Bo Yang

This study aims to develop and validate nomograms for predicting the risk of aneurysm rupture and adverse prognosis in patients with Moyamoya disease (MMD) and associated intracranial aneurysms (IAs). We analyzed 286 saccular and 22 non-saccular IAs from 231 MMD patients. We used logistic regression to identify risk factors for IA rupture and Cox regression to find factors associated with prognosis. Nomograms were constructed using R 4.3.3 software based on these risk factors and validated via receiver operating characteristic (ROC) curves, calibration curves, and clinical decision curves. Among 3293 MMD patients, 231 (7.01%) harbored IAs. Saccular IAs had a higher rupture rate (24.2%) compared to non-saccular IAs (13.64%). Independent risk factors for rupture in non-saccular IAs included the presence of a daughter sac, whereas the location, flow angle, and aspect ratiowere risk factors for saccular IA rupture. Prognostic factors included rerupture and modified Fisher scale. The constructed nomograms demonstrated robust predictive performance in the validation cohort. Our nomograms effectively predict the risk of rupture in saccular IAsand poor prognosis in MMD patients with IAs, offering valuable tools for clinical decision-making.

Moyamoya disease (MMD) suffers from impaired cerebrovascular hemodynamics and high perioperative complications occurrence. This study aims to propose and evaluate the relationship between intraoperative hemodynamics and perioperative complications, and propose a potential compensatory self-recirculation network in MMD. We prospectively enrolled 63 MMD patients undergone combined revascularization, and patients were divided into decreased and increased group according to decreased and increased microvascular transit time (MVTT), respectively. Mean age of all patients was 45.9 ± 9.4 years. The post-bypass hyperperfusion syndrome occurrence was significantly higher in the decreased MVTT group, and the cerebral infarction occurrence was significantly higher in the increased MVTT group. For the hemodynamics of the recipient artery around anastomosis, the parameters of distal site demonstrated a significant higher intensity and shorter time in the decreased MVTT group, while the parameters of the proximal site demonstrated a significant higher intensity and shorter time in the increased MVTT group. Pre-bypass and post-bypass collision of blood flow in artery and vein were firstly observed and illustrated. Intraoperative hemodynamics showed close relationship with perioperative complications. The blood flow of MMD seems to develop a unique compensatory self-recirculation system and contribute to the clinical complications, providing a new insight to the clinical management the pathology of the disease.

Moyamoya disease, characterized by basal cerebral artery obstruction, was studied for differential protein expression to elucidate its pathogenesis. Proteomic analysis of cerebrospinal fluid from 10 patients, categorized by postoperative angiography into good and poor prognosis groups, revealed 46 differentially expressed proteins. Notably, cadherin 18 (CDH18) was the most significantly upregulated in the good prognosis group. In addition, the expression of cadherin 18 (CDH18) and phenotypic transformation-related proteins were measured by qRT-PCR and western blot. The effects of CDH18 in vascular smooth muscle cells were detected by CCK-8, EdU, transwell and wound healing assays. The overexpression of CDH18 in vascular smooth muscle cells (VSMCs) was found to inhibit proliferation, migration, and phenotypic transformation. These findings suggest CDH18 as a potential therapeutic target in moyamoya disease.

Cerebral ischemia‒reperfusion injury (CIRI) is a type of secondary brain damage caused by reperfusion after ischemic stroke due to vascular obstruction. In this study, a CIRI diagnostic model was established by identifying hypoxia-related differentially expressed genes (HRDEGs) in patients with CIRI. The ischemia‒reperfusion injury (IRI)-related datasets were downloaded from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo), and hypoxia-related genes in the Gene Cards database were identified. After the datasets were combined, hypoxia-related differentially expressed genes (HRDEGs) expressed in CIRI patients were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the HRDEGs were performed using online tools. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed with the combined gene dataset. CIRI diagnostic models based on HRDEGs were constructed via least absolute shrinkage and selection operator (LASSO) regression analysis and a support vector machine (SVM) algorithm. The efficacy of the 9 identified hub genes for CIRI diagnosis was evaluated via mRNA‒microRNA (miRNA) interaction, mRNA–RNA-binding protein (RBP) network interaction, immune cell infiltration, and receiver operating characteristic (ROC) curve analyses. We then performed logistic regression analysis and constructed logistic regression models based on the expression of the 9 HRDEGs. We next established a nomogram and calibrated the prediction data. Finally, the clinical utility of the constructed logistic regression model was evaluated via decision curve analysis (DCA). This study revealed 9 critical genes with high diagnostic value, offering new insights into the diagnosis and selection of therapeutic targets for patients with CIRI. : Not applicable.

The lactoferrin (LTF) gene behaves like a tumor suppressor gene in diverse tumors, such as renal cancer, nasopharyngeal carcinoma and gastric cancer. However, the prognostic value of LTF expression in patients with glioblastoma remains unclear. In this study, the expression levels of LTF in patients with GBM were investigated in TCGA, GEPIA, CGGA and GEO database, and a survival analysis of LTF based on TCGA and CGGA was performed. Furthermore, the present study demonstrated the LTF gene co-expression, PPI network, KEGG/GO enrichment and immune cell infiltration analysis on TCGA and TIMER2.0 database. We found that LTF expression was significantly upregulated in GBM samples compared with normal samples and other glioma samples, and Kaplan–Meier analysis demonstrated that the overexpression of LTF were significantly associated with worse overall survival (OS) and 5-year OS in GBM patients (P < 0.05). KEGG/GO enrichment analysis demonstrated that functions of LTF concentrated in immune and inflammatory response and peptidase regulation (P < 0.05). Immune cell infiltration analysis presented that high LTF expression exhibited dysregulated immune infiltration (i.e., CD4 + T cells, neutrophils, macrophages, myeloid dendritic cells and cancer associated fibroblast). LTF was upregulated in tumors and correlated with worse OS in GBM patients, and LTF might function as an oncogene via inducing dysregulated immune infiltration in GBM.

Objective: This study aimed to explore the hemodynamic changes before and after anastomosis in patients with Moyamoya disease (MMD) using multiple models.Methods: We prospectively enrolled 42 MMD patients who underwent combined revascularization. Intraoperative FLOW800 was performed before and after anastomosis, and parameters was collected, including maximum intensity, delay time, rise time, slope, blood flow index, and microvascular transit time (MVTT). Additionally, preoperative and postoperative hemodynamic parameters were measured using color Doppler ultrasonography (CDUS), including peak systolic velocity, end-diastolic velocity, resistance index (RI), pulsatility index (PI), and flow volume. Subsequently, the correlation between FLOW800 and CDUS parameters was explored.Results: A total of 42 participants took part with an average age of 46.5 years, consisting of 19 men and 23 women. The analysis of FLOW800 indicated that both the delay time and rise time experienced a substantial decrease in both the recipient artery and vein. Additionally, the MVTT was found to be significantly reduced after the surgery (5.7 ± 2.2 s vs. 4.9 ± 1.6, p = 0.021). However, no statistically significant differences were observed among the other parameters. Similarly, all postoperative parameters in CDUS hemodynamics exhibited significant alterations in comparison to the preoperative values. The correlation analysis between FLOW800 and CDUS parameters indicated a significant association between MVTT and RI and PI, no significant relationships were found among the other parameters in the two groups.Conclusion: The hemodynamic outcomes of the donor and recipient arteries demonstrated significant changes following bypass surgery. The parameter of time appears to be more precise and sensitive in assessing hemodynamics using FLOW800. Multiple evaluations of hemodynamics could offer substantial evidence for perioperative management.

Objective: This study aimed to identify immune infiltration characteristics and new immunological diagnostic biomarkers in the cerebrovascular tissue of moyamoya disease (MMD) using bioinformatics analysis.Methods: GSE189993 and GSE141022 were downloaded from the GEO database. Differentially expressed gene and PPI analysis were performed. After performing WGCNA, the most significant module associated with MMD was obtained. Next, functional pathways according to GSEA, GO, and KEGG were enriched for the aforementioned core genes obtained from PPI and WGCNA. Additionally, immune infiltration, using the CIBERSORT deconvolution algorithm, immune-related biomarkers, and the relationship between these genes, was further explored. Finally, diagnostic accuracy was verified with ROC curves in the validation dataset GSE157628.Results: A total of 348 DEGs were screened, including 89 downregulated and 259 upregulated genes. The thistle^l module was detected as the most significant module associated with MMD. Functional analysis of the core genes was chiefly involved in the immune response, immune system process, protein tyrosine kinase activity, secretory granule, and so on. Among 13 immune-related overlapping genes, 4 genes (BTK, FGR, PTPN11, and SYK) were identified as potential diagnostic biomarkers, where PTPN11 showed the highest specificity and sensitivity. Meanwhile, a higher proportion of eosinophils, not T cells or B cells, was demonstrated in the specific immune infiltration landscape of MMD.Conclusion: Immune activities and immune cells were actively involved in the progression of MMD. BTK, FGR, PTPN11, and SYK were identified as potential immune diagnostic biomarkers. These immune-related genes and cells may provide novel insights for immunotherapy in the future.

Objective: In recent years, an increasing number of studies have revealed that patients’ preoperative inflammatory response, coagulation function, and nutritional status are all linked to the occurrence, development, angiogenesis, and metastasis of various malignant tumors. The goal of this study is to determine the relationship between preoperative peripheral blood neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR), systemic immune-inflammatory index (SII), platelet to lymphocyte ratio (PLR), and platelet to fibrinogen ratio (FPR). Prognostic nutritional index (PNI) and the prognosis of glioblastoma multiforme (GBM) patients, as well as establish a forest prediction model that includes preoperative hematological markers to predict the individual GBM patient’s 3-year survival status after treatment. Methods: The clinical and hematological data of 281 GBM patients were analyzed retrospectively; overall survival (OS) was the primary endpoint. X-Tile software was used to determine the best cut-off values for NLR, SII, and PLR, and the survival analysis was carried out by the Kaplan–Meier method as well as univariate and multivariate COX regression. Afterward, we created a random forest model that predicts the individual GBM patient’s 3-year survival status after treatment, and the area under the curve (AUC) is used to validate the model’s effectiveness. Results: The best cut-off values for NLR, SII, and PLR in GBM patients’ preoperative peripheral blood were 2.12, 537.50, and 93.5 respectively. The Kaplan–Meier method revealed that preoperative GBM patients with high SII, high NLR, and high PLR had shorter overall survival, and the difference was statistically significant. In addition to clinical and pathological factors. Univariate Cox showed NLR (HR = 1.456, 95% CI: 1.286 ~ 1.649, P < 0.001) MLR (HR = 1.272, 95% CI: 1.120 ~ 1.649, P < 0.001), FPR (HR = 1.183,95% CI: 1.049 ~ 1.333, P < 0.001), SII (HR = 0.218,95% CI: 1.645 ~ 2.127, P < 0.001) is related to the prognosis and overall survival of GBM. Multivariate Cox proportional hazard regression showed that SII (HR = 1.641, 95% CI: 1.430 ~ 1.884, P < 0.001) is also related to the overall survival of patients with GBM. In the random forest prognostic model with preoperative hematologic markers, the AUC in the test set and the validation set was 0.907 and 0.900, respectively. Conclusion: High levels of NLR, MLR, PLR, FPR, and SII before surgery are prognostic risk factors for GBM patients. A high preoperative SII level is an independent risk factor for GBM prognosis. The random forest model that includes preoperative hematological markers has the potential to predict the individual GBM patient’s 3-year survival status after treatment,and assist the clinicians for making a good clinical decision.