Introduction: Subarachnoid hemorrhage (SAH) is a severe hemorrhagic stroke with high mortality. However, there is a lack of clinical tools for predicting in-hospital mortality in clinical practice. LAR is a novel clinical marker that has demonstrated prognostic significance in a variety of diseases.Methods: Critically ill patients diagnosed and SAH with their data in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and the eICU Collaborative Research Database (eICU-CRD) were included in our study. Multivariate logistic regression was utilized to establish the nomogram.Results: A total of 244 patients with spontaneous SAH in the MIMIC-IV database were eligible for the study as a training set, and 83 patients in eICU-CRD were included for external validation. Data on clinical characteristics, laboratory parameters and outcomes were collected. Univariate and multivariate logistic regression analysis identified age (OR: 1.042, P-value: 0.003), LAR (OR: 2.592, P-value: 0.011), anion gap (OR: 1.134, P-value: 0.036) and APSIII (OR: 1.028, P-value: < 0.001) as independent predictors of in-hospital mortality and we developed a nomogram model based on these factors. The nomogram model incorporated with LAR, APSIII, age and anion gap demonstrated great discrimination and clinical utility both in the training set (accuracy: 77.5%, AUC: 0.811) and validation set (accuracy: 75.9%, AUC: 0.822).Conclusion: LAR is closely associated with increased in-hospital mortality of patients with spontaneous SAH, which could serve as a novel clinical marker. The nomogram model combined with LAR, APSIII, age, and anion gap presents good predictive performance and clinical practicability.

Background: Lysyl oxidase enzymes (LOXs), as extracellular matrix (ECM) protein regulators, play vital roles in tumor progression by remodeling the tumor microenvironment. However, their roles in glioblastoma (GBM) have not been fully elucidated. Methods: The genetic alterations and prognostic value of LOXs were investigated via cBioPortal. The correlations between LOXs and biological functions/molecular tumor subtypes were explored in The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). After Kaplan‒Meier and Cox survival analyses, a Loxl1-based nomogram and prognostic risk score model (PRSM) were constructed and evaluated by time-dependent receiver operating characteristic curves, calibration curves, and decision curve analyses. Tumor enrichment pathways and immune infiltrates were explored by single-cell RNA sequencing and TIMER. Loxl1-related changes in tumor viability/proliferation and invasion were further validated by CCK-8, western blot, wound healing, and Transwell invasion assays. Results: GBM patients with altered LOXs had poor survival. Upregulated LOXs were found in IDH1-wildtype and mesenchymal (not Loxl1) GBM subtypes, promoting ECM receptor interactions in GBM. The Loxl1-based nomogram and the PRSM showed high accuracy, reliability, and net clinical benefits. Loxl1 expression was related to tumor invasion and immune infiltration (B cells, neutrophils, and dendritic cells). Loxl1 knockdown suppressed GBM cell proliferation and invasion by inhibiting the EMT pathway (through the downregulation of N-cadherin/Vimentin/Snai1 and the upregulation of E-cadherin). Conclusion: The Loxl1-based nomogram and PRSM were stable and individualized for assessing GBM patient prognosis, and the invasive role of Loxl1 could provide a promising therapeutic strategy.

Glioblastoma (GBM) is a highly malignant and aggressive tumor with poor prognosis. Therefore, the discovery of new prognostic molecular markers is of great significance for clinical prognosis. The CXC chemokine receptor (CXCR) members play a key regulatory role in many cancers. In this study, we explore the clinical value and application of the CXCR members in primary glioblastoma. Two GBM datasets from The Cancer Genome Atlas (TCGA) and The China Glioma Genome Atlas (CGGA) databases were used to explore the relationship between differential expression of CXCRs and GBM subtypes as well as immune infiltration. C-X-C motif chemokine receptor 4 (CXCR4) was screened as an independent prognostic factor, and a nomogram and risk prediction model were developed and tested in the CGGA database using the TCGA database. Receiver operating curve (ROC) and decision curve analysis (DCA) found good accuracy and net benefit of the models. The correlation of CXCR4 with immune infiltration and tumor was analyzed using CancerSEA and TIMER. In in vitro experiments, we found that CXCR4 was significantly overexpressed in glioblastoma and was closely related to the inflammatory response of U251/U87 cells. CXCR4 is an excellent independent prognostic factor for glioblastoma and positively correlates with tumor inflammation.

Background: Apoptosis plays a significant role in secondary brain injury following intracerebral hemorrhage (ICH). Currently, the mechanisms related to cell apoptosis after cerebral hemorrhage are still under investigation.Methods: We identified differentially expressed genes (DEGs) between human ICH patients and normal individuals from the GEO database and conducted GO and KEGG functional enrichment analyses on these DEGs. We then constructed a PPI network and used the MECDE algorithm to identify key genes potentially involved in apoptosis after ICH. Additionally, we identified miRNAs that might regulate apoptotic genes in an mRNA-miRNA interaction network. Finally, we validated the bioinformatics results in a rat ICH model.Results: In the human ICH model, 645 DEGs were identified. GO and KEGG analyses indicated that these DEGs are primarily involved in immune response, inflammatory response, and apoptosis. GSEA analysis showed significant enrichment of DEGs in the apoptotic process. By comparing with apoptosis-related genes in the MSigDB database, we identified 110 apoptosis-related genes among the 645 DEGs. Further PPI and MOCDE analyses of these apoptosis-related genes revealed that BID might be a key gene involved in apoptosis after ICH, which was validated within the rat model of ICH. The mRNA-miRNA interactions network construction suggested that miR1225-3p may be an important miRNA involved in regulating BID expression after ICH.Conclusion: BID plays a critical role in the regulation of apoptosis following intracerebral hemorrhage and serves as a key biomarker in the apoptotic process after hemorrhage.

Ischemic stroke (IS) is associated with high disability and mortality. This study aimed to identify the prognostic predictors and develop a nomogram for a prediction model for ischemic stroke patients after thrombolysis. We retrospectively analyzed data from 359 IS patients who underwent thrombolysis. Clinical characteristics, laboratory parameters, and prognosis data were collected. One-third of the subjects were randomly selected as a validation set (n = 108) for internal validation. Logistic regression analysis was used to derive independent risk indicators. A nomogram was constructed using these indicators, and the performance of the nomogram was assessed by the Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC). The agreement of the model predictions with actual observations was assessed via calibration curves, and the clinical utility of the nomogram was assessed via decision curve analysis. Multivariate logistic regression analysis showed that age, leukocytes, Lactate Dehydrogenase to Albumin Ratio (LAR) and NIHSS were independent predictors of three-month post-thrombolysis prognosis in IS patients. We created a nomogram based on the weighting coefficients of these factors. The AUC curves showed that our model including age, leukocytes, LAR and NIHSS was more accurate in predicting prognosis than a single factor. The calibration curves showed a good fit between actual and predicted probabilities in both the training and validation groups. LAR has a good predictive power for the prognosis of IS patients 3 months after thrombolytic therapy and can be used as a new clinical indicator to establish a practical nomogram.