Feasibility of computed tomography-derived surgical margin assessment in an ex vivo sublobar lung resection model.

Objectives: Computed tomography imaging of a sublobar resection specimen may inform intraoperative surgical margin assessment. However, consistency with final pathological margins has not been previously evaluated. In this study, we investigated the concordance between surgical margin measurements by computed tomography versus pathology measurements using an ex vivo sublobar lung resection model.

Deep learning-based prediction of nodal metastasis in lung cancer using endobronchial ultrasound.

Objective: Endobronchial ultrasound-guided transbronchial needle aspiration is a vital tool for mediastinal and hilar lymph node staging in patients with lung cancer. Despite its high diagnostic performance and safety, it has a limited negative predictive value. Our objective was to evaluate the diagnostic performance of deep learning-based prediction of lung cancer lymph node metastases using convolutional neural networks developed from automatically extracted images of endobronchial ultrasound videos without supervision of the lymph node location.

Comparison of forced and voluntary exercise types on male rat brain monoamine levels, anxiety-like behaviour, and physiological indexes under light and dark phases.

Purpose: Physical exercise improves physical and mental health; however, the differences between voluntary and forced exercise protocols are unclear. In addition, knowledge regarding the consequences of differences in testing timing, such as light and dark phases, in response to exercise type is limited. We investigated the effects of chronic forced and voluntary wheel running on the changes in brain monoamine levels (5-HT: serotonin, DA: dopamine, NA: noradrenaline), anxiety-like behaviours, and physiological stress responses in the light and dark phases.