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The rapid advancement in video technologies in recent years has made the creating and editing of subtitles for a video increasingly feasible. For a long time, however, the pedagogical potentials of subtitling in language teaching and learning have been neglected. To fill this gap, this technology review introduces "VisualSubSync," a free and flexible tool for subtitle editing, as a practical instrument to facilitate the teaching of listening and viewing skills. This review first provides an overview of the main features of the software and then discusses the possible benefits it offers to listening and viewing pedagogies in the English-as-a-foreign-language classroom. Finally, the challenges that teachers and learners may face with subtitling are considered.

Abstract Objectives Triglyceride-glucose (TyG) index, which is a valuable measure of insulin resistance, has been found to have predictive value for cardiovascular disease (CVD). However, its relationship with CVD among individuals with chronic kidney disease (CKD) has not been thoroughly investigated. This study focused on examining the relationship of the TyG index and CVD among CKD patients in United States. Methods 3507 eligible participants from the National Health and Nutrition Examination Survey (2003–2018) were surveyed in this study. Methods such as multivariable logistic regression analysis and smooth curve fitting were employed to estimate how the TyG index is linked to CVD in CKD populations. Subgroup and interaction analyses were conducted in order to figure out potential moderating effects of various factors. Results In this cross-sectional study which based on a population with CKD, 29.5% of patients also had CVD. An independent and positive link of TyG and CVD was revealed (OR 1.213, 95% CI 1.059, 1.389). This association was nonlinear, with a threshold effect observed at a TyG index of 8.98. The results of subgroup analysis suggested that the relationships of TyG and CVD differed according to CKD stage: (OR 1.048, 95% CI 0.857, 1.282) in CKD stages 1–2; (OR 1.267, 95% CI 1.030–1.560) in stage 3; and (OR 2.131, 95% CI 1.224–3.709) in stages 4–5. Interaction analyses further suggested the potential moderating effects of CKD stage. Additionally, among specific CVD types, only coronary heart disease (CHD) had a significant and positive relationship with TyG (OR 1.617, 95% CI 1.123, 2.327). Conclusions TyG index was identified to be independently and positively related to the likelihood of CVD, specifically in populations with an eGFR

Abstract Background In China, Tongguanteng injection (TGT) is widely used in the treatment or adjuvant treatment of various types of cancer. However, the effect and mechanism of TGT in osteosarcoma is not clear. Methods The 143B and MG-63 cells were treated with different concentrations of TGT. Cell proliferation, migration, invasion and apoptosis were detected using CCK8 assay, transwell assay and flow cytometry. Differentially expressed genes (DEGs) were screened using RNA sequencing (RNA-seq). The identified mRNA and protein expression associated with the IRE1/CHOP pathway was validated by RT-PCR and western blot assay. To explore the underlying mechanisms, 4-phenylbutyric acid (4-PBA) was selected as a specific endoplasmic reticulum (ER) stress inhibitor. Small interfering RNA (siRNA) or pEX‐3-ERN1 plasmid was transfected into 143B cells to silence or overexpress IRE1, respectively. The potential downstream proteins, including CHOP, and apoptosis associated proteins, caspase-3 and PARP1 were determined. Furthermore, the effect of TGT was demonstrated in 143B cell tumor-bearing mice in vivo. H&E staining, TUNEL staining and immunohistochemistry were conducted in tumor tissues obtained from the xenograft mouse model. Results TGT was shown to dramatically suppress the proliferation, migration and invasion, and induce apoptosis of osteosarcoma 143B and MG-63 cells in vitro. The identified DEGs included HSPA5 (encoding BiP) and ERN1 (encoding the IRE1 protein), as well as apoptosis-associated gene DDIT3 (encoding the CHOP protein). The term “IRE1-mediated unfolded protein response” was screened to be the most enriched biological process GO term. The expression of ER stress-associated proteins including ATF6, BiP, p-IRE1, XBP1s and CHOP, as well as apoptosis-associated cleaved caspase-3 and cleaved PARP1 proteins, was significantly upregulated by TGT treatment in osteosarcoma 143B cells, suggesting that TGT might promote the apoptosis of osteosarcoma 143B cells through the IRE1/CHOP pathway. Furthermore, knocking down IRE1 with si-IRE1 or inhibiting of ER stress with 4-PBA suppressed the expression of ATF6, BiP, XBP1s and CHOP induced by TGT, as well as the expression of cleaved caspase-3 and cleaved PARP1. On the contrary, overexpressing IRE1 promoted CHOP expression and induced osteosarcoma cell apoptosis. Consistent with in vitro results, TGT dramatically inhibited the tumor growth and promoted the expression of p-IRE1 and CHOP in tumor-bearing mice. Conclusion The findings suggest that TGT exerts an anti-osteosarcoma effect in vitro and in vivo. The underlying mechanism might be associated with the activation of IRE1/CHOP pathway in ER stress. Our findings suggest that targeting IRE1/CHOP pathway might be a potential novel approach for osteosarcoma treatment.

Abstract Axis inhibition protein 1 (AXIN1), a scaffold protein interacting with various critical molecules, plays a vital role in determining cell fate. However, its impact on the antiviral innate immune response remains largely unknown. Here, we identify that AXIN1 acts as an effective regulator of antiviral innate immunity against both DNA and RNA virus infections. In the resting state, AXIN1 maintains the stability of the transcription factor interferon regulatory factor 3 (IRF3) by preventing p62-mediated autophagic degradation of IRF3. This is achieved by recruiting ubiquitin-specific peptidase 35 (USP35), which removes lysine (K) 48-linked ubiquitination at IRF3 K366. Upon virus infection, AXIN1 undergoes a phase separation triggered by phosphorylated TANK-binding kinase 1 (TBK1). This leads to increased phosphorylation of IRF3 and a boost in IFN-I production. Moreover, KYA1797K, a small molecule that binds to the AXIN1 RGS domain, enhances the AXIN1-IRF3 interaction and promotes the elimination of various highly pathogenic viruses. Clinically, patients with HBV-associated hepatocellular carcinoma (HCC) who show reduced AXIN1 expression in pericarcinoma tissues have low overall and disease-free survival rates, as well as higher HBV levels in their blood. Overall, our findings reveal how AXIN1 regulates IRF3 signaling and phase separation-mediated antiviral immune responses, underscoring the potential of the AXIN1 agonist KYA1797K as an effective antiviral agent.

Electrospun fibers prepared from water-soluble polymers (PVP, PVA, and HPMC) were loaded with pregabalin, a BCS I drug, to address its fast release and adverse effects. The drug dissolved partially (1.8–2.8 wt%) in the polymers, with excess pregabalin in crystalline form within the fibers. The solubility of the drug varied with the pH of the dissolution medium. Most of the drug encapsulated into the fibers during electrospinning, but some was lost due to technical reasons. PVP showed no impact on drug release, offering no benefit as a carrier. However, PVA-based fibers exhibited considerably slower release than the dissolution rate of the neat drug and also the release rate from fibers prepared from the other polymers. This indicates the potential of PVA for using it with pregabalin in practical drug formulations with improved release properties. The pH of the dissolution medium influenced solubility and release rate for specific polymers. Overall, the study highlights the importance of polymer selection and pH control in optimizing the release profile of pregabalin in enhanced drug delivery.

AimTo identify optimally therapeutic exercise interventions for improving motor ability among patients with Parkinson’s disease (PD), we conducted a network meta-analysis (NMA) of randomized controlled trials comparing different exercise regimens.MethodsRelevant RCTs were retrieved by searching PubMed, Embase, Cochrane, Web of Science, CINAHL, CBM, China National Knowledge Infrastructure (CNKI), Wan fang, VIP, and other databases from inception to July 9, 2023 is available in English as the primary language. Exercise outcomes as measured by Movement Disorder Society- Unified Parkinson’s Disease Rating Scale Part III (MDS-UPDRS-III) score change were evaluated and ranked using STATA software version 18.0. All included studies were assessed for methodological quality using the Cochrane Risk of Bias tool.ResultsThe final NMA included 71 studies involving 3,732 participants, 87 intervention experiments, and 27distinct interventions. Although most exercise interventions showed some efficacy (reducing MDS-UPDRS-III score), cumulative ranking probability surface (SUCRA) values indicated that the best exercise interventions for motor function improvement were archery (95.6%), riding a bicycle (80.9%), and binary rhythm dance (80.8%).ConclusionAn exercise intervention comprising archery, cycling, and(or) binary rhythm dance may yield superior improvements in motor function among patients with Parkinson’s disease.

Abstract This paper develops a theoretical model of determinants influencing multimodal fake review generation using the theories of signaling, actor-network, motivation, and human–environment interaction hypothesis. Applying survey data from users of China’s three leading E-commerce platforms (Taobao, Jingdong, and Pinduoduo), we adopt structural equation modeling, machine learning technique, and Bayesian complex networks analysis to perform factor identification, path analysis, feature factor importance ranking, regime division, and network centrality analysis of full sample, male sample, and female sample to reach the following conclusions: (1) platforms’ multimodal recognition and governance capabilities exert significant negative moderating effects on merchants’ information behavior, while it shows no apparent moderating effect on users’ information behavior; users’ emotional venting, perceived value, reward mechanisms, and subjective norms positively influence multimodal fake review generation through perceptual behavior control; (2) feature factors of multimodal fake review generation can be divided into four regimes, i.e., regime 1 includes reward mechanisms and perceived social costs, indicating they are key feature factors of multimodal fake review generation; merchant perception impact is positioned in regime 2, signifying its pivotal role in multimodal fake review generation; regime 3 includes multimodal recognition and governance capabilities, supporting/disparaging merchants, and emotional venting; whereas user perception impact is positioned in regime 4, indicating its weaker influence on multimodal fake review generation; (3) both in full sample, male sample, and female sample, reward mechanisms play a crucial role in multimodal fake review generation; perceived value, hiring review control agency, multimodal recognition and governance capabilities exhibit a high degree of correlation; however, results of network centrality analysis also exhibit heterogeneity between male and female samples, i.e., male sample has different trends in closeness centrality values and betweenness centrality values than female sample. This indicates that determinants influencing multimodal fake review generation are complex and interconnected.

Background: China has experienced a COVID-19 wave caused by Omicron XBB variant starting in April 2023. Our aim is to conduct a retrospective analysis exploring the dynamics of the outbreak under counterfactual scenarios that combine the use of vaccines, antiviral drugs, and nonpharmaceutical interventions. Methods: We developed a mathematical model of XBB transmission in China, which has been calibrated using SARS-CoV-2 positive rates per week. Intrinsic age-specific infection-hospitalization risk, infection-ICU risk, and infection-fatality risk were used to estimate disease burdens, characterized as number of hospital admissions, ICU admissions, and deaths. Results: We estimated that in absence of behavioral change, the XBB outbreak in spring 2023 would have resulted in 0.86 billion infections (∼61% of the total population). Our counterfactual analysis shows that the synergetic effect of vaccination (70% vaccination coverage), antiviral treatment (20% receiving antiviral treatment), and moderate nonpharmaceutical interventions (20% isolation and L1 PHSMs) could reduce the number of deaths to levels close to seasonal influenza (1.17 vs. 0.65 per 10,000 individuals and 5.85 vs. 3.85 per 10,000 individuals aged 60+, respectively). The maximum peak prevalence of hospital and ICU admissions are estimated to be lower than the corresponding capacities (8.6 vs. 10.4 per 10,000 individuals and 1.2 vs. 2.1 per 10,000 individuals, respectively). Conclusion: Our findings suggest that the capacity of the Chinese healthcare system was adequate to face the Omicron XBB wave in spring 2023 but, at the same time, supports the importance of administering highly effective vaccine with long-lasting immune response, and the use of antiviral treatments.

Abstract. Gliomas tend to have a poor prognosis and are the most common primary malignant tumors of the central nervous system. Compared with patients with other cancers, glioma patients often suffer from increased levels of psychological stress, such as anxiety and fear. Chronic stress (CS) is thought to impact glioma profoundly. However, because of the complex mechanisms underlying CS and variability in individual tolerance, the role of CS in glioma remains unclear. This review suggests a new proposal to redivide the stress system into two parts. Neuronal activity is dominant upstream. Stress-signaling molecules produced by the neuroendocrine system are dominant downstream. We discuss the underlying molecular mechanisms by which CS impacts glioma. Potential pharmacological treatments are also summarized from the therapeutic perspective of CS.

Southeast Asia is suffering from extreme weather, and its carbon emissions are increasing rapidly. For efficient emission reduction, clarifying the complex sources behind is necessary. This study takes a new perspective of incorporating multiple GHGs (greenhouse gases) into the same analysis framework, employing the STIRPAT model to dissect the contributions of various socio-economic factors to the emissions of CO2, CH4, and F-gases based on panel data. The analysis reveals that the driving coefficients of total population and urbanization rate are several to 10 times higher than those of other factors and can reach up to 2.98 and 4.715 and are the most significant drivers of GHG emissions in the region. Quadratic per capita GDP shows a significant positive driving effect, indicating that most Southeast Asian countries are unlikely to reach the Kuznets point in current development trajectories. The driving coefficients of F-gases in industrialized countries are significantly higher than those of other GHGs, indicating that their growth rate of F-gases will outpace that of CO2 and CH4. In countries with a similar industrial structure, the driving coefficient of CO2 from the secondary industry is up to 0.183 and down to 0.057, shows the influence of specific sector composition in the secondary industry on emissions. These findings provide critical insights for Southeast Asian policymakers aiming to develop effective climate policies.

Background: Tripterygium glycosides (TG) is extracted from the roots of Tripterygium wilfordii Hook F (Lei gong teng, a traditional Chinese medicine). It is widely used in China to treat immunoglobulin A vasculitis nephritis (IgAVN), which is a common secondary glomerular disease. As there are no guidelines for the rational application of TG, we performed this study to evaluate the efficacy and safety of different doses of TG and to determine the optimal treatment for IgAVN. Methods: Ten databases were searched from their inception to April 2023 for randomised controlled trials (RCTs) using TG, TG combined with glucocorticoids (GC), or TG combined with traditional Chinese medicine (TCM) to treat IgAVN. A network meta-analysis was performed following the protocol (CRD42023401645). Results: Forty-four eligible RCTs involving 3402 patients were included. For effective rate, TG 1.5 mg/kg/d (TG1.5) + TCM was ranked as the best intervention, followed by TG 1.0 mg/kg/d (TG1.0) + TCM, TG1.5, TG1.0+GC, TG1.0, TCM, GC, and routine treatment (RT). TG1.0+TCM ranked best in reducing recurrence, followed by TG1.0+GC, GC, TG1.5, and RT. Compared with TG1.0, TG1.0+TCM and TG1.5+TCM effectively reduced liver injury events. Compared with TG1.5, TG1.5+TCM and TG1.0+TCM effectively reduced leukopenia events. No significant differences in the reduction of gastrointestinal events were observed between the interventions. Subgroup analyses explored the effects of the participants’ age. The intervention rankings of the outcomes generally remained consistent. Only a small difference was observed in gastrointestinal events. TCM was the best treatment for reducing gastrointestinal events in paediatric patients. Conclusions: The results showed a positive correlation between dose and efficacy, whereas no relationship was found between dose and adverse events. TCM can boost the efficacy and reduce adverse events when combined with TG. In conclusion, we consider TG1.5+TCM as the best treatment for IgAVN. However, further research is required to confirm these findings.

Abstract Background As the largest substantive organ of animals, the liver plays an essential role in the physiological processes of digestive metabolism and immune defense. However, the cellular composition of the pig liver remains poorly understood. This investigation used single-nucleus RNA sequencing technology to identify cell types from liver tissues of pigs, providing a theoretical basis for further investigating liver cell types in pigs. Results The analysis revealed 13 cells clusters which were further identified 7 cell types including endothelial cells, T cells, hepatocytes, Kupffer cells, stellate cells, B cells, and cholangiocytes. The dominant cell types were endothelial cells, T cells and hepatocytes in the liver tissue of Dahe pigs and Dahe black pigs, which accounts for about 85.76% and 82.74%, respectively. The number of endothelial cells was higher in the liver tissue of Dahe pigs compared to Dahe black pigs, while the opposite tendency was observed for T cells. Moreover, functional enrichment analysis demonstrated that the differentially expressed genes in pig hepatic endothelial cells were significantly enriched in the protein processing in endoplasmic reticulum, MAPK signaling pathway, and FoxO signaling pathway. Functional enrichment analysis demonstrated that the differentially expressed genes in pig hepatic T cells were significantly enriched in the thyroid hormone signaling pathway, B cell receptor signaling pathway, and focal adhesion. Functional enrichment analysis demonstrated that the differentially expressed genes in pig hepatic hepatocytes were significantly enriched in the metabolic pathways. Conclusions In summary, this study provides a comprehensive cell atlas of porcine hepatic tissue. The number, gene expression level and functional characteristics of each cell type in pig liver tissue varied between breeds.

Background: Low-dose ionizing radiation-induced protection and damage are of great significance among radiation workers. We aimed to study the role of glutathione S-transferase Pi (GSTP1) in low-dose ionizing radiation damage and clarify the impact of ionizing radiation on the biological activities of cells. Results: In this study, we collected peripheral blood samples from healthy adults and workers engaged in radiation and radiotherapy and detected the expression of GSTP1 by qPCR. We utilized γ-rays emitted from uranium tailings as a radiation source, with a dose rate of 14 μGy/h. GM12878 cells subjected to this radiation for 7, 14, 21, and 28 days received total doses of 2.4, 4.7, 7.1, and 9.4 mGy, respectively. Subsequent analyses, including flow cytometry, MTS, and other assays, were performed to assess the ionizing radiation’s effects on cellular biological functions. In peripheral blood samples collected from healthy adults and radiologic technologist working in a hospital, we observed a decreased expression of GSTP1 mRNA in radiation personnel compared to the healthy controls. In cultured GM12878 cells exposed to low-dose ionizing radiation from uranium tailings, we noted significant changes in cell morphology, suppression of proliferation, delay in cell cycle progression, and increased apoptosis. These effects were partially reversed by overexpression of GSTP1. Moreover, low-dose ionizing radiation increased GSTP1 gene methylation and downregulated GSTP1 expression. Furthermore, low-dose ionizing radiation affected the expression of GSTP1-related signaling molecules. Conclusions: This study shows that low-dose ionizing radiation damages GM12878 cells and affects their proliferation, cell cycle progression, and apoptosis. In addition, GSTP1 plays a modulating role under low-dose ionizing radiation damage conditions. Low-dose ionizing radiation affects the expression of Nrf2, JNK, and other signaling molecules through GSTP1.

Modern data centers provide the foundational infrastructure of cloud computing. Workload generation, which involves simulating or constructing tasks and transactions to replicate the actual resource usage patterns of real-world systems or applications, plays essential role for efficient resource management in these centers. Data center traces, rich in information about workload execution and resource utilization, are thus ideal data for workload generation. Traditional traces provide detailed temporal resource usage data to enable fine-grained workload generation. However, modern data centers tend to favor tracing statistical metrics to reduce overhead. Therefore the accurate reconstruction of temporal resource consumption without detailed, temporized trace information become a major challenge for trace-based workload generation. To address this challenge, we propose STWGEN, a novel method that leverages statistical trace data for workload generation. STWGEN is specifically designed to generate the batch task workloads based on Alibaba trace. STWGEN contains two key components: a suite of C program-based flexible workload building blocks and a heuristic strategy to assemble building blocks for workload generation. Both components are carefully designed to reproduce synthetic batch tasks that closely replicate the observed resource usage patterns in a representative data center. Experimental results demonstrate that STWGEN outperforms state-of-the-art workload generation methods as it emulates workload-level and machine-level resource usage in much higher accuracy.