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Abstract Background Non-pharmaceutical measures and travel restrictions have halted the spread of coronavirus disease 2019 (COVID-19) and influenza. Nonetheless, with COVID-19 restrictions lifted, an unanticipated outbreak of the influenza B/Victoria virus in late 2021 and another influenza H3N2 outbreak in mid-2022 occurred in Guangdong, southern China. The mechanism underlying this phenomenon remains unknown. To better prepare for potential influenza outbreaks during COVID-19 pandemic, we studied the molecular epidemiology and phylogenetics of influenza A(H3N2) and B/Victoria that circulated during the COVID-19 pandemic in this region. Methods From January 1, 2018 to December 31, 2022, we collected throat swabs from 173,401 patients in Guangdong who had acute respiratory tract infections. Influenza viruses in the samples were tested using reverse transcription-polymerase chain reaction, followed by subtype identification and sequencing of hemagglutinin (HA) and neuraminidase (NA) genes. Phylogenetic and genetic diversity analyses were performed on both genes from 403 samples. A rigorous molecular clock was aligned with the phylogenetic tree to measure the rate of viral evolution and the root-to-tip distance within strains in different years was assessed using regression curve models to determine the correlation. Results During the early period of COVID-19 control, various influenza viruses were nearly undetectable in respiratory specimens. When control measures were relaxed in January 2020, the influenza infection rate peaked at 4.94% (39/789) in December 2021, with the influenza B/Victoria accounting for 87.18% (34/39) of the total influenza cases. Six months later, the influenza infection rate again increased and peaked at 11.34% (255/2248) in June 2022; influenza A/H3N2 accounted for 94.51% (241/255) of the total influenza cases in autumn 2022. The diverse geographic distribution of HA genes of B/Victoria and A/H3N2 had drastically reduced, and most strains originated from China. The rate of B/Victoria HA evolution (3.11 × 10−3, P

The application of low-condensation diesel in cold regions with extremely low ambient temperatures (−14 to −29 °C) has enabled the operation of diesel vehicles. Still, it may contribute to heavy haze pollution in cold regions during winter. Here we examine pollutant emissions from low-condensation diesel in China. We measure the emissions of elemental carbon (EC), organic carbon (OC), and elements, including heavy metals such as arsenic (As). Our results show that low-condensation diesel increased EC and OC emissions by 2.5 and 2.6 times compared to normal diesel fuel, respectively. Indicators of vehicular sources, including EC, As, lead (Pb), cadmium (Cd), chromium (Cr), nickel (Ni), and manganese (Mn), increased by approximately 20.2–162.5% when using low-condensation diesel. Seasonal variation of vehicular source indicators, observed at road site ambient environments revealed the enhancement of PM2.5 pollution by the application of low-condensation diesel in winter. These findings suggest that −35# diesel, a low-cetane index diesel, may enhance air pollution in winter, according to a dynamometer test conducted in laboratory. It raises questions about whether higher emissions are released if −35# diesel is applied to running vehicles in real-world cold ambient environments.

In response to the challenges of accurate identification and localization of garbage in intricate urban street environments, this paper proposes EcoDetect-YOLO, a garbage exposure detection algorithm based on the YOLOv5s framework, utilizing an intricate environment waste exposure detection dataset constructed in this study. Initially, a convolutional block attention module (CBAM) is integrated between the second level of the feature pyramid etwork (P2) and the third level of the feature pyramid network (P3) layers to optimize the extraction of relevant garbage features while mitigating background noise. Subsequently, a P2 small-target detection head enhances the model’s efficacy in identifying small garbage targets. Lastly, a bidirectional feature pyramid network (BiFPN) is introduced to strengthen the model’s capability for deep feature fusion. Experimental results demonstrate EcoDetect-YOLO’s adaptability to urban environments and its superior small-target detection capabilities, effectively recognizing nine types of garbage, such as paper and plastic trash. Compared to the baseline YOLOv5s model, EcoDetect-YOLO achieved a 4.7% increase in mAP0.5, reaching 58.1%, with a compact model size of 15.7 MB and an FPS of 39.36. Notably, even in the presence of strong noise, the model maintained a mAP0.5 exceeding 50%, underscoring its robustness. In summary, EcoDetect-YOLO, as proposed in this paper, boasts high precision, efficiency, and compactness, rendering it suitable for deployment on mobile devices for real-time detection and management of urban garbage exposure, thereby advancing urban automation governance and digital economic development.

Flat-rolled steel sheets are one of the major products of the metal industry. Strip steel’s production quality is crucial for the economic and safety aspects of humanity. Addressing the challenges of identifying the surface defects of strip steel in real production environments and low detection efficiency, this study presents an approach for strip defect detection based on YOLOv5s, termed SDD-YOLO. Initially, this study designs the Convolution-GhostNet Hybrid module (CGH) and Multi-Convolution Feature Fusion block (MCFF), effectively reducing computational complexity and enhancing feature extraction efficiency. Subsequently, CARAFE is employed to replace bilinear interpolation upsampling to improve image feature utilization; finally, the Bidirectional Feature Pyramid Network (BiFPN) is introduced to enhance the model’s adaptability to targets of different scales. Experimental results demonstrate that, compared to the baseline YOLOv5s, this method achieves a 6.3% increase in mAP50, reaching 76.1% on the Northeastern University Surface Defect Database for Detection (NEU-DET), with parameters and FLOPs of only 3.4MB and 6.4G, respectively, and FPS reaching 121, effectively identifying six types of defects such as Crazing and Inclusion. Furthermore, under the conditions of strong exposure, insufficient brightness, and the addition of Gaussian noise, the model’s mAP50 still exceeds 70%, demonstrating the model’s strong robustness. In conclusion, the proposed SDD-YOLO in this study features high accuracy, efficiency, and lightweight characteristics, making it applicable in actual production to enhance strip steel production quality and efficiency.

In recent decades, skin cancer has emerged as a significant global health concern, demanding timely detection and effective therapeutic interventions. Automated image classification via computational algorithms holds substantial promise in significantly improving the efficacy of clinical diagnoses. This study is committed to mitigating the challenge of diagnostic accuracy in the classification of multiclass skin lesions. This endeavor is inherently formidable owing to the resemblances among various lesions and the constraints associated with extracting precise global and local image features within diverse dimensional spaces using conventional convolutional neural network methodologies. Consequently, this study introduces the SkinSwinViT methodology for skin lesion classification, a pioneering model grounded in the Swin Transformer framework featuring a global attention mechanism. Leveraging the inherent cross-window attention mechanism within the Swin Transformer architecture, the model adeptly captures local features and interdependencies within skin lesion images while additionally incorporating a global self-attention mechanism to discern overarching features and contextual information effectively. The evaluation of the model’s performance involved the ISIC2018 challenge dataset. Furthermore, data augmentation techniques augmented training dataset size and enhanced model performance. Experimental results highlight the superiority of the SkinSwinViT method, achieving notable metrics of accuracy, recall, precision, specificity, and F1 score at 97.88%, 97.55%, 97.83%, 99.36%, and 97.79%, respectively.

BackgroundAs China amends its “zero COVID” strategy, a sudden increase in the number of infections may overwhelm medical resources and its impact has not been quantified. Specific mitigation strategies are needed to minimize disruption to the healthcare system and to prepare for the next possible epidemic in advance.MethodWe develop a stochastic compartmental model to project the burden on the medical system (that is, the number of fever clinic visits and admission beds) of China after adjustment to COVID-19 policy, which considers the epidemiological characteristics of the Omicron variant, age composition of the population, and vaccine effectiveness against infection and severe COVD-19. We also estimate the effect of four-dose vaccinations (heterologous and homologous), antipyretic drug supply, non-pharmacological interventions (NPIs), and triage treatment on mitigating the domestic infection peak.ResultAs to the impact on the medical system, this epidemic is projected to result in 398.02 million fever clinic visits and 16.58 million hospitalizations, and the disruption period on the healthcare system is 18 and 30 days, respectively. Antipyretic drug supply and booster vaccination could reduce the burden on emergency visits and hospitalization, respectively, while neither of them could not reduce to the current capacity. The synergy of several different strategies suggests that increasing the heterologous booster vaccination rate for older adult to over 90% is a key measure to alleviate the bed burden for respiratory diseases on the basis of expanded healthcare resource allocation.ConclusionThe Omicron epidemic followed the adjustment to COVID-19 policy overloading many local health systems across the country at the end of 2022. The combined effect of vaccination, antipyretic drug supply, triage treatment, and PHSMs could prevent overwhelming medical resources.

This study aims to promote the communication and cognition of China’s national image in the world by investigating the utilization of multimodal metaphors at the Opening Ceremony of Beijing 2022 Winter Olympics and the national image that the multimodal metaphors indicate. This paper utilizes the multimodal corpus that contains multiple media types such as texts, audio and images to conduct multimodal analysis and to investigate how to achieve effective transmission from three perspectives (the cognitive, emotional, and behavioral aspects). Further, in order to confirm the effectiveness of this transmission, data analysis is carried out based on the comments about the opening ceremony of Beijing Winter Olympics on YouTube. Based on the results of data analysis and discussion, the study concludes four images of China from the Opening Ceremony: a major country with firm cultural self-confidence, with the endeavor to build a human community with a shared future, with advanced science and technology, and with persistence of sustainable development

The involvement of chondrocyte ferroptosis in the development of osteoarthritis (OA) has been observed, and Sarsasapogenin (Sar) has therapeutic promise in a variety of inflammatory diseases. This study investigates the potential influence of Sar on the mechanism of chondrocyte ferroptotic cell death in the progression of osteoarthritic cartilage degradation. An in vivo medial meniscus destabilization (DMM)-induced OA animal model as well as an in vitro examination of chondrocytes in an OA microenvironment induced by interleukin-1β (IL-1β) exposure were employed. Histology, immunofluorescence, quantitative RT-PCR, Western blot, cell viability, and Micro-CT analysis were utilized in conjunction with gene overexpression and knockdown to evaluate the chondroprotective effects of Sar in OA progression and the role of Yes-associated protein 1 (YAP1) in Sar-induced ferroptosis resistance of chondrocytes. In this study we found Sar reduced chondrocyte ferroptosis and OA progression. And Sar-induced chondrocyte ferroptosis resistance was mediated by YAP1. Furthermore, infection of siRNA specific to YAP1 in chondrocytes reduced Sar's chondroprotective and ferroptosis-suppressing effects during OA development. The findings suggest that Sar mitigates the progression of osteoarthritis by decreasing the sensitivity of chondrocytes to ferroptosis through the promotion of YAP1, indicating that Sar has the potential to serve as a therapeutic approach for diseases associated with ferroptosis.

Abstract Background Coronavirus disease 2019 (COVID-19) causes a global pandemic and has devastating effects around the world, however, there are no specific antiviral drugs and vaccines for the constant mutation of SARS-CoV-2. Purpose In this study, we evaluted the antiviral and anti-inflammatory activities of Liushen Capsules (LS) on different novel coronavirus in vitro, studied its therapeutic effects on novel SARS-CoV-2 infected mice and observed the LS’s clinical efficacy and safety in COVID-19. Methods The antiviral and aiti-inflammatory effects of LS on the 501Y.V2/B.1.35 and G/478K.V1/ B.1.617.2 strains were determined in vitro. A hACE2 mouse model of novel SARS-CoV-2 pneumonia was established. Survival rates, histological changes, inflammatory markers, lung virus titers and the expression of the key proteins in the NF-κB/MAPK signaling pathway was detected by western blotting and immumohistochemical staining in the lungs were measured. Subsequently, the disease duration, prognosis of disease, time of negative nucleic acid and the cytokines levels in serum were used to assess the efficacy of treatment with LS in patients. Results The results showed that LS (2, 1, 0.5 μg/mL) could significantly inhibit the replication of the two SARS-CoV-2 variants and the expression of pro-inflammatory cytokines (IL-6, IL-8, IP-10, CCL-5, MIP-1α, IL-1α) induced by the virus in vitro. As for the survival experiment in mice, the survival rate of virus group was 20%, while LS-treatment groups (40, 80, 160 mg/kg) could increase the survival rate to 60, 100 and 100%, respectively. LS (40, 80, 160 mg/kg) could significantly decrease the lung titers in mice and it could improve the pathological changes, inhibit the excessive inflammatory mediators (IFN-α, IFN-γ, IP-10, MCP-1) and the protein expression of p-NF-κB p65 in mice. Moreover, LS could significantly decrease SARS-CoV-2-induced activation of p-NF-κB p65, p-IκBα, and p-p38 MAPK and increase the protein expression of the IκBα. In addition, the patient got complete relief of symptoms after being treated with LS for 6 days and was proven with negative PCR test after being treated for 23 days. Finally, treatment with LS could reduce the release of inflammatory cytokines (IL-6, PDGF-AA/BB, Eotaxin, MCP-1, MIP-1α, MIP-1β, GRO, CCL-5, MCP-3, IP-10, IL-1α). Conclusion LS effectively alleviated novel SARS-CoV-2 or variants induced pneumonia in vitro and in vivo, and improved the prognosis of COVID-19. In light of the efficacy and safety profiles, LS could be considered for the treatment of COVID-19 with a broad-spectrum antiviral and anti-inflammatory agent.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death globally and liver transplantation (LT) can serve as the best curative treatment option. However, HCC recurrence after LT remains the major obstacle to the long-term survival of recipients. Recently, immune checkpoint inhibitors (ICIs) have revolutionized the treatment of many cancers and provided a new treatment strategy for post-LT HCC recurrence. Evidence has been accumulated with the real-world application of ICIs in patients with post-LT HCC recurrence. Notably, the use of these agents as immunity boosters in recipients treated with immunosuppressors is still controversial. In this review, we summarized the immunotherapy for post-LT HCC recurrence and conducted an efficacy and safety evaluation based on the current experience of ICIs for post-LT HCC recurrence. In addition, we further discussed the potential mechanism of ICIs and immunosuppressive agents in regulating the balance between immune immunosuppression and lasting anti-tumor immunity.

Background: Traditional Chinese Medicines (TCMs) are effective strategies for preventing influenza infection. Liushen Capsules can inhibit influenza virus proliferation, significantly mitigate virus-induced inflammation and improve acute lung injury in vitro or in vivo. However, the efficacy and safety of LS in clinical trials, and the role of LS in regulating metabolites in patients are not well known.Materials and methods: A randomized, double-blind, placebo-controlled clinical trial was designed in this study. All participants were enrolled between December 2019 and November 2020. The efficacy and safety were assessed by primary efficacy endpoint ((area under the curve (AUC) analysis)) and secondary endpoint (individual scores for each symptom, remission of symptoms, and rates of inflammatory factors). The serum samples were collected from patients to detect the levels of inflammatory factors using RT-PCR and to identify metabolites using a non-targeted metabolomics ultra-performance liquid chromatography-tandem mass spectrometry (LC-MS).Results: 81 participants from The Second Affiliated Hospital of Guangzhou University of Chinese Medicine and the First Affiliated Hospital of Guangzhou Medical University were completed the full study. After 14 days of intervention, the area under the curve (AUC) of the total symptom scores in LS group was significantly smaller than that in Placebo group (p < 0.001). Alleviation of sore throat, cough and nasal congestion in the LS group was significantly better than that in the Placebo group. The time and number to alleviation of symptoms or complete alleviation of symptoms in LS group was significantly better than that in Placebo group. The adverse effects of clinical therapy were slightly higher in LS group than in Placebo group, but there was no statistical difference. After 14 days of LS intervention, the levels of IL-1ra, Eotaxin, IFN-γ, IL-6, IL-10, IL-13, SCF and TRAIL in serum of participants with influenza infection were significantly decreased compared with Placebo group. It was observed that there were significant differences in the serum metabolic profiles between start- and end- LS groups. Further correlation analysis showed a potential regulatory crosstalk between glycerophospholipids, sphingolipids fatty acyls and excessive inflammation and clinical symptoms. Importantly, it may be closely related to phospholipid, fatty acid, arachidonic acid and amyl-tRNA synthesis pathway metabolic pathways.Conclusion: The study showed there were no clinically significant adverse effects on LS, and a significant improvement in influenza-like symptomatology and inflammatory response in patients treated with LS. Further analysis showed that LS could significantly correct the metabolic disorders in the serum metabolite profile of the patients. This provided new insights into the potential mechanism of LS for the treatment of influenza.

Distinguished features of cities influence the characteristics of CH4 emissions. A city-level emission inventory represents the characteristics of CH4 on a smaller scale, according to the special factors in each city. A city-level emission inventory was established to reveal the characteristics and source profile of CH4 emissions in the coldest province, which is a typical provincial cold region in northeast China. The dominant sources were identified for targeted cities. Rice cultivation, coal mining, oil and gas exploitation, and livestock are the dominant emission sectors. Emissions from other sectors, including wastewater disposal, biomass burning, landfill, etc. were also estimated. The provincial CH4 emissions increased gradually from 2003 to 2012, up to 2993.26 Gg with an annual increase rate of 2.85%; the emissions were 2740.63 in 2020. The emissions of CH4 in Harbin, Daqing, Jiamusi, and Hegang cities were higher than in the other nine cities, which were 337.23 Gg, 330.01 Gg, 328.55 Gg, and 307.42 Gg in 2020, respectively. Agriculture, including the rice cultivation, livestock, and biomass burning sectors contributed to 51.24–62.12% of total emissions, and the contributions increased gradually. Coal mining, oil and gas exploration, and fossil fuel combustion are energy-related sources, which contributed up to 37.91% of the total emissions, and the proportion kept decreasing to 23.87% in 2020. Furthermore, meteorological factors are especially relevant to the region, by which the differences of ambient temperature are over 60 °C (±30 °C). In the summer, CH4 emissions from the rice cultivation, biomass burning, livestock, and landfill sectors are obviously distinct from the heating period (winter), while few differences in CH4 emissions are found from wastewater disposal and the fossil fuel production sectors.

FBLN5, a member of the short fibulins in the fibulin family of extracellular matrix/matricellular proteins, is involved in interactions with components of the basement membrane and extracellular matrix proteins. It plays key roles in endothelial tissues in many vascular diseases. In this study, the relationship between FBLN5 and carotid atherosclerotic plaque stability as well as the regulatory roles of miRNAs were evaluated. Differential gene expression analyses and weighted gene co-expression network analysis (WGCNA) based on the GSE163154 dataset (including 16 samples without intraplaque hemorrhage and 27 samples with intraplaque hemorrhage) in GEO revealed that FBLN5 is related to plaque stability and is the most significantly differentially expressed gene. LASSO regression was used to evaluate genes obtained from the intersection of differentially expressed genes and clinically significant modules identified by WGCNA. A prediction model based on eight genes, including FBLN5, was constructed and showed an accuracy of 0.951 based on an ROC analysis. Low FBLN5 expression in plaque tissues was confirmed by immunohistochemistry and western blotting. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses showed that FBLN5 acted mainly by the maintenance of the cellular matrix and reactive oxygen species production. miRNAs upstream of these eight predictive genes, including FBLN5, were identified and used to construct a network diagram. These results revealed that hsa-mir-128 and hsa-mir-532–3p were upstream regulatory factors of FBLN5, as verified by PCR assays of human plaque tissues demonstrating that both miRNAs were significantly up-regulated. Therefore, FBLN5 may play an important role in carotid atherosclerosis via hsa-mir-128 and hsa-mir-532–3p as well as become an essential target for treatment.

Summary: The recently identified novel cytosolic DNA sensor cyclic GMP-AMP synthase (cGAS) activates the downstream adaptor protein stimulator of interferon genes (STING) by catalysing the synthesis of cyclic GMP-AMP. This in turn initiates an innate immune response through the release of various cytokines, including type I interferon. Foreign DNA (microbial infection) or endogenous DNA (nuclear or mitochondrial leakage) can serve as cGAS ligands and lead to the activation of cGAS-STING signalling. Therefore, the cGAS-STING pathway plays essential roles in infectious diseases, sterile inflammation, tumours, and autoimmune diseases. In addition, cGAS-STING signalling affects the progression of liver inflammation through other mechanisms, such as autophagy and metabolism. In this review, we summarise recent advances in our understanding of the role of cGAS-STING signalling in the innate immune modulation of different liver diseases. Furthermore, we discuss the therapeutic potential of targeting the cGAS-STING pathway in the treatment of liver diseases.

This paper investigates the quasi-synchronization of nonidentical fractional-order memristive neural networks (FMNNs) via impulsive control. Based on a newly provided fractional-order impulsive systems comparison lemma, the average impulsive interval definition, and the Laplace transform, some quasi-synchronization conditions are obtained with fractional order 0

Background: Traditional Chinese Medicines (TCMs) are effective strategies for preventing influenza infection. Liushen Capsules can inhibit influenza virus proliferation, significantly mitigate virus-induced inflammation and improve acute lung injury in vitro or in vivo. However, the efficacy and safety of LS in clinical trials, and the role of LS in regulating metabolites in patients are not well known. Materials and methods: A randomized, double-blind, placebo-controlled clinical trial was designed in this study. All participants were enrolled between December 2019 and November 2020. The efficacy and safety were assessed by primary efficacy endpoint ((area under the curve (AUC) analysis)) and secondary endpoint (individual scores for each symptom, remission of symptoms, and rates of inflammatory factors). The serum samples were collected from patients to detect the levels of inflammatory factors using RT-PCR and to identify metabolites using a non-targeted metabolomics ultra-performance liquid chromatography-tandem mass spectrometry (LC-MS). Results: 81 participants from The Second Affiliated Hospital of Guangzhou University of Chinese Medicine and the First Affiliated Hospital of Guangzhou Medical University were completed the full study. After 14 days of intervention, the area under the curve (AUC) of the total symptom scores in LS group was significantly smaller than that in Placebo group (p < 0.001). Alleviation of sore throat, cough and nasal congestion in the LS group was significantly better than that in the Placebo group. The time and number to alleviation of symptoms or complete alleviation of symptoms in LS group was significantly better than that in Placebo group. The adverse effects of clinical therapy were slightly higher in LS group than in Placebo group, but there was no statistical difference. After 14 days of LS intervention, the levels of IL-1ra, Eotaxin, IFN-B, IL-6, IL-10, IL-13, SCF and TRAIL in serum of participants with influenza infection were significantly decreased compared with Placebo group. It was observed that there were significant differences in the serum metabolic profiles between start- and end- LS groups. Further correlation analysis showed a potential regulatory crosstalk between glycerophospholipids, sphingolipids fatty acyls and excessive inflammation and clinical symptoms. Importantly, it may be closely related to phospholipid, fatty acid, arachidonic acid and amyl-tRNA synthesis pathway metabolic pathways. Conclusion: The study showed there were no clinically significant adverse effects on LS, and a significant improvement in influenza-like symptomatology and inflammatory response in patients treated with LS. Further analysis showed that LS could significantly correct the metabolic disorders in the serum metabolite profile of the patients. This provided new insights into the potential mechanism of LS for the treatment of influenza. [ABSTRACT FROM AUTHOR]