Over the past three decades， China has made significant progress in the prevention and control of viral hepatitis， and the incidence rates of new-onset pediatric hepatitis B virus infections and acute viral hepatitis in the population have reduced to a relatively low level； however， there is still a heavy disease burden of chronic viral hepatitis in China， which severely affects the health status of the population. This study systematically summarizes the achievements of viral hepatitis prevention and control in China， analyzes existing problems and challenges， and proposes comprehensive prevention and control strategies and measures to eliminate viral hepatitis as a public health threat based on the national conditions of China， in order to provide a reference for related departments in China on how to achieve the action targets for eliminating viral hepatitis as a public health threat by 2030.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

BACKGROUND: Mild cognitive impairment (MCI) is common in atrial fibrillation (AF) patients and may develop earlier in those with multiple cardiovascular comorbidities, potentially impairing self-management and treatment adherence. This study aimed to characterize the prevalence and profile of MCI in AF patients, examine its associations with cardiovascular comorbidities, and assess how these comorbidities influence specific cognitive domains. METHODS: This cross-sectional study analyzed data from AF patients who underwent cognitive assessment between 2017 and 2021. Cognitive status was categorized as MCI or non-MCI based on the Montreal Cognitive Assessment. Associations between comorbidities and MCI were assessed by logistic regression, and cognitive domains were compared using the Mann-Whitney U test. RESULTS: Of 4136 AF patients (mean age: 64.7 ± 9.4 years, 64.7% male), 33.5% of patients had MCI. Among the AF patients, 31.2% of patients had coronary artery disease, 20.1% of patients had heart failure, and 18.1% of patients had hypertension. 88.7% of patients had left atrial enlargement, and 11.0% of patients had reduced left ventricular ejection fraction. Independent factors associated with higher MCI prevalence included older age (OR = 1.04, 95% CI: 1.03-1.05, P < 0.001), lower education level (OR = 1.51, 95% CI: 1.31-1.73, P < 0.001), hypertension (OR = 1.28, 95% CI: 1.07-1.52, P = 0.001), heart failure (OR = 1.24, 95% CI: 1.04-1.48, P = 0.020), and lower left ventricular ejection fraction (OR = 1.43, 95% CI: 1.04-1.98, P = 0.028). A higher CHA₂DS₂-VASc score (OR = 1.27, 95% CI: 1.22-1.33, P < 0.001; ≥ 2 points vs. < 2 points), and greater atherosclerotic cardiovascular disease burden (OR = 1.45, 95% CI: 1.02-2.08, P = 0.040; 2 types vs. 0 type) were linked to increased MCI risk. These above factors influenced various cognitive domains. CONCLUSIONS MCI is common in AF and closely associated with cardiovascular multimorbidity. Patients with multiple comorbidities are at higher risk, highlighting the importance of routine cognitive assessment to support self-management and integrated care.

This research study focuses on addressing the limitations of current neuropathic pain (NP) treatments by developing a novel dual-target modulator, E0199, targeting both Na_V1.7, Na_V1.8, and Na_V1.9 and K_V7 channels, a crucial regulator in controlling NP symptoms. The objective of the study was to synthesize a compound capable of modulating these channels to alleviate NP. Through an experimental design involving both in vitro and in vivo methods, E0199 was tested for its efficacy on ion channels and its therapeutic potential in a chronic constriction injury (CCI) mouse model. The results demonstrated that E0199 significantly inhibited Na_V1.7, Na_V1.8, and Na_V1.9 channels with a particularly low half maximal inhibitory concentration (IC₅₀) for Na_V1.9 by promoting sodium channel inactivation, and also effectively increased K_V7.2/7.3, K_V7.2, and K_V7.5 channels, excluding K_V7.1 by promoting potassium channel activation. This dual action significantly reduced the excitability of dorsal root ganglion neurons and alleviated pain hypersensitivity in mice at low doses, indicating a potent analgesic effect without affecting heart and skeletal muscle ion channels critically. The safety of E0199 was supported by neurobehavioral evaluations. Conclusively, E0199 represents a ground-breaking approach in NP treatment, showcasing the potential of dual-target small-molecule compounds in providing a more effective and safe therapeutic option for NP. This study introduces a promising direction for the future development of NP therapeutics.

As global greenhouse gases continue rising, the urgency of more ambitious action is clearer than ever before. China is the world's biggest emitter of greenhouse gases and one of the countries affected most by climate change. The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts. This article aimed to review the evidence of environmental damages and health risks posed by climate change and to provide a new science-based perspective for the delivery of sustainable development goals. Over recent decades, China has experienced a strong warming pattern with a growing frequency of extreme weather events, and the impacts of climate change on China's environment and human health have been consistently observed, with increasing O ₃ air pollution, decreases in water resources and availability, land degradation, and increased risks for both communicable and non-communicable diseases. Therefore, China's climate policy should target the key factors driving climate change and scale up strategic measures to curb carbon emissions and adapt to inevitable increasing climate impacts. It provides new insights for not only China but also other countries, particularly developing and emerging economies, to ensure climate and environmental sustainability whilst pursuing economic growth.
Climate Change ; China ; Humans ; Greenhouse Gases ; Air Pollution ; Sustainable Development ; Environment

Objective To explore the relationship between miR-409-3p and miR-325-3p with the efficacy of inter-ventional therapy in patients with primary liver cancer.Methods Ninety-six patients with primary liver cancer who visited Nanyang Central Hospital from October 2021 to January 2024 were regarded as the liver cancer group.All patients underwent transcatheter arterial chemoembolization(TACE)treatment and were separated into an effective group(complete remission,partial remission)and an ineffective group(disease stability,disease progression)based on the treatment effect.Totally 91 patients with liver cirrhosis who underwent treatment in our hospital during the same period were selected as liver cancer group and 98 healthy individuals who received physical examinations during the same period were selected as the healthy group.Serum miR-409-3p,miR-325-3p levels were detected and analyzed for their correlation.Logistic regression was applied to analyze the relevant factors affecting the effi-cacy of TACE treatment.Receiver operating characteristic(ROC)curve was applied to evaluate their predictive value for TACE treatment efficacy of serum miR-409-3p,miR-325-3p levels.Results Compared with the healthy group,the serum level of miR-409-3p and miR-325-3p in the liver cirrhosis group and liver cancer group were re-duced(P＜0.05).Compared with the liver cirrhosis group,the serum level of miR-409-3p and miR-325-3p in the liver cancer group were also reduced(P＜0.05).Compared with the effective group,the serum level of miR-409-3p and miR-325-3p in the ineffective group significantly decreased(P＜0.05).There was a positive correlation between serum level of miR-409-3p and of miR-325-3p in patients with primary liver cancer(r=0.472,P＜0.001).The elevated level of miR-409-3p and miR-325-3p were protective factors for ineffective TACE treat-ment in primary liver cancer patients(P＜0.05).The combination of serum miR-409-3p and miR-325-3p was su-perior to single prediction in predicting efficacy after TACE treatment in primary liver cancer patients(Zcombination-miR-409-3p=4.556,P＜0.001,Zcombination-miR-325-3p=2.613,P＜0.01).Conclusions The serum level of miR-409-3p as well as miR-325-3p is both reduced in patients with primary liver cancer,and is related to the effi-cacy of interventional therapy.

Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

The cholinergic anti-inflammatory pathway(CAP)is a neuroimmunoregulatory pathway that has attracted much attention in recent years.This pathway releases acetylcholine(ACh)by activating the vagus nerve.The binding of ACh to α7 nicotinic acetylcholine receptor receptors on the surface of macrophages can inhibit the release of proinflammatory factors,so as to effectively regulate the inflammatory response in the body.CAP plays a key role in suppressing excessive inflammatory responses and maintaining immune balance,providing a potential therapeutic pathway for a variety of inflammatory immune diseases.Research progress on the physiological function of CAP and its activation and blocking methods are reviewed in this paper,in order to provide new methods and ideas for treatment of inflammation-related diseases and exploring therapeutic drugs targeting CAP pathway.