Constructing a Classification Model for Cervical Cancer Tumor Tissue and Normal Tissue Based on CT Radiomics.

This study aimed to develop an automated classification framework for distinguishing between cervical cancer tumor and normal uterine tissue, leveraging CT images for radiomics feature extraction. We retrospectively analyzed CT images from 117 cervical cancer patients. To distinguish between cancerous and healthy tissue, we segmented gross tumor volume and normal uterine tissue as distinct regions of interest (ROIs) using manual segmentation techniques.

The association between non-Hodgkin lymphoma and methylation of p73.

To investigate the effects of methylation of the p73 gene on the pathogenesis of non-Hodgkin lymphoma (NHL), the methylation status of the p73 gene promoter and the expression of p73 mRNA were examined in NHLs by methylation-specific polymerase chain reaction (MSP) and reverse transcription-polymerase chain reaction, respectively; p73 protein was detected by Western blotting analysis. Furthermore, the expression of p73 mRNA in NHL cells treated with 5-Aza-2'-deoxycytidine was analyzed. MSP results revealed that the promoter of p73 was methylated in 87.