Background: and Purpose Vertebrobasilar fusiform aneurysms (VBFAs) carry substantial morbidity and mortality, but optimal management for unruptured VBFAs remains unclear. We compared the safety and efficacy of conservative management (CM), stent-assisted coiling (SAC), and flow diverters (FDs) in patients with unruptured VBFAs, focusing on long-term prognosis. Methods: This study included data from a nationwide Chinese cohort of patients with vertebrobasilar dissecting aneurysms. Inverse probability of treatment weighting (IPTW) balanced confounders across groups. The primary outcome was poor prognosis (modified Rankin Scale score >2). Secondary outcomes included aneurysm rupture, ischemic stroke, compression symptoms, and VBFA-related deaths. Logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup and sensitivity analyses were performed. Results: Among 1,115 patients with unruptured VBFAs, 838 (median age, 54 years; 655 men) were included. After IPTW, baseline characteristics were balanced. Median follow-up was 54 months. FD was associated with a lower risk of poor prognosis than CM (OR, 0.48 [95% CI, 0.30 to 0.77]; p=0.002), with no difference between CM and SAC. FD also reduced aneurysm rupture (OR, 0.20 [95% CI, 0.07 to 0.60]; p=0.004) and compression symptoms (OR, 0.30 [95% CI, 0.13 to 0.68]; p=0.004) versus CM. Time-to-event analyses further revealed significant differences in vertebral artery lesions and Type I–II VBFAs, whereas no significant differences were observed in basilar or vertebrobasilar junction lesions or in Type III–IV VBFAs. Conclusions Compared with CM, FD was associated with improved long-term outcomes in unruptured VBFAs, particularly in vertebral artery lesions and Type I–II VBFAs, although residual confounding cannot be excluded.

OBJECTIVE To explore the influencing factors of Shenfukang capsule in the treatment of chronic kidney disease （CKD） and construct a nomogram prediction model for evaluating its therapeutic efficacy. METHODS CKD patients who were hospitalized from July 2019 to August 2022 in the First Affiliated Hospital of Guangxi Medical University and treated with Shenfukang capsule were selected as study subjects. Clinical data of the patients were collected from the hospital’s electronic medical record system， and they were divided into an effective group and an ineffective group based on treatment outcomes. Lasso-Logistic multivariate regression analysis was used to screen the influencing factors of the efficacy of Shenfukang capsule. Using the effectiveness of Shenfukang capsule treatment as the prediction outcome and the screened influencing factors as predictor variables， a nomogram prediction model was constructed using R software. All patients were randomly divided into a training cohort and a validation cohort. The discriminative ability， calibration， and clinical net benefit of the model were evaluated using the receiver operating characteristic （ROC） curve， calibration curve， and decision curve analysis， respectively. RESULTS Lasso-Logistic regression analysis revealed that concurrent diabetes mellitus， decreased levels of blood urea nitrogen， triglycerides， and serum phosphorus， as well as prolonged prothrombin time and elevated apolipoprotein AⅠ levels， were influencing factors for reduced efficacy of Shenfukang capsule in CKD treatment. The evaluation results of the nomogram prediction model showed that the area under curve values were 0.745 and 0.797 in the training and validation cohorts， respectively， which were close and both exceeded 0.70， indicating stable predictive performance. The calibration curves demonstrated good agreement in both datasets， suggesting satisfactory calibration performance. The clinical decision curves were positioned above the two extreme reference lines， indicating high clinical benefit of the model. CONCLUSIONS Diabetes mellitus， blood urea nitrogen， triglycerides， apolipoprotein AⅠ， serum phosphorus， and prothrombin time were factors associated with the efficacy of Shenfukang capsule in CKD patients. The nomogram prediction model established in this study may provide a basis for rational clinical application of Shenfukang capsule and for improving its therapeutic efficacy in CKD.

OBJECTIVE To explore the influencing factors of Shenfukang capsule in the treatment of chronic kidney disease （CKD） and construct a nomogram prediction model for evaluating its therapeutic efficacy. METHODS CKD patients who were hospitalized from July 2019 to August 2022 in the First Affiliated Hospital of Guangxi Medical University and treated with Shenfukang capsule were selected as study subjects. Clinical data of the patients were collected from the hospital’s electronic medical record system， and they were divided into an effective group and an ineffective group based on treatment outcomes. Lasso-Logistic multivariate regression analysis was used to screen the influencing factors of the efficacy of Shenfukang capsule. Using the effectiveness of Shenfukang capsule treatment as the prediction outcome and the screened influencing factors as predictor variables， a nomogram prediction model was constructed using R software. All patients were randomly divided into a training cohort and a validation cohort. The discriminative ability， calibration， and clinical net benefit of the model were evaluated using the receiver operating characteristic （ROC） curve， calibration curve， and decision curve analysis， respectively. RESULTS Lasso-Logistic regression analysis revealed that concurrent diabetes mellitus， decreased levels of blood urea nitrogen， triglycerides， and serum phosphorus， as well as prolonged prothrombin time and elevated apolipoprotein AⅠ levels， were influencing factors for reduced efficacy of Shenfukang capsule in CKD treatment. The evaluation results of the nomogram prediction model showed that the area under curve values were 0.745 and 0.797 in the training and validation cohorts， respectively， which were close and both exceeded 0.70， indicating stable predictive performance. The calibration curves demonstrated good agreement in both datasets， suggesting satisfactory calibration performance. The clinical decision curves were positioned above the two extreme reference lines， indicating high clinical benefit of the model. CONCLUSIONS Diabetes mellitus， blood urea nitrogen， triglycerides， apolipoprotein AⅠ， serum phosphorus， and prothrombin time were factors associated with the efficacy of Shenfukang capsule in CKD patients. The nomogram prediction model established in this study may provide a basis for rational clinical application of Shenfukang capsule and for improving its therapeutic efficacy in CKD.

Central retinal vein occlusion(CRVO)is a retinal vascular disorder that significantly impairs vision, with its underlying mechanisms involving complex interactions across multiple biological systems. This article provides a systematic review of the pathological mechanisms associated with CRVO, emphasizing critical factors such as endothelial dysfunction, arteriosclerosis, thrombophilia, inflammation, and oxidative stress. The pathological mechanisms of CRVO are characterized by arteriosclerosis, which obstructs venous return through a dual mechanism involving mechanical compression and endothelin-1-mediated contraction; endothelial dysfunction, which exacerbates disturbances in blood flow; genetic and acquired coagulation abnormalities that disrupt hemostatic balance and promote thrombosis; and the synergistic effects of inflammation and oxidative stress that activate cytokines, thereby aggravating ischemia and vascular leakage. Innovatively, this review explores emerging mechanisms such as miRNA-mediated vascular regulation via exosomes, gut microbiota-retina crosstalk through the “gut-eye axis,” and systemic metabolic interactions that link local retinal lesions to broader dysregulation of CRVO. These insights underscore the importance of integrated eye-system interventions and provide a theoretical foundation for advancing early biomarker discovery, multitarget therapeutics, and personalized treatment paradigms. By bridging localized pathology and systemic mechanisms, this work promotes a transformative shift toward an integrative medicine model in the diagnosis and management of CRVO.

Central nervous system（CNS） disorders are characterized by complex pathological mechanisms and the presence of the blood-brain barrier（BBB）， which significantly limits the effectiveness of drug therapy. Traditional drug delivery modes include oral administration， intravenous injection and transdermal delivery， which have certain advantages， but it is difficult for the drugs to effectively cross the BBB. Therefore， it is crucial to find drug delivery modes that can efficiently traverse the BBB. Nasal drug delivery， as a non-invasive method， can realize the targeted delivery of drugs to the CNS via three pathways， including olfactory neurons， trigeminal neurons and blood circulation， and shows a broad application prospect in the treatment of CNS diseases. Numerous studies have further confirmed that nasal drug delivery combined with novel drug delivery systems such as lipid nanocarriers， nanoparticles， nanoemulsions and composite in situ gels can effectively load the active components of traditional Chinese medicine（TCM）， and significantly increase drug concentration in the brain， which provides new strategies for the treatment of CNS diseases. In this paper， the current status of drug delivery for CNS diseases was systematically sorted out， the characteristics of nasal drug delivery were discussed in depth， and the research progress of passive targeting， active targeting， and "guiding the meridian" drug delivery strategies for the nasal-to-brain transport of TCM active components was summarized and analyzed， which was aimed to provide references and insights for the development of drugs for CNS diseases and the application of TCM in nasal-to-brain delivery.

Central nervous system（CNS） disorders are characterized by complex pathological mechanisms and the presence of the blood-brain barrier（BBB）， which significantly limits the effectiveness of drug therapy. Traditional drug delivery modes include oral administration， intravenous injection and transdermal delivery， which have certain advantages， but it is difficult for the drugs to effectively cross the BBB. Therefore， it is crucial to find drug delivery modes that can efficiently traverse the BBB. Nasal drug delivery， as a non-invasive method， can realize the targeted delivery of drugs to the CNS via three pathways， including olfactory neurons， trigeminal neurons and blood circulation， and shows a broad application prospect in the treatment of CNS diseases. Numerous studies have further confirmed that nasal drug delivery combined with novel drug delivery systems such as lipid nanocarriers， nanoparticles， nanoemulsions and composite in situ gels can effectively load the active components of traditional Chinese medicine（TCM）， and significantly increase drug concentration in the brain， which provides new strategies for the treatment of CNS diseases. In this paper， the current status of drug delivery for CNS diseases was systematically sorted out， the characteristics of nasal drug delivery were discussed in depth， and the research progress of passive targeting， active targeting， and "guiding the meridian" drug delivery strategies for the nasal-to-brain transport of TCM active components was summarized and analyzed， which was aimed to provide references and insights for the development of drugs for CNS diseases and the application of TCM in nasal-to-brain delivery.

ObjectiveTo investigate the current status of latent tuberculosis infection (LTBI) among the elderly population in rural areas of Changxing County, Zhejiang Province, and to provide an evidence for the development of LTBI prevention and control measures. MethodsBetween January and May 2024, elderly individuals participating in urban and rural residents’ health checkups were screened for Mycobacterium tuberculosis infection using a domestically produced interferon-γ release assay (IGRA) kit. Individuals tested positive by IGRA but without active tuberculosis were classified as LTBI cases. The prevalence of LTBI among the participants was subsequently analyzed. ResultsAmong the 6 765 subjects, 637 tested positive by IGRA, including one identified active tuberculosis patient, resulting in a LTBI prevalence rate of 9.40%. There was a statistically significant difference in positivity rates across different IGRA methodologies (χ²=35.530, P<0.001). Higher LTBI rate was observed in males, individuals with a history of diabetes mellitus, and those with a history of pulmonary tuberculosis, exhibiting statistically significant differences (χ²=32.401, P<0.001; χ²=5.789, P=0.020; χ²=39.248, P<0.001, respectively.) No statistically significant difference in LTBI rate was found across different age groups (χ²=0.238, P=0.971). ConclusionThe prevalence of LTBI among the elderly rural residents in Changxing County is relatively low. Male, individuals with a history of diabetes mellitus, and those with a history of pulmonary tuberculosis have an increased risk of LTBI, warranting targeted risk monitoring and timely interventions.

Objective:To explore predictive value of quantitative evaluation of shear wave ultrasonic elastography(SWUE)on the hardness of soleus muscle for short-term progress of the distal deep venous thrombosis(DVT)of lower extremities.Methods:A total of 100 DVT patients who admitted to the second hospital of Zhangjiakou from January 2021 to December 2023 were retrospectively selected,and they were divided into group with progress(n=45)and group without progress(n=55)according to the results of the ultrasonic reexamination of blood vessels of lower extremities at the 2nd week after they were confirmed.Univariate and multivariate logistics regression analysis were used to analyze the influencing factors for short-term progress of DVT patients.Receiver operating characteristic(ROC)curve was drawn to analyze the applied value of SWUE quantitative assessment for the hardness of soleus muscle in predicting the short-term progress of DVT patients.The coagulation indicators of the two groups before and after treatment were further compared.Results:There were no significant differences between the two groups in cholesterol,neutrophil count,platelet count,central venous catheterization,bed rest,history of thrombosis,injury of vascular wall,and history of surgery for lower limb(P>0.05).The average hardness values of soleus muscle of group with progress and group without progress were respectively(6.46±1.15)kPa and(5.42±1.13)kPa,and the difference of that between two groups was significant(t=4.542,P<0.05).Multivariate logistics regression analysis showed that hardness of soleus muscle was the independent risk factor for short-term progress of DVT patients(OR=3.135,P<0.05).The results of ROC analysis showed that the area under curve(AUC)value of the hardness of soleus muscle in predicting short-term progress of DVT patients was 0.9074(95%CI:0.8175～0.9972),and the best cutoff value was 0.70,and the sensitivity and the specificity were respectively 78.26%and 91.30%at this time.Before treatment,there were no significant differences in the comparison of prothrombin time(PT),activated partial thromboplastin time(APTT),thrombin time(TT)and D-dimer(D-dimer)between the two groups of patients(P>0.05).After treatment,the PT,APTT and TT levels of patients in the group without progress were respectively higher than those in the group with progress,and the D-dimer level was lower than that in the group with progress,there was a statistically significant difference between the two groups(t=3.568,15.176,4.091,9.981,P<0.05),respectively.Conclusion:SWUE quantitative evaluation for the hardness of soleus muscle has a favorable predictive value for the short-term progress of distal DVT of lower extremities,which is contribute to early find the DVT short-term progress,thus can timely adopt intervention measure,and reduce the risk of complication,and improve the prognosis.

ObjectiveTo investigate the prevalence of gynecological and breast diseases among retired or economically disadvantaged women in part of Pudong New Area of Shanghai under the policy support of screening gynecological diseases and breast diseases for retired and women with economic difficulties in life in Shanghai, to analyze the characteristics of these diseases, so as to provide a scientific basis for the improvement of relevant prevention and treatment strategies. MethodsBased on the gynecological census data of 13 031 cases in five towns, including Xinchang Town, Xuanqiao Town, Laogang Town, Wanxiang Town and Shuyuan Town, conducted by Shanghai Pudong Hospital in 2023, descriptive analysis methods were used to explore the prevalence and age characteristics of common gynecological and breast diseases. ResultsThe total detection rate of gynecological and breast diseases among women in the screening area in this study was 68.29%, with uterine fibroid (22.35%), sarcoidosis of the breast (17.06%), cervicitis (15.37%), vaginitis (8.39%) and ovarian cyst (2.61%) ranking the top 5 in the detection rate among the screening population. The differences of the detection rates in the four major diseases [uterine fibroid (χ²=233.217, P<0.001), breast nodules(χ²=169.896, P<0.001), cervicitis (χ²=388.683, P<0.001), and ovarian cysts (χ²=72.298, P<0.001)] by different age groups were statistically significant (P<0.05) . Moreover, the results of pairwise comparison of different age groups showed that the detection rates in the age group under 45 years old and 45‒55 years old were higher than that in the age group of 55‒65 years old and over 65 years old. ConclusionThe detection rate of gynecological and breast diseases in the younger age group was higher, indicating a certain trend of younger onset of diseases. Uterine fibroid, sarcoidosis of the breast , and reproductive tract diseases such as cervicitis, vaginitis, and ovarian cyst are the main diseases affecting the research subjects. Therefore, medical institutions can combine routine work in screening diseases and carry out corresponding health education and health promotion activities for these key diseases to improve women’s health.

BACKGROUND:Fibromyalgia syndrome,as a common rheumatic disease,is related to central sensitization and immune abnormalities.However,the specific mechanism has not been elucidated,and there is a lack of specific diagnostic markers.Exploring the possible pathogenesis of this disease has important clinical significance. OBJECTIVE:To screen the potential diagnostic marker genes of fibromyalgia syndrome and analyze the possible immune infiltration characteristics based on bioinformatics methods,such as weighted gene co-expression network analysis(WGCNA),and machine learning. METHODS:Gene expression profiles in peripheral serum of fibromyalgia syndrome patients and healthy controls were obtained from the gene expression omnibus(GEO)database.The differentially co-expressed genes were screened in the expression profile by differential analysis and WGCNA analysis.Least absolute shrinkage and selection operator(LASSO)and support vector machine-recursive feature elimination(SVM-RFE)machine learning algorithm were further used to identify hub biomarkers,and draw receiver operating characteristic curve(ROC)to evaluate the accuracy of diagnosing fibromyalgia syndrome.Finally,single sample gene set enrichment analysis(ssGSEA)and gene set enrichment analysis(GSEA)were used to evaluate the immune cell infiltration and pathway enrichment in patients with fibromyalgia syndrome. RESULTS AND CONCLUSION:Eight down-regulated differentially expressed genes(DEGs)were obtained after differential analysis of the GSE67311 dataset according to the conditions of log2|(FC)|>0 and P<0.05.After WGCNA analysis,497 genes were included in the module(MEdarkviolet)with the highest positive correlation(r=0.22,P=0.04),and 19 genes were included in the module(MEsalmon2)with the highest negative correlation(r=-0.41,P=6×10-5).After intersecting DEGs and the module genes of WGCNA,seven genes were obtained.Four genes were screened out by LASSO regression algorithm and five genes were screened out by SVM-RFE machine learning algorithm.After the intersection of the two,three core genes were identified,which were germinal center associated signaling and motility like,integrin beta-8,and carboxypeptidase A3.The areas under the ROC curve of the three core genes were 0.744,0.739,and 0.734,respectively,indicating that they have good diagnostic value and can be used as biomarkers for fibromyalgia syndrome.The results of immune infiltration analysis showed that memory B cells,CD56 bright NK cells,and mast cells were significantly down-regulated in patients with fibromyalgia syndrome compared with the control group(P<0.05),and were significantly positively correlated with the above three biomarkers(P<0.05).The enrichment analysis suggested that there were nine fibromyalgia syndrome enrichment pathways,mainly related to olfactory transduction pathway,neuroactive ligand-receptor interaction,and infection pathway.The above results showed that the occurrence and development of fibromyalgia syndrome are related to the involvement of multiple genes,abnormal immune regulation,and multiple pathways imbalance.However,the interactions between these genes and immune cells,as well as their relationships with various pathways need to be further investigated.