CT-based non-invasive identification of the most common gene mutation status in patients with non-small cell lung cancer.

Background: Epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) are mutually exclusive, and they are two important genes that are most prone to mutation in patients with non-small cell lung cancer.

Purpose: This retrospective study investigated the ability of radiomics to predict the mutation status of EGFR and KRAS in patients with non-small cell lung cancer (NSCLC) and guide precision medicine.

Methods: Computed tomography images of 1045 NSCLC patients from five different institutions were collected, and 1204 imaging features were extracted.

Genistein Alleviates High-Fat Diet-Induced Obesity by Inhibiting the Process of Gluconeogenesis in Mice.

Genistein is an isoflavone phytoestrogen that has been shown to improve obesity; however, the underlying molecular mechanisms involved therein have not been clearly elucidated. In this study, we administered genistein to high-fat diet-induced obese mice to investigate its effect on hepatic gluconeogenesis. The results showed that genistein treatment significantly inhibited body weight gain, hyperglycemia, and adipose and hepatic lipid deposition in high-fat diet-induced obese mice.

Deep learning predicts epidermal growth factor receptor mutation subtypes in lung adenocarcinoma.

Purpose: This study aimed to explore the predictive ability of deep learning (DL) for the common epidermal growth factor receptor (EGFR) mutation subtypes in patients with lung adenocarcinoma.

Methods: A total of 665 patients with lung adenocarcinoma (528/137) were recruited from two different institutions. In the training set, an 18-layer convolutional neural network (CNN) and fivefold cross-validation strategy were used to establish a CNN model.