As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

Objective To analyze the deployment of policy instruments and the distribution of stakeholder engagement in provincial policies on nursing assistant training and management.Methods The relevant policy texts on nursing assistant training and management were systematically searched and collected from the official websites of provincial governments and their direct departments,CNKI,and the PKU Law Database.A two-dimensional framework of policy instruments-stakeholder was constructed,and the content analysis was used to classify,encode and quantify policy clauses.Results The study encompassed 20 provincial-level nursing assistant training and management policies,yielding a total of 359 codes.Within the policy instruments dimension,environmental,supply,and demand instruments constituted 66.30％,28.97％,and 4.74％,respectively.In terms of stakeholders,the management-side accounted for 56.55％,providers and trainers for 18.11％each,partners for 5.01％,and demand-side for 2.23％.Both management-side and trainers engaged with 3 policy instruments,providers with 2,and partners and demand-side with one each.Conclusion In the provincial nursing assistant training and management policies,there are differences in the deployment of policy instruments,and the distribution of stakeholders is uneven.Managers should pay attention to publicity guidance and platform construction,improve incentive mechanisms and training programs,and innovate cooperation models with stakeholders,as well as strengthen communication and exchange.

Objective:This study aimed to construct a prediction model for diagnosis of proliferative lupus nephritis based on a machine learning algorithm. Additionally, a user-friendly platform was developed to propose a non-invasive method to assist the pathologic classification of lupus nephritis.Methods:A retrospective analysis was conducted on clinical and pathological data of lupus nephritis patients confirmed by renal biopsy at Zhengzhou University People′s Hospital from January 2017 to August 2023. The study population was randomly divided into training and testing sets in a 7∶3 ratio. Utilizing six machine learning algorithms, classification models were developed. The predictive performance of each model was assessed using metrics such as accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). The optimal model, once identified, was deployed as a web-based calculator for convenient model application. SPSS 25.0 and R 4.2.2 were used to analyze the data.Results:The study included a total of 212 patients, with 138 cases with proliferative lupus nephritis and 74 cases with non-proliferative lupus nephritis. The AUC values for the six models, namely logistic regression, decision tree, random forest, support vector machine, extreme gradient boosting, and light gradient boosting machine, were 0.79, 0.62, 0.79, 0.88, 0.81, and 0.77, respectively; the accuracy rates were 82.54%, 65.08%, 74.60%, 85.71%, 69.84%, 71.43%, respectively. Among them, the support vector machine model demonstrated the optimal performance. This model had deployed as a web-based calculator. Based on feature importance scores, the top 10 influencing factors were identified, including anti URNP antibody, immunoglobulin G, serum globulin, estimated glomerular filtration rate, anti Smith antibody, BMI index, anti dsDNA antibody, uric acid, anti-Rib.p antibody, and gender.Conclusion:A prediction model based on machine learning algorithms was successfully established, and a web calculator was developed to offer a simple and non-invasive method for diagnosing proliferative lupus nephritis. This can assist clinicians in evaluating the risk-benefit ratio of kidney biopsy in patients with lupus nephritis.

Objective To analyze the deployment of policy instruments and the distribution of stakeholder engagement in provincial policies on nursing assistant training and management.Methods The relevant policy texts on nursing assistant training and management were systematically searched and collected from the official websites of provincial governments and their direct departments,CNKI,and the PKU Law Database.A two-dimensional framework of policy instruments-stakeholder was constructed,and the content analysis was used to classify,encode and quantify policy clauses.Results The study encompassed 20 provincial-level nursing assistant training and management policies,yielding a total of 359 codes.Within the policy instruments dimension,environmental,supply,and demand instruments constituted 66.30％,28.97％,and 4.74％,respectively.In terms of stakeholders,the management-side accounted for 56.55％,providers and trainers for 18.11％each,partners for 5.01％,and demand-side for 2.23％.Both management-side and trainers engaged with 3 policy instruments,providers with 2,and partners and demand-side with one each.Conclusion In the provincial nursing assistant training and management policies,there are differences in the deployment of policy instruments,and the distribution of stakeholders is uneven.Managers should pay attention to publicity guidance and platform construction,improve incentive mechanisms and training programs,and innovate cooperation models with stakeholders,as well as strengthen communication and exchange.

Objective:This study aimed to construct a prediction model for diagnosis of proliferative lupus nephritis based on a machine learning algorithm. Additionally, a user-friendly platform was developed to propose a non-invasive method to assist the pathologic classification of lupus nephritis.Methods:A retrospective analysis was conducted on clinical and pathological data of lupus nephritis patients confirmed by renal biopsy at Zhengzhou University People′s Hospital from January 2017 to August 2023. The study population was randomly divided into training and testing sets in a 7∶3 ratio. Utilizing six machine learning algorithms, classification models were developed. The predictive performance of each model was assessed using metrics such as accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). The optimal model, once identified, was deployed as a web-based calculator for convenient model application. SPSS 25.0 and R 4.2.2 were used to analyze the data.Results:The study included a total of 212 patients, with 138 cases with proliferative lupus nephritis and 74 cases with non-proliferative lupus nephritis. The AUC values for the six models, namely logistic regression, decision tree, random forest, support vector machine, extreme gradient boosting, and light gradient boosting machine, were 0.79, 0.62, 0.79, 0.88, 0.81, and 0.77, respectively; the accuracy rates were 82.54%, 65.08%, 74.60%, 85.71%, 69.84%, 71.43%, respectively. Among them, the support vector machine model demonstrated the optimal performance. This model had deployed as a web-based calculator. Based on feature importance scores, the top 10 influencing factors were identified, including anti URNP antibody, immunoglobulin G, serum globulin, estimated glomerular filtration rate, anti Smith antibody, BMI index, anti dsDNA antibody, uric acid, anti-Rib.p antibody, and gender.Conclusion:A prediction model based on machine learning algorithms was successfully established, and a web calculator was developed to offer a simple and non-invasive method for diagnosing proliferative lupus nephritis. This can assist clinicians in evaluating the risk-benefit ratio of kidney biopsy in patients with lupus nephritis.

Objective:To explore the effect of complement component C1s on the proliferation,migration and adhesion of esophageal squamous cell carcinoma(ESCC)cells and on the growth of xenograft tumors in nude mice.Methods:The C1S mRNA ex-pression of ESCC tissues and adjacent normal tissues(ANTs)were analyzed using NCBI-GEO database.The C1s expression of ESCC cell lines was analyzed with RT-qPCR and Western blot.The knockdown or overexpression of C1s in ESCC cells lines was performed using C1s small interfering RNA(siRNA),C1s short hairpin RNA(shRNA)or C1s overexpression lentivirus,and the cell prolifera-tion was detected by CCK-8 assay,cell migration was detected by cell wound healing assay,cell adhesion was detected by cell-matrix adhesion assay,the expressions of matrix metalloproteinases MMP1 and MMP13 were detected by Western blot,and the effect of C1s on the growth of xenograft tumors in nude mice was detected by subcutaneous tumorigenesis assay in nude mice.The expression of CD34 in the xenograft tumors was detected by immunohistochemistry,and the formation of tumor microvessel was analyzed.Results:The expression of C1S mRNA in ESCC tissues was significantly higher than that in ANTs.Knockdown of C1s significantly suppressed proliferation,migration and cell-matrix adhesion of ESCC cells,as well as growth of xenograft tumors in nude mice,while overexpres-sion of C1s had the opposite effects.The expressions of MMP1 and MMP13 were decreased in ESCC cells TE-1 with C1s knockdown.Compared with control group,the microvessel of the xenograft tumors in the C1s overexpression group were more abundant.Conclu-sion:C1s is significantly upregulated in ESCC tissues,and promotes proliferation,migration,cell-matrix adhesion of ESCC cells,and the growth of xenograft tumors.C1s may play an important role in the occurrence and development of ESCC.

Objective:To investigate the diagnostic value of nucleic acid matrix-assisted laser desorption ionization-time of flight mass spectrometry（MALDI-TOF MS）in sputum smear-negative patients with nontuberculous Mycobacterial（NTM）pulmonary disease.Methods:Clinical data of 123 patients suspected of NTM pulmonary disease admitted in Public Health Clinical Center Affiliated to Shandong University between July 2022 and November 2023 were retrospectively analyzed. Bronchoalveolar lavage fluid（BALF）specimens were collected for MALDI-TOF MS assay and MGIT 960 culture. The diagnostic efficacy of MALDI-TOF MS for NTM pulmonary disease in patients with negative sputum smears for acid-fast bacilli was evaluated with receiver operating characteristic（ROC）curve. Statistical analysis was performed using SPSS 26.0 software and MedCalc statistical software.Results:Diagnosis of NTM pulmonary disease was finally confirmed in 66 out of the 123 suspected patients. It took 8 to 24 h for MALDI-TOF MS to identify NTM species and resistance. By MALDI-TOF MS，72 NTM strains were identified，with the Mycobacterium avium complex being the most prevalent（34 strains，47.22%），followed by the Mycobacterium abscessus complex（13 strains，18.06%）；resistance to macrolides was detected in 6 cases，while no resistance to aminoglycosides was found. It took 9 to 45 days for BALF MGIT 960 culture to identify NTM，and took 7 to 15 days for NTM typing and drug sensitivity testing. By BALF MGIT 960 culture，28 NTM strains were identified；and 1 case was found to be resistant to macrolides. Using confirmed diagnosis as the gold standard，MALDI-TOF MS demonstrated higher sensitivity，negative predictive value，and agreement rate compared to MGIT 960 culture（84.85% vs. 42.42%，81.13% vs. 56.32%，80.49% vs. 62.60%， χ2=25.667，8.998，9.664， P<0.05 or <0.01）. The area under ROC curve（AUC）for MALDI-TOF MS was significantly higher than that of MGIT 960 culture（0.801 vs. 0.642， Z=3.300， P=0.001）. Conclusion:Compared to MGIT 960 culture，MALDI-TOF MS exhibits superior diagnostic efficiency in detecting NTM pulmonary disease in patients with acid-fast bacilli smear-negative sputum，with advantage of rapidly identifying NTM species and resistance.

Objective:To investigate the predictive value of serum uric acid/albumin ratio (sUAR) for acute kidney injury (AKI) after cardiac valve surgery.Methods:The clinical data of adult patients undergoing cardiac valve surgery under cardiopulmonary bypass from January 2021 to December 2021 from the Heart Center of Henan Provincial People's Hospital were collected retrospectively, and the sUAR was calculated. All patients were divided into AKI group and non-AKI group according to whether AKI occurred within 7 days after cardiac valve surgery, and the differences of clinical data between the two groups were compared. Multivariate logistic regression model was used to analyze the independent correlation factors of AKI after cardiac valve surgery. The receiver operating characteristic (ROC) curve was used to evaluate the performance of relevant indicators.Results:A total of 422 patients were enrolled, including 194 females (46.0%), 141 hypertension patients (33.4%) and 172 atrial fibrillation patients (40.8%). They were 57 (50, 65) years old. Their sUAR was 8.13 (6.57, 9.54) μmol/g, and hemoglobin was 135 (125, 145) g/L. There were 142 cases in AKI group and 280 cases in non-AKI group, and the incidence of AKI after cardiac valve surgery was 33.6%. Age, atrial fibrillation rate, baseline serum creatinine, N terminal pro B type natriuretic peptide, serum urea,serum uric acid, blood glucose and sUAR were higher in the AKI group than those in the non-AKI group (all P<0.05), and estimated glomerular filtration rate, lymphocyte count,hemoglobin and serum albumin were lower in the AKI group than those in the non-AKI group (all P<0.05). The median cardiopulmonary bypass time of patients in the AKI group was slightly longer than that in the non-AKI group, but the difference was not statistically significant [159 (125, 192) min vs. 151 (122, 193) min, Z=-0.797, P=0.426], and there were no statistically significant differences in other indicators between the two groups. The results of multivariate logistic regression analysis showed that sUAR ( OR=1.467, 95% CI 1.308-1.645, P<0.001), age ( OR=1.045, 95% CI 1.020-1.072, P<0.001), atrial fibrillation ( OR=2.520, 95% CI 1.580-4.020, P<0.001), hemoglobin ( OR=0.984, 95% CI 0.971-0.997, P=0.015) were the independent correlation factors. ROC curve analysis showed that the area under the curve ( AUC) of sUAR predicting AKI after cardiac valve surgery was 0.710 (95% CI 0.659-0.760, P<0.001) with a sensitivity of 85.2% and specificity of 45.0% for the sUAR cut-off point of 7.28 μmol/g. The AUC for the diagnosis of AKI after cardiac valve surgery was 0.780 (95% CI 0.734-0.825, P<0.001) with a sensitivity of 72.5% and specificity of 71.8% for the combination of sUAR with age, hemoglobin and atrial fibrillation. Conclusions:For patients undergoing cardiac valve surgery under cardiopulmonary bypass, preoperative high sUAR is an independent risk factor for postoperative AKI, and sUAR has a certain predictive value for postoperative AKI.