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.

Animals ; Macaca mulatta ; Optic Disk ; Glaucoma ; Craniocerebral Trauma ; Intraocular Pressure ; Low Tension Glaucoma

An intensive breast array sensor was designed based on three-dimensional electrical impedance tomography in this work.Firstly,an electrical impedance sensor for detection of breast cancer was developed.The sensor adopted the integrated design of excitation electrode array and ground electrode to achieve structural simplification.It realized electric field densification through conical matrix and double-layer circumferentially arranged electrode array and improved the detection accuracy of target object through taper optimization.Secondly,the imaging system was designed,and the sensor was optimized by numerical simulation.The simulation results showed that halving the number of electrodes did not affect imaging accuracy of the sensor,but could improve the imaging speed.Finally,the performance of the sensor was verified by experiment.The signal-to-noise ratio and channel consistency of the system were at a good level.The sensor was used to reconstruct three-dimensional image of the experimental model with relative volume of the detection field of 0.4%.The image correlation coefficient of the single target imaging was above 0.6 and the position of the double target object could be clearly identified,and thus the visual detection of breast cancer was realized.

BACKGROUND:Hydroxyapatite is the main inorganic component of bone tissue.The polymer has the structure and function of a biomimetic extracellular matrix.The composites of hydroxyapatite and polymer have been widely studied. OBJECTIVE:To summarize the research status of hydroxyapatite composite polymer materials for bone tissue repair. METHODS:The articles collected in PubMed,Web of Science,CNKI and WanFang databases were searched from January 2010 to April 2023.The Chinese and English search terms were"hydroxyapatite,polymer,composites,degradability,bone defect,bone repair".Finally,75 articles were included for review. RESULTS AND CONCLUSION:Polymers often used in composite with hydroxyapatite for bone tissue repair include natural polymers(collagen,chitosan,alginate,serine protein,cellulose,hyaluronic acid,and polyhydroxybutyrate)and synthetic polymers[polylactic acid,polylactic acid-hydroxyacetic acid copolymer,poly(has-lactide),poly(amino acid)and poly(vinyl alcohol)].The mechanical properties and osteoinductivity of hydroxyapatite/polymer composites were improved compared with pure hydroxyapatite.Hydroxyapatite composite with polymers can be made into porous scaffolds,hydrogels,and coatings for bone repair.Hydroxyapatite/polymer composites can accelerate bone reconstruction with a slow release of loaded drugs and cytokines due to their bionic extracellular matrix structure and function.Based on the diversity of causes of bone defects and the fact that bone repair is a complex continuous process involving multiple biological factors and proteins,repair materials with mechanical properties matching bone tissue,degradation processes synchronized with bone repair,and efficient osteogenesis and vascularization need to be further investigated.

BACKGROUND:Compared with traditional two-dimensional culture,three-dimensional microtissue culture can show greater advantages.However,more favorable cultivation methods in three-dimensional culture still need to be further explored. OBJECTIVE:To evaluate the cell behavior of microtissue and its ability to promote cartilage formation under two three-dimensional culture methods. METHODS:Cartilage-derived microcarriers were prepared by chemical decellularization and tissue crushing.DNA quantification and nuclear staining were used to verify the success of decellularization,and histological staining was used to observe the matrix retention before and after decellularization.The microcarriers were characterized by scanning electron microscopy and CCK-8 assay.Cartilage-derived microtissues were constructed by combining cartilage-derived microcarriers with human adipose mesenchymal stem cells through three-dimensional static culture and three-dimensional dynamic culture methods.The cell viability and chondrogenic ability of the two groups of microtissues were detected by scanning electron microscopy,live and dead staining,and RT-qPCR. RESULTS AND CONCLUSION:(1)Cartilage-derived microcarriers were successfully prepared.Compared with before decellularization,the DNA content significantly decreased after decellularization(P<0.001).Scanning electron microscope observation showed that the surface of the microcarrier was surrounded by collagen,maintaining the characteristics of the natural extracellular matrix of cartilage cells.CCK-8 assay indicated that microcarriers had no cytotoxicity and could promote cell proliferation.(2)Scanning electron microscopy and live and dead staining results showed that compared with the three-dimensional static group,the three-dimensional dynamic group had a more extended morphology of microtissue cells,and extensive connections between cells and cells,between cells and matrix,and between matrix.(3)The results of RT-qPCR showed that the expressions of SOX9,proteoglycan,and type Ⅱ collagen in microtissues of both groups were increased at 7 or 14 days.The relative expression levels of each gene in the three-dimensional dynamic group were significantly higher than those in the three-dimensional static group at 14 days(P<0.05).At 21 days,the three-dimensional static group had significantly higher gene expression compared with the three-diomensional dynamic group(P<0.001).(4)The results showed that compared with three-dimensional static culture microtissue,three-dimensional dynamic culture microtissue could achieve higher expression of chondrogen-related genes in a shorter time,showing better cell viability and chondrogenic ability.

Objective We aimed to assess the serum levels of the glycolysis-related protein hypoxia-inducible factor-1α(HIF-1α)and cytokines in patients with relapsing-remitting multiple sclerosis(RRMS)before and after treatment with the traditional Chinese medicine Yishen Daluo Decoction,as well as their correlation with clinical parameters,and explore the immune regulatory mechanism of Yishen Daluo Decoction on multiple sclerosis.Methods Twenty-eight patients with RRMS in remission recruited from May 2018 to January 2022 in the Multiple Sclerosis Clinic at Dongzhimen Hospital,Beijing University of Chinese Medicine were retrospectively included.Comparisons were made with paired samples from 13 of them before and after Yishen Daluo Decoction treatment.A total of 20 gender-and age-matched healthy controls(HCs)were also recruited.Clinical information was collected from all of the subjects,and the neurological impairments of RRMS patients were assessed with the Expanded Disability Status Scale(EDSS)score.ELISA and SP-X multiplex cytokine assays were used to measure the serum levels of HIF-1 α and 10 cytokines(IL-1β,IL-4,IL-5,IL-6,IL-8,IL-10,IL-12p70,IL-22,IFN-γ,and TNF-α),respectively.Spearman's method was used to analyze the correlation between the serum levels of HIF-1α and cytokines,and the correlation between the serum levels of HIF-1α and cytokines and patients'clinical indicators,including disease duration,the number of attacks,and the EDSS score.Results Serum HIF-1α,IL-4,IL-6,IL-8,IL-10,IL-12p70,IFN-γ,and TNF-α levels in the RRMS group were significantly higher than those in the HC group(P＜0.05).Serum levels of HIF-1α,IL-4,IL-6,and IL-12p70 in the Yishen Daluo Decoction-pre group were significantly higher than those in the Yishen Daluo Decoction-post group(P＜0.05).In addition,the serum HIF-1α level was positively correlated with IL-6(r=0.452,P=0.016)and TNF-α(r=0.524,P=0.004)levels in patients with RRMS.The IFN-γ level was negatively correlated with the EDSS score(r=-0.423,P=0.025),the IL-4 level was negatively correlated with disease duration(r=-0.385,P=0.043),and the TNF-α level was positively correlated with disease duration(r=0.397,P=0.037).Conclusion The regulatory mechanism of Yishen Daluo Decoction on immune imbalance in RRMS may be related to its ability to reduce the serum levels of the glycolysis-related protein HIF-1α in RRMS patients.It is also related to the levels of various inflammatory cytokines.

The assessment of adverse drug events is an important basis for clinical safety evaluation and post-marketing risk control of drugs,and its causality assessment is gaining increasing attention.The existing methods for assessing the causal relationship between drugs and the occurrence of adverse reactions can be broadly classified into three categories:global introspective methods,standardized methods,and probabilistic methods.At present,there is no systematic introduction of the operational details of the various methods in the domestic literature.This paper compares representative causality assessment methods in terms of definition and concept,methodological steps,industry evaluation and advantages and disadvantages,clarifies the basic process of determining the causality of adverse drug reactions,and discusses how to further improve the adverse drug reaction monitoring and evaluation system,with a view to providing a reference for drug development and pharmacovigilance work in China.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

Objective:To develop a prediction tool for 6-year incident risk of frailty among Chinese older adults aged 65 years or above.Methods:Data from the Chinese Longitudinal Healthy Longevity Survey from 2002 to 2018 was used, including 13 676 older adults aged 65 years or above who were free of frailty at baseline. Key predictors of frailty were identified via the least absolute shrinkage and selection operator (LASSO) method, and were thereafter used to predict the incident frailty based on the Cox proportional hazards regression model. The model was internally validated by 2 000 Bootstrap resamples and evaluated for the performance of discrimination and calibration using the area under the receiver operating characteristic curve (AUC) and calibration curve, respectively. The net benefit of the developed prediction tool was evaluated by decision-curve analysis.Results:The M( Q1, Q3) age and follow-up time of the participants were 81.0 (71.0, 90.0) years and 6.0 (4.1, 9.2) years, respectively. A total of 4 126 older persons (30.2%) were recorded with frailty incidents during the follow-up, with the corresponding incidence density of 41.8/1 000 person-years. A total of 15 key predictors of frailty were selected by LASSO, namely, age, sex, race, education years, meat consumption, tea drinking, performing housework, raising domestic animals, playing cards or mahjong, and baseline status of visual function, activities of the daily living score, instrumental activities of the daily living score, hypertension, heart disease, and self-rated health. The prediction model was internally validated with an AUC of 0.802, with the max Youden's index of 0.467 at a risk threshold of 19.0%. The calibration curve showed high consistency between predicted probabilities and observed proportions of frailty events. The decision curve indicated that higher net benefits could be obtained via the prediction model than did strategies based on intervention in all or none participants for any risk threshold less than 59%, and the model-based net benefit was estimated to be 0.10 at a risk threshold of 19.0%. Conclusions:The herein developed 6-year incident risk prediction model of frailty, based on easily accessible questionnaires and physical examination variables, has good predictive performance. It has application potential in identifying populations at high risk of incident frailty.