Exploring vimentin's role in breast cancer via PICK1 alternative polyadenylation and the miR-615-3p-PICK1 interaction.

Breast cancer continues to be a major health issue for women worldwide, with vimentin (VIM) identified as a crucial factor in its progression due to its role in cell migration and the epithelial-to-mesenchymal transition (EMT). This study focuses on elucidating VIM's regulatory mechanisms on the miR-615-3p/PICK1 axis. Utilizing the 4T1 breast cancer cell model, we first used RNA-seq and proteomics to investigate the changes in the APA of PICK1 following VIM knockout (KO).

Developing a Computational Phenotype of the Fourth Universal Definition of Myocardial Infarction for Inpatients.

: The fourth universal definition of myocardial infarction (MI) introduced the differentiation of acute myocardial injury from MI. In this study, we developed a computational phenotype for distinct identification of acute myocardial injury and MI within electronic medical records (EMRs). : Two cohorts were used from a Calgary-wide EMR system: a chart review of 3042 randomly selected inpatients from Dec 2014 to Jun 2015; and 11,685 episodes of care that included cardiac catheterization from Jan 2013 to Apr 2017.

Paravertebral muscle degeneration affects coronal balance in patients with degenerative lumbar scoliosis.

Purpose: This study aimed to investigate the impact of paraspinal muscle (PSM) degeneration on coronal balance in patients with degenerative lumbar scoliosis (DLS) METHODS: In this retrospective cross-sectional study, 127 DLS patients who underwent spinal fusion surgery were reviewed. Preoperative X-rays and MRIs were used to assess PSM degeneration, measured by the cross-sectional area (CSA) and fat infiltration rate (FIR) of the multifidus (MF) and erector spinae (ES) muscles. The ratios of the convex to concave sides, namely RCSA and RFIR, were calculated.

Prediction of real-time cine-MR images during MRI-guided radiotherapy of liver cancer using a GAN-ConvLSTM network.

Background: Respiratory motion during radiotherapy (RT) may reduce the therapeutic effect and increase the dose received by organs at risk. This can be addressed by real-time tracking, where respiration motion prediction is currently required to compensate for system latency in RT systems. Notably, for the prediction of future images in image-guided adaptive RT systems, the use of deep learning has been considered.