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Background: The lack of effective non-invasive diagnostic methods for liver fibrosis hinders timely treatment for chronic hepatitis B (CHB) patients, leading to the progression of advanced liver disease. Circulating microRNAs offer a non-invasive approach to fibrosis assessment. MicroRNA-15a/16-1 (miR-15a/16) was reported to be implicated in fibrosis development, but the role of plasma miR-15a/16 in liver fibrosis assessment remains poorly understood. This study explored the importance of plasma miR-15a/16 in assessing liver fibrosis severity of CHB patients. Methods: Quantitative PCR was utilized to measure the levels of plasma miR-15a/16 in 435 patients with CHB and 74 healthy controls. We assessed the correlation between plasma miR-15a/16 levels and liver fibrosis and cirrhosis using Pearson correlation coefficients, multivariate linear and logistic regression models, and smooth curve fitting. Utilizing the receiver operating characteristic (ROC) curve, we examined the diagnostic potential of plasma miR-15a/16 in severe fibrosis and cirrhosis. Results: Plasma levels of miR-15a/16 in patients with CHB were significantly reduced compared to those in healthy controls. In the CHB cohort, levels were notably decreased in individuals with severe fibrosis or cirrhosis compared to those without severe fibrosis or cirrhosis. Plasma miR-15a/16 levels exhibited a negative relationship with the severity of liver fibrosis, gradually decreasing as the histological fibrosis stage progressed from S0 to S4. Reduced levels of plasma miR-15a/16 were linked to an elevated risk of severe liver fibrosis (miR-15a: odds ratio [OR] = 0.243; 95 % confidence interval [CI]: 0.138, 0.427; miR-16: OR = 0.201; 95 % CI: 0.097, 0.417) and cirrhosis (miR-15a: OR = 0.153; 95 % CI: 0.079, 0.298; miR-16: OR = 0.064; 95 % CI: 0.025, 0.162). MiR-15a achieved an area under the ROC curve of 0.886 and 0.832 for detecting moderate-to-severe fibrosis (S2-S4) and cirrhosis, respectively. MiR-16 demonstrated similar diagnostic values. Conclusion: Plasma miR-15a/16 levels were negatively correlated with the severity of liver fibrosis in CHB patients and could serve as a new non-invasive indicator in evaluating liver fibrosis.

Objective To examine recent patterns regarding oral anticoagulant (OAC) use among patients hospitalised with atrial fibrillation (AF) and quantify the impact of insurance coverage for non-vitamin K oral anticoagulants (NOACs) on quality of care and care inequality regarding OAC use among hospitalised patients with AF.Design Interrupted time series analysis.Setting Hospitals in China.Participants A total of 36 393 patients hospitalised with non-valvular AF were involved between 2015 and 2019 across China.Primary and secondary outcome measures Outcome was the impact of insurance coverage for NOACs on quality of care regarding OAC prescription using interrupted time series analysis with segmented regression models.Results OAC prescription rate during hospitalisation was 52.1% (31.3% for warfarin and 20.8% for NOACs) in patients with high-risk AF and 66.3% (29.8% for warfarin and 36.5% for NOACs) in low-risk patients. Insurance coverage for NOACs was associated with an immediate 10.9% (95% CI 7.6% to 14.3%) increase in NOAC prescription and a 0.33% (95% CI 0.08% to 0.58%) increase in the slope of the secular trend of NOAC prescription among all the patients. Disparities in NOAC prescription among hospitals decreased from 18.9 before the insurance coverage for NOACs to 3.4 after that. Similar results were found in patients with high risk of stroke.Conclusion A large gap exists between clinical practice and guideline recommendations regarding OAC prescription among patients hospitalised with AF in China. Insurance coverage may be an effective healthcare strategy to improve quality of care and reduce care disparities regarding OAC prescription among patients with AF.Trial registration number NCT02309398.

Background and aims: Hepatocellular carcinoma (HCC), which is prevalent worldwide and has a high mortality rate, needs to be effectively diagnosed. We aimed to evaluate the significance of plasma microRNA-15a/16-1 (miR-15a/16) as a biomarker of hepatitis B virus-related HCC (HBV-HCC) using the machine learning model. This study was the first large-scale investigation of these two miRNAs in HCC plasma samples. Methods: Using quantitative polymerase chain reaction, we measured the plasma miR-15a/16 levels in a total of 766 participants, including 74 healthy controls, 335 with chronic hepatitis B (CHB), 47 with compensated liver cirrhosis, and 310 with HBV-HCC. The diagnostic performance of miR-15a/16 was examined using a machine learning model and compared with that of alpha-fetoprotein (AFP). Lastly, to validate the diagnostic efficiency of miR-15a/16, we performed pseudotemporal sorting of the samples to simulate progression from CHB to HCC. Results: Plasma miR-15a/16 was significantly decreased in HCC than in all control groups (P

Summary: The microbiota-gut-brain axis (MGBA) plays a pivotal role in drug addiction. However, the pathophysiological mechanism of MGBA in ketamine addiction remains elusive. The present study investigated the ketamine-induced gut microbiota disorders, intestinal barrier dysfunction, and the alterations in brain function, using a conditioned place preference (CPP) model of ketamine addiction in rats. Compared with the control group, ketamine induced decreased amplitude of low-frequency fluctuation (ALFF) values in the hippocampus, and pyknotic nuclei and concentrated cytoplasm in hippocampal neurons, as well as alterations in gut microbiota composition, shortened ileum villi, and thinner colonic mucosa. We also found that the abundance of gut microbiota exhibited correlations with CPP score, hippocampal ALFF value, length of ileum villi, and thickness of colonic mucosa. Our findings provide evidence for abnormal alterations in the MGBA of ketamine-addicted rats, which improves our understating of the mechanism of ketamine addiction and the potential for developing new therapeutic strategies.

Abstract Background Despite remarkable advancements in cancer immunotherapy, the overall response rate to anti-programmed cell death-1 (anti-PD-1) therapy in hepatocellular carcinoma (HCC) patients remains low. Our previous study has demonstrated the critical role of CacyBP/SIP (Calcyclin-Binding Protein and Siah-1 Interacting Protein) as a regulator of HCC development and progression. However, the possible impact of CacyBP on the tumor immune microenvironment has not yet been clarified. Methods The expressions of CacyBP and Myd88 in HCC cell lines and tissues was detected by bioinformatics analysis, real-time quantitative PCR, western blotting and immunohistochemistry. The interaction between CacyBP and Myd88 was measured using co-immunoprecipitation and immunofluorescence. In vitro and in vivo assays were used to investigate the regulation of CacyBP on tumor-associated macrophages (TAMs). Results We identified that CacyBP was positively correlated with Myd88, a master regulator of innate immunity, and Myd88 was a novel binding substrate downstream of CacyBP in HCC. Additionally, CacyBP protected Myd88 from Siah-1-mediated proteasome-dependent degradation by competitively binding to its Toll/interleukin-1 receptor (TIR) domain. Inhibition of CacyBP-Myd88 signaling subsequently diminished HDAC1-mediated H3K9ac and H3K27ac modifications on the CX3CL1 promoter and reduced its transcription and secretion in HCC cells. Moreover, by using in vitro and in vivo strategies, we demonstrated that depletion of CacyBP impaired the infiltration of TAMs and the immunosuppressive state of the tumor microenvironment, further sensitizing HCC-bearing anti-PD-1 therapy. Conclusions Our findings suggest that targeting CacyBP may be a novel treatment strategy for improving the efficacy of anti-PD-1 immunotherapy in HCC.

In order to address the energy imbalance issue of a series-connected lithium-iron battery pack, this paper proposes an active equalization method based on a reduced-order solving strategy for the Hanoi Tower problem. The proposed scheme utilizes a combined structure of a switching-network circuit and a bidirectional Cuk converter and leverages an ultracapacitor cell as the energy-transfer carrier. Simulation and comparison demonstrate that the exchange of unbalanced energy within the battery pack can be achieved. The proposed approach can effectively achieve various balancing modes such as cell-to-cell, cell-to-string, string-to-cell, and string-to-string with a relatively fast balancing speed.

Modern power systems are confronted with widespread concern on the frequency stability issue due to the widespread integration of randomly fluctuating renewable resources. To address the above concern, this work introduces a load-frequency-control (LFC) scheme based on a parameter tuning strategy for fractional-order proportional–integral–derivative (FOPID) controller. Firstly, a two-area interconnected power system (IPS) model, including thermal, hydro, solar, wind, and gas power generator and a hydrogen-based energy-storage unit, is established. Then, a FOPID controller is designed for this IPS model, and an improved gradient-based optimizer (IGBO) is developed to adaptively regulate the parameters of the FOPID controllers. Finally, the effectiveness of the offered LFC scheme is tested through load disturbance and renewable energy fluctuations test scenarios and provides a comparison and robustness analysis among different schemes. The test results validated that the offered LFC scheme can effectively suppress the frequency fluctuations of the IPS and has excellent robustness.

A crucial area of study in data mining is outlier detection, particularly in the areas of network security, credit card fraud detection, industrial flaw detection, etc. Existing outlier detection algorithms, which can be divided into supervised methods, semi-supervised methods, and unsupervised methods, suffer from missing labeled data, the curse of dimensionality, low interpretability, etc. To address these issues, in this paper, we present an unsupervised outlier detection method based on quantiles and skewness coefficients called ISOD (Interpretable Single dimension Outlier Detection). ISOD first fulfils the empirical cumulative distribution function before computing the quantile and skewness coefficients of each dimension. Finally, it outputs the outlier score. This paper’s contributions are as follows: (1) we propose an unsupervised outlier detection algorithm called ISOD, which has high interpretability and scalability; (2) massive experiments on benchmark datasets demonstrated the superior performance of the ISOD algorithm compared with state-of-the-art baselines in terms of ROC and AP.

Abstract This paper proposes an intelligent Deep Learning (DL) based approach for Data‐Driven Security‐Constrained Unit Commitment (DD‐SCUC) decision‐making. The proposed approach includes data pre‐processing and a two‐stage decision‐making process. Firstly, historical data is accumulated and pre‐processed. Then, the DD‐SCUC model is created based on the Gated Recurrent Unit‐Neural Network (GRU‐NN). The mapping model between system daily load and decision results is created by training the DL model with historical data and then is utilized to make SCUC decisions. The two‐stage decision‐making process outputs the decision results based on various applications and scenarios. This approach has self‐learning capabilities because the accumulation of historical data sets can revise the mapping model and therefore improve its accuracy. Simulation results from the IEEE 118‐bus test system and a real power system from China showed that compared with deterministic Physical‐Model‐Driven (PMD)‐SCUC methods, the approach has higher accuracy, better efficiency in the practical use case, and better adaptability to different types of SCUC problems.

Pyroptosis is a form of cell death mediated by inflammasomes and gasdermins, and the relevance of pyroptosis to neurodegenerative diseases is currently receiving increasing attention. Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease that is closely associated with neuroinflammation. Its main pathological features include β-amyloid (Aβ) deposition, Tau protein hyperphosphorylation and neuronal loss. Aβ, tau-induced microglia pyroptosis and polarization leading to neuroinflammation play an important role in the pathogenesis of AD. Studying the pathogenesis and treatment of AD based on cellular pyroptosis has become a new direction in AD research. In this paper, we review the research progress of pyroptosis and will focus on the pathogenic roles of pyroptosis in AD and the role of targeted inhibition of inflammasome-dependent pyroptosis in AD treatment. These results deepen our understanding of the pathogenesis of AD and provide ideas for the development of new drugs based on the regulation of pyroptosis in AD patients.

Abstract In recent years, graphene based flexible strain sensors have attracted great attention. Although various designed micro/nanostructure morphologies have been introduced to optimize the performance parameters such as sensitivity and working range, there are relatively limited studies on the effective patterning of graphene on various substrates on curved surfaces to manufacture functional devices. In this work, we report a general route to realize the patterning of graphene into predesigned structure on a variety of complex curved substrates. The methodology involves a combination of polydopamine surface modification of the substrate and the spraying process of graphene. The polydopamine modification method preserves the intrinsic electrical properties and stability of graphene, and the modification process by self‐polymerization of dopamine is available on many types of materials of complex shape. This general approach of interface modification to achieve free patterning has capability of large‐scale fabrication. By this interface‐enhancement patterning method, sensing structure of cut‐through channel crack has been obtained, resulting in flexible strain sensors with adjusted high sensitivity (gauge factor of 100–2000 at 1% strain), little hysteresis and conformality of complex surfaces. In addition, the strain sensor array has also been fabricated to detect the deformation spatial distribution of complex curved structural components, thereby expanding their potential applications in wearable electronics.

Abstract Background Complete clearance of intracellular viruses depends on effector cells of innate and adaptive immune systems. This study aimed to identify the relationships among antiviral cytokines produced by natural killer (NK) and T cells and clinical-virological characteristics in untreated chronic hepatitis B (CHB) patients. Methods We measured antiviral cytokines interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), and interleukin-2 (IL-2) produced by T, NK and natural killer T (NKT) cells, respectively, in a cohort with chronic hepatitis B virus (HBV) infection (CHB). We also correlated these cytokines with clinical-virological characteristics using a linear regression model. Results levels of IFN-γ+ and TNF-α+ CD4+ and CD8+ T cells were significantly higher in immune active (IA) phase than in other phases. Immune tolerant (IT) patients showed the lowest expression of IFN-γ by NK and NKT cells, and TNF-α by NK cells. IFN-γ+, TNF-α+ and IL-2+ CD4+ and CD8+ T cells frequencies were similar between IA and gray zone (GZ) phases. Principal component analysis based on cytokines confirmed that most IT patients significantly differed from inactive carriers (IC) and IA patients, while GZ patients were widely scattered. Multivariate analysis showed both T and NK cells producing IFN-γ and TNF-α, but not IL-2, had significant association with serum alanine aminotransferase (ALT). Moreover, IFN-γ+ NKT cells were associated with HBV DNA, while IFN-γ+ CD4+ and CD8+ T cells were correlated with age. Conclusion HBV clinical phases are characterized by distinct cytokine signatures, which showed relationship to viral features in these untreated CHB patients.

Schnitzler syndrome is a rare adult-onset acquired autoinflammatory disorder typically characterized by chronic urticarial rash and immunoglobulin M (IgM) (rarely IgG) monoclonal gammopathy. Its clinical symptoms usually respond well to interleukin-1 blockade therapy, which, however, does not impact the underlying monoclonal gammopathy. Herein, we described a female patient who presented with urticarial rash, recurrent fevers, and fatigue for 7 years. Laboratory investigations revealed IgMκ monoclonal protein and MYD88 L265P mutation, but no lymphoplasmacytic lymphoma on bone marrow examination. She fulfilled the diagnosis of Schnitzler syndrome and was treated with the Bruton tyrosine kinase inhibitor ibrutinib in combination with prednisone. Her symptoms improved dramatically, and the level of IgMκ monoclonal protein also declined. She tolerated the treatment well. This case highlights the potential therapeutic role of Bruton tyrosine kinase inhibitors in Schnitzler syndrome.

How to obtain the optimal decision-making scheme based on the investment behavior of various stakeholders is an important issue that needs to be solved urgently in incremental distribution network planning. To this end, this article introduces the virtual player “Nature” to realize the combination of the game theory and robust optimization and proposes an incremental distribution network source–load–storage collaborate planning method with a multi-agent game. First, the planning and decision-making models of a DG investment operator, a distribution network (DN) company, power consumers, and a distributed energy storage (DES) investment operator are constructed, respectively. Then the static game behaviors between the DG investment operator and distribution network company, as well as the DG investment operator and the DES investment operator, are analyzed based on the transfer relations between these four participants. At the same time, robust optimization is used to deal with the uncertainty of the DG output, and the virtual player “Nature” is introduced to study the dynamic game behavior between the DG investment operator and the distribution company. Finally, a dynamic–static joint game planning model is proposed. The simulation results verify the correctness and effectiveness of the proposed method.

In view of the difficulty of applying the refine modeling of combined heat and power (CHP) units to the optimization scenario of integrated energy system, a CHP unit model based on working point linearization modeling is proposed, and its variable load characteristics are analyzed. Firstly, the dynamic coupling relationship of CHP unit is analyzed, and the nonlinear dynamic model of the unit is constructed. Then, under the pure condensation and heating conditions, the linearized Laplace transform model of the working point is established, and the variable load capacity under the independent action of control variables is analyzed to test the availability of the Laplace model. On this basis, the dynamic adaptive particle swarm optimization algorithm is used for multivariable cooperative control to test the open-loop characteristics of the variable load capacity of the unit. At the same time, the control strategy of electrothermal cooperation and safety self-test is designed to adjust the control variables, and test the closed-loop characteristics of the unit’s regulation ability. Finally, a 300-MW steam extraction CHP unit is taken as an example to verify the applicability of the unit model and the effectiveness of the control strategy.

The fault of power systems introduces a severe challenge in terms of fault recording analysis, and the traditional Prony method cannot perform satisfactorily in the process of signal recordings fitting caused by faults. Therefore, an improved adaptive Prony algorithm is proposed in this article to study the characteristics of fault recordings. Specifically, the search step size is taken as an adaptive variable, and the mean square relative fitting error (MSRFE) is set as the criterion. Then, a large step is employed to rapidly determine an approximate segmentation point in the initial stage of the searching process, and its horizon is gradually reduced to establish an accurate subsegment point. Finally, the Prony algorithm is deployed to analyze the subsegment fitting original signal. The proposed approach has been simulated on an assumed fault signal, and the results validate the accuracy and efficiency of the method.

Abstract In China, the prevalence of undernutrition among children under 5 years of age has declined significantly during recent decades. However, noticeable gaps exist between rural and urban areas. Since 2012, a government‐funded nutrition programme, Ying Yang Bao (YYB; soybean powder‐based iron‐rich supplement) programme, has been implemented in poor rural areas to decrease the risk of developing anaemia among children aged 6–23 months, but there are still inadequate health care awareness, feeding knowledge and skills among caregivers. From June 2018 to December 2020, a child health counselling intervention was delivered through a home visit based on the YYB programme in Liangshan. Child health messages were given by trained village child health assistants while distributing YYB. Surveys were conducted before and after the intervention to analyse changes in child health check‐up frequency, complementary feeding practice and prevalence of undernutrition. After the intervention, the proportion of children who had regular health check‐ups, who were vaccinated and who met the minimum YYB consumption significantly increased from 26.0%, 81.6%, and 67.8% to 59.7%, 95.0%, and 79.2%. Increased rates of IYCF indicators (introduction of solid, semisolid, or soft foods, minimum dietary diversity and consumption of iron‐rich or iron‐fortified foods) were observed after the intervention. The prevalence of stunting, underweight, wasting, and anaemia significantly decreased from 26.3% to 10.8%, 13.4% to 8.7%, 14.0% to 10.5%, and 52.1% to 43.9%. This intervention can be well integrated into the YYB programme with less additional resources. Children in resource‐limited areas will benefit more from a comprehensive nutritional package, including food supplements and child health education.

Summary: Compared with bulk materials, atomically thin two-dimensional (2D) crystals possess a range of unique mechanical properties, including relatively high in-plane stiffness and large bending flexibility. The atomic 2D building blocks can be reassembled into precisely designed heterogeneous composite structures of various geometries with customized mechanical sensing behaviors. Due to their small specific density, high flexibility, and environmental adaptability, mechanical sensors based on 2D materials can conform to soft and curved surfaces, thus providing suitable solutions for functional applications in future wearable devices. In this review, we summarize the latest developments in mechanical sensors based on 2D materials from the perspective of function-oriented applications. First, typical mechanical sensing mechanisms are introduced. Second, we attempt to establish a correspondence between typical structure designs and the performance/multi-functions of the devices. Afterward, several particularly promising areas for potential applications are discussed, following which we present perspectives on current challenges and future opportunities

Rapid and sensitive detection of mercury vapor is of great significance for environmental protection and human health. But the detection method enabling low detection limitation and rapid response at room temperature simultaneously has rarely been reported. In this work, we propose a gold particles decorated reduced graphene oxide sensor for mercury vapor detection. After adding the gold particles, the reduced graphene oxide sensors’ response sensitivity increase by more than 16 times and the response time significantly decreases, which is far less below the results reported by others. The sensor performance improvement should attribute to the distribution of the decorated gold particles, which insert into the layered graphene sheets, as demonstrated by the SEM and XRD results. The increased layer spacing of graphene sheets is conductive to the faster entry/exit of mercury vapor and increases the effective sensing area of graphene. What’s more, the first-principles calculation results confirm the mercury-philicity of gold particles, which also contributes to the increased sensitivity. We further test more performance of the gold particles decorated reduced graphene oxide sensor to mercury vapor, which shows a linear response, low detection limit and good repeatability. The proposed sensor shows rapid response/recovery (6/8 s), low detection limit (0.01 ng/mL), linear response, good repeatability and room temperature detection simultaneously, which shows great application potential for mercury vapor detection.

To highlight the characteristics of PM2.5–O3 pollution in the Central Plains Urban Agglomeration, spatial and temporal characteristics, key meteorological factors, and source pollution data for the area were analyzed. These data from the period 2014–2020 were obtained from state-controlled environmental monitoring stations in seven major cities of the agglomeration. The results revealed the following: (1) Spatially, the PM2.5–O3 pollution days were aggregated in the central area of Xinxiang and decreased toward the north and south. Temporally, during the 2014–2020 period, 50 days of PM2.5–O3 pollution were observed in the major cities of the Central Plains Urban Agglomeration, with an overall decreasing trend. (2) A low-temperature, high-pressure environment appeared unfavorable for the occurrence of PM2.5–O3 pollution days. Wind speeds of 2.14–2.19 m/s and a southerly direction increased the incidence of PM2.5–O3 pollution days. (3) The external transport range in summer was smaller and mainly originated from within Henan Province. These results can provide important reference information for achieving a synergistic control of PM2.5–O3 pollution, determining the meteorological causes, as well as the potential sources, of PM2.5–O3 pollution in polluted areas and promoting air pollution control.

The statistical characteristics of the nighttime noise data of 1000 kV AC transmission lines were investigated, the noise data of the Huainan-Shanghai 1000 kV AC transmission line collected at night (0:00 to 6:00) from September 25, 2015, to February 16, 2016, were statistically analyzed using the nonparametric statistical K-S test, and the outliers were detected using the moving window kernel principal component analysis (MWKPCA). The results show that after the ineffective data are removed by MWKPCA, the 5, 50, and 95% values of the data are basically unchanged. To a certain extent, the method proposed in this paper can remove the invalid audible noise (AN) data of 1000 kV AC transmission lines without affecting the subsequent study of AN, we use various machine learning algorithms to predict the A weight sound level (Awsl) before and after the invalid data rejection, and the results show that the invalid data rejection has contributed to the improvement of the transmission line AN Awsl prediction accuracy.

Competition on distributed generation (DG) investments among multiple stakeholders in a distribution system results in incompleteness of market information, in which each stakeholder does not have full knowledge on investment and operation decisions of other participants. It leads to an incomplete information game among multiple stakeholders. This paper discusses a multi-lateral incomplete information game based approach to study distribution system planning while considering both supply and demand sides competitions. Profit models of three types of stakeholders, including DG investors (i.e., DG units are investor-owned), electricity consumers, and the distribution company, are constructed. The interaction among the stakeholders and their gaming behavior are further studied under the context of multi-lateral incomplete information. Bayesian Nash equilibrium form of the multi-lateral incomplete information game is obtained via Harsanyi transformation. An improved co-evolutionary algorithm is adopted to find the Bayesian Nash equilibrium. Simulation results on a modified IEEE 33-bus test system show that, compared with the complete information game method, the proposed approach presents higher expected profits and more accurate planning schemes. Indeed, the proposed approach reflects the realistic planning process of distribution systems under a deregulated competitive environment, and it ensures fairness of competition among self-interested independent stakeholders while guaranteeing their individual performance.

Abstract Background Hepatitis B virus (HBV) replicates non-cytopathically in the hepatocytes and HBV-related diseases are caused by immune-mediated inflammatory events. This study aimed to identify the relationship between clinical-virological characteristics and immunity in untreated chronic hepatitis B (CHB) patients. Methods A total of 209 CHB patients were categorized into immune tolerant (IT, n = 17), inactive carrier (IC, n = 20), immune active (IA, n = 120), and gray zone (GZ, n = 72) phases. The quantitative hepatitis B surface antigen (qHBsAg), hepatitis B e antigen (HBeAg), anti-HBeAg (HBeAb), HBV genotype, viral mutant and frequencies of interleukin (IL)-4, IL-17, IL-10 and interferon-gamma (IFN-γ) produced by CD4+ and CD8+ T cells were tested. We also correlated these cytokines with clinical-virological characteristics using a linear regression model. Results CD8+ T cells frequency were significantly decreased in IT patients. Levels of CD4+ T cells IL-4+ or IL-10+ were strongly negatively associated with qHBsAg titers. The frequency of IFN-γ produced by CD4+ and CD8+ T cells showed significant positive association with age and alanine aminotransferase (ALT) level, while that had negative association with qHBsAg titers. Additionally, the ratios of mutations in the HBV precore (PC) stop codon and basal core promoter (BCP) and the combined mutations were 32.5, 27.2, and 11.3%, respectively. The frequency of CD4+ T cells IL-17+ was higher in patients with a PC mutation than that in patients carrying a wild-type sequence. Finally, little associations among T cell derived IL-4, IL-10, IL-17, and IFN-γ was observed in the current untreated CHB cohort. Conclusions Several components of the immune system were correlated with HBV factors that influence an inflammatory process during CHB. Of particular relevance are the significant associations of between CD4+ T cells IL-4+ and qHBsAg level, and between CD4+ T cells IL-17+ and the presence of a mutation in PC.

Bmi1 is overexpressed in multiple human cancers. We previously reported the oncogenic function and the transcription regulation mechanisms of Bmi1 in nasopharyngeal carcinoma (NPC). In this study, we observed that the mRNA and the protein levels of Bmi1 were strictly inconsistent in NPC cell lines and cancer tissues. The inhibitors of proteasome and lysosome could not enhance the protein level of Bmi1, indicating that Bmi1 may be post-transcriptionally regulated. The IRESite analysis showed that there were two potential internal ribosome entry sites (IRESs) in the 5′-untranslated region (5′-UTR) of Bmi1. The luciferase assay demonstrated that the 5′-UTR of Bmi1 has IRES activity, which may mediate cap-independent translation. The IRES activity of the Bmi1 5′-UTR was significantly reduced after the mutation of the two IRES elements. Taken together, these results suggested that the IRES elements mediating translation is a novel post-transcriptional regulation mechanism of Bmi1.

In this paper, a new structure for increasing the magnetic gear torque is proposed, which has high torque density and high mechanical properties. The permanent magnets (PMs) of the outer rotor are spoked and magnetized along the tangential direction. The PMs of inner rotor are the surface-mount type and magnetized in the radial direction. The PMs are fixed in the inner and outer rotors' iron yoke that the aim is to keep the PMs from falling off during the rotation. In order to reduce the amount of iron, it is considered to slot on the outer rotor. The two-dimensional finite element method is used for simulating the proposed model. The magnetic field and electromagnetic torque of the magnetic gear are calculated. Compared with the conventional magnetic gear, the results show that the torque transmission capability of the proposed magnetic gear can be substantially improved.

Abstract Background Tuberculosis (TB) and chronic Hepatitis B virus (HBV) infection are common in China. Fist-line anti-TB medications often produce drug-induced liver injury (DILI). This study sought to investigate whether TB patients with chronic HBV co-infection are more susceptible to liver failure and poor outcomes during anti-TB treatment. Methods Eighty-four TB patients developed DILI during anti-TB treatment and were enrolled, including 58 with chronic HBV co-infection (TB-HBV group) and 26 with TB mono-infection (TB group). Clinical data and demographic characteristics were reviewed. The severity of DILI and incidences of liver failure and death were compared. Risk factors of clinical outcomes were defined. Results The patterns of DILI were similar in both groups. Compared with patients in the TB group, patients in the TB-HBV group who did not receive anti-HBV therapy before anti-TB treatment were more susceptible to Grade-4 severity of DILI (36.2% vs. 7.7%, P = 0.005), liver failure (67.2% vs. 38.5%, P = 0.013) and poor outcomes (37.9% vs. 7.7%, P = 0.005). Age > 50 years (48.1% vs. 22.6%, P = 0.049), cirrhosis (50.0% vs. 15.4%, P = 0.046) and total bilirubin > 20 mg/dl (51.6% vs. 14.8%, P = 0.005) were independent risk factors for the rate of death in the TB-HBV group, and HBV DNA > 20,000 IU/ml had borderline significance (44.1% vs. 20.8%, P = 0.081). In the TB-HBV group, nucleos(t)ide analogues as rescue therapy were not able to reduce short-term death (33.3% vs. 36.8%, P = 0.659) once liver failure had occurred. Conclusions Patients on anti-TB therapy with chronic HBV co-infection are more susceptible to developing liver failure and having poor outcomes during anti-TB treatment. Regular monitoring of liver function and HBV DNA level is mandatory. Anti-HBV treatment should be considered in those with high viral levels before anti-TB treatment.

Traditional anti-quantum methods and multi-signature technologies to secure the blockchain against quantum attacks will quickly reduce the efficiency and scalability of the industrial blockchain, where the computational resources will experience a polynomial rise with the increasing number of traders. Here, a quantum blind multi-signature method is proposed for the multi-party transaction to provide anti-quantum security. First, the proposed multi-party transaction frame and quantum key distribution in the industrial blockchain are introduced. It integrates a novel quantum blind multi-signature algorithm that is based on the quantum entanglement mechanism, and it is absolutely secure in theory. Second, the anti-quantum multi-signature algorithm is illustrated, where there are four phases, i.e., initialization, signing, verification, and implementation. Third, the security and complexity of the proposed framework are analyzed and compared with related methods in references, and our proposed method is verified to be able to offer good computational performance and blockchain scalability for multi-party transaction. Last, the paper is summarized and future research directions are proposed.

Abstract Background There is limited information on innate immunity, especially natural killer (NK) cell function, in different chronic hepatitis B (CHB) stages. Therefore, we examined whether the clinical staging strategy accurately reflects veritable NK cell immunity. Methods A total of 237 eligible CHB patients and 22 healthy controls were enrolled in our study. Demographic and clinical data were collected, and the CHB phases (immune active-IA, immune tolerant phase-IT, inactive CHB-IC, and grey zone-GZ) were classified according to the latest American Association for the Study of Liver Disease guidelines. Peripheral blood mononuclear cells from patients and healthy controls were tested for NK cell frequency, phenotype and function using flow cytometry. Results A significant decrease in activating receptor NKp44 and NKp46 expression and significant increase of exhaustion molecule Tim-3 expression were observed in NK cells from CHB patients. Reduced cytokine secretion and preserved or elevated cytotoxic function were also observed. Patients in the IT group exhibited comparable cytokine secretion and cytolytic capacity as age-matched IA patients. NK cell anti-viral functions were preserved in GZ patients. Some of the NK cell function in patients who were excluded from treatment by the current treatment guidelines was less compromised than patients who qualified for treatment. Conclusion Our findings provide evidence of veritable NK cell immunity during different natural history phases in treatment-naïve patients with chronic HBV Infection. Chronic HBV infection hindered NK cell function in CHB patients. However, the presumed IT and GZ statuses of CHB patients based on the clinical parameters may not accurately reflect the inner immune status of these patients and should be reconsidered. Some patients excluded from treatment by the current treatment guidelines may be able to be selected as candidates for treatment.

Abstract G2 and S phase-expressed-1 (GTSE1) regulates G1/S cell cycle transition. It was recently reported to be overexpressed in certain human cancers, but its significance and mechanism(s) in hepatocellular carcinoma (HCC) remain unknown. Here, we showed preferential GTSE1 upregulation in human HCC tissues and cell lines that positively correlated with Ki67. GTSE1 knockdown by short hairpin RNA resulted in deficient colony-forming ability and depleted capabilities of HCC cells to migrate and invade. Conversely, exogenous GTSE1 overexpression enhanced colony formation and stimulated HCC cell migration and invasion. Furthermore, GTSE1 silencing was associated with the downregulation of N-cadherin, β-catenin, and Snail, whereas GTSE1 overexpression caused the opposite effects. GTSE1 upregulated Snail via both transcription and protein degradation pathways. Additionally, GTSE1 modulated the sensitivity of HCC to 5-fluorouracil therapy. High GTSE1 correlates with chemo-resistance, while low GTSE1 increases drug sensitivity. Kaplan-Meier survival analysis indicated that high GTSE1 levels were significantly associated with poor overall survival. In conclusion, high expression of GTSE1 is commonly noted in HCC and is closely correlated with migration and invasion by epithelial-to-mesenchymal transition (EMT) modulation. Activated GTSE1 significantly interferes with chemotherapy efficacy and influences the probability of survival of patients with HCC. GTSE1 may thus represent a promising molecular target.

Abstract Natural killer (NK) cells play a major role in anti-viral immunity as first line defense during hepatitis B infection, particularly in untreated patients whose T cells functions are profoundly impaired. Cytokine interferon (IFN)-γ and tumor necrosis factor (TNF)-α produced by NK cells are important anti-viral factors. However, there is lack of a quantifiable model to evaluate cytokine responses by NK cells. In this study, almost half of the patients (47.9%) beyond treatment criteria had high cytokine activity, although it was lower than those recommended for antiviral therapy (78.2%). Moreover, we developed a model that low levels of HBsAg, HBcAb, and albumin and high fibrosis values predicted strong antiviral cytokine production by NK cells. Based on the cut-off score (0.361) obtained from the multivariable model, patients with 67%, 8%, 92%, and 74% in immune-active (IA), immune-tolerant (IT), immune-inactive (IC), and grey zone (GZ), respectively, showed active antiviral cytokines produced by NK cells. These results suggest that those who possess activated cytokine responses beyond the current treatment criteria may have potential implications for the timing of antiviral therapy to achieve better virus control.

Abstract Background Liver fibrosis which mainly occurs upon chronic hepatitis virus infection potentially leads to portal hypertension, hepatic failure and hepatocellular carcinoma. However, the immune status of Th17 and Treg cells in liver fibrosis is controversial and the exact mechanisms remain largely elusive. Methods Liver tissues and peripheral blood were obtained simultaneously from 32 hepatitis B virus infected patients undergoing surgery for hepatocellular carcinoma at the medical center of Sun Yat-sen University. Liver tissues at least 3 cm away from the tumor site were used for the analyses. Levels of Th17 cells and regulatory T cells were detected by flow cytometry analysis and immunohistochemistry. In vitro experiment, we adopted magnetic cell sorting to investigate how hepatic stellate cells regulate the levels of Th17 cells and regulatory T cells. Results We found that hepatic Th17 cells and regulatory T cells were increased in patients with advanced stage HBV-related liver fibrosis. Hepatic stellate cells upregulated the levels of Th17 cells and regulatory T cells via PGE2/EP2 and EP4 pathway. Conclusions We found that the increased levels of Th17 cells and regulatory T cells were upregulated by hepatic stellate cells. These results may provide insight into the role of hepatic stellate cells and Th17 cells and regulatory T cells in the persistence of fibrosis and into the occurrence of hepatocellular carcinoma following cirrhosis.

Summary: CD4+ T cells play critical roles in directing immunity, both as T helper and as regulatory T (Treg) cells. Here, we demonstrate that hepatocytes can modulate T cell populations through engulfment of live CD4+ lymphocytes. We term this phenomenon enclysis to reflect the specific enclosure of CD4+ T cells in hepatocytes. Enclysis is selective for CD4+ but not CD8+ cells, independent of antigen-specific activation, and occurs in human hepatocytes in vitro, ex vivo, and in vivo. Intercellular adhesion molecule 1 (ICAM-1) facilitates T cell early adhesion and internalization, whereas hepatocytes form membrane lamellipodia or blebs to mediate engulfment. T cell internalization is unaffected by wortmannin and Rho kinase inhibition. Hepatocytes engulf Treg cells more efficiently than non-Treg cells, but Treg cell-containing vesicles preferentially acidify overnight. Thus, enclysis is a biological process with potential effects on immunomodulation and opens a new field for research to fully understand CD4+ T cell dynamics in liver inflammation. : Enclysis describes the enclosure of live CD4+ T cells in intracellular vesicles. Davies et al. show that hepatocytes engulf regulatory T (Treg) cells and preferentially delete them. Enclysis is distinct from entosis, efferocytosis, and suicidal emperipolesis and may be targeted to control T cell populations in the liver during inflammation. Keywords: T cells, hepatocytes, enclysis, entosis, efferocytosis, endocytosis, emperipolesis, cell-in-cell structures, liver, β-catenin

A novel microcavity structure based on 1-D parity-time (PT) symmetric photonic crystal (PC) is presented to get the embedded monolayer graphene absorption enhanced significantly, which paves a path to achieve ultrastrong, controllable, and anisotropic graphene absorption for incident eigenfrequency wave from near infrared to visible. When oscillation of absorption is at the center of the PT broken phase, because of exact matching usage of gain and loss modulation, and singular strong coupling effects that are induced by the PT symmetric PC behind graphene layer, ultrastrong and nonreciprocal graphene absorption can be obtained, and the maximum could reach the order of 105. This approach offers a way to improve the responsivities of graphene-based optodetectors and even to the design of direction sensitive graphene optical communication components.

Due to the rapid development of phasor measurement units (PMUs) and the wide area of interconnection of modern power systems, the security of power systems is confronted with severe challenges. A novel framework based on data for static voltage stability margin (VSM) assessment of power systems is presented. The proposed framework can select the key operation variables as input features for the assessment based on partial mutual information (PMI). Before the feature selection procedure is completed by PMI, a feature preprocessing approach is applied to remove redundant and irrelevant features to improve computational efficiency. Using the selected key variables, a voltage stability assessment (VSA) model based on iterated random forest (IRF) can rapidly provide the relative VSM results. The proposed framework is examined on the IEEE 30-bus system and a practical 1648-bus system, and a desirable assessment performance is demonstrated. In addition, the robustness and computational speed of the proposed framework are also verified. Some impact factors for power system operation are studied in a robustness examination, such as topology change, variation of peak/minimum load, and variation of generator/load power distribution.

In this paper, an extreme simple single-optical-waveguide ring (SOWR) is designed to generate strong photonic localizations by considering the similarities between electrons in electronic mesoscopic networks and photons in optical waveguide networks (OWNs). This interesting structure is designed based on the single-electronic-mesoscopic ring that can produce huge electronic persistent currents. We obtain the fitting formulas of the intensity, site number, and site positions for the maximal photonic localization in a SOWR. These interesting SOWRs may provide attractive applications like multichannel high-efficiency energy storages, high power super luminescent light emitting diodes, optical switches, and other correlative all-optical devices. Moreover, the approach of referencing single-electronic-mesoscopic ring to design SOWR may offer a new way to devise optical structures being capable of producing strong photonic localizations and may also deepen people's knowledge on the correlation between OWN and the electronic mesoscopic network.

To achieve automatic generation control coordination in the islanded smart grid environment resulted from the increasing penetration of renewable energy, a novel ecological population cooperative control (EPCC) strategy is proposed in this paper. The proposed EPCC, based on the new win-loss criterion and the time tunnel idea, can compute the win-loss criterion accurately and converge to Nash equilibrium rapidly. Moreover, based on a multiagent system stochastic consensus game (MAS-SCG) framework, a frequent information exchange between agents (AGC units) is implemented to rapidly calculate optimal power command, which achieves the optimal cooperative control of the islanded smart grid. The PDWoLF-PHC(λ), WPH strategy (wolf pack hunting), DWoLF-PHC(λ), Q(λ)-learning, and Q-learning are implemented into the islanded smart grid model for the control performance analysis. Two case studies have been done, including the modified IEEE standard two-area load frequency control power system model and the islanded smart grid model with distributed energy and microgrids. The effectiveness, stronger robustness, and better adaptability in the islanded smart grid of the proposed method are verified. Compared with five other smart ones, EPCC can improve convergence speed than that of others by nearly 33.9%–50.1% and the qualification rate of frequency assessment effectively by 2%–64% and can reduce power generation cost.

Nowadays, haze has become a big trouble in our society. One of the significant solutions is to introduce renewable energy on a large scale. How to ensure that power system can adapt to the integration and consumption of new energy very well has become a scientific issue. A smart generation control which is called hierarchical and distributed control based on virtual wolf pack strategy is explored in this study. The proposed method is based on multiagent system stochastic consensus game principle. Meanwhile, it is also integrated into the new win-lose judgment criterion and eligibility trace. The simulations, conducted on the modified power system model based on the IEEE two-area load frequency control and Hubei power grid model in China, demonstrate that the proposed method can obtain the optimal collaborative control of AGC units in a given regional power grid. Compared with some smart methods, the proposed one can improve the closed-loop system performances and reduce the carbon emission. Meanwhile, a faster convergence speed and stronger robustness are also achieved.

Background: The function of CD69 expressed on T cells in chronic hepatitis B (CHB) remains unclear. We aimed to elucidate the roles of CD69 on T cells in the disease process and in antiviral therapy for CHB. Methods: We enrolled 335 treatment-naive patients with CHB and 93 patients with CHB on antiviral therapy. CD69, antiviral cytokine production by T cells, T-helper (Th) cells, and inhibitory molecules of T cells were measured using flow cytometry, and clinical-virological characteristics were examined dynamically during antiviral therapy. Results: CD69 expression on CD3+, CD4+, and CD8+ T cells was the lowest in the immune-active phase and was negatively correlated with liver transaminase activity, fibrosis features, inflammatory cytokine production by T cells, and Th-cell frequencies but positively with inhibitory molecules on T cells. CD69 expression on CD3+, CD4+, and CD8+ T cells decreased after 48 weeks of antiviral therapy, and patients with hepatitis B e antigen (HBeAg) seroconversion in week 48 showed lower CD69 expression on T cells at baseline and week 48. The area under the ROC curve of CD69 expression on T cells at baseline for predicting HBeAg seroconversion in week 48 was 0.870, the sensitivity was 0.909, and the specificity was 0.714 (P =0.002). Conclusions: CD69 negatively regulates T-cell immunity during CHB, and its expression decreases with antiviral therapy. CD69 expression predicts HBeAg seroconversion in week 48. CD69 may play an important negative role in regulating T cells and affect the efficacy of antiviral therapy. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive exploration into the integration of Internet of Things (IoT), big data analysis, cloud computing, and Artificial Intelligence (AI), which has led to an unprecedented era of connectivity. We delve into the emerging trend of machine learning on embedded devices, enabling tasks in resource-limited environments. However, the widespread adoption of machine learning raises significant privacy concerns, necessitating the development of privacy-preserving techniques. One such technique, secure multi-party computation (MPC), allows collaborative computations without exposing private inputs. Despite its potential, complex protocols and communication interactions hinder performance, especially on resource-constrained devices. Efforts to enhance efficiency have been made, but scalability remains a challenge. Given the success of GPUs in deep learning, leveraging embedded GPUs, such as those offered by NVIDIA, emerges as a promising solution. Therefore, we propose an Embedded GPU-based Secure Two-party Computation (EG-STC) framework for Artificial Intelligence (AI) systems. To the best of our knowledge, this work represents the first endeavor to fully implement machine learning model training based on secure two-party computing on the Embedded GPU platform. Our experimental results demonstrate the effectiveness of EG-STC. On an embedded GPU with a power draw of 5 W, our implementation achieved a secure two-party matrix multiplication throughput of 5881.5 kilo-operations per millisecond (kops/ms), with an energy efficiency ratio of 1176.3 kops/ms/W. Furthermore, lever-aging our EG-STC framework, we achieved an overall time acceleration ratio of 5--6 times compared to solutions running on server-grade CPUs. Our solution also exhibited a reduced runtime, requiring only 60% to 70% of the runtime of previously best-known methods on the same platform. In summary, our research contributes to the advancement of secure and efficient machine learning implementations on resource-constrained embedded devices, paving the way for broader adoption of AI technologies in various applications. [ABSTRACT FROM AUTHOR]