RESUMEN
Glioblastoma (GBM) is an extremely aggressive tumor associated with a poor prognosis that impacts the central nervous system. Increasing evidence suggests an inherent association between glucose metabolism dysregulation and the aggression of GBM. Polo-like kinase 4 (PLK4), a highly conserved serine/threonine protein kinase, was found to relate to glioma progression and unfavorable prognosis. As revealed by the integration of proteomics and phosphoproteomics, PLK4 was found to be involved in governing metabolic processes and the PI3K/AKT/mTOR pathway. For the first time, this study supports evidence demonstrating that PLK4 activated PI3K/AKT/mTOR signaling through direct binding to AKT1 and subsequent phosphorylating AKT1 at S124, T308, and S473 to promote tumorigenesis and glucose metabolism in glioma. In addition, PLK4-mediated phosphorylation of AKT1 S124 significantly augmented the phosphorylation of AKT1 S473. Therefore, PLK4 exerted an influence on glucose metabolism by stimulating PI3K/AKT/mTOR signaling. Additionally, the expression of PLK4 protein exhibited a positive correlation with AKT1 phosphorylation in glioma patient tissues. These findings highlight the pivotal role of PLK4-mediated phosphorylation of AKT1 in glioma tumorigenesis and dysregulation of glucose metabolism.
Asunto(s)
Glioblastoma , Glioma , Naftalenos , Piperazinas , Humanos , Proteínas Proto-Oncogénicas c-akt/metabolismo , Fosfatidilinositol 3-Quinasas/metabolismo , Serina-Treonina Quinasas TOR/metabolismo , Glioma/genética , Glioma/patología , Fosforilación , Glioblastoma/patología , Carcinogénesis , Transformación Celular Neoplásica , Glucosa , Proteínas Serina-Treonina Quinasas/metabolismoRESUMEN
This paper presents an innovative approach for predicting timing errors tailored to near-/sub-threshold operations, addressing the energy-efficient requirements of digital circuits in applications, such as IoT devices and wearables. The method involves assessing deep path activity within an adjustable window prior to the root clock's rising edge. By dynamically adapting the prediction window and supply voltage based on error detection outcomes, the approach effectively mitigates false predictions-an essential concern in low-voltage prediction techniques. The efficacy of this strategy is demonstrated through its implementation in a near-/sub-threshold 32-bit microprocessor system. The approach incurs only a modest 6.84% area overhead attributed to well-engineered lightweight design methodologies. Furthermore, with the integration of clock gating, the system functions seamlessly across a voltage range of 0.4 V-1.2 V (5-100 MHz), effectively catering to adaptive energy efficiency. Empirical results highlight the potential of the proposed strategy, achieving a significant 46.95% energy reduction at the Minimum Energy Point (MEP, 15 MHz) compared to signoff margins. Additionally, a 19.75% energy decrease is observed compared to the zero-margin operation, demonstrating successful realization of negative margins.
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Introduction: The similarity between ankylosing spondylitis (AS) and ulcerative colitis (UC) in incidence rate and pathogenesis has been revealed. But the common pathogenesis that explains the relationship between AS and UC is still lacked, and the related genetic research is limited. We purposed to explore shared biomarkers and pathways of AS and UC through integrated bioinformatics. Methods: Gene expression data of AS and UC were obtained in the GEO database. We applied weighted gene co-expression network analysis (WGCNA) to identify AS-related and UC-related co-expression gene modules. Subsequently, machine learning algorithm was used to further screen hub genes. We validated the expression level and diagnostic efficiency of the shared diagnostic gene of AS and UC in external datasets. Gene set enrichment analysis (GSEA) was applied to analyze pathway-level changes between disease group and normal group. Finally, we analyzed the relationship between hub biomarker and immune microenvironment by using the CIBERSORT deconvolution algorithm. Results: 203 genes were obtained by overlapping AS-related gene module and UC-related gene module. Through SVM-RFE algorithm, 19 hub diagnostic genes were selected for AS in GSE25101 and 6 hub diagnostic genes were selected for UC in GSE94648. KCNJ15 was obtained as a common diagnostic gene of AS and UC. The expression of KCNJ15 was validated in independent datasets, and the results showed that KCNJ15 were similarly upregulated in AS samples and UC samples. Besides, ROC analysis also revealed that KCNJ15 had good diagnostic efficacy. The GSEA analysis revealed that oxidative phosphorylation pathway was the shared pathway of AS and UC. In addition, CIBERSORT results revealed the correlation between KCNJ15 gene and immune microenvironment in AS and UC. Conclusion: We have explored a common diagnostic gene KCNJ15 and a shared oxidative phosphorylation pathway of AS and UC through integrated bioinformatics, which may provide a potential diagnostic biomarker and novel insight for studying the mechanism of AS-related UC.
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Rhinoplasty focuses on the establishment of the structural support of nasal cartilage and the shaping of the nasal tip. The purpose of this study was to explore the application of "double tower" folding ear cartilage transplantation for nasal tip shaping in rhinoplasty.