Seed implant brachytherapy (SIBT) is a promising treatment modality for parotid gland cancers (PGCs). However, the current clinical standard dose calculation method based on the American Association of Physicists in Medicine (AAPM) Task Group 43 (TG-43) Report oversimplifies patient anatomy as a homogeneous water phantom medium, leading to significant dose calculation errors due to heterogeneity surrounding the parotid gland. Monte Carlo Simulation (MCS) can yield accurate dose distributions but the long computation time hinders its wide application in clinical practice.
Through the thorough exploration of the adaptive filter structure and the LMS adaptive filter algorithm, the filter performance of the adaptive filter algorithm can be clearly mastered. The solution formula of LMS algorithm is based on it, and DSP software programming and Matlab simulation programming methods are used to lay the foundation for the effective implementation of LMS algorithm. Therefore, based on the adaptive filtering algorithm, the embedded software simulation development system is analyzed to help the application of adaptive filtering theory.
Abstract Objective As a single‐transmembrane protein of the FXYD family, FXYD6 plays different roles under physiological and pathological status, especially in the nervous system. This study aims to identify FXYD6 as a biomarker for glioma, by analyzing its expression and methylation patterns. Methods Using TCGA and GTEx datasets, we analyzed FXYD6 expression in various tissues, confirming its levels in normal brain and different glioma grades via immunoblotting and immunostaining. FXYD6 biological functions were explored through enrichment analysis, and tumor immune infiltration was assessed using ESTIMATE and TIMER algorithms. Pearson correlation analysis probed FXYD6 associations with biological function‐related genes. A glioma detection model was developed using FXYD6 methylation data from TCGA and GEO. Consistently, a FXYD6 methylation‐based prognostic model was constructed for glioma via LASSO Cox regression. Results FXYD6 was observed to be downregulated in GBM and implicated in a range of cellular functions, including synapse formation, cell junctions, immune checkpoint, ferroptosis, EMT, and pyroptosis. Hypermethylation of specific FXYD6 CpG sites in gliomas was identified, which could be used to build a diagnostic model. Additionally, FXYD6 methylation‐based prognostic model could serve as an independent factor as well. Conclusions FXYD6 is a promising biomarker for the diagnosis and prognosis of glioma, with its methylation‐based prognostic model serving as an independent factor. This highlights its potential in clinical application for glioma management.
Conventional Monte Carlo methods are often used to solve some hard second kind Fredholm integral equations such as the difficult global illumination problems due to its dimensional independence. However, the convergence rate of the quasi-Monte Carlo methods for numerical integration is superior to that of the Monte Carlo methods. We present two mixed strategies that make use of both the statistical properties of random numbers and the uniformity properties of quasi-random numbers to build up walk histories for solving the global illumination. In the framework of the proposed strategies, experimental results have been obtained from rendering the test scenes. The computations indicate that the mixed strategies can outperform Monte Carlo or quasi-Monte Carlo used alone.
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