Objective To analyze the disease burden of chronic kidney disease (CKD) in the Belt and Road countries and its change trend. Methods It was a cross-sectional epidemiological study based on surveillance data. Data on age-standardized prevalence rate (ASPR) and age-standardized mortality rate (ASMR) of CKD were derived from the 2019 Global Burden of Disease Study. The annual percentage change (APC) was calculated to evaluate the ASPR trend of CKD from 1990 to 2019. Results In 2019, the number of CKD cases and deaths in the Belt and Road countries was 426 million and 798 000, respectively, accounting for 61.1% and 55.9% of CKD cases and deaths worldwide. The ASPR and ASMR of CKD in China were 8.1% and 11.2 per 100 000 population, slightly lower than the global average. Countries in North America and Oceania had a higher burden of CKD, and European countries had a lower burden. In the etiology, hypertension and diabetes-related CKD morbidity and mortality accounted for 23.7% and 68.8% of total CKD morbidity and mortality, respectively. From 1990 to 2019, the ASPR of CKD increased in 150 countries (98.0%) and the fastest increase was observed in Morocco (APC=1.52%). The hotspots with high ASPR of CKD were located in Belt and Road countries from Asia, South/North America and Oceania, and the hotspots with high ASMR were distributed in countries from Africa, South/North America and Oceania. The sociodemographic index and life expectancy were positively correlated with the ASPR of CKD (r=0.409, P<0.001; r=0.361, P<0.001) , and negatively correlated with the ASMR of CKD (r=-0.317, P<0.001; r=-0.391, P<0.001). Conclusions Belt and Road countries have substantial disease burdens of CKD, and the prevalence rate of CKD is rising fast. Health cooperation among member states should be strengthened to jointly address the challenges posed by chronic diseases such as CKD.

Objective To identify the risk factors, and develop and validate a risk prediction model for abnormal bone mass in end?stage renal disease (ESRD) patients. Methods It was a retrospective cross-sectional study. The clinical and laboratory data of ESRD patients who were hospitalized in the Department of Nephrology, Zhongda Hospital Affiliated to Southeast University from January 2022 to May 2023 were collected retrospectively. The patients were randomly divided into training and validation cohorts at a ratio of 7∶3. They were further divided into normal and abnormal bone mass groups according to the T value measured by dual-energy X-ray absorptiometry (DXA). Then, backward stepwise regression and least absolute shrinkage and selection operator (LASSO) were respectively used to develop the risk prediction model for abnormal bone mass in ESRD patients. Akaike information criterion (AIC), bayesian information criterion (BIC), and accuracy were used to evaluate the performance of these two models, after which the preferable model was selected. Moreover, the receiver operating characteristic (ROC) curve, calibration curve, Hosmer-Lemeshow test, and decision curve analyses (DCA) were applied to evaluate the diagnostic performance of the preferable model. Finally, a dynamic nomogram for individual assessment was constructed based on the preferable model. Results A total of 254 ESRD patients were enrolled, including 160 (63.0%) males, 161 (63.4%) hemodialysis patients, and 202 (79.5%) patients with abnormal bone mass. There was no significant difference in the prevalence of abnormal bone mass between training group (n=178) and validation group (n=76) (79.2% vs. 80.3%, χ²=0.036,P=0.849). The final variables and variable parameters included in the LASSO and stepwise regression models were the same, which were five variables: age, body mass index, hypertension, diabetes, and osteocalcin. Both models also had the same AIC, BIC, and accuracy in the training group, which were 113.45, 132.54, and 0.837, respectively. Therefore, the LASSO model and the stepwise regression model performed consistently in this study and could be considered as the same model, hereafter referred to as the Model. The Model's area under the ROC curve in the training and validation groups was 0.923 (95%CI 0.884-0.963) and 0.809 (95%CI 0.675-0.943), respectively. The optimal cutoff for the training group was 0.858, with a sensitivity of 0.801, a specificity of 0.973 and an accuracy of 0.837; when this cutoff value was taken, the validation group's sensitivity was 0.689, specificity was 0.800, and accuracy was 0.711. The Model demonstrated excellent performance in the calibration curve, Hosmer-Lemeshow test (P>0.05), and DCA. Finally, based on the five predictors of the Model, a dynamic nomogram was created for clinicians to enter baseline clinical parameters for early identification of high-risk patients with abnormal bone mass. Conclusions A dynamic nomogram for abnormal bone mass in ESRD patients is constructed with good predictive performance based on the prediction model, which can be used as a practical approach for the personalized early screening and auxiliary diagnosis of the potential risk factors and assist physicians in making a personalized diagnosis for patients.

Objective To evaluate the clinical application value of iohexol plasma clearance assay in assessing glomerular filtration rate (GFR) in patients with chronic kidney disease (CKD), and identify alternative methods of ^99mTc-diethylene triamine pentaacetic acid renal kinetic imaging (Gates) method for measuring GFR (^99mTc?mGFR). Methods It was a cross-sectional study. The CKD patients hospitalized in the Department of Nephrology at the Second Affiliated Hospital of Nanjing Medical University between October 2022 and September 2023 were enrolled. Iohexol plasma clearance was determined by collecting blood samples at 2 and 4 hours after intravenous administration of 5 ml iohexol, and high performance liquid chromatography was used to measure the plasma concentration of iohexol. Br?chner-Mortensen and Jacobsson formulas were used to calculate the double and single plasma iohexol clearance, respectively. CKD-epidemiology collaboration equation based on serum creatinine concentration was used to calculate the estimated GFR (eGFR). Pearson's coefficient was performed to analyze the correlation of iohexol dual plasma clearance assay-measured GFR (iohexol?DS?mGFR), iohexol single plasma 4 hours clearance assay-measured GFR (iohexol?SS_4h?mGFR), iohexol single plasma 2 hours clearance assay-measured GFR (iohexol?SS_2h?mGFR) and eGFR with ^99mTc?mGFR as the gold standard. Bland?Altman analysis, 95% limits of agreement, and intra-correlation coefficient were used to compare the diagnostic concordance of Iohexol?DS?mGFR, Iohexol?SS_4h?mGFR, Iohexol?SS_2h?mGFR and eGFR with ^99mTc?mGFR. Results The study enrolled 64 CKD patients, aged (58.91±13.08) years old, comprising of 38 males and 26 females. The distribution of patients across CKD stages based on ⁹⁹Tc?mGFR was as follows: 12 patients (18.8%) in stage 1, 14 patients (21.9%) in stage 2, 26 patients (40.6%) in stage 3, 10 patients (15.6%) in stage 4, and 2 patients (3.1%) in stage 5. The Pearson correlation analysis revealed that the correlation coefficients of iohexol?DS?mGFR, iohexol-SS_4h?mGFR, iohexol?SS_2h?mGFR and eGFR with ^99mTc?mGFR were 0.925, 0.867, 0.820 and 0.894 (all P<0.001), respectively. The median deviation of absolute value of iohexol?DS?mGFR, iohexol-SS_4h?mGFR, iohexol?SS_2h?mGFR and eGFR in the total study population were 6.66, 9.63, 11.47 and 9.59 ml·min^-1·(1.73 m²)^-1, respectively. The proportions of iohexol?DS?mGFR, iohexol-SS_4h?mGFR, iohexol?SS_2h?mGFR and eGFR located in the gold-standard GFR ± 10% interval (P10) were 35.9%, 29.7%, 26.6% and 29.7%, respectively, and the proportions located in the gold-standard GFR ± 30% interval ( P30 ) were 87.5%, 68.8%, 60.9% and 73.4%, respectively. Conclusions Iohexol dual plasma clearance is well correlated and consistent with ^99mTc?mGFR. It is a safe and easy alternative to isotope ^99mTc?mGFR for clinical use in determining GFR.

Objective To analyze the clinical characteristics of pediatric atypical hemolytic uremic syndrome (aHUS), and provide clinical experience for the diagnosis and treatment of aHUS in China. Methods It was a single-center retrospective study. Fifteen aHUS children treated and having complete clinical data at Children's Hospital of Nanjing Medical University between December 31, 2017 and October 15, 2023 were enrolled to analyze the clinical features covering laboratory examinations, genetic testing results, and clinical manifestations. The children were classified based on genetic testing and complement factor H (CFH) antibody detection results to analyze the corresponding clinical characteristics. Results Among the 15 aHUS patients. There were 8 males and 7 females. The onset age was 5.1 (0.7, 10.8) years old. All patients underwent genetic testing, with 9/15 of aHUS-related gene mutation, revealing 2 de novo mutations in complement factors-related genes. Among 11 patients screened for CFH antibody, 6 tested positive. C3 was detected in 14 patients, and C3 decreased in 9 patients. In laboratory examinations, there were notable decreases in red blood cell (RBC) count in 13 patients, platelet (PLT) count in 15 patients, hemoglobin (Hb) in 15 patients and estimated glomerular filtration rate (eGFR) in 14 patients. Blood urea nitrogen (BUN) and serum creatinine (Scr) were markedly elevated in 13 patients and 9 patients, respectively. Twelve patients exhibited elevated transaminase levels, and 14 patients exhibited elevated lactate dehydrogenase (LDH) levels. Clinically, 11 patients had triggers, and 4 patients had clear family histories. Common clinical features including anemia, thrombocytopenia, proteinuria and hematuria were in 15 patients. There were statistically significant differences in RBC count (Z=-2.84, P=0.005), PLT count (Z=-6.65, P<0.001), Hb (t=-3.71, P=0.002), LDH (Z=3.76, P=0.002), BUN (Z=2.71, P=0.017), and eGFR (Z=-3.65, P=0.003) before and after treatment except alanine transaminase, aspartate transaminase, Scr and complement C3 (all P>0.05). There were no significant differences in onset age, RBC count, PLT count, Hb, LDH, alanine transaminase, aspartate transaminase, Scr, BUN, eGFR, and C3 between aHUS-related gene mutation and non-mutation groups, and CFH antibody-positive and negative groups (all P>0.05). Conclusions aHUS is marked by severity, and has diverse clinical manifestations. There are no significant differences in clinical presentation at admission between hereditary and acquired aHUS, highlighting the critical importance of genetic testing and complement-related factor detection in diagnosing aHUS etiology. The family history plays a supportive role in diagnosis of aHUS.

Objective To investigate the effect and mechanism of forkhead box K1 (FOXK1) in acute kidney injury (AKI), and to provide new ideas and targets for preventing and treating AKI. Methods Three models of AKI were established: 30 male specific pathogen free wild type C57BL/6 mice aged 8-10 weeks and weighting 22-24 g were randomly divided into saline group (0.9% normal saline 0.1 ml/10 g, intraperitoneal injection), lipopolysaccharide (LPS) group (LPS solution 10 mg/kg, intraperitoneal injection), cisplatin group (cisplatin solution 20 mg/kg, intraperitoneal injection), ischemia-reperfusion (IR) group, and sham-operated group by the random number table, with 6 mice in each group. The mice in each group were sacrificed 24 hours after modeling to obtain experimental materials. The serum creatinine (Scr) and blood urea nitrogen (BUN) were tested to measure the renal function. HE staining was performed to observe histopathological changes of renal tissues. Western blotting was used to detect the protein expression ofFOXK1, kidney injury molecule 1 (KIM-1), autophagy markers p62, Beclin1 and LC3 in renal tissues. Quantitative real-time PCR was used to detect the mRNA expression of Foxk1. Human renal tubular epithelial cells (HK?2 cells) were exposed to hypoxia for 24 h, followed by reoxygenation for 6 h to establish an in vitro AKI model induced by hypoxia reoxygenation (HR). The expression changes of the above indicators in HK?2 cells were detected. Then, Foxk1 gene deletion in renal tubular epithelial cells was performed in vivo and in vitro, and AKI models were induced to observe the expression changes of the above indicators. Results Compared with the saline group, Scr, BUN and the protein expression level of KIM-1 were higher in LPS group and cisplatin group (all P<0.05), while FOXK1 protein and mRNA expression had no significant change (both P>0.05). Compared with the sham-operated group, Scr, BUN and the protein expression level of KIM-1 were higher, and the expression levels of FOXK1 protein and mRNA were significantly lower in the IR group (all P<0.05). FOXK1 protein and mRNA expression levels in the HR-induced AKI cell model group were lower than those in the control group (both P<0.05). In the in vivo experiments, compared with the sham-operation group, the renal tubular injury was more aggravated, Scr and BUN were higher, p62 protein expression was lower, and the protein expression levels of KIM-1, Beclin1 and LC3 were higher in the IR group (all P<0.05). Compared with Foxk1^flox/flox IR goup, renal tubular injury was more alleviated, Scr, BUN and the protein expression levels of KIM-1 and p62 were lower, while the protein expression levels of Beclin1 and LC3 were higher in Foxk1^cKO IR group (all P<0.05). Compared with shCtrl HR group, shFoxk1 HR group had lower protein expression levels of KIM?1 and p62 and higher expression levels of Beclin1 and LC3 in vitro (all P<0.05). Conclusions The expression of FOXK1 is decreased in ischemic AKI model. Foxk1 deficiency alleviates renal tubular epithelial cell injury and protects against ischemic AKI through activating autophagy.