Rare diseases pose significant diagnostic and therapeutic challenges,carrying a high disease burden,their management critically reflects a nation's public health resilience.Currently,China faces key challenges such as scarce treatments,fragmented services,and low drug accessibility in rare disease care,which urgently require systemic solutions.Digital-intelligent technology as a key breakthrough are expected to resolve the challenges in this field.Although its application in the field of rare diseases is gradually expanding,there is a lack of systematic compilation of studies to elucidate how to precisely enhance the precision,synergy and sustainability of diagnosis and treatment.The key challenges in rare disease care concentrate in four areas:inefficiency in prenatal screening,uneven distribution of medical resources,low efficiency in social organization collaboration,and ineffective information dissemination.The"4C"strategy,based on digital-intelligent technology,can address these issues:①coordination,boost prenatal screening awareness and capacity via digital-intelligent platforms to strengthen prevention;②cooperation,deepen collaboration within specialist networks,empowering institutions to enhance diagnostic capacity;③co-creation,empower support organizations to optimize resources,efficiency;④cognition,minimize information dissipation through efficient platforms,improving patient and family quality of life.This establishes an integrated digital-intelligent rare disease model encompassing"screening-diagnosis-treatment-care".

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Urolithiasis represents a prevalent clinical challenge marked by high recurrence rates and morbidity，with existing preventive strategies struggling to effectively curb its epidemic trajectory，thereby posing a significant threat to public health. The etiology of this condition is intricate，involving a complex network of interactions spanning classical supersaturation-crystallization theory，Randall’s plaque theory，and multifactorial elements such as cellular injury，inflammatory responses，metabolic derangements，the gut-kidney axis，immune dysregulation，and genetic predisposition. However，the critical mechanisms initiating stone formation and the early pathophysiological processes remain incompletely elucidated，constituting the core impasse in current preventive strategies. This review systematically synthesizes classical theories and cutting-edge advancements in urolithiasis etiology research，emphasizing the urgent need to integrate emerging technologies，including high-dimensional omics，advanced imaging modalities，and artificial intelligence，to dissect pivotal pathological nodes in early stone formation. Such interdisciplinary efforts are essential to overcome cognitive bottlenecks and ultimately achieve personalized，precision-based prevention strategies.

A novel epileptic seizure prediction prediction model based on multichannel temporal and spatial feature extractions is presented.The model applies Stockwell transform to the original multichannel electroencephalogram(EEG)signals for extracting time-frequency components.To address the issue of insignificant difference between preseizure and interseizure time-frequency features,an adaptive feature module composing of ConvNeXt,SENet and pyramid pooling module is designed to enhance the ability of capturing key time-frequency features in each EEG channel.Meanwhile,a prediction model based on Bi-NLSTM is constructed to improve the spatiotemporal dependence between the time-frequency features of multichannel high-order EEG for further promoting the epilepsy classification performance.On the CHB-MIT dataset,the model has an accuracy,sensitivity,specificity and AUC of 96.0%,97.8%,96.8%and 0.987,respectively,and the false positive rate per hour decreased to 0.038,outperforming the existing mainstream methods.In addition,the effect of each component on the model performance is verified by ablation study.The proposed method improves the overall performance for seizure prediction effectively by optimizing local time-frequency feature extraction and enhancing multichannel spatiotemporal dependence.

Rare diseases pose significant diagnostic and therapeutic challenges,carrying a high disease burden,their management critically reflects a nation's public health resilience.Currently,China faces key challenges such as scarce treatments,fragmented services,and low drug accessibility in rare disease care,which urgently require systemic solutions.Digital-intelligent technology as a key breakthrough are expected to resolve the challenges in this field.Although its application in the field of rare diseases is gradually expanding,there is a lack of systematic compilation of studies to elucidate how to precisely enhance the precision,synergy and sustainability of diagnosis and treatment.The key challenges in rare disease care concentrate in four areas:inefficiency in prenatal screening,uneven distribution of medical resources,low efficiency in social organization collaboration,and ineffective information dissemination.The"4C"strategy,based on digital-intelligent technology,can address these issues:①coordination,boost prenatal screening awareness and capacity via digital-intelligent platforms to strengthen prevention;②cooperation,deepen collaboration within specialist networks,empowering institutions to enhance diagnostic capacity;③co-creation,empower support organizations to optimize resources,efficiency;④cognition,minimize information dissipation through efficient platforms,improving patient and family quality of life.This establishes an integrated digital-intelligent rare disease model encompassing"screening-diagnosis-treatment-care".

Objective:To investigate the role of mRNA expression in the pathogenesis of gout by analyzing the difference of gene expression in peripheral blood mononuclear cells(PBMCs)among acute gouty(AG),intermittent gouty(IG)and health con-trols(HC).Methods:AG patients,IG patients and HC were enrolled in this study.RNA-seq and bioinformatics techniques were used to observe the differences of mRNA expression in PBMCs of different groups,and to explore the genes and signaling pathways as-sociated with gout attack.GO and KEGG databases were used to investigate the biological functions of differentially expressed genes and the relationship between genes and signaling pathways.Genes involved in the KEGG enriched PPAR signaling pathway(CYP27A1,ACSL1,CD36,PPARG,ANGPTL4,PLIN2)were validated in PBMCs from 35 patients with AG,35 patients with IG,and 35 normal healthy subjects using real-time PCR.Results:Compared with HC group,there were 222 significant differential genes in AG group,including 193 up-regulated genes and 29 down-regulated genes.GO analysis showed that the genes differentially ex-pressed in AG group were mainly enriched in the regulation of multicellular biological processes such as inflammation,trauma,and stress response and immune response regulation compared with HC group.However,KEGG analysis showed that the up-regulated genes in AG group were enriched in"Toll-like receptor signaling pathway""complement and coagulation cascades""PPAR signaling pathway""lipid and atherosclerosis""osteoclast differentiation""cytokine-cytokine receptor interaction""chemokine signaling path-way""IL-17 signaling pathway",and"cholesterol metabolism"compared with HC group.The results of PCR validation of related genes in the PPAR signaling pathway showed that the expression levels of ACSL1,CD36,PPARG,and PLIN2 in the AG group were higher than those in the control group(P<0.05),and the expression levels of CYP27A1 and ANGPTL4 in the AG group were not dif-ferent from those in the HC group(P>0.05).Conclusion:PPAR signaling pathway may be involved in the pathogenesis of AG,of which ACSL1,CD36,PPARG,and PLIN2 may be used as potential therapeutic targets for acute gouty arthritis;CYP27A1 and ANG-PTL4 may not be associated with the pathogenesis of AG.

A novel epileptic seizure prediction prediction model based on multichannel temporal and spatial feature extractions is presented.The model applies Stockwell transform to the original multichannel electroencephalogram(EEG)signals for extracting time-frequency components.To address the issue of insignificant difference between preseizure and interseizure time-frequency features,an adaptive feature module composing of ConvNeXt,SENet and pyramid pooling module is designed to enhance the ability of capturing key time-frequency features in each EEG channel.Meanwhile,a prediction model based on Bi-NLSTM is constructed to improve the spatiotemporal dependence between the time-frequency features of multichannel high-order EEG for further promoting the epilepsy classification performance.On the CHB-MIT dataset,the model has an accuracy,sensitivity,specificity and AUC of 96.0%,97.8%,96.8%and 0.987,respectively,and the false positive rate per hour decreased to 0.038,outperforming the existing mainstream methods.In addition,the effect of each component on the model performance is verified by ablation study.The proposed method improves the overall performance for seizure prediction effectively by optimizing local time-frequency feature extraction and enhancing multichannel spatiotemporal dependence.

Objective:To investigate the role of mRNA expression in the pathogenesis of gout by analyzing the difference of gene expression in peripheral blood mononuclear cells(PBMCs)among acute gouty(AG),intermittent gouty(IG)and health con-trols(HC).Methods:AG patients,IG patients and HC were enrolled in this study.RNA-seq and bioinformatics techniques were used to observe the differences of mRNA expression in PBMCs of different groups,and to explore the genes and signaling pathways as-sociated with gout attack.GO and KEGG databases were used to investigate the biological functions of differentially expressed genes and the relationship between genes and signaling pathways.Genes involved in the KEGG enriched PPAR signaling pathway(CYP27A1,ACSL1,CD36,PPARG,ANGPTL4,PLIN2)were validated in PBMCs from 35 patients with AG,35 patients with IG,and 35 normal healthy subjects using real-time PCR.Results:Compared with HC group,there were 222 significant differential genes in AG group,including 193 up-regulated genes and 29 down-regulated genes.GO analysis showed that the genes differentially ex-pressed in AG group were mainly enriched in the regulation of multicellular biological processes such as inflammation,trauma,and stress response and immune response regulation compared with HC group.However,KEGG analysis showed that the up-regulated genes in AG group were enriched in"Toll-like receptor signaling pathway""complement and coagulation cascades""PPAR signaling pathway""lipid and atherosclerosis""osteoclast differentiation""cytokine-cytokine receptor interaction""chemokine signaling path-way""IL-17 signaling pathway",and"cholesterol metabolism"compared with HC group.The results of PCR validation of related genes in the PPAR signaling pathway showed that the expression levels of ACSL1,CD36,PPARG,and PLIN2 in the AG group were higher than those in the control group(P<0.05),and the expression levels of CYP27A1 and ANGPTL4 in the AG group were not dif-ferent from those in the HC group(P>0.05).Conclusion:PPAR signaling pathway may be involved in the pathogenesis of AG,of which ACSL1,CD36,PPARG,and PLIN2 may be used as potential therapeutic targets for acute gouty arthritis;CYP27A1 and ANG-PTL4 may not be associated with the pathogenesis of AG.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Urolithiasis represents a prevalent clinical challenge marked by high recurrence rates and morbidity，with existing preventive strategies struggling to effectively curb its epidemic trajectory，thereby posing a significant threat to public health. The etiology of this condition is intricate，involving a complex network of interactions spanning classical supersaturation-crystallization theory，Randall’s plaque theory，and multifactorial elements such as cellular injury，inflammatory responses，metabolic derangements，the gut-kidney axis，immune dysregulation，and genetic predisposition. However，the critical mechanisms initiating stone formation and the early pathophysiological processes remain incompletely elucidated，constituting the core impasse in current preventive strategies. This review systematically synthesizes classical theories and cutting-edge advancements in urolithiasis etiology research，emphasizing the urgent need to integrate emerging technologies，including high-dimensional omics，advanced imaging modalities，and artificial intelligence，to dissect pivotal pathological nodes in early stone formation. Such interdisciplinary efforts are essential to overcome cognitive bottlenecks and ultimately achieve personalized，precision-based prevention strategies.