Thyroid Nodule Classification in Ultrasound Images by Fine-Tuning Deep Convolutional Neural Network.

With many thyroid nodules being incidentally detected, it is important to identify as many malignant nodules as possible while excluding those that are highly likely to be benign from fine needle aspiration (FNA) biopsies or surgeries. This paper presents a computer-aided diagnosis (CAD) system for classifying thyroid nodules in ultrasound images. We use deep learning approach to extract features from thyroid ultrasound images. Ultrasound images are pre-processed to calibrate their scale and remove the artifacts. A pre-trained GoogLeNet model is then fine-tuned using the pre-processed image samples which leads to superior feature extraction. The extracted features of the thyroid ultrasound images are sent to a Cost-sensitive Random Forest classifier to classify the images into "malignant" and "benign" cases. The experimental results show the proposed fine-tuned GoogLeNet model achieves excellent classification performance, attaining 98.29% classification accuracy, 99.10% sensitivity and 93.90% specificity for the images in an open access database (Pedraza et al. 16), while 96.34% classification accuracy, 86% sensitivity and 99% specificity for the images in our local health region database.

Rapamycin reduces fibroblast proliferation without causing quiescence and induces STAT5A/B-mediated cytokine production.

Rapamycin is a well-known inhibitor of the Target of Rapamycin (TOR) signaling cascade; however, the impact of this drug on global genome function and organization in normal primary cells is poorly understood. To explore this impact, we treated primary human foreskin fibroblasts with rapamycin and observed a decrease in cell proliferation without causing cell death. Upon rapamycin treatment chromosomes 18 and 10 were repositioned to a location similar to that of fibroblasts induced into quiescence by serum reduction. Although similar changes in positioning occurred, comparative transcriptome analyses demonstrated significant divergence in gene expression patterns between rapamycin-treated and quiescence-induced fibroblasts. Rapamycin treatment induced the upregulation of cytokine genes, including those from the Interleukin (IL)-6 signaling network, such as IL-8 and the Leukemia Inhibitory Factor (LIF), while quiescent fibroblasts demonstrated up-regulation of genes involved in the complement and coagulation cascade. In addition, genes significantly up-regulated by rapamycin treatment demonstrated increased promoter occupancy of the transcription factor Signal Transducer and Activator of Transcription 5A/B (STAT5A/B). In summary, we demonstrated that the treatment of fibroblasts with rapamycin decreased proliferation, caused chromosome territory repositioning and induced STAT5A/B-mediated changes in gene expression enriched for cytokines.