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Automated coronary angiography assessment requires precise vessel segmentation, a task complicated by uneven contrast filling and background noise. Our research introduces an ensemble U-Net model, SE-RegUNet, designed to accurately segment coronary vessels using 100 labeled angiographies from angiographic images. SE-RegUNet incorporates RegNet encoders and squeeze-and-excitation blocks to enhance feature extraction. A dual-phase image preprocessing strategy further improves the model's performance, employing unsharp masking and contrast-limited adaptive histogram equalization. Following fivefold cross-validation and Ranger21 optimization, the SE-RegUNet 4GF model emerged as the most effective, evidenced by performance metrics such as a Dice score of 0.72 and an accuracy of 0.97. Its potential for real-world application is highlighted by its ability to process images at 41.6 frames per second. External validation on the DCA1 dataset demonstrated the model's consistent robustness, achieving a Dice score of 0.76 and an accuracy of 0.97. The SE-RegUNet 4GF model's precision in segmenting blood vessels in coronary angiographies showcases its remarkable efficiency and accuracy. However, further development and clinical testing are necessary before it can be routinely implemented in medical practice. [ABSTRACT FROM AUTHOR]

A growing body of studies has demonstrated that dysregulated splicing profiles constitute pivotal mechanisms for carcinogenesis. In this study, we identified discriminative splicing profiles of colorectal cancer (CRC) cells compared to adjacent normal tissues using deep RNA-sequencing (RNA-seq). The RNA-seq results and cohort studies indicated a relatively high ratio of exon 4-excluded neuro-oncological ventral antigen 1 (Nova1−4) and intron 2-retained SRSF6 (SRSF6+intron 2) transcripts in CRC tissues and cell lines. Nova1 variants exhibited differential effects on eliminating SRSF6 expression in CRC cells by inducing SRSF6+intron 2 transcripts which were considered to be the putative target of alternative splicing-coupled nonsense-mediated decay mechanism. Moreover, the splicing profile of vascular endothelial growth factor (VEGF)165/VEGF165b transcripts was relevant to SRSF6 expression, which manipulates the progression of CRC calls. These results highlight the novel and hierarchical role of an alternative splicing cascade that is involved in the development of CRC. [ABSTRACT FROM AUTHOR]