To investigate the current management status of chronic kidney disease (CKD) in the Tibet region and explore the disparities in diagnosis, treatment, and education among hospitals of different levels and healthcare professionals, so as to provide a basis for formulating prevention and control strategies and standardized management for CKD in high-altitude and alpine regions.

A cross-sectional questionnaire-based survey was conducted among healthcare professionals from the Tibet region who participated in CKD standardized training for primary care physicians in September 2025. The survey covered CKD screening, current status of diagnosis, treatment and management, nursing care, and patient education, as well as the training needs of professionals. Disparities in diagnosis, treatment, and management of CKD between hospitals of different levels and between nephrology and non-nephrology staff were compared.

A total of 54 valid questionnaires were collected. The average altitude of the hospitals where the respondents worked was 3, 650 meters. Of the respondents, 79.6% were from tertiary hospitals, and 68.5% were engaged in nephrology practice. The availability of routine CKD-related tests (complete blood count, blood glucose, blood lipids, serum creatinine, and urinalysis) in hospitals of the Tibet region exceeded 90%, while the availability of the urine microalbumin-to-creatinine ratio (UACR) test was 74.1%. Tertiary hospitals demonstrated superior capability in detecting UACR (χ²=10.864, P<0.01), ferritin (χ²=6.642, P=0.01), and erythropoietin (χ²=5.130, P=0.024) compared to primary care institutions (including secondary and primary hospitals). Calcium channel blockers were the most frequently used antihypertensive agents for renal hypertension (37.4%), followed by renin-angiotensin-aldosterone system inhibitors (29.6%). Regarding anemia management, 31.5% of respondents reported difficulties in diagnosing "true" anemia in high-altitude regions. Nephrologists demonstrated more experience in using intravenous iron (χ²=4.598, P=0.032), erythropoiesis-stimulating agents (χ²=11.977, P<0.01), and hypoxia-inducible factor prolyl hydroxylase inhibitors (χ²=12.362, P<0.01) compared to non-nephrology staff. Deficiencies were observed in patient education. Only 38.9% of healthcare workers were able to provide systematic education, while 51.5% offered verbal guidance. Nursing practice was mainly constrained by a lack of skills training (37.0%) and insufficient manpower (35.2%). In terms of multidisciplinary collaboration, 66.1% of the hospitals had access to online or offline consultation channels. The training needs of healthcare professionals focused primarily on guideline interpretation (75.9%), nutritional management (72.2%), and the standardized management of CKD complications (68.5%).

In the Tibet region, primary care institutions demonstrated relatively limited detection capabilities in CKD management compared to tertiary hospitals. Furthermore, continuing education and nursing resource allocation in local healthcare facilities require further strengthening or optimization.

To investigate the mechanism of jagged canonical Notch ligand 2 (Jag2) mediating early inflammation in acute kidney injury via crosstalk between renal vascular endothelial cells and mononuclear macrophages.

Male C57BL/6J mice were used to establish a bilateral renal ischemia-reperfusion injury (IRI) model. The mice were randomly divided into three groups with 6 mice in each group: the sham operation group, the model group (administered with 10 mg/kg isotype control IgG via tail vein injection at 24 h before IRI modeling and immediately after modeling), and the Jag2 blockade group (administered with an equal dose of Jag2 neutralizing antibody via tail vein injection at 24 h before IRI modeling and immediately after modeling). Renal injury and protein expression were assessed using histopathological staining, measurement of serum creatinine and urea nitrogen, and western blotting. Human umbilical vein endothelial cells (HUVEC) were used to establish a hypoxia/reoxygenation (H/R) model. After the H/R treatment, HUVEC in control group and Jag2 gene-knockdown group were co-cultured with human monocytic leukemia cell line tohoku hospital pediatrics-1 (THP-1), respectively. Then flow cytometry was applied to compare the proportion of CD86⁺ cells among the groups. After stimulating the mouse monocyte-macrophage leukemia cell line Raw264.7 with exogenous recombinant Jag2 protein, transcriptome sequencing was used to screen for changes in related signaling pathways, and the results were verified by Western blotting and qPCR.

After the renal IRI modeling, renal tubular injury at the corticomedullary junction of the mice kidneys was significant, with elevated levels of serum creatinine and blood urea nitrogen. The expressions of kidney injury molecule-1 and interleukin-1β were markedly upregulated (all P<0.05). Immunofluorescence results showed that Jag2 colocalized with the endothelial cell marker endomucin, and the fluorescence positive area of Jag2 in renal tissues of the model group was obviously larger than that in the sham operation group. Intervention experiments showed that Jag2 neutralizing antibody significantly alleviated the renal tubular necrosis, attenuated the deterioration of renal function, and downregulated the expression of kidney injury molecule-1 and interleukin-1β in the IRI mice (all P< 0.05). Co-culture experiments after the H/R treatment showed that the proportion of CD86⁺ cells was significantly lower in the HUVEC of Jag2 knockout group co-cultured with THP-1 cells than that in the HUVEC of the control group co-cultured with THP-1 cells (P<0.05). Transcriptome sequencing revealed that Jag2 activated multiple inflammation-related signaling pathways including the phosphatidylinositol 3-kinase (PI3K)-protein kinase B (AKT) signaling pathway. Experiments on Raw264.7 cells also demonstrated that Jag2 could upregulate the protein level of phosphorylated AKT, as well as the mRNA levels of interleukin-1β and interleukin-6 in the mouse mononuclear macrophages (all P<0.05).

Jag2 can induce the transformation of mononuclear macrophages into a pro-inflammatory phenotype through the crosstalk between renal vascular endothelial cells and mononuclear macrophages, activate inflammation-related signaling pathways such as PI3K-AKT, and promote the production of inflammatory cytokines, thereby driving the progression of inflammation in the early stage of acute kidney injury.

To investigate whether the high-glucose environment in the distal renal tubule induced by empagliflozin triggers senescence of distal tubular cells as well its potential signaling pathways.

Nine-week-old male C57BL/6 mice were selected and randomly divided into an empagliflozin group [intragastric administration of empagliflozin at 10 mg/(kg·d) and a control group (intragastric administration of an equal volume of normal saline), with six mice in each group. After 4 weeks of consecutive intervention, tissues were harvested, and blood glucose and urine glucose were measured. Immunofluorescence staining and Western blot were performed to detect the expression of senescence-related markers p16, p21, and p53 in distal renal tubules. Transcriptome sequencing was used to screen potential signaling pathways, and gene set enrichment analysis was carried out subsequently. Mouse distal renal tubular epithelial cells were divided into a control group (untreated), a mannitol group (30 mmol/L mannitol), and a high-glucose group (30 mmol/L glucose). After 24 h of incubation, cellular senescence was assessed by senescence-associated β-galactosidase staining. The mRNA expression of the senescence marker p21 and ferroptosis-related genes (Alox15, Ncoa4, Slc11a2, Gpx4) was determined by RT-qPCR. All data were analyzed using GraphPad Prism software.

Compared with the control group, urinary glucose was significantly increased in the empagliflozin group (P<0.05). Immunofluorescence and Western blot analysis showed that the expression levels of p21 and p53 were markedly upregulated in the renal distal tubules of empagliflozin-treated mice (all P<0.05). Transcriptome sequencing and gene set enrichment analysis revealed that ferroptosis-related pathways were significantly activated in the empagliflozin group (adjusted q<0.05). The expression of ferroptosis-related genes Alox15, Ncoa4, and Slc11a2 was upregulated, while Gpx4 expression was downregulated in both mouse renal tissues and cultured mouse distal renal tubular epithelial cells (all P<0.05).

Empagliflozin induced elevation of urinary glucose in mouse renal distal tubules promoted cellular senescence, which may be mediated by the activation of ferroptosis-related pathways.

To construct a diagnostic and prediction model based on machine learning for fatigue status in patients with diabetic kidney disease (DKD), so as to provide a basis for early screening and intervention.

A retrospective analysis was conducted on patients with DKD admitted to the Seventh Affiliated Hospital of Anhui University of Chinese Medicine from January 2023 to June 2025. The patients were divided into a fatigue group (score ≥ 4 points) and a non-fatigue group (score < 4 points) according to the Fatigue Severity Scale (FSS). Demographic, clinical, laboratory, and medication data of the patients were collected. Robust features were screened via LASSO regression. Repeated stratified nested cross-validation was adopted. The predictive performances of LASSO logistic regression, Random Forest (RF), and Light Gradient Boosting Machine (LightGBM) models were compared. And the clinical application value of the models was evaluated using decision curve analysis.

A total of 166 patients with DKD were enrolled, including 78 cases in the fatigue group and 88 cases in the non-fatigue group. The incidence of fatigue among the DKD patients was 46.99% (78/166). Eleven robust features were screened out via LASSO regression, namely estimated glomerular filtration rate, hemoglobin, albumin, urinary albumin/creatinine ratio, age, carbon dioxide combining power, glycated hemoglobin, diuretic use, sleep disorder, heart failure, and sodium-glucose cotransporter 2 inhibitor use. Internal validation results showed that the LightGBM model achieves the best predictive performance, with an area under the receiver operating characteristic curve of 0.836, a Brier score of 0.175, a sensitivity of 0.756, and a specificity of 0.795. The calibration curve indicated that the model had a good calibration effect. And the decision curve analysis revealed that this model yielded good clinical net benefit within the threshold range of 0.05-0.60.

The diagnostic prediction model built based on LightGBM effectively identified the fatigue status in the DKD patients, facilitating early clinical risk stratification and intervention decision-making.

To explore the correlation of serum prealbumin and albumin-globulin ratio with renal function and prognosis in patients with diabetes mellitus complicated with chronic kidney disease.

Patients with diabetes mellitus complicated with chronic kidney disease treated in our hospital from November 1, 2022 to October 31, 2024 were prospectively enrolled. All subjects were followed up for 1 year and divided into good prognosis group and poor prognosis group according to follow-up outcomes. Serum prealbumin, albumin-to-globulin ratio and renal function parameters were compared. Correlation was analyzed using Spearman software, multivariate Cox regression model was adopted to analyze prognostic influencing factors, and receiver operating characteristic curve was used to evaluate its predictive efficiency.

A total of 287 patients with diabetes mellitus complicated with chronic kidney disease were enrolled, including 208 cases in the good prognosis group and 79 cases in the poor prognosis group. The serum albumin-to-globulin ratio was negatively correlated with blood urea nitrogen, serum creatinine, and urinary albumin/creatinine ratio (P<0.05). Serum prealbumin was negatively correlated with blood urea nitrogen and serum creatinine, while positively correlated with eGFR (P<0.05). Compared with the good prognosis group, the poor prognosis group showed lower levels of serum albumin, albumin-to-globulin ratio, serum prealbumin, and eGFR, but higher levels of serum globulin, glycated hemoglobin, triglyceride, blood urea nitrogen, serum creatinine, urinary albumin, and urinary albumin/creatinine ratio (all P<0.05). Serum albumin-to-globulin ratio (HR=0.674), serum prealbumin (HR=0.982), blood urea nitrogen (HR=1.915), and eGFR (HR=0.948) were independent influencing factors for poor prognosis (P<0.05). The area under the curve for poor prognosis in single-item tests of serum albumin-to-globulin ratio, serum prealbumin, blood urea nitrogen, and eGFR was 0.799, 0.722, 0.887, and 0.632, respectively.

The serum prealbumin and albumin-to-globulin ratio in the patients with diabetes mellitus complicated with chronic kidney disease were correlated with the renal function and prognosis, possessing certain predictive value.

To explore the potential effects and mechanisms of Benincasae Exocarpium on arteriovenous fistula maturation based on network pharmacology and bioinformatics.

The AVF vascular tissue gene expression datasets GSE220796 and GSE119296 were downloaded from the Gene Expression Omnibus (GEO). The inflammation response-related gene sets were obtained from the Molecular Signatures Database (MSigDB) matched with the Gene Set Enrichment Analysis (GSEA) software, and differentially expressed inflammation-related genes (DE-IRGs) were screened. Pathway enrichment analysis was conducted via the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A protein-protein interaction (PPI) network was constructed, and hub genes of the network were screened using seven topological algorithms built into plugins of the bioinformatics visualization software Cytoscape. Chemical constituents contained in Benincasae Exocarpium were retrieved via the High-throughput Experiment- and Reference-guided database of traditional Chinese medicine (HERB) and the Symptom Mapping database (SymMap). The SwissTargetPrediction database was adopted to predict potential target genes corresponding to the active ingredients of Benincasae Exocarpium. The target genes of active ingredients from Benincasae Exocarpium and core genes associated with AVF were screened out, and cavity-detection-guided blind docking software version 2 (CB-DOCK2) was used for molecular docking verification.

A total of 44 DE-IRGs associated with AVF maturation were identified, being mainly enriched in biological processes such as cellular response to bacterial molecules, leukocyte-cell adhesion, and cellular response to biological stimuli, as well as the Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathway and the tumor necrosis factor (TNF) signaling pathway. PPI network analysis identified hub genes as IL10, SELL, ICAM1, CXCL9, CD69, CCL2, LIF, CXCL8, CCRL2, and IL6, while 14 active chemical constituents of Benincasae Exocarpium were screened out. The SwissTargetPrediction tool was used to predict 448 potential target genes, and the intersection of these target genes and DE-IRGs yielded 5 shared genes as PDE4B, ICAM1, CCL2, HIF1A and NFKBIA. The molecular docking results showed that the binding energies of uralenol and licoflavonol A with HIF1A were -7.8 kcal/mol and -6.9 kcal/mol, respectively. The binding energies of ferulic acid and licoricone with PDE4B were -7.4 kcal/mol and -10.1 kcal/mol, respectively. And the binding energy of uralenin with CCL2 was -8.4 kcal/mol.

Benincasae Exocarpium may promote the maturation of AVF through pathways such as targeted regulation of inflammation genes related to AVF maturation, inhibition of inflammatory responses, and mediation of vascular remodeling.

With its unique advantages in processing massive and complex data, machine learning has opened up new avenues to break through the existing bottlenecks in the treatment and prognostic prediction of IgA nephropathy. In terms of treatment decision-making, reinforcement learning and multi-task learning are capable of simulating the long-term efficacy of different clinical intervention plans, and accurately balance the therapeutic benefits and potential risks. In terms of efficacy evaluation, supervised learning and graph neural networks can effectively screen hormone-sensitive biomarkers and explore the key molecular pathways of IgA nephropathy. In terms of prognosis prediction, deep learning survival analysis models such as ensemble learning and DeepSurv can achieve refined risk stratification for IgA nephropathy, while temporal models including Transformer can dynamically track changes in renal function. This paper reviews the latest research progress of machine learning in the precise treatment of IgA nephropathy, as well as its application status in fields such as pathological image analysis and mobile health platforms, aiming to promote the transformation of IgA nephropathy treatment from traditional empirical therapy to a data-driven precision treatment mode.

Under the macro-context of the "Healthy China" strategy and innovation-driven development, and aiming to meet the urgent demand for high-level research talents in the new era of the 21st century, this paper is grounded in the mission of the State Key Laboratory of Kidney Diseases. It conducts an in-depth reflection and systematic reconstruction of the current training system for novice postgraduates, addressing issues such as the underlying logic of scientific research, varying levels of research literacy, fragmented rotation plans, and monotonous training models. In response, this paper uniquely proposes a new model for academic postgraduate training that is scientific and efficient. Centered on the goal of research serving clinical practice and the main task of enhancing independent research capabilities and innovative potential, the model integrates ideological construction, the stimulation of subjective initiative, improving research literacy, and optimizing rotation plans combined with diverse teaching strategies. This work provides a replicable and scalable paradigm of best practices for the precise cultivation and rapid development of academic postgraduates in nephrology in the new era, thereby contributing to the high-quality and sustainable development of nephrology research in China.