In recent years, generative artificial intelligence (AI) technologies have achieved remarkable progress in the early screening, risk prediction, disease progression assessment, and clinical trial design of glaucoma.Using advanced algorithms, such as generative adversarial networks, variational autoencoders, and diffusion models, researchers have synthesized high-quality structural images of the optic disc, macular region, and retinal nerve fiber layer, which effectively alleviates the limitations of scarce clinical imaging data and label imbalance.These methods have substantially improved the accuracy and generalization of deep learning models in visual field defect prediction, structure-function mapping, and longitudinal disease progression simulation.Meanwhile, multimodal generative approaches that integrate imaging data, visual field tests, and clinical features have facilitated individualized prediction of glaucoma progression.In addition, large language models have shown preliminary potential in ophthalmic image interpretation, clinical text information extraction, and decision support, providing new insights into intelligent ophthalmic diagnosis and treatment.However, the clinical implementation of generative AI in glaucoma faces challenges.The pathological authenticity and cross-device consistency of generated images require further validation, which may affect the reliability of early glaucoma detection.The heterogeneous characteristics of different glaucoma subtypes, such as open-angle and angle-closure glaucoma, also limit the generalization of synthetic data.Moreover, issues related to model interpretability (" black-box" nature), artifact generation, data privacy, and ethical governance remain key barriers to clinical translation.In the future, it is expected that establishing large-scale training frameworks that incorporate multicenter, multimodal, and multiethnic datasets will enhance model robustness and clinical applicability.Furthermore, generative AI may contribute to remote ophthalmic care and personalized precision therapy by enhancing low-quality image, reconstructing missing data, and simulating dynamic disease courses.This article reviews the current applications, core technologies, and challenges of generative AI in glaucoma diagnosis and management, and discusses its future directions and translational potential in clinical ophthalmology.

The development of blood purification materials has progressed from cellulose membranes to high-strength polymer membranes, but the blood compatibility of the membranes remains a major challenge for their clinical applications. In this review, blood purification materials were categorized according to the commonly used material surface modification strategies, including surface grafting of anticoagulant groups, surface coating of materials and electrostatic layer-by-layer self-assembly, covalent attachment of superhydrophilic hydrogels, and blending method. Anticoagulant properties such as clotting time and surface hydrophilicity of various blood purification materials were also discussed to further analyze the value and challenges of blood purification materials in clinical practice.

In recent years, generative artificial intelligence (AI) technologies have achieved remarkable progress in the early screening, risk prediction, disease progression assessment, and clinical trial design of glaucoma.Using advanced algorithms, such as generative adversarial networks, variational autoencoders, and diffusion models, researchers have synthesized high-quality structural images of the optic disc, macular region, and retinal nerve fiber layer, which effectively alleviates the limitations of scarce clinical imaging data and label imbalance.These methods have substantially improved the accuracy and generalization of deep learning models in visual field defect prediction, structure-function mapping, and longitudinal disease progression simulation.Meanwhile, multimodal generative approaches that integrate imaging data, visual field tests, and clinical features have facilitated individualized prediction of glaucoma progression.In addition, large language models have shown preliminary potential in ophthalmic image interpretation, clinical text information extraction, and decision support, providing new insights into intelligent ophthalmic diagnosis and treatment.However, the clinical implementation of generative AI in glaucoma faces challenges.The pathological authenticity and cross-device consistency of generated images require further validation, which may affect the reliability of early glaucoma detection.The heterogeneous characteristics of different glaucoma subtypes, such as open-angle and angle-closure glaucoma, also limit the generalization of synthetic data.Moreover, issues related to model interpretability (" black-box" nature), artifact generation, data privacy, and ethical governance remain key barriers to clinical translation.In the future, it is expected that establishing large-scale training frameworks that incorporate multicenter, multimodal, and multiethnic datasets will enhance model robustness and clinical applicability.Furthermore, generative AI may contribute to remote ophthalmic care and personalized precision therapy by enhancing low-quality image, reconstructing missing data, and simulating dynamic disease courses.This article reviews the current applications, core technologies, and challenges of generative AI in glaucoma diagnosis and management, and discusses its future directions and translational potential in clinical ophthalmology.

Postoperative pain, a common problem in perioperative management, has negative impact on patients' experience and functional recovery. The development of postoperative pain is not only related to direct surgical trauma, but also a series of preventable perioperative risk factors, among which perioperative sleep quality should not be neglected. In recent years, more and more researches have indicated that poor perioperative sleep quality is a risk factor for both acute and chronic postoperative pain, and some researches have even pointed out that sleep quality can directly influence patients' pain threshold. Therefore, this review aims to summarize current research progress on the influence of perioperative sleep quality on postoperative pain, hoping to provide reference for improving the perioperative pain management for patients.

This paper provides a comprehensive analysis of the current state of intelligent ophthalmology in China, including technological advancements, academic exchange platforms, policy support, future challenges, and potential solutions. Technologically, remarkable progress have been made in various areas of intelligent ophthalmology in China, including diabetic retinopathy, fundus image analysis, and crucial aspects such as quality assessment of medical artificial intelligence products, clinical research methods, technological evaluation, and industrial standards. Researchers are constantly improving the safety and standardization of intelligent ophthalmology technology by formulating clinical application guidelines and standards. Academic exchange platforms have been established to provide extensive collaboration opportunities for professionals across diverse fields, and various academic journals serve as publication platforms for intelligent ophthalmology research. Regarding public policy, the Chinese government has not only established a supportive policy environment for the advancement of intelligent ophthalmology through various documents and regulations, but provided a legal basis and management framework. However, there are still challenges to overcome, such as technological innovation, data privacy and security, outdated regulations, and talent shortages. To tackle these issues, there is a requirement for increased technological research and development, the establishment of regulatory frameworks, talent cultivation, and greater awareness and acceptance of new technologies among patients. By comprehensively addressing these challenges, intelligent ophthalmology in China is expected to continue leading the industry's global development, bringing more innovation and convenience to the field of ophthalmic healthcare.

新冠病毒感染疫情严重威胁着世界各国人民的生命健康。目前，对病毒感染的防治研究主要集中在抑制病毒与分子受体的结合上。AXL作为新发现的严重急性呼吸综合征冠状病毒2型（SARS-CoV-2）受体，在协助病毒感染人体呼吸系统中发挥着重要作用，是未来临床干预的潜在靶点。本研究对已发表的单细胞测序数据进行整理和分析，发现AXL在年轻人肺细胞中的表达水平明显高于老年人。人胚肺二倍体成纤维细胞（2BS）是衰老研究的公认细胞株。本文采用2BS细胞构建复制性细胞衰老模型，发现年轻细胞中AXL的蛋白水平明显高于衰老细胞，据此推测年轻人感染的风险可能更高，需要注意防护。我们发现一种羊栖菜褐藻多糖硫酸酯组分（SFW-3）可显著下调年轻2BS细胞中AXL的表达水平，表明SFW-3具有一定的抗SARS-CoV-2感染的研究价值，同时表明2BS细胞株也可作为潜在的SARS-CoV-2体外感染模型。
Humans ; SARS-CoV-2 ; Sargassum/metabolism* ; Diploidy ; Sulfates/metabolism* ; COVID-19 ; Polysaccharides/pharmacology* ; Lung

DNA damage repair (DDR) genes are overexpressed in liver cancer. Studies have found that DDR is closely related to the occurrence and development of liver cancer. There is a synergistic effect between DDR inhibitors and chemotherapy and targeted drugs for liver cancer. DDR inhibitors can enhance the sensitivity of radiotherapy. Some DDR genes can be used as biomarkers for the prognosis of liver cancer.

Objective To establish a test of autoantibody-panel for the diagnosis of autoimmune cerebellitis (AC) and determine the prevalence of AC in patients with cerebellar ataxia of unknown etiology.Methods Autoantibody screening tests with indirect immunofluorescence were performed in serum and cerebrospinal fluid (CSF) samples of 400 previously'idiopathic'Chinese patients with cerebral ataxia (inpatients and outpatients in Peking Union Medical College Hospital or referred from hospitals of Beijing Encephalitis Group from 2016 to 2018).Immunotherapy was given to autoantibody positive patients and the effectiveness of immunotherapy was assessed.Detailed AC autoantibodies panel included anti-glutamate decarboxylase 65 (GAD65) antibody,anti-Tr (delta notch-like epidermal growth factor-related receptor (DNER)) antibody,anti-zinc finger protein 4 (ZIC4) antibody,anti-inositol 1,4,5-trisphosphate receptor 1 (ITPR1) antibody,anti-homer protein homolog 3 (Homer 3) antibody,anti-neurochondrin (NCDN) antibody,anti-carbonic anhydrase-related protein (CARP) antibody and anti-Purkinje cell antibody 2 (PCA2) antibody.Results Eight out of 400 (2％) ataxia patients were positive for this AC panel tests,of whom two were positive for anti-GAD65 antibody,two for anti-Tr antibody,one for anti-PCA2 antibody,one for anti-Homer 3 antibody and two were positive for serum anti-NCDN antibody.Autoantibodies against ZIC4,ITPR1 and CARP were not detected in this cohort.Two of the eight ataxia patients also presented with limbic encephalitis,and only one anti-GAD antibody patient was screened with underlying small cell lung carcinoma (SCLC).All the eight patients received immunotherapy and four experienced partial response.Conclusions Autoimmune cerebellitis is the cause of acquired cerebellar ataxia.Tests of autoantibodies associated with AC have diagnostic value for paraneoplastic and non-paraneoplastic cerebellar ataxia.Immunotherapy may yield partial response in patients with AC.

Objective To investigate the difference of CCAAT/enhancer-binding protein α (C/EBP-α) gene induced apoptosis between hepatocytes and hepatic stellate cells (HSC) in mice with liver fibrosis.Methods Sixty BALB/c mice were evenly divided into normal group,model group,treatment group,blank control group and negative control group,12 mice in each group.Except the mice of normal control group,the mice of other groups were treated with intraperitoneal injection of CCl4 to establish liver fibrosis mice model.Mice of treatment group,blank control group and negative control group were administrated with C/EBP-α carried adenovirus (Ad-C/EBP-α),phosphate buffered solution and empty vector of adenovirus (Ad-EGFP) respectively through tail vein for the first week.The expression of C/EBP-α and α-smooth muscle actin (α-SMA) was detected by immunohistochemistry method.Sinusoidal endothelial structure of peri-portal regions and far from portal regions was observed by transmission electron microscope (TEM).Terminal dexynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) was applied to detect apoptosis of cells in liver tissue.The degree of liver fibrosis in mice was determined with sirius red staining and hydroxyproline content measurement.Single factor variance analysis was performed for comparison among multiple groups,and t test was used for comparison between two groups.Results C/EBP-α was expressed in nucleus of hepatocyte in normal control group mice.The expression decreased in model group,blank control group and negative control group.However,the expression of C/EBP-α of treatment group increased,and mainly expressed in cells located in perisinusoidal and perivascular.Hepatic sinusoids was distorted,blood vessel wall thickened.Hepatocyte degeneration and lots of lipid droplets was found in model group,blank control group and negative control group.The thicken degree of endothelial layer of blood vessel of treatment group was lower than that of model group.The percentage of sirius red positive cells of normal group,model group,treatment group,blank control group and negative control group was (0.10±0.03)％,(5.81±0.32)％,(2.32±0.45)％,(6.34± 0.81)％ and (6.10± 0.92)％,respectively; content of hydroxyproline was (0.07±0.00) μg/mg,(0.69 ± 0.10) μg/mg,(0.19±0.06) μg/mg,(0.56±0.03) μg/mg and (0.64±0.08) μg/mg,respectively; the percentage of α-SMA positive cells was (0.50 ±0.03)％,(5.30 ± 0.52)％,(2.15 ± 0.29)％,(5.53 ± 0.43) ％ and (5.42 ± 0.25) ％,respectively; the number of TUNEL positive cells was (0.25 ± 0.08),(0.15±0.02),(7.10±1.53),(0.13±0.03) and (0.18±0.07),respectively.The differences between the groups were statistically significant (F=113.74,148.29,292.43 and 140.25,all P＜0.05).The difference between normal group and model group,between model group and treatment group,between treatment group and blank control group,between treatment group and negative control group were statistically significant (tarirus positive cell =-52.54,-16.20,-10.60 and-7.99,thydroxyproline content =-168.00,11.53,11.07 and 12.54,ta SMA pusitive cells-24.77,-13.82,15.94 and 18.37,tTUNEL positive cells =3.26,-11.91,-11.95 and-11.88,all P＜ 0.05),there was no statistically significant difference between model group and blank control group,between model group and negative control group (both P＞0.05).TUNEL positive cells mainly located in perisinusoidal and perivascular of liver in mice,which was consistent with the distribution of α-SMA-positive cells.Conclusion C/EBP-α could effectively relieve CCl4 induced liver fibrosis in mice mainly through inducing HSC apoptosis,however no apoptosis effect on hepatocytes.

Objectivo To analyze urine organic acids in the urine using gas chromatography-mass spectrometry(GC/MS)for diagnosis of inherited metabolic diseases,especially for organic acids metabolic disorders.Methods 195 clinical urine samples from the patients with suspected organic acids metabolic disorders and 5 normal urine from adults were collected.After mixing some urine with intemal standards according to the concentration creatinine and adding hydroxylamine hydrochloride to mixture,the organic acids with hydroxyl group were oximated to the ketobodies.Organic acids were extracted twice with ethyl acetate and ethyl ether and derivatized with BSTFA-TMCS.An the organic acids were determined with Agilent GC/MS 6890/5973i with scan model.the mass-to-charge ratio range is 50-550 m/z,all data were nalyzed with Agilent GCMSD ChemStationG1701DA.We also investigated the linearity, accurate,precision.recovery and Carry-over by determining the internal standards in normal samples and positive organic acids in spiked control samples.Results More than one hundred kinds of organic acids in urine samples can be analyzed with this method.According to the two internal standards in normal urine samples,the minimal detection limit MMA and 2.PA was 2.5-2.8 μmol/L.Intra-and interassay coefficient of variation for MMA and 2-PA are both less than 10%.Pre-processing Interassay coefficient by sequential preparations of the same sample was 14%.The recoveries of the spiked samples were 95%-105%.Carryover analysis was less than 1%.All the parameters meet the requirement for clinical diagnosis.12 samples demonstrated positive including 6 cases of methylmalonic acidemia,1 case of propionic acidemia,3 cases of tyrosinemia Ⅰ,1 case of maple syrup urine disease and 1 cases of ketosis.Conclusions The method for the determination of organic acids in urine by GC/MS has been successfully established.It can be used for clinical screening and diagnosis for inherited genetic metabolic diseases.