Uveal melanoma(UM)is the most common primary intraocular malignancy in adults, characterized by high invasiveness and unique metastatic biological features. Although local treatments(such as proton beam therapy and brachytherapy)can effectively control the primary lesion, approximately 50% of patients eventually develop distant metastasis, with the liver being the primary target organ(occurring in 90% of cases). This highlights a paradigm shift in treatment focus from mere local control to systemic prevention and management. For metastatic UM(mUM), current treatment strategies encompass biomarker-guided molecular targeted therapy, immunotherapy(including Tebentafusp, vaccines, and oncolytic virus therapy), and liver-directed therapy. Focusing on the synergy between local and systemic prevention and control, this article systematically elaborates on the precision local treatment for primary UM, the decision-making pathway for systemic treatment of metastatic UM based on molecular subtyping, the integration of local and systemic therapies for liver metastases, and the translational value of nanomedicine in addressing therapeutic bottlenecks. It provides insights for optimizing clinical management of mUM and developing novel therapeutic strategies.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

Objective:To investigate the role and mechanism of leucine-rich α-2-glycoprotein 1 (LRG1) in the fibrosis of human pterygium fibroblasts (HPFs).Methods:A total of 30 nasal primary pterygium tissues from patients who underwent pterygium excision surgery and 30 nasal normal conjunctival tissues from patients who underwent strabismus correction surgery were collected from the First Affiliated Hospital of Harbin Medical University between January 2022 and March 2023, serving as the pterygium group and normal control group, respectively.LRG1 protein expression in both groups was detected by immunofluorescence staining.The mRNA and protein levels of LRG1 and transforming growth factor-β1 (TGF-β1) were evaluated by quantitative real-time PCR (qRT-PCR) and Western blot.Primary HPFs were cultured from excised pterygium tissues using tissue block adhesion method, and cell morphology was observed.Vmentin and cytokeratin were identified by immunofluorescence staining.HPFs were divided into recombinant human LRG1 (rhLRG1) group and blank control group treated with or without 10 μg/ml rhLRG1 for 24 hours, respectively, and cell migration was evaluated via scratch assay.Additionally, HPFs were divided into blank control group, LRG1 overexpression group and LRG1 knockdown group.HPFs in LRG1 overexpression group and LRG1 knockdown group were transfected with LRG1 overexpression plasmids and small interfering RNA for 24 hours, respectively.TGF-β1 mRNA level was evaluated by qRT-PCR and expression of TGF-β1, fibronectin (FN), type Ⅲ collagen (COL3), and α-smooth muscle actin (α-SMA) proteins were evaluated by Western blot.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Harbin Medical University (No.2022IIT026).Written informed consent was obtained from each subject.Results:HPFs were successfully isolated, exhibiting spindle-shaped morphology with whorled arrangement, positive identification for vimentin, and negative immunofluorescence staining for cytokeratin.The migration rate of the rhLRG1 group was (83.01±2.56)%, significantly higher than (50.32±4.97)% of the blank control group ( t=9.59, P<0.001).Immunofluorescence staining results showed that compared with normal conjunctival tissue, LRG1 protein was significantly higher expressed in pterygium tissue and was widely distributed in fibrous connective tissue and epithelial layer.Both mRNA and protein levels of LRG1 and TGF-β1 were significantly higher in the pterygium group than in the normal control group (mRNA: t=10.18, 6.15, both P<0.05.protein: t=6.83, 8.79, both P<0.05).In the LRG1 overexpression group, mRNA level of TGF-β1, and protein levels of FN, COL3 and α-SMA were significantly increased compared with the blank control and LRG1 knockdown groups (all P<0.05). Conclusions:LRG1 promotes fibrosis and enhances the migration ability in HPFs, and its mechanism may be associated with the upregulation of the TGF-β1 signaling pathway.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

Objective:To investigate the role and mechanism of leucine-rich α-2-glycoprotein 1 (LRG1) in the fibrosis of human pterygium fibroblasts (HPFs).Methods:A total of 30 nasal primary pterygium tissues from patients who underwent pterygium excision surgery and 30 nasal normal conjunctival tissues from patients who underwent strabismus correction surgery were collected from the First Affiliated Hospital of Harbin Medical University between January 2022 and March 2023, serving as the pterygium group and normal control group, respectively.LRG1 protein expression in both groups was detected by immunofluorescence staining.The mRNA and protein levels of LRG1 and transforming growth factor-β1 (TGF-β1) were evaluated by quantitative real-time PCR (qRT-PCR) and Western blot.Primary HPFs were cultured from excised pterygium tissues using tissue block adhesion method, and cell morphology was observed.Vmentin and cytokeratin were identified by immunofluorescence staining.HPFs were divided into recombinant human LRG1 (rhLRG1) group and blank control group treated with or without 10 μg/ml rhLRG1 for 24 hours, respectively, and cell migration was evaluated via scratch assay.Additionally, HPFs were divided into blank control group, LRG1 overexpression group and LRG1 knockdown group.HPFs in LRG1 overexpression group and LRG1 knockdown group were transfected with LRG1 overexpression plasmids and small interfering RNA for 24 hours, respectively.TGF-β1 mRNA level was evaluated by qRT-PCR and expression of TGF-β1, fibronectin (FN), type Ⅲ collagen (COL3), and α-smooth muscle actin (α-SMA) proteins were evaluated by Western blot.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Harbin Medical University (No.2022IIT026).Written informed consent was obtained from each subject.Results:HPFs were successfully isolated, exhibiting spindle-shaped morphology with whorled arrangement, positive identification for vimentin, and negative immunofluorescence staining for cytokeratin.The migration rate of the rhLRG1 group was (83.01±2.56)%, significantly higher than (50.32±4.97)% of the blank control group ( t=9.59, P<0.001).Immunofluorescence staining results showed that compared with normal conjunctival tissue, LRG1 protein was significantly higher expressed in pterygium tissue and was widely distributed in fibrous connective tissue and epithelial layer.Both mRNA and protein levels of LRG1 and TGF-β1 were significantly higher in the pterygium group than in the normal control group (mRNA: t=10.18, 6.15, both P<0.05.protein: t=6.83, 8.79, both P<0.05).In the LRG1 overexpression group, mRNA level of TGF-β1, and protein levels of FN, COL3 and α-SMA were significantly increased compared with the blank control and LRG1 knockdown groups (all P<0.05). Conclusions:LRG1 promotes fibrosis and enhances the migration ability in HPFs, and its mechanism may be associated with the upregulation of the TGF-β1 signaling pathway.

Objective:To report the nationwide surveillance results of pathogenic profiles and antimicrobial resistance patterns of Gram-positive bloodstream infections in China in 2023.Methods:The clinical isolates of Gram-posttive bacteria from blood cultures were collected in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System（BRICS）during January to December 2023. Antimicrobial susceptibility testing was performed using the dilution method recommended by the Clinical and Laboratory Standards Institute（CLSI）. Statistical analyses were conducted using WHONET 5.6 and SPSS 25.0 software.Results:A total of 4 385 Gram-positive bacterial isolates were obtained from 60 participating center. The top five pathogens were Staphylococcus aureus（ n=1 544，35.2%），coagulase-negative Staphylococci（ n=1 441，32.9%）， Enterococcus faecium（ n=574，13.1%）， Enterococcus faecalis（ n=385，8.8%），and α-hemolytic Streptococci（ n=187，4.3%）. The prevalence of methicillin-resistant Staphylococcus aureus（MRSA）and methicillin-resistant coagulase-negative Staphylococci（MRCNS）was 26.2%（405/1 544）and 69.8%（1 006/1 441），respectively. Notably，all Staphylococci remained susceptible to glycopeptide or daptomycin. Staphylococcus aureus demonstrated excellent susceptibility（>97.0%）to cephalobiol，rifampicin，trimethoprim-sulfamethoxazole，linezolid，minocycline，tigecycline，and eravacycline. No Enterococcus exhibiting resistance to linezolid were detected. Glycopeptide resistance was uncommon but more frequent in Enterococcus faecium（resistance to vancomycin and teicoplanin：both 1.7%）compared to Enterococcus faecalis（both 0.3%）. The detection rates of MRSA and MRCNS exhibited significant regional variations across the country（ χ2=17.674 and 148.650，respectively，both P<0.001）. No vancomycin-resistant Enterococci were detected in central China. Institutional comparison demonstrated higher prevalence of MRSA（ χ2=14.111， P<0.001）and MRCNS（ χ2=4.828， P=0.028）in provincial hospitals than that in municipal hospitals. Socioeconomic analysis identified elevated detection rates of both MRSA（ χ2=18.986， P<0.001）and MRCNS（ χ2=4.477， P=0.034）in less developed regions（per capita GDP

Objective:To report the results of bacterial resistant investigation collaborative system（BRICS）on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2023，and provide reference for clinical tretment of bloodstream infections and prevention and control of bacterial resistance.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of BRICS were collected during January 2023 to December 2023. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 were used to analyze the data.Results:During the study period，11 492 strains of Gram-negative bacteria were collected from 60 hospitals，of which 10 098（87.9%）were Enterobacterales and 1 394（12.1%）were non-fermentative bacteria. The top 5 bacterial species were Escherichia coli（50.0%）， Klebsiella pneumoniae（26.1%）， Pseudomonas aeruginosa（5.1%）， Acinetobacter baumannii complex（5.0%）and Enterobacter cloacae complex（4.1%）. The ESBL-producing rates in Escherichia coli， Klebsiella pneumoniae and Proteus mirablilis were 46.8%（2 685/5 741），18.3%（549/2 999）and 44.0%（77/175），respectively. The prevalence of carbapenem-resistant Escherichia coli（CREC）and carbapenem-resistant Klebsiella pneumoniae（CRKP）were 1.3%（76/5 741）and 15.0%（450/2 999）；32.9%（25/76）and 78.0%（351/450）of CREC and CRKP were sensitive to ceftazidime/avibactam combination，respectively. 94.7%（72/76）and 90.2%（406/450）of CREC and CRKP were sensitive to aztreonam/avibactam combination. Furthermore，57.9%（44/76）and 79.1%（356/450）were sensitive to imipenem/relebactam combination. The prevalence of carbapenem-resistant Acinetobacter baumannii（CRAB）complex was 64.6%（370/573），while more than 80.0% of CRAB complex was sensitive to tigecycline，eravacycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa（CRPA）was 17.0%（99/581）. There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of important Gram-negative bacteria resistance among different regions in China，with statistically significant differences in the prevalence of CREC，CRKP，CRPA and CRAB complex（ χ2=10.6，28.6，10.8 and 19.3， P<0.05）. The prevalence of ESBL-producing Escherichia coli， CREC，CRAB complex and CRKP were higher in provincial hospitals than those in municipal hospitals（ χ2=12.5，9.8，12.7 and 57.8，all P<0.01）. Conclusions:Gram-negative bacteria are the main pathogens causing bloodstream infections in China，and Escherichia coli is ranked in the top，while the trend of Klebsiella pneumoniae increases continuously with time. CRKP infection shows a slow upward trend，CREC infecton maintains a low prevalence level，and CRAB complex infection continues to exhibit a high prevalence rate. The composition and resistance patterns of pathogens causing bloodstream infections vary to some extent across different regions and levels of hospitals in China.

Radiation-induced intestinal injury is caused by high dose of radiation in the abdomen and pelvis. The disease is characterized by complicated pathological mechanisms and poses significant challenges to clinical treatment, seriously affecting the quality of life and health of patients. Current treatments in modern medicine offer limited efficacy and are often associated with adverse side effects. Traditional Chinese medicine monomers inhibit inflammatory factors (e.g., tumor necrosis factor-α and interleukin-1β) and regulate the antioxidant enzyme system (e.g., improving the activity of superoxide dismutase) to effectively reduce the symptoms of radiation-induced intestinal injury with minimal side effects. Through targeted delivery of nanoparticles, nanotechnology can accurately deliver the active ingredients of traditional Chinese medicine to damaged intestinal tissues, thus improving their bioavailability and therapeutic effects. This paper reviews the mechanisms of Chinese medicine monomers in the prevention and treatment of radiation-induced intestinal injury and the application of nanotechnology for enhanced efficiency. The paper also discusses the clinical potential of these approaches. These results provide a reference for future research and clinical practice.

Objective To construct a prognostic model of centrosome amplification-related genes(CARGs)by machine learning and evaluate its prediction performance for the prognosis of esophageal squamous cell carcinoma(ESCC).Methods CARGs were obtained from Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)datasets.The RNA-sequencing(RNA-seq)transcriptome datasets of ESCC were retrieved from The Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO),and assigned into training and validation sets,respectively.Subsequently,single-sample gene set enrichment analysis(ssGSEA)and weighted gene co-expression network analysis(WGCNA)were employed to screen CARGs.A prognostic model of CARGs was constructed by incorporating 12 machine learning algorithms,and univariate and multivariate Cox regression analyses were applied to evaluate whether the 12 models as an independent prognostic factor or not.Eventually,15 paired ESCC and adjacent non-tumor tissue samples were collected from the Department of Gastroenterology of the Second Affiliated Hospital of Army Medical University,and real-time quantitative PCR(RT-qPCR)and immunohistochemistry staining were performed to detect the expression of these genes ESCC samples.Results Our 9-CARGs prediction model for ESCC prognosis was constructed.RT-qPCR confirmed that the mRNA expression levels of DENR,TRIP13,BRCA2,TTF2,TCFL5 and NUP188 were significantly higher in ESCC tissues than normal tissues(P<0.05),and the protein levels of DENR,TRIP13,TTF2 and TCFL5 were also elevated when compared to normal tissues.Conclusion DENR,TRIP13,TTF2 and TCFL5 are highly expressed and closely associated with poor prognosis of ESCC,suggesting their potential roles in the pathogenesis and progression of this malignancy.

Toxoplasma gondii is a single-celled parasite that infects nearly all warm-blooded animals, including humans (Montoya and Liesenfeld, 2004). It occurs worldwide and can persist for a lifetime in mammals. Humans get infected by eating undercooked meat of animals containing the tissue cysts of this parasite. In immune-competent individuals, T. gondii infection usually does not cause significant clinical symptoms, whereas in pregnant or immunocompromised individuals, T. gondii infection (toxoplasmosis) can cause more serious problems like abortion and even death (Dunn et al., 1999; Wang et al., 2017). A combination of pyrimethamine and sulfadiazine is usually used to treat toxoplasmosis, although it is generally inefficient and causes side effects (Alday and Doggett, 2017). Worse still, there is a lack of vaccines to prevent T. gondii infection in humans or animals.
Toxoplasma/enzymology* ; Animals ; Humans ; Toxoplasmosis ; Mitochondria/enzymology* ; Protozoan Proteins/metabolism*