ObjectiveTo investigate the recurrence of ischemic stroke (IS) and to analyze the association between four indices of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) and the risk of IS recurrence by analyzing the follow-up data related to IS in the community-based natural population of Songjiang District, Shanghai, so as to provide a scientific basis for improving the prognosis of stroke patients in the community and controlling IS recurrence. MethodsA prospective follow-up study was conducted among the IS patients in the community-based cohort population, collecting data about patient’s age, gender, disease history, biochemical indicators, and etc. Cox regression model and restricted cubic spline model were used to analyze the relationship between different levels of plasma lipids and the recurrence of IS in these patients. ResultsA total of 1 368 patients with IS were included. The total follow-up duration was 7 171.46 person-years, with a median follow-up time of 6.24 years. There were 420 cases of IS recurrence, resulting in a cumulative recurrence rate of 30.70%. The results of multivariate Cox regression analysis showed that the recurrence risk of IS was reduced when the baseline TC and LDL-C levels of IS patients were in the ranges of 4.65‒5.67 mmol·L^-1 and 2.52‒3.46 mmol·L^-1, respectively. The results of restricted cubic spline analysis showed a U-shaped relationship between baseline TC and LDL-C levels and the recurrence risk in IS patients. ConclusionThe cumulative recurrence rate of patients with IS in the community of Songjiang District in Shanghai is high, and the levels of TC and LDL-C at baseline survey are correlated with the recurrence of IS in these patients. It is suggested to pay more attention to the levels of LDL-C and TC in patients with IS, so as to improve the prognosis.

Objective:To investigate the expression of long noncoding RNA (lncRNA) BMPR1B-AS1 in ovarian cancer and its impact on prognosis, so as to evaluate its value as a potential biomarker.Methods:The TCGA, GEPIA, and UALCAN databases were used to retrospectively analyze the expression differences of BMPR1B-AS1 in gynecological tumors, and prognostic analysis was performed in combination with clinical data. The expression level of BMPR1B-AS1 in ovarian cancer tissues and cell lines was verified by real-time fluorescent quantitative reverse transcription polymerase chain reaction (RT-qPCR), and univariate and multivariate Cox regression models were used to analyze its relationship with the prognosis of ovarian cancer.Results:Database analysis showed that the expression of BMPR1B-AS1 in ovarian cancer and endometrial cancer was higher than that in the non-tumor group (all P<0.05), and high expression of BMPR1B-AS1 in ovarian cancer was associated with better prognosis ( P<0.05). Experimental verification showed that the expression of BMPR1B-AS1 in ovarian cancer tissues was significantly higher than that in benign ovarian tissues, and the expression of BMPR1B-AS1 in ovarian cancer cell lines was higher than that in normal human ovarian epithelial cells ( P<0.05). Cox regression analysis indicated that high expression of BMPR1B-AS1 was an independent protective factor for the prognosis of ovarian cancer ( P<0.05). Conclusions:The expression of BMPR1B-AS1 in ovarian cancer and endometrial cancer is higher than that in non-tumor groups, and it is an independent protective factor for good prognosis in ovarian cancer patients. It may serve as a new biomarker, providing new ideas for the diagnosis and treatment of ovarian cancer.

Objective:To investigate the expression of long noncoding RNA (lncRNA) BMPR1B-AS1 in ovarian cancer and its impact on prognosis, so as to evaluate its value as a potential biomarker.Methods:The TCGA, GEPIA, and UALCAN databases were used to retrospectively analyze the expression differences of BMPR1B-AS1 in gynecological tumors, and prognostic analysis was performed in combination with clinical data. The expression level of BMPR1B-AS1 in ovarian cancer tissues and cell lines was verified by real-time fluorescent quantitative reverse transcription polymerase chain reaction (RT-qPCR), and univariate and multivariate Cox regression models were used to analyze its relationship with the prognosis of ovarian cancer.Results:Database analysis showed that the expression of BMPR1B-AS1 in ovarian cancer and endometrial cancer was higher than that in the non-tumor group (all P<0.05), and high expression of BMPR1B-AS1 in ovarian cancer was associated with better prognosis ( P<0.05). Experimental verification showed that the expression of BMPR1B-AS1 in ovarian cancer tissues was significantly higher than that in benign ovarian tissues, and the expression of BMPR1B-AS1 in ovarian cancer cell lines was higher than that in normal human ovarian epithelial cells ( P<0.05). Cox regression analysis indicated that high expression of BMPR1B-AS1 was an independent protective factor for the prognosis of ovarian cancer ( P<0.05). Conclusions:The expression of BMPR1B-AS1 in ovarian cancer and endometrial cancer is higher than that in non-tumor groups, and it is an independent protective factor for good prognosis in ovarian cancer patients. It may serve as a new biomarker, providing new ideas for the diagnosis and treatment of ovarian cancer.

ObjectiveTo analyze the incidence， recovery rate and associated factors of nonalcoholic fatty liver disease （NAFLD） among residents aged 65 years old and above in Xinqiao Community of Songjiang， Shanghai， and to provide basic data for further efficient community management. MethodsData of annual geriatric physical examination program for residents aged 65 and above were collected in Xinqiao Community， Songjiang from 2016 to 2022. Those residents who participated twice or more were included in this analysis. Data were collated into longitudinal form. For each participant， data of the first physical examination was used as baseline， and each subsequent examination was taken as follow-up. Incidence and recovery rate of NAFLD were calculated. Cox proportional hazard models were used to explore the associated factors and their changes with the onset and recovery of NAFLD. ResultsDuring the study period， a total of 11 983 residents participated in physical examinations， of which 8 644 participated twice or more， and 8 154 had no history of excessive alcohol consumption. B-ultrasound showed that there were 5 267 residents without NAFLD and 2 887 with NAFLD at baseline. After a median follow-up of 3.3 years， the incidence density of NAFLD in this population was estimated to be 11.5 per 100 person-years， and the recovery density was 23.4 per 100 person-years. The incidence density of NAFLD was negatively associated with age， and positively associated with baseline BMI， abdominal obesity， high fasting blood glucose， and high triglycerides. The recovery density was negatively associated with baseline BMI and abdominal obesity. Compared with those with normal BMI at both baseline and follow-up， those with persistent obesity showed the highest risk of NAFLD （males： HR： 3.19， 95%CI： 2.16-4.70； females： HR： 3.34， 95%CI： 2.46-4.54） and the lowest potential of recovery （males： HR： 0.58， 95%CI： 0.42-0.82； females： HR： 0.58， 95%CI： 0.44-0.77）. Persistently high triglycerides were also associated with a higher risk of developing the disease. ConclusionResidents aged 65 years old and above in Xinqiao， Shanghai had a higher incidence and recovery rate of NAFLD. Women， being obese and having hyperlipidemia are at a higher risk for the development and persistence of NAFLD.

Objective:To investigate the expression of retinoic acid receptor responsive gene 2 (RARRES2), microtubule microfilament cross-linking factor 1 (MACF1), and core protein polysaccharide (DCN) in cerebrospinal fluid (CSF) of patients with neurosyphilis, and their diagnostic value for neurosyphilis.Methods:A total of 64 non neurosyphilis syphilis patients (syphilis group) and 78 neurosyphilis patients (neurosyphilis group) admitted to the Second Hospital of Nanjing between June 2020 and September 2022 were included. Among neurosyphilis patients, there were 48 early neurosyphilis patients (early group) and 30 late neurosyphilis patients (late group). Patients with neurosyphilis are treated with routine symptomatic therapy and antibiotic therapy to expel syphilis. The mRNA levels of RARRES2, MACF1, and DCN in CSF of patients with neurosyphilis before and after treatment were detected by quantitative real-time polymerase chain reaction (qRT-PCR). The National Institutes of Health Stroke Scale (NIHSS) was used to evaluate the neurological function of patients with neurosyphilis before and after treatment. The diagnostic value of various indicators for neurosyphilis was analyzed using receiver operating characteristic (ROC) curves.Results:The mRNA levels of RARRES2, MACF1, and DCN in CSF of patients with neurosyphilis were higher than those in the syphilis group (all P<0.001). The mRNA levels of RARRES2, MACF1, and DCN in the CSF of patients with advanced neurosyphilis were higher than those in the early group (all P<0.001). Compared with before treatment, the NIHSS score and RARRES2, MACF1, and DCN mRNA levels of neurosyphilis patients decreased after treatment (all P<0.001). The area under the curve (AUC), sensitivity, and specificity of the combined diagnosis of RARRES2, MACF1, and DCN mRNA in CSF for neurosyphilis were 0.995%, 100.00%, and 93.75%, respectively. The AUC and sensitivity were higher than those of individual diagnosis. Conclusions:The expression of RARRES2, MACF1, and DCN is elevated in CSF of patients with neurosyphilis, and is associated with disease severity and treatment response. These three genes may be candidate biomarkers for diagnosing neurosyphilis.

OBJECTIVE To investigate the effects of aucubin （Auc） on the malignant biological behavior of breast cancer cells by regulating cyclin-dependent kinase 1（CDK1）/cyclin B1（CCNB1）/Polo-like kinase 1 （PLK1） signaling pathway. METHODS Human breast cancer cells MCF-7 were divided into control group， Auc low-， medium- and high-concentration groups （AUC-L， AUC-M， AUC-H groups， 20， 40 and 80 μmol/L Auc）， Auc-H+pcDNA-NC group （80 μmol/L Auc+transfected pcDNA- NC plasmid）， and Auc-H+pcDNA-CDK1 group （80 μmol/L Auc+transfected pcDNA-CDK1 plasmid）. Cell proliferation， clonal formation， invasion and migration abilities， apoptosis and cycle distribution， and the expressions of related proteins of apoptosis， epithelial-mesenchymal transformation （EMT） and CDK1/CCNB1/PLK1 signaling pathway were detected in each group. The transplanted tumor model of BALB/c nude mice was established by subcutaneous inoculation of MCF-7 cell suspension， and the mice were divided into control group and Auc group （12 mice in each group）. The tumor volume， mass and the expressions of related proteins of CDK1/CCNB1/PLK1 signaling pathway in tumor tissues were detected. RESULTS Compared with control group， the number of clonal formation， proliferation rate， cell invasion number， scar healing rate， G1/G0 phase and S phase cell proportions， and the expressions of B cell lymphoma-2 （Bcl-2）， N-cadherin， fibronectin， CDK1， CCNB1 and PLK1 were decreased significantly （P＜0.05）. The apoptotic rate， G2/M phase cell proportion and the expressions of Bcl-2 associated X protein and E-cadherin were significantly increased， in a dose-dependent manner （P＜0.05）. Compared with the Auc-H+pcDNA-NC group， there was no statistical significance in the above indexes in the Auc-H group （P＞0.05）， while the above indexes in the Auc-H+ pcDNA-CDK1 group were significantly reversed （P＜0.05）. Compared with the control group， the tumor volume and mass， and the expressions of CDK1， CCNB1 and PLK1 in tumor tissue of Auc group were significantly decreased （P＜0.05）. CONCLUSIONS Auc can inhibit the proliferation， invasion and migration of breast cancer cells， induce cell cycle arrest， and inhibit the progression of EMT， which may be related to inhibiting the activation of the CDK1/CCNB1/PLK1 signaling pathway.

Objective To explore the mechanism of dendrobine in the treatment of diabetic kidney disease(DKD)by intervening immunity using network pharmacology,bioinformatics and Western blot.Methods The targets of dendrobine were screened by Pharmmaper,Superpred and other databases.The disease targets of DKD were screened from GeneCards,OMIM and other databases.The immune-related targets were searched in Immport,In-nateDB and other databases.The intersection of the above three was obtained via Venn diagram.The PPI map of intersection targets was constructed by STRING software combined with Cytoscape software,and the core targets in the interaction network were mined by CytoHubba plug-in.The data set GSE142025 was obtained from GEO,and immune infiltration and WGCNA analysis were performed using the R language CIBERSORT package.GSE1009,GSE30122 and GSE142025 were used for gene differential expression analysis and ROC verification.The correla-tion between core targets and immune cell phenotype was analyzed.Molecular docking and molecular dynamics sim-ulation analysis were used to test the binding force of dendrobine to key targets.Western blot was used to detect the expression of HSP90AA1 in HK-2 cells.Results A total of 128 intersecting genes,including HSP90AA1,LCK and EGFR,were obtained,and the core targets involved HSP90AA1,LCK and STAT3;molecular docking and molecular dynamics simulation analyses showed that the protein of HSP90AA1 could bind well with dendrobine.Western blot experiments showed that compared with the control group,HSP90AA1 was significantly down-regula-ted in the high glucose group.Compared with the high glucose group,HSP90AA1 was significantly up-regulated in the dendrobine group.Conclusion Dendrobine can intervene in diabetic kidney disease by regulating the expres-sion of HSP90AA1.

Liquid chromatography-electrospray ionization tandem mass spectrometry(LC-ESI-MS)is a widely utilized technique for in vivo pharmaceutical analysis.Ionization interference within electrospray ion source,occurring between drugs and metabolites,can lead to signal variations,potentially compromising quantitative accuracy.Currently,method validation often overlooks this type of signal interference,which may result in systematic errors in quantitative results without matrix-matched calibration.In this study,we conducted an investigation using ten different groups of drugs and their corresponding me-tabolites across three LC-ESI-MS systems to assess the prevalence of signal interference.Such in-terferences can potentially cause or enhance nonlinearity in the calibration curves of drugs and metabolites,thereby altering the relationship between analyte response and concentration for quanti-fication.Finally,we established an evaluation scheme through a step-by-step dilution assay and employed three resolution methods:chromatographic separation,dilution,and stable labeled isotope internal standards correction.The above strategies were integrated into the method establishment process to improve quantitative accuracy.

Humans ; Asthma/drug therapy* ; Biological Therapy

Objective:To explore the classification performance of combined model constructed from CT signs combined with radiomics for discriminating COVID-19 pneumonia and other viral pneumonia.Methods:The clinical and CT imaging data of 181 patients with viral pneumonia confirmed by reverse transcription-polymerase chain reaction in 15 hospitals of Yunnan Province from March 2015 to March 2020 were analyzed retrospectively. The 181 patients were divided into COVID-19 group (89 cases) and non-COVID-19 group (92 cases), which were further divided into training cohort (126 cases) and test cohort (55 cases) at a ratio of 7∶3 using random stratified sampling. The CT signs of pneumonia were determined and the radiomics features were extracted from the initial unenhanced chest CT images to build independent and combined models for predicting COVID-19 pneumonia. The diagnostic performance of the models were evaluated using receiver operating characteristic (ROC) analysis, continuous net reclassification index (NRI) calibration curve and decision curve analysis.Results:The combined models consisted of 3 significant CT signs and 14 selected radiomics features. For the radiomics model alone, the area under the ROC curve (AUC) were 0.904 (sensitivity was 85.5%, specificity was 84.4%, accuracy was 84.9%) in the training cohort and 0.866 (sensitivity was 77.8%, specificity was 78.6%, accuracy 78.2%) in the test cohort. After combining CT signs and radiomics features, AUC of the combined model for the training cohort was 0.956 (sensitivity was 91.9%, specificity was 85.9%, accuracy was 88.9%), while that for the test cohort was 0.943 (sensitivity was 88.9%, specificity was 85.7%, accuracy was 87.3%). The AUC values of the combined model and the radiomics model in the differentiation of COVID-19 group and the non-COVID-19 group were significantly different in the training cohort ( Z=-2.43, P=0.015), but difference had no statistical significance in the test cohort ( Z=-1.73, P=0.083), and further analysis using the NRI showed that the combined model in both the training cohort and the test cohort had a positive improvement ability compared with radiomics model alone (training cohort: continuous NRI 1.077, 95 %CI 0.783-1.370; test cohort: continuous NRI 1.421, 95 %CI 1.051-1.790). The calibration curve showed that the prediction probability of COVID-19 predicted by the combined model was in good agreement with the observed value in the training and test cohorts; the decision curve showed that a net benefit greater than 0.6 could be obtained when the threshold probability of the combined model was 0-0.75. Conclusion:The combination of CT signs and radiomics might be a potential method for distinguishing COVID-19 and other viral pneumonia with good performance.