Age-related macular degeneration(ARMD)is a progressive visual impairment fundus disease that frequently occurs in individuals aged >55 years. The main risk factors are aging, long-term smoking, genetics, and racial differences. Pathogenesis includes abnormal function of the retinal pigment epithelium, damaged blood-retinal barrier, and abnormal immune function. Currently, intravitreal injection(IVI)of anti-vascular endothelial growth factor(VEGF)drugs is the preferred treatment option for ARMD in clinical practice. However, it also faces challenges such as repeated treatments, high medical costs, and poor patient compliance. The predicament in the treatment of ARMD has given rise to several new treatment options. This article aims to review the treatment methods and progress of dry ARMD and wet ARMD, providing new ideas for addressing the limitations of the current clinical anti-VEGF treatment.

ObjectiveTo explore the complex network relationships among pain, kinesiophobia, social participation and knee function in patients after total knee arthroplasty (TKA), and to analyze the moderating effects of different socio-structural factors on the rehabilitation network from an ethical equity perspective. MethodsA convenience sampling method was used to select 291 patients who underwent TKA in Qilu Hospital of Shandong University from May to July, 2023. Pain was assessed using Numerical Rating Scale, kinesiophobia with Chinese short version of the Tampa Scale for Kinesiophobia, social participation with Impact on Participation and Autonomy Questionnaire, and knee function with Hospital for Special Surgery Knee Score. A partial correlation network among pain, kinesiophobia, social participation and knee function was constructed using Graphical Least Absolute Shrinkage and Selection Operator. Key variables were identified through node centrality and bridge centrality analysis. Network Comparison Tests (NCT) were used to analyze network differences among subgroups based on different socio-structural characteristics. ResultsIn the network model, the nodes with the highest strength centrality were indoor participation, activity behavior and activity pain. Bridge centrality analysis indicated that activity pain, knee function, indoor participation and activity cognition were key bridge nodes. NCT revealed no significant differences in overall network structure or global strength among subgroups based on residence, education level or payment method (P > 0.05). However, significant differences in edge weights were found for specific edges such as activity cognition-activity behavior and knee function-indoor participation (P < 0.05). ConclusionThere is a network of interactions among pain, kinesiophobia, social participation and knee function in patients after TKA, with nodes such as indoor participation and activity pain playing key roles in the rehabilitation process. Although the overall rehabilitation network is similar across different socio-structural groups, variations exist in specific relational pathways among patients from rural areas, those with lower education levels, and those with out-of-pocket payment. This suggests that clinical rehabilitation interventions should focus on these core nodes and implement targeted support strategies for socio-structurally disadvantaged groups to promote rehabilitation equity.

Disease computable phenotype is a data model designed to identify specific clinical conditions or characteristics, which automatically extracts information from clinical databases such as electronic health records through algorithms. Phenotypic data for rare diseases often reside in unstructured text. Due to the scarcity of rare disease cases, atypical symptoms, and insufficient physician experience, misdiagnosis and underdiagnosis rates remain high. In this context, the application of computable phenotype technology holds promise for improving the accuracy and efficiency of rare disease diagnosis. This article reviews the current research status, challenges, and opportunities of computable phenotype technology in biomedicine, particularly in the field of rare diseases, and proposes a development and validation framework for rare disease computable phenotypes, aiming to provide research and development insights for computable phenotypes to empower the diagnosis and treatment of rare diseases.

OBJECTIVE: To investigate the current status of clinical genetics specialization development and the diagnostic and therapeutic capabilities for hereditary diseases across medical institutions in Shanghai, and to assess the necessity and feasibility of establishing training bases for clinical genetics specialists. METHODS: By employing a cross-sectional survey design, the Clinical Genetics Committee of Shanghai Medical Association has conducted questionnaire surveys from March to April 2025 across 54 healthcare institutions in Shanghai (including 33 tertiary hospitals and 21 secondary hospitals). The survey involved administrative departments and medical personnel from 15 clinical specialties. The survey has covered current genetic disease diagnosis and treatment practices, relevant and specialised disease types, genetic department establishment, testing capabilities, personnel teams, and training requirements. RESULTS: The results revealed that 78.0% of clinical departments surveyed had treated patients with hereditary disorders. Shanghai possesses diagnostic and therapeutic expertise for over 95% of hereditary diseases listed in its rare disease catalogue, reflecting both the practical clinical demand for such conditions and the city's overall diagnostic and therapeutic strengths in this field. Nevertheless, significant disparities exist in the development of genetics departments across different tiers of healthcare institutions. Resources for genetic testing capabilities (including molecular, cellular, and biochemical testing) are also unevenly distributed across different tiers of hospitals. The survey further revealed that only 26.0% of departments believe that their current physician structure fully meets the diagnostic and treatment demands. Over 90% of departments consider standard training for clinical genetic specialists necessary, with 74.0% expressing willingness to participate in establishing training bases. Based on above findings and thorough deliberation, the Clinical Genetics Committee of the Shanghai Medical Association proposes advancing specialist training and discipline development through establishing a standard training system. The committee has drafted a three-year training protocol featuring a "joint training"-centered model, recommending a pilot-first, dynamically optimized strategy for steadily advancing training base development. CONCLUSION Shanghai faces substantial demand for genetic disease diagnosis and treatment, yet exhibits shortcomings in clinical genetics specialization development, resource allocation, and talent pipeline cultivation. To establish a standard training system holds significant practical importance and is underpinned by a broad demand.
Humans ; China ; Surveys and Questionnaires ; Genetic Diseases, Inborn/genetics* ; Cross-Sectional Studies ; Genetics, Medical/education* ; Genetic Testing

Objective: To compare the consistency between bioelectrical impedance analysis (BIA) and dual energy X ray absorptiometry (DXA) in measuring body composition among Tibetan children and adolescents and to explore the applicability of BIA in plateau region, so as to provide scientific and convenient body composition measurement support among children and adolescents. Methods: From May to June, 2022, a total of 344 Tibetan children and adolescents aged 6-17 years were selected from Golmud Municipal National Middle School and Changjiangyuan Nationality Primary School in Qinghai Province by cluster sampling method, and their fat mass, fat mass percentage and lean mass were measured by DXA and BIA. The consistency and correlation between the two methods were assessed by using the Wilcoxon rank-sum test, Spearman correlation analysis, intraclass correlation coefficient (ICC), and Bland-Altman analysis. Results: DXA measured fat mass and fat mass percentage were significantly higher than those obtained by BIA (6-12 years old: Z =9.91, 11.28; 13-17 years old: Z =9.02, 10.21), while lean mass and lean mass percentage were significantly lower than BIA results (6-12 years old: Z =-11.60, -11.30; 13-17 years old: Z =-10.77, -10.36) (all P < 0.05 ). The two methods showed strong correlations in fat mass and lean mass (all r >0.80, all ICC >0.90), but exhibited poor agreement in fat mass percentage and lean mass percentage (6-12 years old: Lin s CCC =0.64, 0.41; 13-17 years old: Lin s CCC = 0.79 , 0.35). Bland-Altman analysis showed that the difference between the two methods was negatively correlated with the average value in FM%(6-12 years old: r =-0.75, 13-17 years old: r =-0.79, both P <0.01). Conclusion BIA and DXA show high consistency in measuring body fat mass and lean body mass in Tibetan children and adolescents, although some bias is still present in certain individuals.

Antibodies play a critical role in adaptive immune responses and serve as key components in disease diagnosis and treatment. These molecules exhibit dynamic post-translational modifications (PTMs), such as glycosylation and phosphorylation, which regulate their effector functions. To date, nearly all of our knowledge about antibody repertoires has come from B cell receptor (BCR) sequencing (BCR-seq), which facilitates the profiling of clonal composition and the tracing of maturation trajectories within B-cell repertoires. However, circulating antibodies found in bodily fluids—such as serum, saliva, milk, mucosal secretions, and cerebrospinal fluid—exhibit diversities and specificities beyond what BCR-seq alone can predict. Therefore, identifying and quantifying antibody clonotypes at the protein level could enhance diagnosis, prognosis, and treatment strategies in personalized medicine. The critical gap between genotype and phenotype necessitates complementary methodologies that enable the direct characterization of antibody proteins in their native functional states. Mass spectrometry (MS)-based antibody repertoire sequencing (Ab-seq) is currently the only feasible approach for this task and primarily includes database-dependent methods—such as bottom-up, middle-down, and top-down approaches—as well as database-independent de novo sequencing technology. These strategies enable multi-level, high-precision characterization ranging from peptides and domains to intact antibody molecules. Unlike the shotgun strategy commonly used in routine proteomics, obtaining full sequences of all antibodies presents unique challenges. It requires specialized methodological adaptations to address issues related to dynamic range, sequence variation, and sample complexity. This review introduces the technical principles, methodological workflows, and recent applications of various mass spectrometry-based antibody repertoire sequencing (Ab-seq) strategies, with a focus on approaches designed to improve sequence coverage and identification accuracy. These include multi-enzyme digestion, hybrid fragmentation methods, and artificial intelligence-assisted de novo sequencing. By systematically comparing database-dependent techniques—such as bottom-up, middle-down, and top-down approaches—with database-independent de novo sequencing, this review outlines their respective advantages and limitations in terms of sample throughput, sequence coverage, post-translational modification characterization, and data analysis complexity. In addition, this review discusses emerging technological trends, including the integration of ion mobility separation, native mass spectrometry, and artificial intelligence-driven data interpretation, which are expected to enhance the depth and accuracy of antibody characterization. Although current methods continue to face challenges related to sample complexity, dynamic range, and unambiguous sequence variant assignment, we emphasize the importance of integrating BCR-seq and Ab-seq data to construct gene-protein association maps. These maps help validate sequence accuracy and facilitate epitope discovery. This dual-platform strategy helps bridge the gap between genotype and phenotype, thereby enhancing both the resolution and scope of antibody repertoire studies. Such an integrative approach also offers a valuable tool for therapeutic antibody development, structure-function analysis, and precise evaluation of vaccine efficacy.

ObjectiveTo explore the potential mechanism of Xiaoqinglongtang（XQL） in the prevention and treatment of high altitude pulmonary edema（HAPE） by network pharmacology， molecular docking， and molecular dynamics simulation， and to verify it by in vivo animal model. MethodsIn this study， the active ingredients， drug targets， and HAPE-related targets of XQL were collected from BATMAN-TCM， GeneCards， and Online Mendelian Inheritance in Man（OMIM） databases. The protein-protein interaction（PPI） network was constructed by using intersection targets， and the core targets were screened and visualized by Cytoscape software. Functional annotation and pathway analysis of the intersection targets were performed by gene ontology （GO） and Kyoto encyclopedia of genes and genomes （KEGG） functional enrichment. AutoDock and GROMACS were used to evaluate the binding ability of active ingredients to key targets. In the experimental verification part， a mouse model of HAPE induced by hypobaric hypoxia（simulated 6 000 m altitude for 48 h） was established. The control effect was evaluated by hematoxylin-eosin（HE） staining， lung tissue water content， lung tissue wet/dry weight ratio， real-time quantitative polymerase chain reaction（Real-time PCR） detection of gene expression levels， and immunohistochemistry and Western blot detection of key protein expression. ResultsA total of 355 active ingredients of XQL， 2 142 targets， 716 HAPE-related targets， and 236 intersection targets were obtained by network pharmacology analysis. Key core targets such as interleukin （IL）-6， tumor necrosis factor （TNF）， protein kinase B1 （Akt1）， and hypoxia-inducible factor-1α （HIF-1α） were screened. The results of GO analysis of common targets involved 738 biological processes（BP）， 72 cellular components（CC）， and 135 molecular functions（MF）. KEGG analysis effectively enriched two important signaling pathways： Phosphoinositol 3-kinase （PI3K）/Akt and HIF-1α. The results of molecular docking and molecular dynamics simulation showed that the screened active ingredients had good binding ability with key targets. In the HAPE model induced by hypobaric hypoxia（6 000 m， 48 h）， the lung tissue water content， lung tissue wet/dry weight ratio， and pathological injury score of the model group were significantly increased（P<0.01）， accompanied by exudation of a large number of red blood cells in the alveoli and alveolar interstitium， a significant increase in inflammatory cells， a significant widening of the alveolar septum， and mutual fusion between the alveoli. The XQL administration group significantly improved the above pathological changes（P<0.01）. The results of inflammatory factor expression showed that compared with the control group， the model group showed significantly up-regulated expression of TNF-α， IL-6， and IL-1β in the lung tissue（P<0.01）. Compared with the model group， the XQL administration group had significantly decreased expression of inflammatory factors（P<0.05， P<0.01）. The mRNA expression of key pathway related genes PI3K， Akt1， mammalian target of rapamycin（mTOR）， and HIF-1α was significantly increased in the model group（P<0.01）， and decreased in a concentration-dependent manner after XQL administration（P<0.05， P<0.01）. The expression levels of key proteins PI3K， phosphorylation（p）-PI3K， Akt1， p-Akt1， mTOR， p-mTOR， and HIF-1α in lung tissue were analyzed by immunohistochemistry and Western blot. Compared with the blank group， the model group showed increased expression of key proteins（P<0.05， P<0.01）. Compared with the model group， the XQL administration group exhibited decreased expression of key proteins（P<0.05， P<0.01）. ConclusionXQL can reduce lung inflammation and improve HAPE. The mechanism may be related to the regulation of PI3K/Akt/mTOR and HIF-1α pathways. This study provides a new idea and a theoretical basis for the treatment of HAPE with XQL.

Infective endocarditis (IE) is a life-threatening infectious disease. Although histopathological examination remains the gold standard for definitive diagnosis, it is performed in only a minority of patients; thus, the diagnosis of IE continues to rely predominantly on clinical manifestations. However, IE presents with highly variable systemic symptoms that often lack cardiac-specific features, posing significant diagnostic challenges. To address this complexity, multiple diagnostic criteria have been developed, integrating clinical presentation, imaging findings, and microbiological evidence. Over the past three decades, substantial shifts in the microbiological and epidemiological profiles of IE, coupled with advances in imaging modalities and laboratory diagnostics, have profoundly influenced diagnostic approaches, driving continuous refinement of diagnostic criteria. This review provides a comprehensive overview of the major diagnostic criteria for IE, traces their historical evolution, evaluates recent updates and diagnostic performance, and offers theoretical insights and practical implications to guide future research.

Objective To investigate the expression profile, prognostic value, gene co-expression network, and immunomodulatory role of BRF1 in a pan-cancer context, and to explore its biological functions and molecular regulatory mechanisms in esophageal squamous cell carcinoma (ESCC). Methods The pan-cancer dataset from The Cancer Genome Atlas (TCGA) was utilized to analyze the differential expression of BRF1 in tumor versus normal tissues, its association with patient survival, pathway enrichment for co-expressed genes, and immune features (including immune checkpoints, cytokines, and immune cell infiltration). The expression profile of BRF1 in ESCC was validated using the Gene Expression Omnibus (GEO) database. In vitro, BRF1 was knocked down in ESCC cells using siRNA. Cell proliferation and migration were assessed by MTT and Transwell assays, respectively. The expression levels of proliferation- and migration-related proteins were detected by Western blotting. The correlation between BRF1 and ferroptosis was analyzed using TCGA data. Results BRF1 was significantly upregulated in over 20 types of cancer, and its high expression was associated with poor prognosis in patients with adrenocortical carcinoma and prostate adenocarcinoma. BRF1 was found to positively regulate the T-cell-mediated cell death pathway in esophageal adenocarcinoma and was associated with the circadian rhythm regulation pathway in pancreatic adenocarcinoma. The correlation of BRF1 with immune checkpoints, cytokine networks, and immune cell infiltration was found to be cancer type-specific. In vitro experiments demonstrated that knocking down BRF1 significantly inhibited the proliferation of ESCC cells, accompanied by the downregulation of the proliferation marker PCNA. Cell migration was also significantly impaired, with decreased expression of Vimentin and MMPs and increased expression of E-cadherin. Furthermore, the expression of BRF1 was positively correlated with that of ferroptosis-antagonizing genes, such as GPX4, HSPA5, and SLC7A11. Conclusion BRF1 plays complex roles in pan-cancer, participating in the regulation of tumorigenesis, progression, and immune infiltration. BRF1 promotes the proliferation and migration of ESCC cells, a mechanism potentially associated with the regulation of ferroptosis resistance. These findings suggest that BRF1 could be a potential therapeutic target for ESCC.

Patients with Takayasu arteritis combined with aortic valve disease often have a poor prognosis following surgical valve replacement, frequently encountering complications such as perivalvular leakage, valve detachment, and anastomotic aneurysm. This article presents a high-risk case wherein severe aortic valve insufficiency associated with Takayasu arteritis was successfully managed through transcatheter aortic valve implantation via the transapical approach. The patient had satisfactory valve function with no complications observed during the six-month postoperative follow-up. This case provides a minimally invasive and feasible alternative for the clinical management of such high-risk patients.