Chronic cerebral hypoperfusion (CCH) plays an important role in the occurrence and development of vascular dementia (VD). Recent studies have indicated that multiple stages of immune-inflammatory response are involved in the process of cerebral ischemia, drawing increasing attention to immune therapies for cerebral ischemia. This study aims to identify potential immune therapeutic targets for CCH using bioinformatics methods from an immunological perspective. We identified a total of 823 differentially expressed genes associated with CCH, and further screened for 9 core immune-related genes, namely RASGRP1, FGF12, SEMA7A, PAK6, EDN3, BPHL, FCGRT, HSPA1B and MLNR. Gene enrichment analysis showed that core genes were mainly involved in biological functions such as cell growth, neural projection extension, and mesenchymal stem cell migration. Biological signaling pathway analysis indicated that core genes were mainly involved in the regulation of T cell receptor, Ras and MAPK signaling pathways. Through LASSO regression, we identified RASGRP1 and BPHL as key immune-related core genes. Additionally, by integrating differential miRNAs and the miRwalk database, we identified miR-216b-5p as a key immune-related miRNA that regulates RASGRP1. In summary, the predicted miR-216b-5p/ RASGRP1 signaling pathway plays a significant role in immune regulation during CCH, which may provide new targets for immune therapy in CCH.
Humans ; Computational Biology/methods* ; Brain Ischemia/therapy* ; Immunotherapy ; MicroRNAs/genetics* ; Signal Transduction ; Dementia, Vascular/genetics* ; Chronic Disease

Identifying drug-drug interactions (DDIs) is essential to prevent adverse effects from polypharmacy. Although deep learning has advanced DDI identification, the gap between powerful models and their lack of clinical application and evaluation has hindered clinical benefits. Here, we developed a Multi-Dimensional Feature Fusion model named MDFF, which integrates one-dimensional simplified molecular input line entry system sequence features, two-dimensional molecular graph features, and three-dimensional geometric features to enhance drug representations for predicting DDIs. MDFF was trained and validated on two DDI datasets, evaluated across three distinct scenarios, and compared with advanced DDI prediction models using accuracy, precision, recall, area under the curve, and F1 score metrics. MDFF achieved state-of-the-art performance across all metrics. Ablation experiments showed that integrating multi-dimensional drug features yielded the best results. More importantly, we obtained adverse drug reaction reports uploaded by Xiangya Hospital of Central South University from 2021 to 2023 and used MDFF to identify potential adverse DDIs. Among 12 real-world adverse drug reaction reports, the predictions of 9 reports were supported by relevant evidence. Additionally, MDFF demonstrated the ability to explain adverse DDI mechanisms, providing insights into the mechanisms behind one specific report and highlighting its potential to assist practitioners in improving medical practice.

Humans ; Uric Acid ; Cross-Sectional Studies ; Spondylarthritis/diagnostic imaging* ; C-Reactive Protein ; Spondylitis, Ankylosing

Objective:To compare the clinical utility of 18F-prostate specific membrane antigen (PSMA)-1007 and 18F-FDG PET/CT imaging in newly diagnosed hepatocellular carcinoma (HCC). Methods:From April 2022 to July 2022, 17 patients (14 males, 3 females, age 36-73(54.4±10.1) years) with newly diagnosed HCC who underwent 18F-FDG and 18F-PSMA-1007 PET/CT imaging within 3 d in the First Affiliated Hospital of Zhengzhou University were prospectively enrolled. ROIs were drawn from normal liver tissue (L), abdominal aorta (A), right gluteus medius (M), and SUV max of these regions were compared with the SUV max of primary tumor (T). Wilcoxon rank sum test and Kruskal-Wallis rank sum test were used to analyze the data. Results:18F-FDG PT/CT, 18F-PSMA-1007 PET/CT and enhanced MRI detected 1(0, 2), 2(1, 5) and 2(1, 4) tumor lesions of the liver in each patient respectively ( H=7.10, P=0.029), and 18F-PSMA-1007 detected more lesions than 18F-FDG ( P=0.024). Although SUV max of 18F-PSMA-1007 in HCC was significantly higher than that of 18F-FDG (25.7(17.1, 45.1) vs 6.3(2.9, 12.4); z=3.39, P=0.001), there was no significant difference of T/L ratio between 18F-PSMA-1007 and 18F-FDG PET/CT imaging (2.7(2.1, 4.7) vs 1.6(1.0, 4.5); z=0.52, P=0.602). T/A and T/M ratios were significantly higher in 18F-PSMA-1007 PET/CT imaging than those in 18F-FDG PET/CT imaging ( z values: 3.15, 3.53, P values: 0.002, <0.001). 18F-PSMA-1007 PET/CT imaging found high uptake foci in the liver and ribs in 2 cases, which were pathologically confirmed as bone metastasis of HCC, while those lesions were not found by 18F-FDG imaging. Conclusion:Compared with 18F-FDG, 18F-PSMA-1007 PET/CT demonstrates higher tumor uptake, more intrahepatic tumors foci and distant bone metastases.

Objective:To find clues potentially valuable for fighting against infection with human respiratory syncytial virus (HRSV), the differentially expressed genes in HEp-2 cells infected with HRSV were analyzed.Methods:Gene expression profiles of HEp-2 cells infected with HRSV were collected from the public gene expression omnibus (GEO) database. The differentially expressed genes following HRSV infection at each time point of 4, 8, 12, and 15 hours were found using R language. The differentially expressed genes were analyzed by gene ontology (GO), KEGG pathway and protein-protein interaction network (PPI). Genes with relatively high protein interaction in PPI were randomly selected for quantitative reverse transcription-polymerase chain reaction (qRT-PCR) verification at the transcription level from HEp-2 cells after HRSV infection at 4 hours.Results:A total of 101 differentially expressed genes were determined, including 92 upregulated genes and 9 downregulated genes. Function enrichment analysis revealed that HRSV infection could cause significant changes in multiple signaling pathways such as immune response in HEp-2 cells. The results of qRT-PCR were consistent with the trend of transcriptome data.Conclusions:The differentially expressed genes and the change of signaling pathways in HRSV-infected HEp-2 cells is of great significance to the studies on pathogenic mechanism and prevention of HRSV infection.

Objective: To construct and confirm a predictive model for the risks of cardiovascular diseases (CVD) with metabolic syndrome (MS) and its factors in Xinjiang Kazakh population. Methods: A total of 2 286 Kazakh individuals were followed for 5 years from 2010 to 2012 as baseline survey. They were recruited in Xinyuan county, Yili city, Xinjiang. CVD cases were identified via medical records of the local hospitals in 2013, 2016 and 2017, respectively. Factor analysis was performed on 706 MS patients at baseline, and main factors, age, and sex were extracted from 18 medical examination indexs to construct a predictive model of CVD risk. After excluding the subjects with CVD at baseline and incomplete data, 2007 were used as internal validation, and 219 Kazakhs in Halabra Township were used as external validation. Logistic regression discriminations were used for internal validation and external validation, as well as to calculate the probability of CVD for each participant and receiver operating characteristic curves. Results: The prevalence of MS in Kazakh was 30.88%. Seven main factors were extracted from the Kazakh MS population, namely obesity factor, blood lipid and blood glucose factor, liver function factor, blood lipid factor, renal metabolic factor, blood pressure factor, and liver enzyme factor. The area under the curve (AUC) for predicting CVD in the internal validation was 0.773 (95%CI 0.754-0.792). In the external validation, the AUC for predicting CVD was 0.858 (95%CI 0.805-0.901). Conclusions The CVD risk prediction model constructed by 7 main factors extracted from Kazakh MS patients has high validation efficiency and can be used for risk assessment of CVD in Xinjiang Kazakh population.

Objective Analyze the effect of emergency thrombolytic therapy on door to needle time (DNT) in patients with acute ischemic stroke (AIS) and effect.Method Selected 182 cases of AIS patients underwent intravenous thrombolysis at the First Hospital of Qinhuangdao from May 2015 to June 2017.Thrombolytic therapy group (83 cases),for the May 2015-May 2016 after neurological consultation intravenous thrombolysis patients;Emergency thrombolytic group(99 cases),for the June 2016-June 2017 emergency thrombolysis group Emergency Department of intravenous thrombolysis patients.Compare the two groups of DNT,thrombolytic therapy 24 h symptomatic hemorrhage conversion rate,Thrombolysis 24 h,7 dNIHSS score,7 dthrombolysis and 3 months thrombolysis and thrombolysis 3 months improved Rankin score (mRs).Results There was no significant difference in baseline characteristics between the two groups (P＞0.05).Compared with the consultation group,the DNT[(69.77±11.66)min vs (80.12±15.49) min,t=5.745,P ＜ 0.01] of emergency thrombolytic group was significantly shortened,and the good score[39(39.4％) vs 21(25.3％),x2=4.272,P=0.039] at 3 months after treatment was significantly higher (P＜0.05);Treatment of 24 h intracranial hemorrhage conversion rate[12(12.12％) vs 5(6.02％),x2=1.982,P=0.159]、Treatment 7d mortality rate [10(10.10％) vs 6(7.22％),x2=0.464,P=0.496],3 months mortality rate [14(14.14％) vs 11 (13.25％),x2=0.030,P=0.862]、There was no significant difference in the 24h effective rate [57(57.6％) vs 53(63.8％),x2=0.745,P=0.388] and 7d effective rate [50(50.5％) vs 46(55.4％),x2=0.438,P0.508] after treatment (P＞0.05).Conclusions The emergency thrombolytic model can shorten the DNT of rt-PA intravenous thrombolysis in patients with AIS.The safety and efficacy of DNT are not different from the neurological consultation mode,and can improve the good prognosis rate.

Objective: To compare metabolic syndrome(MS)with Framingham risk score as predictors of cardiovascular disease(CVD)among Kazakhs population. Methods: The participants were the residents who had been followed up for more than 5 years in representative areas of Kazakhs in Xinjiang. We assigned MS a continuous risk score for predicting the development of CVD based on the weights of MS components. MS and Framingham risk score were compared in terms of their ability in predicting years in representative areas of Kazakhs in Xinjiang. We assigned MS a continuous risk score for predicting the development of CVD based on the weights of MS components. MS and Framingham risk score were compared in terms of their ability in predicting development of CVD using Cox regression and receiver operating characteristic curve. Results: The incidence of CVD was 13.87%. The incidence of CVD was higher in the MS group than it in the non-MS group(21.59% vs 11.10%, P<0.001). The area under the receiver operating characteristic(ROC)curve of MS risk score was significantly larger than that of MS classification(0.727 vs 0.585, P<0.001); the area under the curve of MS risk score was close to that of Framingham risk score(0.732 vs 0.727, P=0.673). The association between CVD and each quintile of MS risk score was more significant than that between Framingham risk score and CVD under the same exposed condition(4.61, 9.33, 14.15, 22.29 vs 3.69, 6.36, 8.47, 16.99). Conclusion MS risk score that included age may be a better predictor of CVD among Kazakhs population.

Wnt signaling has emerged as a major regulator of tissue development by governing the self-renewal and maintenance of stem cells in most tissue types. As a key upstream regulator of the Wnt pathway, the transmembrane E3 ligase ZNRF3 has recently been established to play a role in negative regulation of Wnt signaling by targeting Frizzled (FZD) receptor for ubiquitination and degradation. However, the upstream regulation of ZNRF3, in particular the turnover of ZNRF3, is still unclear. Here we report that ZNRF3 is accumulated in the presence of proteasome inhibitor treatment independent of its E3-ubiquitin ligase activity. Furthermore, the Cullin 1-specific SCF complex containing β-TRCP has been identified to directly interact with and ubiquitinate ZNRF3 thereby regulating its protein stability. Similar with the degradation of β-catenin by β-TRCP, ZNRF3 is ubiquitinated by β-TRCP in both CKI-phosphorylation- and degron-dependent manners. Thus, our findings not only identify a novel substrate for β-TRCP oncogenic regulation, but also highlight the dual regulation of Wnt signaling by β-TRCP in a context-dependent manner where β-TRCP negatively regulates Wnt signaling by targeting β-catenin, and positively regulates Wnt signaling by targeting ZNRF3.
Cells, Cultured ; Humans ; Proteolysis ; Ubiquitin-Protein Ligases ; metabolism ; Ubiquitination ; beta-Transducin Repeat-Containing Proteins ; metabolism

Objective To establish a patient-derived tumor xenograft (PDTX) model and to observe the latency and rate of tumor formation, tumor size, tumor invasion and metastasis of transplanted tumors. Methods Seven patients with chest tumor in Drum Tower Hospital from April to December 2015 were chosen. There were 5 males and 2 females with age ranging from 61-71 years, including 4 patients of esophageal tumor and 3 patients of lung tumor. PDTX model was established by surgical removal of fresh tumor tissues of these patients and transplantation in NODPrkdcem26Il2rgem26Nju subcutaneous (NCG) mice. The latency and rate of tumor formation, tumor size, tumor invasion and metastasis of transplanted tumors were observed, and pathology of HE staining and immunohistochemical testing results were compared between PDTX model and the patients. Results PDTX model was successfully established in 4 patients, and the success rate was 66.7%, including 2 patients of esophageal cancer. The PDTX model retained the differentiation, morphological and structural characteristics of original tumors. Conclusion Pathology and molecular biology characteristics of PDTX model are consistent with the original tumor, which can be an “avatar” of tumor patients for clinical pharmacodynamics screening and new drug research and development.