Hemodynamics study of anterior cerebral artery with different sac centerline lengths for rupture risk assessment.

The present research extensively investigates the significance of the sac centerline length of the anterior cerebral artery (ACA) on aneurysm rupture risk. Hemodynamic factors influencing aneurysm rupture are assessed to identify critical regions prone to rupture. Wall shear stress is analyzed by modeling blood flow in three real saccular ACA cases with varying sac centerline lengths. A one-way fluid-solid interaction (FSI) model is employed to examine the interaction between blood flow and vessel deformation. The computational study reveals that wall shear stress on the ACA saccular aneurysm wall is significantly higher when the sac centerline length is shorter. Conversely, the mean oscillatory index changes with different sac centerline lengths, showing that an increase in sac centerline length leads to higher blood oscillation within the sac area in ACA cases.

Optimized risk stratification strategy for glioma patients based on the feature genes of poor immune cell infiltration patterns.

BACKGROUND: Gliomas, originating from glial cells within the brain or spinal cord, are common central nervous system tumors with varying degrees of malignancy that influence the complexity and difficulty of treatment. The current strategies, including traditional surgery, radiotherapy, chemotherapy, and emerging immunotherapies, have yielded limited results. As such, our study aims to optimize risk stratification for a more precise treatment approach. We primarily identify feature genes associated with poor immune cell infiltration patterns through various omics algorithms and categorize glioma patients based on these genes to enhance the accuracy of patient prognosis assessment. This approach can underpin individualized treatment strategies and facilitate the discovery of new therapeutic targets. METHODS: We procured datasets of gliomas and normal brain tissues from TCGA, CGGA, and GTEx databases. Clustering was conducted using the input of 287 immune cell feature genes. Hub genes linked with the poor prognosis subtype (C1) were filtered through WGCNA. The TCGA dataset served as the discovery cohort and the CGGA dataset as the external validation cohort. We constructed a prognostic model related to feature genes from poor immune cell infiltration patterns utilizing LASSO-Cox regression. Comprehensive analyses of genomic heterogeneity, tumor stemness, pathway relevance, immune infiltration patterns, treatment response, and potential drugs were conducted for different risk groups. Gene expression validation was performed using immunohistochemistry (IHC) on 98 glioma samples and 11 normal brain tissue samples. RESULTS: Using the filtered immune cell-related genes, glioma patients were stratified into C1 and C2 subtypes through clustering. The C1 subtype exhibited a worse prognosis, with upregulated genes primarily enriched in immune response, extracellular matrix, etc., and downregulated genes predominantly enriched in neural signal transduction and neural pathway-related aspects. Seven advanced algorithms were used to elucidate immune cell infiltration patterns of different subtypes. In addition, WGCNA identified hub genes from poor immune infiltration patterns, and a prognostic model was constructed accordingly. High-risk patients demonstrated shorter survival times and higher risk scores as compared to low-risk patients. Multivariate Cox regression analysis revealed that, after adjusting for confounding clinical factors, risk score was a vital independent predictor of overall survival (OS) (P < 0.001). The established nomogram, which combined risk scores with WHO grade and age, accurately predicted glioma patient survival rates at 1, 3, and 5 years, with AUCs of 0.908, 0.890, and 0.812, respectively. This risk score enhanced the nomogram's reliability and informed clinical decision-making. We also comprehensively analyzed genomic heterogeneity, tumor stemness, pathway relevance, immune infiltration patterns, treatment response, and potential drugs for different risk groups. In addition, we conducted preliminary validation of the potential PLSCR1 gene using IHC with a large sample of gliomas and normal brain tissues. CONCLUSION: Our optimized risk stratification strategy for glioma patients has the potential to improve the accuracy of prognosis assessment. The findings from our omics research not only enhance the understanding of the functions of feature genes related to poor immune cell infiltration patterns but also offer valuable insights for the study of glioma prognostic biomarkers and the development of individualized treatment strategies.

Inflammatory myofibroblastic tumor of the central nervous system: A case report.

BACKGROUND: An inflammatory myofibroblastic tumor (IMT) occurring in the central nervous system is very rare, and thus its pathogenesis is unknown. This case report and literature review aimed to explore the pathogenesis, clinical features, imaging findings, pathological characteristics, immunohistochemical characteristics, diagnoses, treatments, and risks of postoperative recurrence of IMT in the central nervous system. CASE SUMMARY: A 67-year-old woman was admitted to the hospital with an exophthalmic protrusion and double vision in the left eye that had persisted for 3 mo. Magnetic resonance imaging (MRI) showed a 2.4 cm × 1.3 cm heterogeneous large mass in the bottom of the left anterior cranial fossa, which was closely related to the dura mater. Before surgery, we suspected the mass to be meningioma. The entire mass was successfully removed under neuronavigation and electrophysiological monitoring, and postoperative pathology indicated an IMT with extensive infiltration of chronic inflammatory cells and scattered multinucleated giant cells. Head MRI at the 3-mo follow-up showed that the tumor at the bottom of left anterior cranial fossa had been completely resected without recurrence. CONCLUSION: From the histological, immunohistochemical, and genetic analyses, the present case suggests that the pathogenesis of IMT-CNS is related to autoimmunity.