To assess the clinical value of mechanical thrombectomy (MT) combined with intravenous thrombolysis (IVT) in acute ischemic stroke (AIS) by comparing it with the MT alone. In this study, we conducted a comprehensive meta-analysis of both observational and randomized controlled studies (RCTs) to investigate various outcomes. Our search for relevant studies was conducted between January 2011 and June 2022 in four major databases: PubMed, Embase, WOS, and Cochrane Library. We collected data on several outcomes, including functional independence (FI; defined as modified Rankin Scale score of 0 to 2), excellent outcomes (mRS 0–1), successful recanalization (SR), symptomatic intracerebral hemorrhage (sICH), any intracerebral hemorrhage (aICH), and mortality at three months or discharge. The primary efficacy outcome and safety outcome were FI and sICH, respectively, whereas excellent outcomes and SR were considered secondary efficacy outcomes. Additionally, mortality and aICH were analyzed as secondary safety outcomes. We employed the Mantel–Haenszel fixed-effects model for RCTs when I² < 50%, otherwise the random-effects model was utilized. For observational studies and subgroup analyses, we used the random-effects model to minimize potential bias. A total of 55 eligible studies (nine RCTs and 46 observational studies) were included. For RCTs, the MT + IVT group was superior in FI (OR: 1.27, 95% CI: 1.11–1.46), excellent outcomes (OR: 1.21, 95% CI: 1.03–1.43), SR (OR: 1.23, 95% CI: 1.05–1.45), mortality (OR: 0.72, 95% CI: 0.54–0.97) in crude analyses. In adjusted analyses, the MT + IVT group reduced the risk of mortality (OR: 0.65, 95% CI: 0.49–0.88). However, the difference in FI between the MT + IVT group and the MT alone group was not significant (OR: 1.17, 95% CI: 0.99–1.38, Fig. 3a). For observational studies, the results of FI (OR: 1.34, 95% CI: 1.16–1.33), excellent outcomes (OR: 1.30, 95% CI: 1.09–1.54), SR (OR: 1.23, 95% CI: 1.05–1.44), mortality (OR: 0.70, 95% CI: 0.64–0.77) in the MT + IVT group were better. Additionally, the MT + IVT group increased the risk of hemorrhagic transformation (HT) including sICH (OR: 1.16, 95% CI: 1.11–1.21) and aICH (OR: 1.24, 95% CI: 1.05–1.46) in crude analyses. In adjusted analyses, significant better outcomes were seen in the MT + IVT group on FI (OR: 1.36, 95% CI: 1.21–1.52), excellent outcomes (OR: 1.49, 95% CI: 1.26–1.75), and mortality (OR: 0.73, 95% CI: 0.56–0.94). The MT + IVT therapy did improve the prognosis for AIS patients and did not increase the risk of HT compared with MT alone therapy.

Background: Alzheimer’s disease (AD) represents a progressive neurodegenerative disorder characterized by the accumulation of misfolded amyloid beta protein, leading to the formation of amyloid plaques and the aggregation of tau protein into neurofibrillary tangles within the cerebral cortex. The role of carbohydrates, particularly apolipoprotein E (ApoE), is pivotal in AD pathogenesis due to its involvement in lipid and cholesterol metabolism, and its status as a genetic predisposition factor for the disease. Despite its significance, the mechanistic contributions of Lipid Metabolism-related Genes (LMGs) to AD remain inadequately elucidated. This research endeavor seeks to bridge this gap by pinpointing biomarkers indicative of early-stage AD, with an emphasis on those linked to immune cell infiltration. To this end, advanced machine-learning algorithms and data derived from the Gene Expression Omnibus (GEO) database have been employed to facilitate the identification of these biomarkers.Methods: Differentially expressed genes (DEGs) were identified by comparing gene expression profiles between healthy individuals and Alzheimer’s disease (AD) patients, using data from two Gene Expression Omnibus (GEO) datasets: GSE5281 and GSE138260. Functional enrichment analysis was conducted to elucidate the biological relevance of the DEGs. To ensure the reliability of the results, samples were randomly divided into training and validation sets. The analysis focused on lipid metabolism-related DEGs (LMDEGs) to explore potential biomarkers for AD. Machine learning algorithms, including Support Vector Machine-Recursive Feature Elimination (SVM-RFE) and the Least Absolute Shrinkage and Selection Operator (LASSO) regression model, were applied to identify a key gene biomarker. Additionally, immune cell infiltration and its relationship with the gene biomarker were assessed using the CIBERSORT algorithm. The Integrated Traditional Chinese Medicine (ITCM) database was also referenced to identify Chinese medicines related to lipid metabolism and their possible connection to AD. This comprehensive strategy aims to integrate modern computational methods with traditional medicine to deepen our understanding of AD and its underlying mechanisms.Results: The study identified 137 genes from a pool of 751 lipid metabolism-related genes (LMGs) significantly associated with autophagy and immune response mechanisms. Through the application of LASSO and SVM-RFE machine-learning techniques, four genes—choline acetyl transferase (CHAT), member RAS oncogene family (RAB4A), acyl-CoA binding domain-containing protein 6 (ACBD6), and alpha-galactosidase A (GLA)—emerged as potential biomarkers for Alzheimer’s disease (AD). These genes demonstrated strong therapeutic potential due to their involvement in critical biological pathways. Notably, nine Chinese medicine compounds were identified to target these marker genes, offering a novel treatment approach for AD. Further, ceRNA network analysis revealed complex regulatory interactions involving these genes, underscoring their importance in AD pathology. CIBERSORT analysis highlighted a potential link between changes in the immune microenvironment and CHAT expression levels in AD patients, providing new insights into the immunological dimensions of the disease.Conclusion: The discovery of these gene markers offers substantial promise for the diagnosis and understanding of Alzheimer’s disease (AD). However, further investigation is necessary to validate their clinical utility. This study illuminates the role of Lipid Metabolism-related Genes (LMGs) in AD pathogenesis, offering potential targets for therapeutic intervention. It enhances our grasp of AD’s complex mechanisms and paves the way for future research aimed at refining diagnostic and treatment strategies.

Purpose To assess the clinical value of mechanical thrombectomy (MT) combined with intravenous thrombolysis (IVT) in acute ischemic stroke (AIS) by comparing it with the direct MT (dMT). Method We conducted a systematic review and meta-analysis involving studies from four databases including PubMed, Embase, WOS, and Cochrane Library. We collected observational studies and randomized controlled studies (RCTs) published from January 2011 to June 2022, providing data about outcomes in terms of functional independence (FI), excellent outcomes (mRS score:0-1), successful recanalization (SR), symptomatic intracerebral hemorrhage (sICH), any intracerebral hemorrhage (aICH), and mortality at three-month or discharge. Results A total of 55 eligible studies (nine RCTs and 46 observational studies) were included. For RCTs, the MT+IVT group was superior in FI (OR:1.27, 95%CI:1.11-1.46), excellent outcomes (OR:1.21, 95%CI:1.03-1.43), SR (OR:1.23, 95%CI:1.05-1.45), mortality (OR:0.72, 95%CI: 0.54-0.97) in crude analyses. In adjusted analyses, the MT+IVT group reduced the risk of mortality (OR:0.65, 95%CI: 0.49-0.88). For observational studies, the results of FI (OR:1.34, 95%CI:1.16-1.33), excellent outcomes (OR:1.30, 95%CI:1.09-1.54), SR (OR:1.23, 95%CI:1.05-1.44), mortality (OR:0.70, 95%CI:0.64-0.77) in the MT+IVT group were better. Additionally, the MT+IVT group increased the risk of hemorrhagic transformation (HT) including sICH (OR:1.16, 95%CI:1.11-1.21) and aICH (OR:1.24, 95%CI:1.05-1.46) in crude analyses. In crude analyses, significant better outcomes were seen in the MT+IVT group on FI (OR:1.36, 95%CI:1.21-1.52), excellent outcomes (OR:1.49, 95%CI:1.26-1.75), and mortality (OR:0.73, 95%CI: 0.56-0.94). Conclusions The MT+IVT therapy did improve the prognosis for AIS patients and did not increase the risk of HT compared with dMT therapy.