Machine Learning Models for Brain Arteriovenous Malformations Presenting with Hemorrhage Based on Clinical and Angioarchitectural Characteristics.

RATIONALE AND OBJECTIVES: This study aims to develop the best diagnostic model for brain arteriovenous malformations (bAVMs) rupture by using machine learning (ML) algorithms. MATERIALS AND METHODS: We retrospectively included 353 adult patients with ruptured and unruptured bAVMs. The clinical and radiological data on patients were collected. The significant variables were selected using univariable logistic regression. We constructed and compared the predictive models using five supervised ML algorithms, multivariable logistic regression, and R2eDAVM scoring system. A complementary systematic review and meta-analysis of studies was aggregated to explore the potential predictors for bAVMs rupture. RESULTS: We found that a small nidus size of <3 cm, deep and infratentorial location, longer filling time, and deep and single venous drainage were associated with a higher risk of bAVMs rupture. The multilayer perceptron model showed the best performance with an area under the curve value of 0.736 (95% CI 0.67-0.801) and 0.713 (95% CI 0.647-0.779) in the training and test dataset, respectively. In our pooled analysis, we also found that the male sex, a single feeding artery, hypertension, non-White race, low Spetzler-Martin grade, and coexisting aneurysms are risk factors for bAVMs rupture. CONCLUSION: This study further demonstrated the clinical and angioarchitectural characteristics in predicting bAVMs hemorrhage.

Investigating Causal Effects of Hematologic Traits on Lung Cancer: A Mendelian Randomization Study.

BACKGROUND: Observational studies have suggested blood cell counts may act as predictors of cancer. It is not known whether these hematologic traits are causally associated with lung cancer. METHODS: Two-sample bidirectional univariable Mendelian randomization (MR) and multivariable MR (MVMR) were performed to investigate the causal association between hematologic traits and the overall risk of lung cancer and three histologic subtypes [lung adenocarcinoma, squamous cell lung cancer, and small cell lung cancer (SCLC)]. The instrumental variables of 23 hematologic traits were strictly selected from large-scale genome-wide association studies. Inverse-variance weighted method and five extra methods were used to obtain robust causal estimates. RESULTS: We found evidence that genetically influenced higher hematocrit [OR, 0.845; 95% confidence interval (CI), 0.783-0.913; P = 1.68 × 10-5] and hemoglobin concentration (OR, 0.868; 95% CI, 0.804-0.938; P = 3.20 × 10-4) and reticulocyte count (OR, 0.923; 95% CI, 0.872-0.976; P = 5.19 × 10-3) decreased lung carcinoma risk, especially in ever smokers. MVMR further identified hematocrit independently of smoking as an independent predictor. Subgroup analysis showed that a higher plateletcrit level increased the risk of small cell lung carcinoma (OR, 1.288; 95% CI, 1.126-1.474; P = 2.25 × 10-4). CONCLUSIONS: Genetically driven higher levels of reticulocyte count and hematocrit decreased lung cancer risk. Higher plateletcrit had an adverse effect on SCLC. Hematologic traits may act as low-cost factors for lung cancer risk stratification. IMPACT: Further studies are required to elucidate the potential mechanisms underlying the dysregulation of homeostasis related to hematologic traits, such as subclinical inflammation.

Genetically predicted tobacco consumption and risk of intracranial aneurysm: a Mendelian randomization study.

Several observational studies have suggested that tobacco consumption is a risk factor for intracranial aneurysms (IAs). We here genetically predict the causal association between specific smoking features and biomarkers for smokers and IA risk. The Mendelian randomization (MR) analysis considered summary statistics from the largest current genome-wide association studies of smoking and IA. The inverse-variance weighted (IVW) method, weighted median method, MR-RAPS, and multiple variants Mendelian randomization (MVMR) were performed to estimate the effect of different smoking features and drinking in IA. We observed significant causal effects of smoking on the risk of both aneurysmal subarachnoid hemorrhage (aSAH) and unruptured IA (uIA). The ORs of IAs based on the IVW method were 1.890 (95% CI 1.486-2.405) of ever smoking regularly. MVMR analysis afforded odds ratios of 1.685 (95% CI 1.136-2.501). In the further subgroup analysis, a similar causal relationship was observed in aSAH. Moreover, our analyses suggested that higher blood cotinine level and cadmium increases aSAH risk, and ORs were 1.235 (95%CI 1.009-1.186) and 1.235 (95%CI 1.046-1.458), respectively. Our study suggests that ever smoking regularly is associated with the IA risk, which includes both uIA and aSAH. Besides, higher blood cadmium and cotinine level may increases IA and aSAH risk. Thus, tobacco control should be promoted as primordial prevention for IAs, and screening for patients with a smoking history is emphasized.

Animal model contributes to the development of intracranial aneurysm: A bibliometric analysis.

Introduction: Studies on intracranial aneurysms (IAs) using animal models have evolved for decades. This study aimed to analyze major contributors and trends in IA-related animal research using bibliometric analysis. Methods: IA-related animal studies were retrieved from the Web of Science database. Microsoft Excel 2010, GraphPad Prism 6, VOSviewer, and CiteSpace were used to collect and analyze the characteristics of this field. Results: A total of 273 publications were retrieved. All publications were published between 1976 and 2021, and the peak publication year is 2019. Rat model were used in most of the publications, followed by mice and rabbits. Japan (35.5%), the United States (30.0%), and China (20.1%) were the top three most prolific countries. Although China ranks third in the number of publications, it still lacks high-quality articles and influential institutions. Stroke was the most prolific journal that accepted publications related to IA research using animal models. Circulation has the highest impact factor with IA-related animal studies. Hashimoto N contributed the largest number of articles. Meng hui journal published the first and second highest cited publications. The keywords "subarachnoid hemorrhage," "macrophage," "rupture," "mice," "elastase," "gene," "protein," "proliferation," and "risk factors" might be a new trend for studying IA-related animal research. Conclusions: Japan and the Unites States contributed the most to IA-related animal studies, in terms of both researchers and institutions. Although China ranks third in terms of the number of publications, it should strengthen the quality of its publications. Researchers should pay attention to the latest progress of Stroke, Journal of Neurosurgery, Neurosurgery, and Circulation for their high-quality IA-related animal studies. Using animal IA models, especially mice, to investigate the molecular mechanisms of IA may be the frontier topic now and in future.

The Coordination of mTOR Signaling and Non-Coding RNA in Regulating Epileptic Neuroinflammation.

Epilepsy accounts for a significant proportion of the burden of neurological disorders. Neuroinflammation acting as the inflammatory response to epileptic seizures is characterized by aberrant regulation of inflammatory cells and molecules, and has been regarded as a key process in epilepsy where mTOR signaling serves as a pivotal modulator. Meanwhile, accumulating evidence has revealed that non-coding RNAs (ncRNAs) interfering with mTOR signaling are involved in neuroinflammation and therefore articipate in the development and progression of epilepsy. In this review, we highlight recent advances in the regulation of mTOR on neuroinflammatory cells and mediators, and feature the progresses of the interaction between ncRNAs and mTOR in epileptic neuroinflammation.

The Transcriptional Landscapes and Key Genes in Brain Arteriovenous Malformation Progression in a Venous Hypertension Rat Model Revealed by RNA Sequencing.

BACKGROUND: Brain arteriovenous malformations (bAVM) are abnormal vascular lesions characterized by direct connections between arteries and veins without an intervening capillary bed. The primary goal for brain AVM treatment is to prevent rupture and hemorrhage; however, the underlying molecular mechanisms are still unknown. METHODS: We constructed venous hypertension (VH) rat model with end-to-end anastomosis of the proximal left common carotid artery and the left distal external jugular vein. Thirty-eight adult rats were randomly assigned to four groups: the 0-week (n=5), the 1-week VH group (n=12), the 3-week VH group (n=9), and the 6-week VH group (n=12). We measured the hemodynamics and diameter of the arterialized veins. An RNA sequencing of arterialized veins was conducted, followed by comprehensive bioinformatics analysis to identify key genes and biological pathways involved in VH progression. The candidate genes from RNA-Seq were validated by RT-qPCR and immunostaining in human tissues. RESULTS: We observed high-flow and low resistance characteristics in VH models. A total of 317 upregulated and 258 downregulated common genes were consistently differentially expressed during VH progression. Thirteen co-expression modules were obtained by WGCNA analysis, and 4 key modules were identified. Thirteen genes: Adamts8, Adamtsl3, Spon2, Adamtsl2, Chad, Itga7, Comp, Itga8, Bmp6, Fst, Smad6, Smad7, Grem1, and Nog with differential expressions were identified using the density of maximum neighborhood component (DMNC) algorithm in Cytohubba. The expression of five potential genes (Adamts8, Adamtsl3, Spon2, Adamtsl2, Itga8) were increased in RT-qPCR, while in human bAVM tissue, the protein levels of Adamtsl2 and Itga8 were significant elevated and Spon2 and Adamtsl3 were decreased. CONCLUSION: The identified gene networks of Adamtsl3, Spon2, Adamtsl2, and Itga8 provided key genes for further intervention.

Comprehensive analysis of immunocyte infiltration and the key genes associated with intraplaque hemorrhage in carotid atherosclerotic plaques.

PURPOSE: To identify key biomarkers associated with intraplaque hemorrhage (IPH). METHODS: We conducted a comprehensive analysis combined with DEGs, xCell, WGCNA, GSEA, and GSVA methods to identify immune infiltration cells and key genes involved in IPH by using GSE163154 from the gene expression omnibus (GEO). E-MTAB-1470 and E-MTAB-2055 from the ArrayExpress database were utilized as the verification datasets. Finally, the candidate hub genes were further validated by RT-qPCR in clinical samples. RESULTS: A total of 280 genes were upregulated and 234 genes were downregulated in GSE163154. Among the upregulated pathways, the lysosome and chemokine signaling pathway were enriched, while the vascular smooth muscle (VSMC) contraction and focal adhesion were downregulated. In addition, ten coexpression modules were obtained by using the WGCNA method and two IPH and immunity-related modules were identified. In total, 454 genes overlapped by DEGs and WGCNA results were imported into Cytoscape to construct a protein-protein network. Eight genes (FCER1G, ITGB2, VAV1, CSF1R, ITGAM, TYROBP, PTK2, and PTPN11) were identified as the IPH-related gene set with area under curves (AUC) of 0.961, 0.905, and 0.857 in GSE163154, E-MTAB-2055, and E-MTAB-1470, respectively. The expression of four genes (ITGB2, VAV1, ITGAM, TYROBP) from our analysis were consistent with RT-qPCR results. CONCLUSION: Eight genes were found to be involved in IPH, and four genes (ITGB2, VAV1, ITGAM, TYROBP) may be an important biomarkers for IPH.

Advanced high resolution three-dimensional imaging to visualize the cerebral neurovascular network in stroke.

As an important method to accurately and timely diagnose stroke and study physiological characteristics and pathological mechanism in it, imaging technology has gone through more than a century of iteration. The interaction of cells densely packed in the brain is three-dimensional (3D), but the flat images brought by traditional visualization methods show only a few cells and ignore connections outside the slices. The increased resolution allows for a more microscopic and underlying view. Today's intuitive 3D imagings of micron or even nanometer scale are showing its essentiality in stroke. In recent years, 3D imaging technology has gained rapid development. With the overhaul of imaging mediums and the innovation of imaging mode, the resolution has been significantly improved, endowing researchers with the capability of holistic observation of a large volume, real-time monitoring of tiny voxels, and quantitative measurement of spatial parameters. In this review, we will summarize the current methods of high-resolution 3D imaging applied in stroke.