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Abstract Idiopathic inflammatory myopathy (IIM) with autoantibodies recognizing the signal recognition particle (SRP) is characterized by prominent proximal weakness, infrequent extramuscular involvement, dramatically elevated creatine kinase levels, and myofiber necrosis with few inflammatory cell infiltrates in muscle tissue. To enhance understanding of the clinically used diagnosis and treatment of this disease, this study presents a single-center experience and analysis of a Chinese cohort with anti-SRP IIM. The most recent European Neuromuscular Center criteria were used to include Anti-SRP IIM patients from September 2016 to November 2019. Prior to treatment initiation, all sera were collected for the detection of anti-SRP autoantibodies and other myositis-related autoantibodies. Muscle strength, concurrent autoimmune conditions, comorbidities like interstitial lung disease (ILD), treatment outcomes, and follow-up results were also documented. Univariate logistic regression was employed to determine factors affecting prognosis. Among 271 patients with IIM, we identified 23 (8.5%) patients with anti-SRP IIM. Lower limb muscle weakness was frequently more severe. Interstitial lung disease (ILD) was observed in 50% of anti-SRP IIM patients. The presence of ILD may serve as a predictor of a poor prognosis, as revealed by univariate logistic regression analysis (odds ratio, 3.8, 95% CI: 1.0-6.8, p = 0.05).This Chinese Anti-SRP IIM cohort from Hunan province seems to have higher incidences of ILD, and associated ILD may be a risk factor for a poor prognosis. To fully understand the specific role of the anti-SRP autoantibody in this unique subset with ILD, further research is necessary.

Hepatocellular carcinoma (HCC) poses a significant clinical challenge due to high mortality and limited treatment options. Radiofrequency ablation (RFA) is commonly used but can be limited by tumor recurrence. This study explores the potential of combining RFA with an attenuated Salmonella strain carrying siRNA-PD-L1 and endostatin to enhance HCC treatment. In this study, an H22 subcutaneous tumor mouse model was used, with animals divided into five groups for treatment with a blank control, a blank Salmonella plasmid, RFA alone, siRNA-PD-L1-endostatin, or a combination of RFA and siRNA-PD-L1-endostatin. The combination therapy significantly reduced tumor growth, angiogenesis, and PD-L1/VEGF expression in tumor tissues post-RFA. Additionally, it induced tumor cell apoptosis, inhibited proliferation and migration, and increased the infiltration of T lymphocytes, granzyme B+ T cells, and CD86+macrophages within tumors. There was also a notable rise in T and NK cell populations in the spleen. In conclusion, combining RFA with siRNA-PD-L1-endostatin delivered by attenuated Salmonella synergistically enhances anti-tumor effects, boosts the anti-tumor immune response, and improves RFA efficacy for HCC.

Background: Natural killer cells, interconnected with patient prognosis and treatment response, play a pivotal role in the tumor immune microenvironment and may serve as potential novel predictive biomarkers for renal cell carcinoma. Methods: Clear cell renal cell carcinoma transcriptome data and the corresponding clinical data were obtained from the Cancer Genome Atlas (TCGA) database. Single-cell sequencing data were sourced from the Gene Expression Omnibus (GEO) database. A risk model was established by integrating ten different machine learning algorithms, which resulted in 101 combined models. The model with the highest average C-index was selected for further analysis, and was assessed using nomogram, time-dependent receiver operating characteristics (ROC) and Kaplan–Meier survival analysis. The differences in immune infiltration fractions, clinicopathological features, and response to various targeted therapies and immunotherapy between high- and low-risk groups were investigated. Furthermore, qRT-PCR, IHC, colony formation test, CCK8 assay and flow cytometry were conducted to explore the expression pattern and function of ARHGAP9 in our own patient samples and renal cancer cell lines. Results: Totally, 156 NK cell-related genes and 5189 prognosis-related genes were identified, and 36 genes of their intersection demonstrated prognostic value. A risk model with 18 genes was established by Coxboost plus plsRcox, which can accurately predict the prognosis of ccRCC patients. Significant correlations were determined between risk score and tumor malignancy and immune cell infiltration. Meanwhile, a combination of tumor mutation burden plus risk score could have higher accuracy of predicting clinical outcomes. Moreover, high-risk group patients were more likely to be responsive to targeted therapy but show no response to immunotherapy. Conclusions: Intricate signaling interactions between NK cells and various cellular subgroups were depicted and the developmental trajectory of NK cells was elucidated. A NK cells-related risk model was established, which can provide reliable prognostic information and identified patients with more probability of benefiting from therapy.

The accuracy and speed of zinc detection in polymetallic ores directly affect the accuracy and efficiency of field zinc exploration. At present, the transportation of polymetallic ore samples to the laboratory for testing has problems such as long addition cycles, insufficient stability and accuracy in detecting high levels of zinc. The effects of different methods of removing organic matter and sulfur from polymetallic ore samples, different oxidants, whether the sample solution was centrifuged, and different ammonia removal methods on the detection speed, stability, and accuracy of zinc in polymetallic ore samples were compared. A EDTA coordination titration method that can quickly detect zinc in polymetallic ore samples in the field was developed. Using this method, six parallel analyses were conducted on four polymetallic national standard materials with low, medium, and high zinc content. The relative deviation and relative error of zinc content were 0.00% to 2.11% and 0.00% to 2.41%, respectively. The research results indicate that using high-temperature calcination to remove organic matter and sulfur from polymetallic ore samples, and centrifuging and filtering the polymetallic ore sample solution can greatly improve the sample pretreatment speed. The use of milder oxidants and dropwise addition of hydrochloric acid for ammonia removal can improve the stability and accuracy of the detection method.

Data-driven models utilizing machine learning algorithms provide an effective approach for predicting power in heavy-duty gas turbines, extracting valuable insights from large-scale operational datasets. However, global unified models often struggle to meet the accuracy requirements of all data when dealing with complex and variable operating conditions, leading to limited prediction accuracy for local conditions. To address this problem, a clustering modification method is introduced to develop a novel power prediction model for heavy-duty gas turbines. In this study, the Support Vector Regression (SVR) prediction model is combined with a k-means clustering modification model, enabling the model to adapt to different operational conditions. Operational data from an E-class gas turbine are carefully preprocessed, including filtering, noise reduction, and steady-state selection, to enhance data quality. Then, the k-means algorithm is employed to classify operational conditions, with tailored modification models trained for each category. These modification models refine predictions to accommodate variations in specific operating states. Experimental results demonstrate that the composite model achieves a 32.66% reduction in MAPE and an increase in R2 to 0.9982 compared to single-model approaches. The analysis further highlights that training the model with 70% of the annual data achieves optimal prediction accuracy and stability. Additionally, the model significantly reduces high-error occurrences, with 75% of predictions having errors below 0.2946%. This method improves the precision and adaptability of power prediction for gas turbines, providing a practical framework that enhances the reliability of real-world applications and supports the advancement of data-driven energy systems.

To at the low robustness of the existing model for occluded object detection, an occluded object detection algorithm based on fuzzy sample anchor box IoU Matching degree Deviation Aware(IoU_MDA)is proposed. Firstly, fuzzy samples are defined based on Anchor-based, which reflects the degree of object occlusion. Secondly, IoU_MDA is proposed to quantify the degree of interference experienced by fuzzy samples. Then, IoU_MDA_Loss is constructed based on IoU_MDA, combined with IoU and the balance parameter $\Phi$ . To address class imbalance issues and enhance model generality, intra-class and inter-class fuzzy weights, and fuzzy sample focusing parameters are designed on the basis of the initial IoU_MDA_Loss. An occluded object training scheme is designed based on IoU perception, and non-fuzzy sample weight balancing parameters are constructed. Finally, IoU_MDA_Loss is merged with Focal Loss to obtain IoU_MDA_Focal Loss, simultaneously enhancing the detection performance of fuzzy samples and difficult-to-distinguish samples. The experimental results on the WiderPerson and VOC2007 datasets show that the mAP of IoU_MDA_Loss has increased by 2.04%, 2.36%, and IoU_MDA_Focal Loss has increased by 1.82%, 2.65%, respectively, compared to the baseline model. The detection performance surpasses current mainstream algorithms.

Abstract To clarify the risk of tuberculosis (TB) infection in patients with Takayasu arteritis (TAK). In this study, we conducted a comprehensive search across multiple databases, including PubMed, Web of Science, Embase, Cochrane, and Medline, from the inception of the Literature Library to May 16, 2023. Using a specific set of keywords, including “Takayasu Arteritis”, “Tuberculosis”, and “Mycobacterium tuberculosis”, the main objective of this search was to identify all relevant observational studies, including case-control studies, cohort studies, and cross-sectional studies, that report the prevalence of TB in individuals diagnosed with TAK. Two independent evaluators rigorously screened the studies, extracted data, and assessed the study quality using the Joanna Briggs Institute (JBI) critical appraisal tools. Statistical analyses were conducted using R software version 4.3.0, which allowed for the synthesis of prevalence and subgroup analyses. Subgroup analyses were stratified based on quality scores, World Health Organization regional categorizations, and TB categories. Assessment of publication bias was performed using a funnel plot. The study included a total of 30 studies with 5548 participants. The findings showed that individuals with TAK exhibited an average prevalence of TB infection at 31.27% (95% CI 20.48–43.11%). Significantly, the prevalence of TB infection demonstrated notable regional disparities, ranging from 16.93% (95% CI 7.71–28.76%) in the Western Pacific Region to 63.58% (95% CI 35.70–87.66%) in the African Region. Moreover, the study revealed that patients with TAK displayed a high prevalence of latent TB infection (LTBI) at 50.01% (95% CI 31.25–68.77%) and active TB at 14.40% (95% CI 9.03–20.68%). The high heterogeneity observed in the data highlights significant variability in TB infection rates among the populations studied, with the African Region exhibiting the highest rates. The study concludes that there is a high prevalence of TB infection in the TAK population, with regional variations. Consideration should be given to implementing rigorous TB screening measures and preventive interventions specifically tailored for the TAK population.

Abstract Titanium dioxide (TiO2)-based photodynamic antibacterial (PDA) agents present a novel approach for addressing drug-resistant bacterial infections and the associated tissue damage. However, the suboptimal dispersibility, negative charge, and weak photocatalytic activity under visible light of TiO2 hinder its practical applications. This study aimed to address these limitations by developing a highly hydrophilic and dispersed Zn-TiO2/reduced graphene oxide (rGO) (HTGZ) nano-system with exceptional visible light catalytic activity and tissue repair ability. HTGZ produced an antibacterial ratio over 98% within a short time, likely due to the enhanced production of reactive oxygen species under visible light. After being co-cultured for 4 days, L929 cells and BMSCs maintained over 90% activity, indicating that HTGZ had no significant cytotoxicity. Furthermore, the transcriptomic and metabolic analyses revealed that the antibacterial mechanism mainly came from the destruction of cell membranes and the disruption of various metabolic processes, such as purine metabolism and fatty acid biosynthesis. Critically, results of in vivo experiments had authenticated that HTGZ significantly promoted infected tissue regeneration by slaughtering bacteria and release Zn2+. After 14 days, the wound area was only one-third that of the control group. Overall, the enhanced antibacterial efficacy and wound-healing potential position HTGZ as a promising nano-antibacterial medication for the clinical treatment of infectious bacterial diseases.

Under the background of general financial knowledge confidence and insufficient retirement planning, this study investigates the relationship between overconfident financial knowledge and consumer retirement planning. Using data from the National Financial Capability Study, this study employs probit regressions and finds that consumers with overconfident financial knowledge are less likely to have retirement planning, that is, contribute to retirement accounts regularly. This study further explores the mediators in this relationship and concludes that consumers who are overconfident in their financial knowledge tend to be more preference to risk, fail to make ends meet, and do not care about their financial situation, therefore are less likely to plan for retirement. Furthermore, compared to retirement accounts such as 401(k) that are through an employer, consumers with overconfident financial knowledge are more willing to engage in those such as IRA that are not through an employer. This study also finds that underconfident financial knowledge, another type of incorrect subjective evaluation of financial knowledge, is positively associated with retirement planning. Based on these findings, this study recommends policymakers reduce financial knowledge overconfidence, guide individuals to regularly pay attention to their financial situation, and encourage employers to actively participate in retirement plans. JEL Classification: D12, N30, D80, D91.

Abstract Pressure fluctuation due to rotor-stator interaction in turbomachinery is unavoidable, inducing strong vibration in the equipment and shortening its lifecycle. The investigation of optimization methods for an industrial centrifugal pump was carried out to reduce the intensity of pressure fluctuation to extend the lifecycle of these devices. Considering the time-consuming transient simulation of unsteady pressure, a novel optimization strategy was proposed by discretizing design variables and genetic algorithm. Four highly related design parameters were chosen, and 40 transient sample cases were generated and simulated using an automatic program. 70% of them were used for training the surrogate model, and the others were for verifying the accuracy of the surrogate model. Furthermore, a modified discrete genetic algorithm (MDGA) was proposed to reduce the optimization cost owing to transient numerical simulation. For the benchmark test, the proposed MDGA showed a great advantage over the original genetic algorithm regarding searching speed and effectively dealt with the discrete variables by dramatically increasing the convergence rate. After optimization, the performance and stability of the inline pump were improved. The efficiency increased by more than 2.2%, and the pressure fluctuation intensity decreased by more than 20% under design condition. This research proposed an optimization method for reducing discrete transient characteristics in centrifugal pumps.

Introduction China initialised the expanded hepatitis A vaccination programme (EHAP) in 2008. However, the effectiveness of the programme remains unclear. We aimed to comprehensively evaluate the effectiveness of EHAP in the country.Methods Based on the provincial data on the incidence of hepatitis A (HepA), the population and meteorological variables in China, we developed interrupted time series (ITS) models to estimate the effectiveness of EHAP with the autocorrelation, seasonality and the meteorological confounders being controlled. Results were also stratified by economic zones, age groups and provinces.Results We found a 0.9% reduction (RR=0.991, 95% CI: 0.990 to 0.991) in monthly HepA incidence after EHAP, which was 0.3% greater than the reduction rate before EHAP in China. Across the three economic regions, we found a 1.1% reduction in HepA incidence in both central and western regions after EHAP, which were 0.3% and 1.2% greater than the reduction rates before EHAP, respectively. We found a decreased reduction rate for the eastern region. In addition, we found generally increased reduction rate after EHAP for age groups of 0–4, 5–14 and 15–24 years. However, we found decreased reduction rate among the 25–64 and ≥65 years groups. We found a slight increased rate after EHAP in Shanxi Province but not elsewhere.Conclusion Our finding provides comprehensive evidence on the effectiveness of EHAP in China, particularly in the central and western regions, and among the population aged 0–24 years old. This study has important implications for the adjustment of vaccination strategies for other regions and populations.

Abstract Background and Aims Leisure sedentary behavior (LSB) is associated with the risk of cancer, but the causal relationship between them has not been clarified. The aim of this study was to assess the potential causal association between LSB and risk of 15 site‐specific cancers. Methods The causal association between LSB and cancer were assessed with univariate Mendelian randomization (UVMR) and multivariate Mendelian randomization (MVMR). 194 SNPs associated with LSB (from the UK Biobank 408,815 individuals) were adopted as the instrument variables. Sensitivity analyses were performed to ensure the robustness of the results. Results UVMR analysis revealed that television watching significantly increased the risk of endometrial cancer (OR = 1.29, 95% CI = 1.02–1.64, p = 0.04) (mainly the endometrioid histology [OR = 1.28, 95% CI = 1.02–1.60, p = 0.031])，breast cancer (OR = 1.16, 95% CI = 1.04–1.30, p = 0.007) (both ER+ breast cancer [OR = 1.17, 95% CI = 1.03–1.33, p = 0.015], and ER− breast cancer [OR = 1.55, 95% CI = 1.26–1.89, p = 2.23 × 10−5]). Although causal association was not found between television watching and ovarian cancer, it was seen in low grade and low malignant potential serous ovarian cancer (OR = 1.49, 95% CI = 1.07–2.08, p = 0.018). However, significant results were not obtained in the UVMR analysis between driving, computer use and the 15 types of cancer. Further MVMR analysis indicated that the above results are independent from most metabolic factors and dietary habits, but mediated by educational attainment. Conclusion LSB in form of television watching has independent causal association with the risk of endometrial cancer, breast cancer, and ovarian cancer.

This study employed the gravity model approach to explore the predictors of textile product exports of the top 10 major textile producers. A specific dataset was generated and used to estimate the effects of 14 textile commodities selected in specific countries using Poisson regression and panel data from 1990 to 2021. The 10 major textile export countries hold significance in the global industry, providing comprehensive insights into export factors. Their diverse representation aids in understanding the challenges faced by exporters across continents. These countries possess substantial export markets and showcase various strategies and trade policies. Reliable data availability enables accurate analysis of factors affecting textile exports. Studying these countries enhances export performance and informs global industry strategies. Estimated results indicate that the real exchange rate, real GDP of the reporting country, preferential trade agreements, and the common border are significant positive predictors for textile exports of all commodities. The results further show that distance, average weighted tariff, and language have negative effects on the textile exports of all selected commodities. The transportation cost, measured by distance, is a barrier to textile commodity exports. The findings highlight the significant factors influencing textile exports and provide insights for exporters, policymakers, and researchers in the industry. Notably, this study addresses the challenges encountered by textile product export companies. These challenges include trade barriers, regulatory compliance, fluctuating exchange rates, intense competition, rising production costs, and market access barriers. By analyzing these challenges within the gravity model framework, the study aims to offer comprehensive insights into the complexities faced by textile exporters and their impact on the industry. The outcome of this study will be beneficial for the world’s major textile producers in setting their export targets and strategies to promote textile and cotton exports. The study suggests that the major exporters should benefit from moving exports to rich markets, which are situated at a nearby distance. The results of this study can be valuable for exporters in setting export targets, devising strategies, and formulating trade policies to overcome these challenges and enhance the competitiveness of the textile industry. The corresponding practical implications include the need to strategically manage exchange rates, focus on promoting exports to rich economies, reduce transportation costs, leverage preferential trade agreements, manage average weighted tariffs, address language barriers, and develop strategic export objectives and strategies. This research offers valuable insights for policymakers and society regarding factors influencing textile exports by major producers. Policymakers can utilize this information to inform trade regulations, exchange rate management, and the promotion of preferential trade agreements, enhancing export competitiveness and fostering sustainable practices. The research promotes international cooperation by encouraging collaboration and the sharing of best practices among reporting and partner countries. The findings contribute to economic growth, job creation, and improved standards of living, benefiting society as a whole.

Maintaining temperature profile in a solid oxide fuel cell (SOFC) is one of the essential issues that need to be addressed during the load tracking. In this paper, a novel control scheme with three-loop structure is developed to mitigate SOFC temperature profile variation. This scheme can simply implemented by three variable-speed blowers. The first blower is an anode recirculation blower used to maintain anode inlet temperature, the second one is a cathode recirculation blower used to maintain cathode inlet temperature, and the last one is an air blower used to maintain cathode outlet temperature. Compared with other simple schemes with only one-loop or two-loop structure, the scheme with three-loop structure achieves the best performance in mitigating SOFC internal temperature profile variation and guaranteeing a safe margin on operation limits. With a 10% system load step drop, the three-loop control scheme presents the best performance in rapidity and stability, with a much smaller overshoot, a much shorter settling time, and the smallest ITAE criterion. The SOFC temperature profile variation is also smallest (deviating within 4.7 K). Time-dependent temperature gradient is much less than 3.0 K/min. Temperature gradient is significant less than 10 K/cm. Steam to carbon ratio is also kept more than 2.0. Furthermore, the three-loop control scheme can perform high system efficiency, which reaches 53.9% at the 90% load. As a result, the three-loop SOFC temperature control scheme is robust in safe and efficient operation.

This study aims to investigate the associations between financial education and consumer stock market satisfaction. Consumer financial education is measured through the objective aspect incorporating formal and informal financial knowledge education, and the subjective aspect is reflected through consumers’ attitudes toward financial education. Using data from China’s urban consumers, the results indicate a positive association between financial education and consumer stock market satisfaction. The findings suggest that consumers who were financially literate at high schools or colleges are more satisfied in participating in the stock market. Moreover, consumers who spend more money and time, as well as those who think financial education is more important, feel more satisfied in participating in stock market investment activities. The results imply that it is necessary to increase the supply of formal financial education in high schools and universities, encourage consumers to invest more in the informal education of financial knowledge, and promote policymakers to formulate informative policies to make consumers aware of the importance of financial education.

Abstract Background Aim of this multicenter, observational, cross-sectional study was to evaluate health-related quality of life (HRQoL) and treatment satisfaction of current medications in Chinese knee OA patients. Methods Brief Pain Inventory (BPI), Treatment Satisfaction Questionnaire (TSQM-1.4), and HRQoL (EQ-5D-5L) were assessed in total of 601 OA of knee patients. Impact on QoL (EQ-5D-5L) and treatment satisfaction (TSQM-1.4) by BPI-Severity score (

Introduction Resveratrol, a polyphenol extracted from many plant species, has emerged as a promising pro-apoptotic agent in various cancer cells. However, the role of resveratrol in cell proliferation and apoptosis of fibroblast-like synoviocytes in rheumatoid arthritis (RA-FLS) is not fully understood. The study was aimed at elucidating the role of resveratrol in cell proliferation and apoptosis of RA-FLS and the underlying molecular mechanism. Material and methods Cultured RA-FLSs were subjected to tumour necrosis factor α (TNF-α). The cell proliferation was measured by Cell Counting Kit-8 assay. Cell apoptosis and cell cycle of RA-FLSs were determined by flow cytometry. The levels of apoptosis or autophagy or cell cycle-related protein were detected by immunoblot analysis. Results In our study, we confirmed that resveratrol reversed TNF-α mediated cell proliferation in RA-FLS. Meanwhile, resveratrol blocked cells at the G2/M stage and reduced the ratio of S phase cells through upregulation of p53 and consequently led to apoptotic cell death. Quite interestingly, we found that resveratrol reversed TNF-α-induced autophagy. Inhibition of autophagy by resveratrol or autophagy inhibitor or Beclin-1 siRNA suppressed TNF-α mediated cell survival and promoted cell apoptosis. However, the autophagy inducer rapamycin (RAPA) reversed the effect of resveratrol on autophagy and cell proliferation. Mechanistic studies revealed that resveratrol inhibited the activation of the phosphoinositide 3-kinases/serine-threonine kinase (PI3K/AKT) pathway. Inhibition of PI3K/AKT pathway by inhibitor LY294002 or resveratrol increased the expression of p53 and decreased the expression of cycle protein (cyclin B1), which further led to block cells in the G2/M arrest. Conclusions Our preliminary study indicated that resveratrol may suppress RA-FLS cell survival and promote apoptosis at least partly through regulation of autophagy and the AKT-p53 axis.

An accurate gas turbine performance model is important for system performance evaluation. To minimize the simulated performance error, an adaption method using coefficients of scaling factors is applied to tune the component characteristic maps and make the gas turbine model meet measurements of a few randomly sampled points. However, the field data are non-homogeneously distributed. In this situation, randomly selecting a few sampling may lead to the inappropriate correction of the component characteristic maps and lower the prediction accuracy of model. Firstly, the coefficients of scaling factors are introduced to construct the performance adaption optimization problem of the gas turbine model. Secondly, the k-means clustering algorithm is applied to divide the 146 field data points into 10 different categories, and then the points closest to the cluster centers are selected to form the sampling set. Thirdly, a particle swarm optimization algorithm is used to search the optimal scaling factors. As a result, the model error decreases from 2.947% to 0.610%. Finally, the proposed method is validated with the remaining field data of a real E-class gas turbine. The average predicted error is 0.466%. Compared with the performance results obtained by random sample, the model based on cluster sampling shows a better accuracy.

Natural products have emerged as “rising stars” for treating viral diseases and useful chemical scaffolds for developing effective therapeutic agents. The nonstructural protein NS5B (RNA-dependent RNA polymerase) of NADL strain BVDV was used as the action target based on a molecular docking technique to screen herbal monomers for anti-BVDV viral activity. The in vivo and in vitro anti-BVDV virus activity studies screened the Chinese herbal monomers with significant anti-BVDV virus effects, and their antiviral mechanisms were initially explored. The molecular docking screening showed that daidzein, curcumin, artemisinine, and apigenin could interact with BVDV-NADL-NS5B with the best binding energy fraction. In vitro and in vivo tests demonstrated that none of the four herbal monomers significantly affected MDBK cell activity. Daidzein and apigenin affected BVDV virus replication mainly in the attachment and internalization phases, artemisinine mainly in the replication phase, and curcumin was active in the attachment, internalization, replication, and release phases. In vivo tests demonstrated that daidzein was the most effective in preventing and protecting BALB/C mice from BVDV infection, and artemisinine was the most effective in treating BVDV infection. This study lays the foundation for developing targeted Chinese pharmaceutical formulations against the BVDV virus.

The Lassa virus (LASV) causes Lassa fever, a highly infectious and lethal agent of acute viral hemorrhagic fever. At present, there are still no effective treatments available, creating an urgent need to develop novel therapeutics. Some benzimidazole compounds targeting the arenavirus envelope glycoprotein complex (GPC) are promising inhibitors of LASV. In this study, we synthesized two series of LASV inhibitors based on the benzimidazole structure. Lentiviral pseudotypes bearing the LASV GPC were established to identify virus entry inhibitors. Surface plasmon resonance (SPR) was further used to verify the binding activities of the potential compounds. Compounds 7d−Z, 7h−Z, 13c, 13d, and 13f showed relatively excellent antiviral activities with IC50 values ranging from 7.58 to 15.46 nM and their SI values above 1251. These five representative compounds exhibited stronger binding affinity with low equilibrium dissociation constants (KD < 8.25 × 10−7 M) in SPR study. The compound 7h−Z displayed the most potent antiviral activity (IC50 = 7.58 nM) with a relatively high SI value (2496), which could be further studied as a lead compound. The structure–activity relationship indicated that the compounds with lipophilic and spatially larger substituents might possess higher antiviral activity and a much larger safety margin. This study will provide some good guidance for the development of highly active compounds with a novel skeleton against LASV.

Abstract Background The objectives of this study were to assess the maintenance of effect of duloxetine 60 mg once-daily (QD) in Chinese patients with chronic pain due to osteoarthritis (OA) of the knee or hip and to provide additional long-term safety data. Methods This was an open-label, extension phase of a randomized, double-blind, placebo-controlled clinical trial. Eligible patients were outpatients who met the American College of Rheumatology clinical and radiographic criteria for OA with a rating ≥4 on Brief Pain Inventory (BPI) 24-h average pain. After completing the 13-week placebo-controlled phase, patients originally assigned to placebo were titrated to duloxetine 60 mg QD (PLA_DLX), whereas patients originally assigned to duloxetine 60 mg QD remained on the same dose of duloxetine (DLX_DLX) for another 13 weeks. The maintenance effect of duloxetine 60 mg QD during the extension phase was evaluated by a 1-sided 97.5% confidence interval (CI) of the baseline-to-endpoint change in the extension phase for patients who took duloxetine and reported ≥30% reduction in BPI average pain at the end of placebo-controlled phase (placebo-controlled phase duloxetine responders). Other BPI severity and interference items, as well as safety and tolerability, were assessed. Results Of 342 patients entering the extension phase, 162 (97.6%) DLX_DLX-treated patients and 157 (89.2%) PLA_DLX-treated patients completed this phase. Most patients (76.0%) were female. Mean age was 60.6 years. Mean BPI average pain was 5.5 at baseline of the placebo-controlled phase. Among 113 placebo-controlled phase duloxetine responders, mean change in BPI average pain during the extension phase was − 0.59 (from 2.47 to 1.88); the upper bound of the 1-sided 97.5% CI was − 0.31 and less than the pre-specified non-inferiority margin of a 1.5-point increase (p

Infection with Yersinia pestis (Y. pestis) may cause pneumonic plague, which is inevitably fatal without treatment. Gentamicin (GM), an aminoglycoside antibiotic, is a drug commonly used in the treatment of plague. However, it requires repeated intramuscular or intravenous administration. Pulmonary drug delivery is noninvasive, with the advantages of local targeting and reduced risk of systemic toxicity. In this study, GM powders were prepared using spray-drying technology. The powders displayed good physical and chemical properties and met the requirements for human pulmonary inhalation. The formulation of the powders was optimized using a 32 full factorial design. A formulation of 15% (w/w) of L-leucine was prepared, and the spray-drying process parameters using an inlet temperature of 120°C and a 15% pump rate were determined to produce the best powder. In addition, the optimized GM spray-dried powders were characterized in terms of morphology, crystallinity, powder fluidity, and aerodynamic particle size distribution analysis. In a mouse model of pneumonic plague, we compared the therapeutic effects among three administration routes, including subcutaneous injection, liquid atomization, and dry powder atomization. In conclusion, our data suggest that inhalation therapy with GM spray-dried powders is an effective treatment for pneumonic plague.

Bovine viral diarrhea virus (BVDV), a positive-strand RNA virus of the genus Pestivirus in the Flaviviridae family, is the causative agent of viral diarrheal disease in bovine. BVDV has been used as a surrogate model for the hepatitis C virus (HCV) to evaluate the efficacy of antiviral drugs. The plant flavonol quercetin causes multiple health-promoting effects in humans and animals. It can be made into a variety of additives, and it exerts a variety of immunomodulatory effects with the potential to be used as an antiviral agent. However, quercetin’s antiviral effect and mechanism of action on BVDV are still unclear. Therefore, this study was designed to evaluate quercetin’s effect on BVDV virus replication in vitro and in vivo and elucidate its mechanism of action. A CCK-8 kit was used to analyze the toxicity of the quercetin to the MDBK cells. Western blot, qRT-PCR, TCID50, and histological analysis were used to determine the mechanism of quercetin’s anti-BVDV activity. An oxidative stress kit was used to evaluate the effects of quercetin on ROS, antioxidant enzymes, and MDA indexes. The effect of quercetin on IL-2 and IFN-γ in the serum of mice was determined by using an ELISA kit. The results showed that quercetin inhibits Hsp70, blocks BVDV infection in the early stage of virus infection and inhibits BVDV replication by inhibiting oxidative stress or ERK phosphorylation. In addition, quercetin alleviated the decrease in IFN-γ and IL-2 in the serum of BVDV-infected mice. Quercetin ameliorated BVDV-induced histopathological changes. In summary, this study demonstrated for the first time the role of Hsp70 in BVDV infection and the potential application of quercetin in treating BVDV infection.

Acute infection of bovine viral diarrhea virus (BVDV) is associated with immune dysfunction and can cause peripheral blood lymphopenia and lymphocyte apoptosis. Our previous study has confirmed that programmed death-1 (PD-1) blockade inhibits peripheral blood lymphocytes (PBL) apoptosis and restores proliferation and anti-viral immune functions of lymphocytes after BVDV infection in vitro. However, the situation in vivo remains to be further studied and confirmed. Therefore, in this study, we established a BALB/c mouse model of acute BVDV infection with cytopathic (CP) BVDV (strain NADL) and non-cytopathic (NCP) BVDV (strain NY-1). Then, we examined the mRNA and protein levels of PD-1 and programmed death-ligand 1 (PD-L1) in peripheral blood mononuclear cells (PBMC) from BVDV-infected mice and analyzed the effects of PD-1 blockade on the proportions of CD3+, CD4+, and CD8+ T cell subsets, the apoptosis and proliferation of PBL, and the production of IL-2 and IFN-γ. We found that leukopenia, lymphocytopenia, and thrombocytopenia were developed in both CP and NCP BVDV-infected mice at day 7 of post-infection. The mRNA and protein expression of PD-1 and PD-L1 were significantly upregulated in CP and NCP BVDV-infected mice. Moreover, PD-1/PD-L1 upregulation was accompanied by leukopenia and lymphopenia. Additionally, PD-1 blockade inhibited PBL apoptosis and virus replication, restored the proportions of CD3+, CD4+, and CD8+ T cell subsets, and increased IFN-γ production and p-ERK expression in BVDV-infected mice. However, blocking PD-1 did not significantly affect PBL proliferation and IL-2 production in NCP BVDV-infected mice. Our findings further confirmed the immunomodulatory role of PD-1 in peripheral blood lymphocytopenia in vivo and provided a scientific basis for exploring the molecular mechanism of immune dysfunction caused by acute BVDV infection.

Background: There is heterogeneity in the clinical manifestations and responses to drugs in RA patients due to variety of factors such as genes and environment. Despite advances in the treatment of rheumatoid arthritis (RA), approximately 40% of RA patients still do not achieve primary clinical outcomes in randomized trials, and its low remission rate and high economic consumption remain unresolved, especially in developing countries. Iguratimod (IGU) is a new disease-modifying anti-rheumatic drug (DMARD) with a low price that has demonstrated good efficacy and safety in clinical trials and was approved for active RA in China and Japan. As the most populous country in the Western Pacific region, it is warranted to conduct a study with a large scale of patients in a real-life setting. Our study confirms the new option for RA patients, which is potentially benificial for public health in developing countries. Methods: This was a nationwide, prospective real-world study of IGU. Eligible subjects were active adult RA patients who aged 18 to 85 with or without multiple comorbidities such as hypertension and diabetes with DMARDs at a stable dosage for at least 12 weeks, or without ongoing DMARDs. A two-stage design was used for this study. In the first stage (the first 12 weeks), IGU 25 mg bid was added as monotherapy or to the background therapy, and in the second stage (the latter 12 weeks), adjustment of RA medicines other than IGU was allowed according to the participants’ disease activity. The primary endpoints were American College of Rheumatology 20% response (ACR20) 24 weeks and adverse events during 24 weeks. The secondary endpoints were ACR50 and ACR70 over 24 weeks, the changes of DAS28 and Health Assessment Questionnaire (HAQ) at week 12 and week 24 from baseline. The trial was registered with ClinicalTrials.gov, number NCT01554917. Findings: Between March 2012 and January 2015, 1759 participants were enrolled, of whom 81•5% (1433/1759) completed the study. Notably, 1597 patients in the full analysis set were assessed for the effectiveness and 1751 patients were in the safety analysis set; 71•9% (1148/1597) of the patients achieved the primary endpoint of ACR20 response at week 24, and 51•7% (906/1751) patients had at least 1 adverse event (AE). The incidence of the clinical significant AE (grade≥3) of special interest was 3•4% (54 patients for grade 3 and 6 patients for grade 4), and 0•7% (13/1751) of patients developed SAEs associated with IGU. The most common clinical significant AEs were infection in 0•6% (10/1751) of the patients, abdominal discomfort in 0•5% (9/1751) of the patients including 0•2% (3/1751) gastric ulcer, fracture in 0•4% (7/1751), and increased alanine aminotransferase (ALT) in 0•2% (3/1751) of the patients. The secondary endpoint of ACR50 and ACR70 response rates at week 24 were 47•4% (757/1597) and 24•0% (384/1597). DAS28 was 4•11±1•27 and 3•75±1•32 at week 12 and 24, which was significantly decreased -1•40±1•10 and -1•75±1•26 compared with baseline (P

Gas path fault diagnosis of a gas turbine is a complex task involving field data analysis and knowledge-based reasoning. In this paper, a data-knowledge hybrid driven method for gas path fault diagnosis is proposed by integrating a physical model-based gas path analysis (GPA) method with a fault diagnosis ontology model. Firstly, a physical model-based GPA method is used to extract the fault features from the field data. Secondly, a virtual distance mapping algorithm is developed to map the GPA result to a specific fault feature criteria individual described in the ontology model. Finally, a fault diagnosis ontology model is built to support the automatic reasoning of the maintenance strategy from the mapped fault feature criteria individual. To enhance the ability of selecting a proper maintenance strategy, the ontology model represents more abundant knowledge from several sources, such as fault criteria analysis, physical structure analysis, FMECA (failure mode, effects, and criticality analysis), and the maintenance logic decision tool. The availability of the proposed hybrid driven method is verified by the field fault data from a real GE LM2500 PLUS gas turbine unit. The results indicate that the hybrid driven method is effective in detecting the path fault in advance. Furthermore, diversified fault information, such as fault effects, fault criticality, fault consequence, and fault detectability, could be provided to support selecting a proper maintenance strategy. It is proven that the data-knowledge hybrid driven method can improve the capability of the gas path fault detection, fault analysis, and maintenance strategy selection.

Our study aimed to investigate the effect of cigarette smoking on the clinical phenotype of patients registered in the Chinese Systemic Lupus Erythematosus (SLE) Treatment and Research (CSTAR) group registry database, the first online registry of Chinese patients with SLE.A prospective cross-sectional study of Chinese SLE patients was conducted using the CSTAR. Our case-control analysis was performed on age- and gender-matched subjects to explore the potential effect of cigarette smoking on the clinical manifestation of SLE.Smokers comprised 8.9% (65/730) of patients, and the ratio of females/males was 19/46. Thirty-nine patients were current smokers, and 26 were ex-smokers. Data showed significant differences between smokers and nonsmokers in the following areas: nephropathy (58.5% vs. 39.2%; p = 0.003), microscopic hematuria (30.8% vs. 19.1%; p = 0.025), proteinuria (53.8% vs. 34.4%; p = 0.002), and SLE Disease Activity Index(DAI) scores (12.38±8.95 vs. 9.83±6.81; p = 0.028). After adjusting for age and gender, significant differences between smokers and nonsmokers were found with photosensitivity (35.9% vs. 18%; p = 0.006), nephropathy (59.4% vs. 39.8%; p = 0.011), and proteinuria (54.7% vs. 35.2%). Although smokers tended to have greater disease severity compared with nonsmokers (SLEDAI scores: 12.58±8.89 vs.10.5±7.09), the difference was not significant (p = 0.081).Cigarette smoking triggers the development and exacerbation of SLE, especially with respect to renal involvement. Chinese smokers with SLE should be advised to discontinue cigarette use.