Myopic traction maculopathy(MTM)is a common vision-threatening complication in patients with high myopia. With the global increase in high myopia, the prevalence of MTM has been rising worldwide, leading to a growing burden of disease, economic costs,and social impact. The emergence and development of optical coherence tomography(OCT)have provided robust technical support for the staging of MTM. Based on the evolving understanding of its pathological mechanisms and natural course, various staging systems have been proposed and applied in clinical practice, offering crucial guidance for the personalized management of MTM patients. Additionally, innovations and refinements in surgical techniques and materials, such as pars plana vitrectomy(PPV), posterior scleral reinforcement, and macular buckling(MB), have expanded the therapeutic options for MTM. This article systematically reviews the staging systems and treatment strategies for MTM, focusing on the role of OCT-based staging in guiding individualized treatment plans. It also summarizes the current evidence on the efficacy and safety of existing and emerging surgical approaches, including PPV, MB, and their combined procedures. The review further proposes that future research should focus on developing predictive models integrating multimodal data to clarify surgical timing and indications, as well as conducting large-scale, multicenter randomized controlled trials to explore the selection of PPV, MB, or combined surgeries. The review aims to discuss personalized treatment for MTM, providing theoretical foundations and practical directions for optimizing clinical management and improving patient prognosis for MTM patients.

BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

Objective To establish and evaluate a nomogram prediction model for spontaneous peritonitis in HBV-related primary liver cancer.Methods A retrospective study was conducted on 1298 patients with HBV-related primary liver cancer hospitalized in the Kunming Third People's Hospital from January 2012 to December 2022.General data and serological indicators were collected,and patients were divided into infection group(n=262)and control group(n=1036)based on the occurrence of spontaneous peritonitis.Univariate and LASSO regression analyses were used to screen variables,followed by binary logistic regression to analyze the influencing factors of spontaneous peritonitis in HBV-related primary liver cancer patients,leading to the establishment of a nomogram prediction model.Finally,the Hosmer-lemeshow(H-L)goodness of fit test,receiver operating characteristic(ROC)curve,calibration curve,decision curve analysis(DCA)and clinical impact curve(CIC)were utilized to evaluate the fit degree,accuracy,calibration,and clinical practicability of the nomogram prediction model.Results Single factor analysis revealed significant differences between infection group and control group in portal vein cancer thrombus(PVTT),Child-Pugh grade,China Liver Cancer Staging(CNLC)stage,alcohol consumption history,smoking history,white blood cell count(WBC),neutrophil count(NE),hemoglobin(Hb),fibrinogen(FIB),abnormal prothrombin(PIVKA-Ⅱ),aspartate aminotransferase(AST),alanine aminotransferase(ALT),total protein(TP),prealbumin(PA),γ-glutamyltransferase(GGT),alkaline phosphatase(ALP),cholinesterase(CHE),total bile acid(TBA),total cholesterol(TC),low density lipoprotein(LDL),creatinine(Cr),HBV DNA,CD3+T cells count,CD4+T cells count,CD8+T cells count,CD4+T cells/CD8+T cells ratio,procalcitonin(PCT),serum amyloid A(SAA),interleukin-6(IL-6),high-sensitivity C-reactive protein(hs-CRP),alpha-fetoprotein(AFP),and IL-4(P＜0.05).LASSO regression analysis identified 5 variables:Child-Pugh grade,PVTT,WBC,CHE and hs-CRP.Binary logistic regression analysis indicated that Child-Pugh grade(Grade B:OR=5.780,95％CI 3.271-10.213,P＜0.001;Grade C:OR=14.818,95％CI 7.697-28.526,P＜0.001),PVTT(OR=2.893,95％CI 2.037-4.108,P＜0.001),WBC(OR=1.088,95％CI 1.031-1.148,P=0.002),and hs-CRP(OR=1.005,95％CI 1.001-1.010,P=0.026)were the independent risk factors of spontaneous peritonitis in HBV-related primary liver cancer patients.Using these 4 variables,a nomogram prediction model was constructed and evaluated.The P-value of the H-L goodness of fit test was 0.760.Moreover,the area under ROC curve(AUC)was 0.866,with a sensitivity of 0.870 and a specificity of 0.716.The average absolute error of the calibration curve is 0.022.DCA and CIC analyses demonstrated that the nomogram prediction model possessed some clinical utility.Conclusion The nomogram prediction model for spontaneous peritonitis in HBV-related primary liver cancer patients,constructed using Child-Pugh grade,PVTT,WBC and hs-CRP,exhibits a high fitting degree and accuracy,with the prediction probability highly consistent with the actual occurrence probability,and possesses certain clinical practicability.

Objective To develop and validate a fast Monte Carlo(MC)-based patient-specific quality assurance(PSQA)tool using the treatment log files that is suitable to be used in the online adaptive radiotherapy for pencil beam scanning proton therapy(PBSPT-ART).Methods The proposed tool first used the delivery log file of a PBSPT plan to reversely reconstruct the PBSPT(rPBSPT)plan,and then used an in-house developed graphic processing unit(GPU)-accelerated virtual particle MC(VPMC)dose engine to calculate the dose distribution of the rPBSPT plan.The rPBSPT dose calculated by VPMC was then compared to the rPBSPT dose calculated by another independent MC dose engine(MCsquare),using 3D gamma analysis to verify the accuracy of VPMC calculation.As a demonstration of the feasibility of developed log file-based PSQA,the VPMC calculated dose of the rPBSPT plan was compared to the pre-delivery second check dose of the corresponding PBSPT plan calculated by MCsquare,using 3D gamma analysis.3D gamma analysis employes a criterion of 2 mm/2%/10%.Twenty patients with different disease sites were representatively selected to validate the efficiency and accuracy of the tool.Results The average calculation time of a rPBSPT plan by VPMC was(5.88±4.00)s in the accuracy verification.Compared to MCsquare,the passing rate of the 3D gamma analysis was 99.47%±0.72%.In the proposed PSQA tool demonstration,the passing rate of comparing the VPMC calculated rPBSPT dose to MCsquare calculated second check dose of the corresponding PBSPT plan was 98.91%±0.92%.Conclusion The accuracy and efficiency of the tool can meet the requirements of PSQA in the online PBSPT-ART workflow.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective:To observe the effect of modified autologous skull defect repair in patients with traumatic brain injury and its influence on neurological function and living ability.Methods:104 patients with traumatic brain injury who were admitted to our hospital from March 2022 to August 2024 were included,they were divided into Group A[37 cases,poly ether ether ketone(PEEK)skull defect repair],Group B(35 cases,traditional titanium mesh skull defect repair),and Group C(32 cases,modified autologous skull defect repair).Perioperative indicators,neurological function,activity of daily living,quality of life,satisfaction,and incidence of postoperative complications were compared among three groups.Results:There were no differences in the operation time,operation blood loss and postoperative hospital stay among the three groups(P＞0.05).The hospitalization costs of Group A,Group B and Group C decreased successively(P＜0.05).Activity of Daily Living(ADL)scores at 3 and 6 months after surgery increased among three groups,while National Institutes of Health Stroke Scale(NIHSS)scores decreased(P＜0.05).There was no significant difference in physiological function,social function,psychological function,and material life among the three groups at 6 months after surgery(P＞0.05).The overall satisfaction rate in Group C was higher than that of Group A and Group B(P＜0.05).The overall incidence of complications in Group C was lower than that in Group A and Group B(P＜0.05).Conclusion:PEEK,traditional titanium mesh,and modified autologous skull are used in skull defect repair,operation time,operation blood loss and postoperative hospital stay are comparable,they can also reduce neurological function damage,improve living ability,and enhance the quality of life of patients,however,PEEK is relatively expensive,the satisfaction of traditional titanium mesh is low,andincidence of postoperative complications are relatively high.

Objective:To analyze the characteristics and general patterns of adverse drug reactions associated with aripiprazole, and to identify potential risk signals, thereby providing references for the safe and rational use of medications in clinical practice.Methods:This is a descriptive study that collected and summarized reports of adverse reactions to aripiprazole submitted by medical institutions in Anhui Province to the National Center for Adverse Drug Reaction Monitoring, China from January 2019 to December 2024. The basic characteristics of patients, the treatment regimens used, the timing of adverse drug reaction occurrence, the clinical manifestations of the affected systems, and the outcomes of these adverse drug reactions were statistically analyzed to identify the clinical characteristics and risk factors of adverse drug reactions associated with aripiprazole.Results:A total of 1 106 adverse reaction case reports related to aripiprazole were collected, with a male-to-female ratio of 1:1.29 ( χ2 = 8.64, P = 0.003) and an average age of (35 ± 16) years. The primary diseases treated included schizophrenia (768 cases, 69.44%), bipolar affective disorder (96 cases, 8.68%), and depressive disorder (75 cases, 6.78%). Adverse reactions occurred within the first 2 weeks of medication in 689 cases (62.29%). All medications were oral formulations, with 978 cases (88.43%) falling within the recommended daily dose range of 10-30 mg/d, while 15 cases (1.36%) exceeding the maximum recommended dose of 30 mg/d. The most common clinical manifestations were related to the nervous system (696 cases, 62.93%), followed by cardiovascular system manifestations (146 cases, 13.20%). The majority of adverse reactions showed improvement or recovery (1 052 cases, 95.12%). Conclusions:Aripiprazole is widely used in clinical practice, and the occurrence of adverse reactions is correlated with patient characteristics and treatment regimens. It is advisable to enhance the rational clinical use and monitoring of aripiprazole. Such measures will aid in preventing or reducing the occurrence of severe adverse reactions.

Objective:To develop a self-efficacy scale of milk donation and test its reliability and validity, in order to provide a scientific evaluation tool for the corresponding study.Methods:According to Bandura′s self-efficacy theory and consensus-based standards for the selection of health measurement instruments, the scale was developed by means of literature search, article pool establishment and expert letter consultation. A pre-survey was conducted on 30 newborn bereaved women, a formal investigation was conducted on 231 newborn bereaved women, and 115 newborn bereaved women were selected for exploratory factor analysis. Confirmatory factor analysis was performed on 116 parturients with neonatal loss to determine the reliability and validity of the scale.Results:The final scale includes 3 dimensions and 13 items. Three common factors were extracted by exploratory factor analysis, and the cumulative variance contribution rate was 77.962%. A scale with three dimensions, included breast milk donation resilience, breast milk donation cognition and breast milk donation motivation, and 13 items was determined. Confirmatory factor analysis showed that the model fit of the scale was good ( χ2/ df = 1.390, RMSEA = 0.063, RMR = 0.046, NFI = 0.924, NNFI = 0.971, GFI = 0.924, CFI = 0.977). The content validity index was 0.835. Cronbach′s α coefficient of the total volume table was 0.919, and the coefficients of each dimension were 0.892, 0.905 and 0.844, respectively. The broken half reliability of the scale was 0.893, and the broken half reliability of each dimension was 0.857, 0.881 and 0.711, respectively. The retest reliability of the scale was 0.814, and the retest reliability of each dimension was 0.803, 0.825 and 0.767, respectively. Conclusions:The scale has good reliability and validity, and can be used to evaluate the self-efficacy of milk donation in lost newborns.

Background: Aristolochic acid II (AAII), a major nephrotoxic and carcinogenic component of aristolochic acids (AAs), has been less studied compared with its well-characterized analog, aristolochic acid I (AAI). Although AAs are known to induce carcinogenesis via DNA adduct formation, the toxicity mechanisms, environmental prevalence, and long-term health impacts of AAII remain poorly understood. Objective: This study aimed to systematically evaluate AAII’s acute and chronic toxicity, carcinogenic mechanisms, and environmental exposure patterns using integrated murine models and phytochemical analyses to clarify its toxicological profile and associated health risks. Methods: C57BL/6J mice were used in the following experiments: (1) determination of AAII content in 3 commonly used Aristolochia medicinal materials via liquid chromatography-mass spectrometry/mass spectrometry; (2) acute toxicity testing with single doses of 10, 20, or 40 mg/kg; and (3) chronic exposure with 1 or 10 mg/kg administered every other day for 24 weeks, followed by 21 to 40 weeks of postexposure monitoring. Histopathological examination, whole-exome sequencing, biochemical assays, and micronucleus tests were performed to assess multi-organ damage, tumorigenesis, genomic mutation signatures, and direct clastogenicity. Phytochemical analyses were used to evaluate environmental distribution. Results: (1) A single 40 mg/kg dose of AAII induced dose-dependent renal tubular degeneration without hepatotoxicity; (2) the 10 mg/kg group showed significant mortality (20%), tumor incidence (33.3%, primarily forestomach and bladder transitional cell carcinomas), persistent renal interstitial fibrosis, and subclinical hepatic injury. Chronic exposure to 1 mg/kg still induced 13.3% mortality and 15.5% tumor incidence over a 64-week period; (3) whole-exome sequencing revealed a predominance of C>T mutations and pathway enrichment in chemical carcinogenesis and cytochrome P450-mediated metabolism, indicating reactive metabolite-driven mechanisms distinct from classical AA-DNA adducts; and (4) no histopathological changes were observed in nontarget organs (brain, heart, and testes), and micronucleus assays confirmed the absence of direct clastogenicity. Conclusion: This study highlights the delayed carcinogenic risks of low-dose chronic AAII exposure and emphasizes the need to update regulatory frameworks to ensure the safe use of aristolochiaceae-containing herbal products.