An interpretable machine learning model for stroke recurrence in patients with symptomatic intracranial atherosclerotic arterial stenosis.

Background and objective: Symptomatic intracranial atherosclerotic stenosis (SICAS) is the most common etiology of ischemic stroke and one of the main causes of high stroke recurrence. The recurrence of stroke is closely related to the prognosis of ischemic stroke. This study aims to develop a machine learning model based on high-resolution vessel wall imaging (HR-VWI) to predict the risk of stroke recurrence in SICAS. Methods: This study retrospectively collected data from 180 SICAS stroke patients treated at the hospital between 2020.01 and 2022.01. Relevant imaging and clinical data were collected, and follow-up was conducted. The dataset was divided into a training set and a validation set in a ratio of 7:3. We employed the least absolute shrinkage and selection operator (LASSO) regression to perform a selection on the baseline data, laboratory tests, and neuroimaging data generated by HR-VWI scans collected from the training set. Finally, five machine learning techniques, including logistic regression model (LR), support vector machine (SVM), Gaussian naive Bayes (GNB), Complement naive Bayes (CNB), and k-nearest neighbors algorithm (kNN), were employed to develop a predictive model for stroke recurrence. Shapley Additive Explanation (SHAP) was used to provide visualization and interpretation for each patient. The model's effectiveness was evaluated using average accuracy, sensitivity, specificity, precision, f1 score, PR curve, calibration curve, and decision curve analysis. Results: LASSO analysis revealed that "history of hypertension," "homocysteine level," "NWI value," "stenosis rate," "intracranial hemorrhage," "positive remodeling," and "enhancement grade" were independent risk factors for stroke recurrence in SICAS patients. In 10-fold cross-validation, the area under the curve (AUC) ranged from 0.813 to 0.912 in ROC curve analysis. The area under the precision-recall curve (AUPRC) ranged from 0.655 to 0.833, with the Gaussian Naive Bayes (GNB) model exhibiting the best ability to predict stroke recurrence in SICAS. SHAP analysis provided interpretability for the machine learning model and revealed essential factors related to the risk of stroke recurrence in SICAS. Conclusion: A precise machine learning-based prediction model for stroke recurrence in SICAS has been established to assist clinical practitioners in making clinical decisions and implementing personalized treatment measures.

An integrative analysis of single-cell and bulk transcriptome and bidirectional mendelian randomization analysis identified C1Q as a novel stimulated risk gene for Atherosclerosis.

Background: The role of complement component 1q (C1Q) related genes on human atherosclerotic plaques (HAP) is less known. Our aim is to establish C1Q associated hub genes using single-cell RNA sequencing (scRNA-seq) and bulk RNA analysis to diagnose and predict HAP patients more effectively and investigate the association between C1Q and HAP (ischemic stroke) using bidirectional Mendelian randomization (MR) analysis. Methods: HAP scRNA-seq and bulk-RNA data were download from the Gene Expression Omnibus (GEO) database. The C1Q-related hub genes was screened using the GBM, LASSO and XGBoost algorithms. We built machine learning models to diagnose and distinguish between types of atherosclerosis using generalized linear models and receiver operating characteristics (ROC) analyses. Further, we scored the HALLMARK_COMPLEMENT signaling pathway using ssGSEA and confirmed hub gene expression through qRT-PCR in RAW264.7 macrophages and apoE-/- mice. Furthermore, the risk association between C1Q and HAP was assessed through bidirectional MR analysis, with C1Q as exposure and ischemic stroke (IS, large artery atherosclerosis) as outcomes. Inverse variance weighting (IVW) was used as the main method. Results: We utilized scRNA-seq dataset (GSE159677) to identify 24 cell clusters and 12 cell types, and revealed seven C1Q associated DEGs in both the scRNA-seq and GEO datasets. We then used GBM, LASSO and XGBoost to select C1QA and C1QC from the seven DEGs. Our findings indicated that both training and validation cohorts had satisfactory diagnostic accuracy for identifying patients with HPAs. Additionally, we confirmed SPI1 as a potential TF responsible for regulating the two hub genes in HAP. Our analysis further revealed that the HALLMARK_COMPLEMENT signaling pathway was correlated and activated with C1QA and C1QC. We confirmed high expression levels of C1QA, C1QC and SPI1 in ox-LDL-treated RAW264.7 macrophages and apoE-/- mice using qPCR. The results of MR indicated that there was a positive association between the genetic risk of C1Q and IS, as evidenced by an odds ratio (OR) of 1.118 (95%CI: 1.013-1.234, P = 0.027). Conclusion: The authors have effectively developed and validated a novel diagnostic signature comprising two genes for HAP, while MR analysis has provided evidence supporting a favorable association of C1Q on IS.

Intermediate analysis of magnesium alloy covered stent for a lateral aneurysm model in the rabbit common carotid artery.

OBJECTIVE: To analyze the outcomes of a magnesium alloy covered stent (MACS) for a lateral aneurysm model in common carotid artery (CCA). METHODS: In 32 rabbits, a MACS (group A, n = 17) or a Willis covered stent (WCS; group B, n = 15) was inserted and the rabbits were sacrificed 1, 3, 6, or 12 months after stenting. Angiography and intravascular ultrasound (IVUS) were performed at 3, 6, and 12 months. Scanning electron microscopy was performed for six stents in each group at 1, 3, and 6 months, and histopathology and histomorphology were conducted at 3 (n = 4), 6 (n = 4), and 12 (n = 12) months. RESULTS: Final angiography showed complete occlusion of the aneurysms in 12 cases. IVUS at 6 and 12 months revealed a significant increase in mean lumen area of the stented CCA in group A and also showed greater mean lumen area in group A than in group B. The endothelialization process was quicker in group A than in group B. CONCLUSION: MACS is effective for occlusion of lateral aneurysms and is superior to WCS in growth of the stented CCA and endothelialization. Further work is needed to make this device available for human use. KEY POINTS: • The MACS is an effective approach for occlusion of a lateral aneurysm. • IVUS showed that the CCA could grow following degradation of the MACS. • The lumen area of the stented CCA was excellent in MACS. • HE staining displayed the degradation of the magnesium alloy stent. • Combination of IVUS and DSA were applied in this study.

Platelet-derived growth factor-ß expression in rabbit models of cerebral vasospasm following subarachnoid hemorrhage.

Subarachnoid hemorrhage (SAH), one of the serious types of stroke incurred by bleeding into the space surrounding the brain, occurs when brains are deprived of oxygen by various factors, particularly an interruption to the blood supply or a ruptured aneurysm. Cerebral vasospasm (CVS) is one of the most common complications of SAH. It has been proposed that platelet­derived growth factor (PDGF) is involved in CVS. The aim of the present study was to analyze expression of PDGF in rabbit models of CVS. Post-SAH CVS rabbit models were created using endovascular puncture and employed to analyze the expression patterns of PDGF by enzyme-linked immunosorbent assay and immunohistochemistry. The results indicated that the creation of the rabbit model of CVS induced using endovascular puncture was successful and demonstrated the double phase changes observed in human CVS. The acute stage started at 12 h post-SAH with narrowing of the vascular lumen diameter. This narrowing appeared again on the seventh day in delayed CVS alongside increased thickness of vessel walls. PDGF-ß expression was observed in vascular smooth muscle cells of the rabbit models. PDGF-ß was expressed as early as 3 h post-SAH, it was evident after 1 day and reached a peak in 7 days, suggesting that PDGF-ß is involved in the early stages of CVS. In the current study, it was confirmed that PDGF-ß expression was present in the rabbit models of CVS, which may aid the elucidation of the pathogenesis of CVS, and also provide useful information for diagnosis and treatment of CVS.

Synergistic antitumor activity of reversine combined with aspirin in cervical carcinoma in vitro and in vivo.

A recent report showed that reversine treatment could induce murine myoblasts dedifferentiation into multipotent progenitor cells and inhibit proliferation of some tumors, and other reports showed that apoptosis of lung adenocarcinoma cells could be induced by aspirin. The aim of the present study was to evaluate the synergistic antitumor effects of reversine and aspirin on cervical cancer. The inhibition rate of reversine and aspirin on cervical cancer cell lines' (HeLa and U14) was determined by MTT method, cell cycle of HeLa and U14 cells was analyzed by FACS, mitochondrial membrane potential of HeLa and U14 was detected using a JC-1 kit. HeLa and U14 colony formation was analyzed by soft agar colony formation assay. The expression of caspase-3, Bcl-2/Bax, cyclin D1 and p21 was detected by qRT-PCR and Western Blotting. Moreover, tumor weight and tumor volume was assessed using a murine model of cervical cancer with U14 cells subcutaneously (s.c.) administered into the neck, separately or combined with drug administration via the intraperitoneal (i.p.) route. The inhibition rate of cells in the combination group (10 µmol/L reversine, 10 mmol/L aspirin) increased significantly in comparison to that when the drugs were used alone (P < 0.05); moreover, this combination could synergistically inhibit the proliferation of five cervical cancer cell lines (HeLa, U14, Siha, Caski and C33A). In the therapeutic mouse model, tumor weight and tumor volume of cervical cancer bearing mice was more reduced when compared with the control agents (P < 0.05) in tumor-bearing mice. The combination of reversine and aspirin exerts synergistic growth inhibition and apoptosis induction on cervical cancers cells.

HDAC6 siRNA inhibits proliferation and induces apoptosis of HeLa cells and its related molecular mechanism.

OBJECTIVE: To investigate the effects of histone deacetylase 6 (HDAC6) siRNA on cell proliferation and cell apoptosis of the HeLa cervical carcinoma cell line and the molecular mechanisms involved. METHODS: Division was into three groups: A, the untreated group; B, the control siRNA group; and C, the HDAC6 siRNA group. Lipofectamine 2000 was used for siRNA transfection, and Western blot analysis was used to determine the protein levels. Cell proliferation and apoptosis were characterized using a CCK-8 assay and flow cytometry, respectively. RESULTS: HDAC6 protein expression in the HDAC6 siRNA-transfection group was significantly lower (P < 0.05) than in the untreated and control siRNA groups. The CCK-8 kit results demonstrated that the proliferation of HeLa cells was clearly inhibited in the HDAC6 siRNA transfection group (P < 0.05). In addition, flow cytometry revealed that the early apoptotic rate (26.0% ± 0.87%) was significantly elevated (P < 0.05) as compared with the untreated group (10.6% ± 1.19%) and control siRNA group (8.61% ± 0.98%). Furthermore, Western blot analysis indicated that bcl-2 protein expression in the HDAC6 siRNA-transfection group was down-regulated, whereas the expression of p21 and bax was up-regulated. CONCLUSION: HDAC6 plays an essential role in the occurrence and development of cervical carcinoma, and the down-regulation of HDAC6 expression may be useful molecular therapeutic method.