RESUMEN
New biomarkers for early diagnosis of gastric cancer (GC), the second leading cause of cancer-related death, are urgently needed. IGFBP7, known to play various roles in multiple tumours, is complexly regulated across diverse cancer types, as evidenced by our pancancer analysis. Bioinformatics analysis revealed that IGFBP7 expression was related to patient prognosis, tumour clinicopathological characteristics, tumour stemness, microsatellite instability and immune cell infiltration, as well as the expression of oncogenes and immune checkpoints. GSEA links IGFBP7 to several cancer-related pathways. IGFBP7 deficiency inhibited GC cell proliferation and migration in vitro. Furthermore, an in vivo nude mouse model revealed that IGFBP7 downregulation suppressed the tumorigenesis of GC cells. Western blotting analysis showed that the JAK1/2-specific inhibitor ruxolitinib could rescue alterations induced by IGFBP7 overexpression in GC cells. Additionally, our bioinformatics analysis and in vitro assays suggested that IGFBP7 is regulated by DNA methylation at the genetic level and that the RNA m6A demethylase FTO modulates it at the posttranscriptional level. This study emphasizes the clinical relevance of IGFBP7 in GC and its influence on cell proliferation and migration via the JAK/STAT signalling pathway. This study also highlights the regulation of IGFBP7 in GC by DNA and m6A RNA methylation.
Asunto(s)
Movimiento Celular , Proliferación Celular , Metilación de ADN , Regulación Neoplásica de la Expresión Génica , Proteínas de Unión a Factor de Crecimiento Similar a la Insulina , Factores de Transcripción STAT , Transducción de Señal , Neoplasias Gástricas , Neoplasias Gástricas/patología , Neoplasias Gástricas/genética , Neoplasias Gástricas/metabolismo , Humanos , Movimiento Celular/genética , Proteínas de Unión a Factor de Crecimiento Similar a la Insulina/metabolismo , Proteínas de Unión a Factor de Crecimiento Similar a la Insulina/genética , Animales , Ratones , Línea Celular Tumoral , Factores de Transcripción STAT/metabolismo , Ratones Desnudos , Quinasas Janus/metabolismo , Femenino , Masculino , Metilación de ARNRESUMEN
Deep learning technology can improve sensing efficiency and has the ability to discover potential patterns in data; the efficiency of user behavior recognition in the field of smart homes has been further improved, making the recognition process more intelligent and humanized. This paper analyzes the optical sensors commonly used in smart homes and their working principles through case studies and explores the technical framework of user behavior recognition based on optical sensors. At the same time, CiteSpace (Basic version 6.2.R6) software is used to visualize and analyze the related literature, elaborate the main research hotspots and evolutionary changes of optical sensor-based smart home user behavior recognition, and summarize the future research trends. Finally, fully utilizing the advantages of cloud computing technology, such as scalability and on-demand services, combining typical life situations and the requirements of smart home users, a smart home data collection and processing technology framework based on elderly fall monitoring scenarios is designed. Based on the comprehensive research results, the application and positive impact of optical sensors in smart home user behavior recognition were analyzed, and inspiration was provided for future smart home user experience research.
