve was analyzed to evaluate the diagnostic efficiency of the selected factors. Results Soluble triggering receptor expressed on myeloid cell-1 (sTREM-1) and presepsin were significantly higher in ACLF-sepsis patients compared with ACLF patients with no infection (P