Objective:To explore the effect and mechanism of Chlorfortunone A(ChlA) in the treatment of diabetic nephropathy(DN) in mice.Methods:The DN model mice were assigned to DN, low-dose ChlA(ChlAL) and high-dose ChlA(ChlAH), and the normal control groups(Ctrl). Kidney tissue was analyzed via HE and Masson staining, and urine albumin, fasting blood glucose and kidney weight were measured. Collagen1 and α-SMA proteins were detected in renal tissues. The level of GSH-px, SOD, CAT, and TGF-β were detected. The TGF-β/Smad2 pathway in kidney tissue was detected. The mechanism was verified by setting the high glucose+ ChlA+ TGF-β group in MPC-5 cells. The proliferation of the cells and DCFDA staining were detected.Results:Compared to the Ctrl group, the DN group had significantly higher UACR and kidney weight( P<0.001). High-dose ChlA reduced UACR and kidney weight( P<0.05), with no effect on blood glucose( P>0.05). Masson staining showed reduced fibrosis with ChlA treatment. Collagen I and α-SMA expressions were significantly higher in DN( P<0.001) and decreased with ChlA treatment( P<0.05). GSH-px, SOD, and CAT levels were lower in DN( P<0.001), while TGF-β was elevated( P<0.001); ChlA increased antioxidant enzymes and decreased TGF-β( P<0.05). The TGF-β/Smad2 pathway was upregulated in DN( P<0.001) and inhibited by ChlA( P<0.001). In vitro, ChlA reduced cell proliferation( P<0.05) and increased ROS levels( P<0.001). Conclusions:ChlA alleviates kidney injury and fibrosis in DN mice, reduces oxidative stress, which may be related to the inhibition of the TGF-β/Smad2 pathway.

The α-Klotho protein is an anti-aging protein encoded by the Klotho gene and mainly exists in the renal tubules in the form of type 1 membrane protein (membrane-boundform). The extracellular domain of the membrane-bound α-Klotho protein can be cleaved and secreted into the circulation, which is called soluble α-Klotho. Soluble α-Klotho is the main form that can be detected in the body fluid. This paper mainly reviews the biological functions of soluble α-Klotho in the kidney and its possible molecular biological mechanisms, and also summarizes the role of soluble α-Klotho in various kidney diseases and the effects of α-Klotho on the other organs.

Objective:To analyze the liver histological characteristics and clinically related factors in inactive hepatitis B surface antigen (HBsAg) carriers (IHC), and also explore whether antiviral treatment is necessary for IHC, as defined in the 2022 version of the hepatitis B prevention and treatment guidelines.Methods:A multicenter, retrospective cohort study was conducted. Two hundred and thirty-one IHC cases who underwent liver biopsy histopathological examination in nine medical institutions, including Beijing Youan Hospital affiliated with Capital Medical University, from January 2018 to December 2023 were included. General informative data, clinical serological markers, and transient elastography (TE) examination results were collected. Patients were divided into a positive (148 cases) and a negative group (83 cases) according to the results of hepatitis B virus (HBV) DNA detection. The differences in liver pathological inflammatory activity (G) and liver fibrosis stage (S) were analyzed between the two groups to explore the correlation between liver tissue conditions and clinically related factors. Comparsions of normally distributed continwous data, skeukd continuous data, and categorical data between groups are performed using t tests, Mann-Whitney U tests and χ2 tests, respectively. Results:The age of 231 IHC cases was 43 (38, 51) years old, with 95.2% (220/231) aged ≥30 years, and males accounted for 64.9% (150/231). HBsAg and HBV DNA levels were 131.9 (20.8, 400.9) IU/mL and 94.0 (0, 448.5) IU/mL, respectively, of which 35.9% (83/231) were HBV DNA negative (<20 IU/mL). The remarkable proportions of G≥2, S≥2, and liver injury (G≥2 and/or S≥2) in liver tissue were 16.5% (38/231), 29% (67/231), and 35.9% (83/231), respectively. The S≥2 proportion was significantly higher in the HBV DNA-negative group than the positive group (42.2% vs. 21.6%, P<0.001), and it mainly occurred in the population cohort over 30 years old (44.9% vs. 31.0%, P=0.04). The liver stiffness measurement (LSM), aspartate transaminase to platelet ratio index (APRI), and platelet (PLT) were significantly higher in the S≥2 group than the S<2 group ( P<0.05). Conclusion:Clinicians can comprehensively evaluate the degree of liver fibrosis in IHC based on clinical factors such as age, PLT, APRI, and LSM, even if the liver histological results are lacking. The China 2022 version guidelines define that nearly half of IHC has histological indications for antiviral therapy, and liver biopsy and prompt treatment can be recommended.

Objective:To explore the effect and mechanism of Chlorfortunone A(ChlA) in the treatment of diabetic nephropathy(DN) in mice.Methods:The DN model mice were assigned to DN, low-dose ChlA(ChlAL) and high-dose ChlA(ChlAH), and the normal control groups(Ctrl). Kidney tissue was analyzed via HE and Masson staining, and urine albumin, fasting blood glucose and kidney weight were measured. Collagen1 and α-SMA proteins were detected in renal tissues. The level of GSH-px, SOD, CAT, and TGF-β were detected. The TGF-β/Smad2 pathway in kidney tissue was detected. The mechanism was verified by setting the high glucose+ ChlA+ TGF-β group in MPC-5 cells. The proliferation of the cells and DCFDA staining were detected.Results:Compared to the Ctrl group, the DN group had significantly higher UACR and kidney weight( P<0.001). High-dose ChlA reduced UACR and kidney weight( P<0.05), with no effect on blood glucose( P>0.05). Masson staining showed reduced fibrosis with ChlA treatment. Collagen I and α-SMA expressions were significantly higher in DN( P<0.001) and decreased with ChlA treatment( P<0.05). GSH-px, SOD, and CAT levels were lower in DN( P<0.001), while TGF-β was elevated( P<0.001); ChlA increased antioxidant enzymes and decreased TGF-β( P<0.05). The TGF-β/Smad2 pathway was upregulated in DN( P<0.001) and inhibited by ChlA( P<0.001). In vitro, ChlA reduced cell proliferation( P<0.05) and increased ROS levels( P<0.001). Conclusions:ChlA alleviates kidney injury and fibrosis in DN mice, reduces oxidative stress, which may be related to the inhibition of the TGF-β/Smad2 pathway.

The α-Klotho protein is an anti-aging protein encoded by the Klotho gene and mainly exists in the renal tubules in the form of type 1 membrane protein (membrane-boundform). The extracellular domain of the membrane-bound α-Klotho protein can be cleaved and secreted into the circulation, which is called soluble α-Klotho. Soluble α-Klotho is the main form that can be detected in the body fluid. This paper mainly reviews the biological functions of soluble α-Klotho in the kidney and its possible molecular biological mechanisms, and also summarizes the role of soluble α-Klotho in various kidney diseases and the effects of α-Klotho on the other organs.

Objective:To analyze the liver histological characteristics and clinically related factors in inactive hepatitis B surface antigen (HBsAg) carriers (IHC), and also explore whether antiviral treatment is necessary for IHC, as defined in the 2022 version of the hepatitis B prevention and treatment guidelines.Methods:A multicenter, retrospective cohort study was conducted. Two hundred and thirty-one IHC cases who underwent liver biopsy histopathological examination in nine medical institutions, including Beijing Youan Hospital affiliated with Capital Medical University, from January 2018 to December 2023 were included. General informative data, clinical serological markers, and transient elastography (TE) examination results were collected. Patients were divided into a positive (148 cases) and a negative group (83 cases) according to the results of hepatitis B virus (HBV) DNA detection. The differences in liver pathological inflammatory activity (G) and liver fibrosis stage (S) were analyzed between the two groups to explore the correlation between liver tissue conditions and clinically related factors. Comparsions of normally distributed continwous data, skeukd continuous data, and categorical data between groups are performed using t tests, Mann-Whitney U tests and χ2 tests, respectively. Results:The age of 231 IHC cases was 43 (38, 51) years old, with 95.2% (220/231) aged ≥30 years, and males accounted for 64.9% (150/231). HBsAg and HBV DNA levels were 131.9 (20.8, 400.9) IU/mL and 94.0 (0, 448.5) IU/mL, respectively, of which 35.9% (83/231) were HBV DNA negative (<20 IU/mL). The remarkable proportions of G≥2, S≥2, and liver injury (G≥2 and/or S≥2) in liver tissue were 16.5% (38/231), 29% (67/231), and 35.9% (83/231), respectively. The S≥2 proportion was significantly higher in the HBV DNA-negative group than the positive group (42.2% vs. 21.6%, P<0.001), and it mainly occurred in the population cohort over 30 years old (44.9% vs. 31.0%, P=0.04). The liver stiffness measurement (LSM), aspartate transaminase to platelet ratio index (APRI), and platelet (PLT) were significantly higher in the S≥2 group than the S<2 group ( P<0.05). Conclusion:Clinicians can comprehensively evaluate the degree of liver fibrosis in IHC based on clinical factors such as age, PLT, APRI, and LSM, even if the liver histological results are lacking. The China 2022 version guidelines define that nearly half of IHC has histological indications for antiviral therapy, and liver biopsy and prompt treatment can be recommended.

Renal biopsy has been an essential part of the diagnosis and management of kidney disease. In recent years, the rapid development of artificial intelligence (AI) technology based on convolutional neural networks has significantly facilitated its utilization in nephrology. This article focuses on the research of AI in the recognition of tissue structure and pathological diagnosis of kidney biopsy. It elaborates on the identification and segmentation of kidney tissue structure and pathological features, as well as its auxiliary role in disease diagnosis across three dimensions: light microscopy, immunofluorescence, and electron microscopy. The aim is to provide a reference for the application of AI in renal pathology research and precision medicine.

Hyperkalemia is one of the common ion metabolism disorders in clinical practice. Hyperkalemia is defined as serum potassium higher than 5.0 mmol/L according to the guidelines at home and abroad. Acute severe hyperkalemia can cause serious consequences, such as flaccid paralysis, fatal arrhythmia, and even cardiac arrest. The use of renin-angiotensin- aldosterone system inhibitors, β-blockers and diuretics, low-sodium and high-potassium diets, and the presence of related comorbidities increase the occurrence of hyperkalemia. Hyperkalemia risk exist in all clinical departments, but there is a lack of a standardization in the management of multi- department cooperation in hospital. Therefore, a number of domestic nephrology and cardiology department experts have discussed a management model for multi-department cooperation in hyperkalemia, formulating the management standard on hospital evaluation, early warning, diagnosis and treatment, and process. This can promote each department to more effectively participate in nosocomial hyperkalemia diagnosis and treatment, as well as the long-term management of chronic hyperkalemia, improving the quality of hyperkalemia management in hospital.

Acute kidney injury (AKI) is one of the most common diseases worldwide, and its incidence and mortality rate are increasing year by year. The key to improve the prognosis of AKI is early diagnosis and early intervention. As an endogenous nephrotoxic substance, the increase or decrease of serum calcium has a certain suggestive effect on the diagnosis and treatment of AKI. We reviewed the research progress of the relationship between serum calcium and AKI, to improve clinicians' understanding of the role of serum calcium in the diagnosis and treatment of AKI.

Objective:To screen the incidence of proteinuria in rural areas of Shanxi province and construct a risk prediction model of proteinuria based on machine learning algorithm.Methods:It was a cross-sectional investigation study. The residents ≥30 years old in rural areas of Shanxi province from April to November 2019 were screened by multi-stage stratified sampling method, and data from questionnaire surveys, physical examinations, and laboratory examinations were collected. Urine albumin/creatinine ratio ≥30 mg/g was defined as proteinuria, and the incidence of proteinuria was calculated. Subjects were divided into proteinuria group and non-proteinuria group. The machine learning binary classification model of proteinuria and non-proteinuria was constructed based on the stackable integrated logistic regression algorithm (SE-LR), logistic regression, support vector machine, decision tree, random forest and extreme gradient lift algorithms, respectively. The area under the receiver operating characteristic curve, accuracy, recall, and F1 weights were used to evaluate the predictive efficiency of the comparison models. Finally, the importance of the predictive features of the model with the best overall performance was ranked.Results:There were 8 869 rural residents included in the study, aged (58.59±9.49) years old, with 3 872 males (43.66%) and 4 997 females (56.34%). The prevalence of proteinuria in rural areas of Shanxi province was 13.49% (1 196/8 869). Blood pressure, pulse, body mass index, waist circumference, proportion of obesity or overweight, proportion of hypertension, proportion of moderate to severe salt intake, glycosylated hemoglobin, uric pH value, urinary specific gravity, proportion of positive urinary occult blood, proportion of positive urinary glucose, proportion of positive urinary ketone body, proportion of urinary red blood cell count ≥5/μl, proportion of urinary white blood cell count ≥10/μl and urinary α1 microglobulin in the proteinuria group were all higher than those in the non-proteinuria group (all P<0.05). The proportions of lack of exercise and drinking history in the proteinuria group were lower than those in non-proteinuria group (both P<0.05). The overall performance of SE-LR model was the best, with the area under the curve (0.736, 95% CI 0.719-0.746) slightly lower than that of the logistic regression model (0.745, 95% CI 0.680-0.762), and the highest accuracy (0.844), recall rate (0.621) and F1 weighting value (0.801). In the SE-LR model, the orders of importance of the top 10 features were urinary α1- microglobulin, urinary occult blood, urinary sugar, uric acid basicity, smoking history,overweight or obesity, body mass index, total cholesterol, glycosylated hemoglobin and hypertension. Conclusions:The prevalence of proteinuria is high in rural areas of Shanxi province. The risk prediction model of proteinuria established by machine learning algorithm can predict the risk of proteinuria and identify its risk factors, which can provide a scientific basis for disease prevention, intervention, and treatment in the community and clinic to a certain extent.