ObjectivesA radiomics-based explainable eXtreme Gradient Boosting (XGBoost) model was developed to predict central cervical lymph node metastasis (CCLNM) in patients with papillary thyroid carcinoma (PTC), including positive and negative effects.MethodsA total of 587 PTC patients admitted at Binzhou Medical University Hospital from 2017 to 2021 were analyzed retrospectively. The patients were randomized into the training and test cohorts with an 8:2 ratio. Radiomics features were extracted from ultrasound images of the primary PTC lesions. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator regression were used to select CCLNM positively-related features and radiomics scores were constructed. Clinical features, ultrasound features, and radiomics score were screened out by the Boruta algorithm, and the XGBoost model was constructed from these characteristics. SHapley Additive exPlanations (SHAP) was used for individualized and visualized interpretation. SHAP addressed the cognitive opacity of machine learning models.ResultsEleven radiomics features were used to calculate the radiomics score. Five critical elements were used to build the XGBoost model: capsular invasion, radiomics score, diameter, age, and calcification. The area under the curve was 91.53% and 90.88% in the training and test cohorts, respectively. SHAP plots showed the influence of each parameter on the XGBoost model, including positive (i.e., capsular invasion, radiomics score, diameter, and calcification) and negative (i.e., age) impacts. The XGBoost model outperformed the radiologist, increasing the AUC by 44%.ConclusionsThe radiomics-based XGBoost model predicted CCLNM in PTC patients. Visual interpretation using SHAP made the model an effective tool for preoperative guidance of clinical procedures, including positive and negative impacts.
Transcriptional enhanced associate domain (TEAD) proteins together with their transcriptional coactivator yesassociated protein (YAP) and transcriptional coactivator with the PDZ-binding motif (TAZ) are important transcription factors and cofactors that regulate gene expression in the Hippo pathway. In mammals, the TEAD families have four homologues: TEAD1 (TEF-1), TEAD2 (TEF-4), TEAD3 (TEF-5), and TEAD4 (TEF-3). Aberrant expression and hyperactivation of TEAD/YAP signaling have been implicated in a variety of malignancies. Recently, TEADs were recognized as being palmitoylated in cells, and the lipophilic palmitate pocket has been successfully targeted by both covalent and noncovalent ligands. In this report, we present the medicinal chemistry effort to develop MYF-03-176 (compound 22) as a selective, cysteine-covalent TEAD inhibitor. MYF-03-176 (compound 22) significantly inhibits TEAD-regulated gene expression and proliferation of the cell lines with TEAD dependence including those derived from mesothelioma and liposarcoma.
The American Academy of Pediatrics has previously expressed concerns about the thematic content of television (TV) and the amount of time children spend viewing TV. The objective of this study was to determine the positive and negative themes depicted in a select number of TV shows targeted toward adolescents. We analyzed the thematic content depicted in the first season of 26 Netflix TV shows. The mean occurrences/h for positive and negative themes were 39.53 and 47.20, respectively. The most common positive themes were “encouragement from a friend/peer,” “demonstrating honesty,” and “staying true to oneself” (5.98, 5.38, and 3.72 mean occurrences/h, respectively). The most common negative themes were “dishonesty,” “cursing,” and “selfishness,” (5.30, 4.96, and 4.85 mean occurrences/h, respectively). We suggest that health care providers become aware of TV thematic content and promote media education, and we encourage co-viewing and active mediation by parents/guardians with their children.
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