Chinese hamster ovary (CHO) cells are the most established and versatile mammalian expression system for the large-scale production of recombinant therapeutic proteins, owing to their genetic stability, adaptability to serum-free suspension culture, and ability to perform human-like post-translational modifications. More than 70% of biologics approved by the U.S. Food and Drug Administration rely on CHO-based production platforms, underscoring their central role in modern biopharmaceutical manufacturing. Despite these advantages, CHO systems continue to face three persistent bottlenecks that limit their potential for high-yield, reproducible, and cost-efficient production: excessive metabolic burden during high-density culture, heterogeneity of glycosylation patterns, and progressive loss of long-term expression stability. This review provides an integrated analysis of recent advances addressing these challenges and proposes a forward-looking framework for constructing intelligent and sustainable CHO cell factories. In terms of metabolic regulation, excessive lactate and ammonia accumulation disrupts energy balance and reduces recombinant protein synthesis efficiency. Optimization of culture parameters such as temperature, pH, dissolved oxygen, osmolarity, and glucose feeding can effectively alleviate metabolic stress, while supplementation with modulators including sodium butyrate, baicalein, and S-adenosylmethionine promotes specific productivity (qP) by modulating apoptosis and chromatin structure. Furthermore, genetic engineering strategies—such as overexpression of MPC1/2, HSP27, and SIRT6 or knockout of Bax, Apaf1, and IGF-1R—have demonstrated significant improvements in cell viability and product yield. The combination of multi-omics metabolic modeling with artificial intelligence (AI)-based prediction offers new opportunities for building self-regulating CHO systems capable of dynamic adaptation to environmental stress. Regarding glycosylation uniformity, which determines therapeutic efficacy and immunogenicity, gene editing-based glycoengineering (e.g., FUT8 knockdown or ST6Gal1 overexpression) has enabled the humanization of CHO glycan profiles, minimizing non-human sugar residues and enhancing drug stability. Process-level strategies such as galactose or manganese co-feeding and fine control of temperature or osmolarity further allow rational regulation of glycosyltransferase activity. Additionally, in vitro chemoenzymatic remodeling provides a complementary route to construct human-type glycans with defined structures, though industrial applications remain constrained by cost and scalability. The integration of model-driven process design and AI feedback control is expected to enable real-time prediction and correction of glycosylation deviations, ensuring batch-to-batch consistency in continuous biomanufacturing. Long-term expression stability, another critical challenge, is often impaired by promoter silencing, chromatin condensation, and random genomic integration. Molecular optimization—such as the use of improved promoters (CMV, EF-1α, or CHO endogenous promoters), Kozak and signal peptide refinement, and incorporation of chromatin-opening elements (UCOE, MAR, STAR)—helps maintain durable transcriptional activity, while site-specific integration systems including Cre/loxP, Flp/FRT, φC31, and CRISPR/Cas9 can enable single-copy, position-independent gene insertion at genomic safe-harbor loci, ensuring stable, predictable expression. Collectively, this review highlights a paradigm shift in CHO system optimization driven by the convergence of genome editing, synthetic biology, and artificial intelligence. The transition from empirical optimization to rational, data-driven design will facilitate the development of programmable CHO platforms capable of autonomous regulation of metabolic flux, glycosylation fidelity, and transcriptional activity. Such intelligent cell factories are expected to accelerate the transformation from laboratory-scale research to industrial-scale, high-consistency, and economically sustainable biopharmaceutical manufacturing, thereby supporting the next generation of efficient and customizable biologics manufacturing.

Chinese hamster ovary (CHO) cells are the most established and versatile mammalian expression system for the large-scale production of recombinant therapeutic proteins, owing to their genetic stability, adaptability to serum-free suspension culture, and ability to perform human-like post-translational modifications. More than 70% of biologics approved by the U.S. Food and Drug Administration rely on CHO-based production platforms, underscoring their central role in modern biopharmaceutical manufacturing. Despite these advantages, CHO systems continue to face three persistent bottlenecks that limit their potential for high-yield, reproducible, and cost-efficient production: excessive metabolic burden during high-density culture, heterogeneity of glycosylation patterns, and progressive loss of long-term expression stability. This review provides an integrated analysis of recent advances addressing these challenges and proposes a forward-looking framework for constructing intelligent and sustainable CHO cell factories. In terms of metabolic regulation, excessive lactate and ammonia accumulation disrupts energy balance and reduces recombinant protein synthesis efficiency. Optimization of culture parameters such as temperature, pH, dissolved oxygen, osmolarity, and glucose feeding can effectively alleviate metabolic stress, while supplementation with modulators including sodium butyrate, baicalein, and S-adenosylmethionine promotes specific productivity (qP) by modulating apoptosis and chromatin structure. Furthermore, genetic engineering strategies—such as overexpression of MPC1/2, HSP27, and SIRT6 or knockout of Bax, Apaf1, and IGF-1R—have demonstrated significant improvements in cell viability and product yield. The combination of multi-omics metabolic modeling with artificial intelligence (AI)-based prediction offers new opportunities for building self-regulating CHO systems capable of dynamic adaptation to environmental stress. Regarding glycosylation uniformity, which determines therapeutic efficacy and immunogenicity, gene editing-based glycoengineering (e.g., FUT8 knockdown or ST6Gal1 overexpression) has enabled the humanization of CHO glycan profiles, minimizing non-human sugar residues and enhancing drug stability. Process-level strategies such as galactose or manganese co-feeding and fine control of temperature or osmolarity further allow rational regulation of glycosyltransferase activity. Additionally, in vitro chemoenzymatic remodeling provides a complementary route to construct human-type glycans with defined structures, though industrial applications remain constrained by cost and scalability. The integration of model-driven process design and AI feedback control is expected to enable real-time prediction and correction of glycosylation deviations, ensuring batch-to-batch consistency in continuous biomanufacturing. Long-term expression stability, another critical challenge, is often impaired by promoter silencing, chromatin condensation, and random genomic integration. Molecular optimization—such as the use of improved promoters (CMV, EF-1α, or CHO endogenous promoters), Kozak and signal peptide refinement, and incorporation of chromatin-opening elements (UCOE, MAR, STAR)—helps maintain durable transcriptional activity, while site-specific integration systems including Cre/loxP, Flp/FRT, φC31, and CRISPR/Cas9 can enable single-copy, position-independent gene insertion at genomic safe-harbor loci, ensuring stable, predictable expression. Collectively, this review highlights a paradigm shift in CHO system optimization driven by the convergence of genome editing, synthetic biology, and artificial intelligence. The transition from empirical optimization to rational, data-driven design will facilitate the development of programmable CHO platforms capable of autonomous regulation of metabolic flux, glycosylation fidelity, and transcriptional activity. Such intelligent cell factories are expected to accelerate the transformation from laboratory-scale research to industrial-scale, high-consistency, and economically sustainable biopharmaceutical manufacturing, thereby supporting the next generation of efficient and customizable biologics manufacturing.

Objective To investigate the prevalence of soil-transmitted nematode human infections in Hubei Province from 2016 to 2023, so as to provide insights into formulation of soil-transmitted nematodiasis control strategies and evaluation of soil-transmitted nematodiasis control effectiveness. Methods There were 10 surveillance points established in Hubei Province for soil-transmitted nematodiasis each year from 2016 to 2023. The surveillance points were divided into eastern, western, southern, northern and central regions according to geographical locations, and one administrative village was sampled from a township in each region as a surveillance point. Then, at least 200 permanent residents at ages of over 3 years were randomly sampled at each point, with at least 1 000 individuals sampled. Soil-transmitted nematode infection was detected using a modified Kato-Katz thick smear method (two slides for one stool sample), and Enterobius vermicularis infection was additionally detected with a cellophane tape test among children at ages of 3 to 9 years. The prevalence of soil-transmitted nematode human infections was descriptively analyzed. Results A total of 80 547 individuals underwent surveillance for soil-transmitted nematodiasis in Hubei Province from 2016 to 2023, and a total of 262 individuals were detected with soil-transmitted nematode infections, including two cases with mixed infections, yielding an overall prevalence rate of 0.33% (262/80 547). The prevalence rates of hookworm, Ascaris lumbricoides, Trichuris trichiura, and E. vermicularis infections were 0.02% (20/80 547), 0.07% (55/80 547), 0.02% (15/80 547) and 0.22% (174/80 547), respectively, appearing a parasite species-specific prevalence rate (χ² = 250.235, P < 0.05), and the prevalence rates of soil-transmitted nematode infections were 0.50%(51/10271),0.37%(34/9120),0.39%(39/10099),0.40%(41/10168), 0.36% (37/10 234), 0.45% (46/10 211), 0.03% (3/10 238) and 0.11% (11/10 206) in Hubei Province from 2016 to 2023, respectively, showing a year-specific prevalence rate (χ² = 60.589, P < 0.05). Soil-transmitted nematode infections were detected across 36 surveillance points, and there was a significant difference in the prevalence of soil-transmitted nematode infections among surveillance points (0.02% to 3.30%, P < 0.001). In addition, the differences in prevalence rates of human soil-transmitted nematode infection among different age groups (χ² = 531.091, P < 0.05), occupations (P < 0.001), and education levels (P < 0.001) were all statistically significant. Among these, the children at ages of 3 to 9 years old (1.40%, 174/12 461), nursery-school children (1.69%, 90/5 312) and preschool-aged children (1.56%, 93/5 969) were relatively high. Conclusions The overall prevalence of soil-transmitted nematodiasis was low in Hubei Province from 2016 to 2023; however, the prevalence varied across regions and among populations, with E. vermicularis as the predominant species of soil-transmitted nematode. Soil-transmitted nematodiasis control should be given a high priority in key areas in Hubei Province, and preschool children, primary school students, and individuals with a low educational level are recommended as key target populations for health education and interventions.

OBJECTIVE: To investigate the Wnt signaling pathway and miRNAs mechanism of extracts of Plastrum Testudinis (PT) in the treatment of osteoporosis (OP). METHODS: Thirty female Sprague Dawley rats were randomly divided into 5 groups by random number table method, including sham group, ovariectomized group (OVX), ovariectomized groups treated with high-, medium-, and low-dose PT (160, 80, 40 mg/kg per day, respectively), with 6 rats in each group. Except for the sham group, the other rats underwent bilateral ovariectomy to simulate OP and received PT by oral gavage for 10 consecutive weeks. After treatment, bone mineral density was measured by dual-energy X-ray absorptiometry; bone microstructure was analyzed by micro-computed tomography and hematoxylin and eosin staining; and the expressions of osteogenic differentiation-related factors were detected by immunochemistry, Western blot, and quantitative polymerase chain reaction. In addition, Dickkopf-1 (Dkk-1) was used to inhibit the Wnt signaling pathway in bone marrow mesenchymal stem cells (BMSCs) and miRNA overexpression was used to evaluate the effect of miR-214 on the osteogenic differentiation of BMSCs. Subsequently, PT extract was used to rescue the effects of Dkk-1 and miR-214, and its impacts on the osteogenic differentiation-related factors of BMSCs were evaluated. RESULTS: PT-M and PT-L significantly reduced the weight gain in OVX rats (P<0.05). PT also regulated the bone mass and bone microarchitecture of the femur in OVX rats, and increased the expressions of bone formation-related factors including alkaline phosphatase, bone morphogenetic protein type 2, collagen type I alpha 1, and runt-related transcription factor 2 when compared with the OVX group (P<0.05 or P<0.01). Meanwhile, different doses of PT significantly rescued the inhibition of Wnt signaling pathway-related factors in OVX rats, and increased the mRNA or protein expressions of Wnt3a, β-catenin, glycogen synthase kinase-3β, and low-density lipoprotein receptor-related protein 5 (P<0.05 or P<0.01). PT stimulated the osteogenic differentiation of BMSCs inhibited by Dkk-1 and activated the Wnt signaling pathway. In addition, the expression of miR-214 was decreased in OVX rats (P<0.01), and it was negatively correlated with the osteogenic differentiation of BMSCs (P<0.01). MiR-214 mimic inhibited Wnt signaling pathway in BMSCs (P<0.05 or P<0.01). Conversely, PT effectively counteracted the effect of miR-214 mimic, thereby activating the Wnt signaling pathway and stimulating osteogenic differentiation in BMSCs (P<0.05 or P<0.01). CONCLUSION PT stimulates bone formation in OVX rats through β-catenin-mediated Wnt signaling pathway, which may be related to inhibiting miR-214 in BMSCs.
Animals ; MicroRNAs/genetics* ; Female ; Rats, Sprague-Dawley ; Wnt Signaling Pathway/genetics* ; Osteogenesis/genetics* ; Mesenchymal Stem Cells/cytology* ; Cell Differentiation/drug effects* ; Bone Density/drug effects* ; Ovariectomy ; Osteoporosis/drug therapy* ; beta Catenin/metabolism* ; Rats ; Intercellular Signaling Peptides and Proteins/metabolism* ; Drugs, Chinese Herbal/pharmacology*

ObjectiveTo clarify whether epigallocatechin gallate （EGCG） is involved in the clearance of amyloid β-protein （Aβ） and autophagy induction by microglia， so as to explore the potential mechanisms of EGCG in the prevention and treatment of Alzheimer's disease （AD）. MethodsSix-month-old APP/PS1 mice were randomly divided into model and EGCG groups， with some additional wild type （WT） mice as the control group， each group consisting of 15 mice. The EGCG group received continuous gavage administration［5 mg/（kg·d）］ for 8 weeks， followed by the open field test and Y-maze to assess the learning and memory abilities of the mice. Thioflavin-S staining was used to evaluate the content and distribution of amyloid β-protein （Aβ）in the brain parenchyma of the mice， and immunofluorescence was employed to detect the expression levels of Aβ_1-42， glial fibrillary acidic protein （GFAP）， and ionized calcium-binding adapter molecule 1 （Iba1） in the hippocampal tissue of the mice. Additionally， N9 mouse microglial cells were induced with 20 µmol/L Aβ_1-42， and the cell viability was measured after treatment with different concentrations of EGCG （5 µmol/L， 10 µmol/L， 20 µmol/L）. Western blotting was used to detect the levels of Aβ_1-42， low density lipoprotein receptor-related protein 1（LRP1）， receptor for advanced glycation endproducts （RAGE）， amyloid precursor protein （APP）， insulin degrading enzyme （IDE）， neprilysin （NEP）， microtubule associated protein 1 hydrogen chain 3（LC3）-Ⅱ/LC3-Ⅰ， phosphatidylinositol 3-hydroxy kinase（PI3K）， p-PI3K， protein kinase B （AKT）， p-AKT， mammalian target of rapamycin （mTOR）， p-mTOR， and histone deacetylase 6（HDAC6）. Finally， through the co-culture of microglial cells and neuronal SH-SY5Y cells， cell viability and Caspase-3 levels were measured to verify the protective effect of EGCG-mediated Aβ clearance on neurons. ResultsEGCG increased the activity time and frequency of APP/PS1 mice in the central area of the open field （P<0.05）， and enhanced the percentage of alternation in the Y-maze test （P<0.01）； EGCG reduced Aβ deposition in the hippocampal tissue of APP/PS1 mice and increased the number of microglia； in vitro experiments showed that EGCG improved the survival rate of Aβ-induced N9 cells （P<0.01）， upregulated RAGE activity （P<0.05）， and promoted the internalization and phagocytosis of Aβ （P<0.01）. ECGC activated microglial autophagy by downregulating the level of HDAC6 （P<0.05）， inhibiting the phosphorylation of PI3K， AKT， mTOR （P<0.001）， and increasing the LC3-Ⅱ/LC3-I ratio （P<0.001）； EGCG improved the survival rate of SH-SY5Y cells （P<0.05） and reduced the activity of Caspase-3 （P<0.01） by clearing Aβ_1-42 through microglia， and had a protective effect on neurons. ConclusionEGCG activates microglial autophagy to clear Aβ by targeting and inhibiting the HDAC6-PI3K/AKT/mTOR axis.

Objective: To investigate the distribution of IgM anti-A/B titers among group O whole blood donors in Jiangsu, establish a low-titer threshold, and analyze the demographic characteristics of low-titer donors, so as to provide data for recruiting low-titer group O whole blood (LTOWB) donors. Methods: Plasma samples from 1 009 group O whole blood donors were tested for IgM anti-A and anti-B titers using the microplate technique. The distribution of antibody titers was analyzed to establish a low-titer threshold. The distribution trends of titers across different demographic groups were also analyzed. Results: The peak titer for anti-A, anti-B were 64 (31.5%), 4 (23.8%), respectively, The proportion of donors with both anti-A and anti-B titers below 64 was 97.3% (982/1 009). The mean anti-A titer was higher than anti-B titer. Anti-A titers were higher in female donors than in male donors (P<0.05). The anti-A titers differed significantly among different age groups (P<0.05). However, no significant difference in titers was observed based on the number of donations (P>0.05). Conclusion: A titer of 64 can be used as the reference threshold of LTOWB in Jiangsu. Male donors of appropriate age are more suitable than female donors for establishing an emergency panel of LTOWB mobile donors.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective:To elucidate the epidemiological characteristics and temporal trends of out-of-hospital cardiac arrest (OHCA) in Shenzhen.Methods:Retrospective data on OHCA cases managed by emergency medical services (EMS) and admitted to network hospitals in Shenzhen from January 1, 2011 to December 31, 2022, were collected following the Utstein template. Demographic characteristics, event information, treatment, and resuscitation outcomes were included. Descriptive statistics, Joinpoint time trend analysis and a multivariate logistic regression were employed to identify factors influencing the return of spontaneous circulation (ROSC) after prehospital resuscitation.Results:A total of 46 053 EMS-accessed OHCA were included, of which 16 330 (35.46%) received EMS resuscitation. The crude incidence of EMS-accessed OHCA increased significantly from 15.51 per 100 000 in 2011 to 44.73 per 100 000 in 2022, with a significant overall upward trend (AAPC=11.83%, 95% CI: 8.33%-15.44%, P<0.001). Among EMS-treated OHCA, the bystander cardiopulmonary resuscitation (CPR) rate rose from 5.11% to 20.90% (AAPC=13.68%, 95% CI: 9.11%-18.44%, P<0.001), while prehospital ROSC rates increased from 2.33% to 8.62% (AAPC=17.53%, 95% CI: 13.01%-22.23%, P<0.001), both showing significant upward trends. Among EMS-treated OHCA patients, those with events occurring in public places (a OR=1.28, 95% CI: 1.06-1.55, P=0.006), presumed cardiovascular etiology (a OR=1.95, 95% CI: 1.65-2.32, P<0.001), initial shockable rhythm on monitoring (a OR=2.56, 95% CI: 1.08-3.15, P<0.001), bystander CPR (a OR=1.43, 95% CI: 1.16-1.76, P<0.001), airway opening (a OR=2.39, 95% CI: 1.70-3.46, P<0.001), and defibrillation (a OR=1.29, 95% CI: 1.06-1.57, P=0.010) had higher ROSC rates. Conversely, males (a OR=0.67, 95% CI: 0.55-0.81, P<0.001), the older (a OR=0.99, 95% CI: 0.98-0.99, P<0.001), and longer symptom onset to call 120 time of [10, 20) min (a OR=0.52, 95% CI: 0.39-0.70, P<0.001), [20, 30) min (a OR=0.33, 95% CI: 0.24-0.47, P<0.001), and ≥ 30 min (a OR=0.35, 95% CI: 0.25-0.49, P<0.001) were associated with lower prehospital resuscitation success rates. Conclusions:The incidence of OHCA in Shenzhen exhibited a significant upward trend from 2011 to 2022. Public location of arrest and early recognition-intervention were critical determinants of outcomes. Enhancing prehospital ROSC requires targeted improvements in the prehospital survival chain, including widespread public CPR training and optimized EMS accessibility.

Traditional Chinese medicine(TCM)is an ancient medical system distinctive and effective in treating cancer,depression,coronavirus disease 2019(COVID-19),and other diseases.However,the relatively abstract diagnostic methods of TCM lack objective measurement,and the complex mechanisms of action are difficult to comprehend,which hinders the application and internationalization of TCM.Recently,while breakthroughs have been made in utilizing methods such as network pharmacology and virtual screening for TCM research,the rise of machine learning(ML)has significantly enhanced their inte-gration with TCM.This article introduces representative methodological cases in quality control,mechanism research,diagnosis,and treatment processes of TCM,revealing the potential applications of ML technology in TCM.Furthermore,the challenges faced by ML in TCM applications are summarized,and future directions are discussed.

Objective To summarize the clinical and genetic characteristics of end-stage renal disease caused by PLCE1 gene mutations.Methods A retrospective analysis of the clinical and genetic features of three children from a family with PLCE1 gene mutations was conducted,along with a literature review of hereditary kidney disease cases caused by PLCE1 gene mutations.Results The proband was an 8-year-old male presenting with nephrotic syndrome stage 4 chronic kidney disease.Renal biopsy showed focal segmental glomerulosclerosis.Two years and five months after kidney transplantation,the patient had persistent negative proteinuria and normal renal function.Whole-exome sequencing identified two pathogenic heterozygous variants:c.961C>T and c.3255_3256delinsT,with c.3255_3256delinsT being a novel mutation.Family screening revealed no renal involvement in the parents,but among five siblings,one brother died at age of 4 years from end-stage renal disease.A 7-year-old sister presented with proteinuria and bilateral medullary sponge kidney,with proteinuria resolving after one year of follow-up.A 3-year-old brother died after kidney transplantation due to severe pneumonia.The literature review included 45 patients with hereditary kidney disease caused by PLCE1 gene mutations.The main clinical phenotype was nephrotic syndrome(87%,39/45),and renal pathology predominantly showed focal segmental glomerulosclerosis(57%,16/28).No mutation hotspots were identified.Conclusions Compound heterozygous mutations in the PLCE1 gene can lead to rapid progression of the disease to end-stage renal disease,with favorable outcomes following kidney transplantation.Family screening is crucial for early diagnosis,and medullary sponge kidney may be a novel phenotype associated with these gene mutations.Citaion:[Chinese Journal of Contemporary Pediatrics,2025,27(5):580-587]