Lung cancer has the highest mortality rate among all malignant tumors. The key to reducing lung cancer mortality is the accurate diagnosis of pulmonary nodules in early-stage lung cancer. Computer-aided diagnostic techniques are considered to have potential beyond human experts for accurate diagnosis of early pulmonary nodules. The detection and classification of pulmonary nodules based on deep learning technology can continuously improve the accuracy of diagnosis through self-learning, and is an important means to achieve computer-aided diagnosis. First, we systematically introduced the application of two dimension convolutional neural network (2D-CNN), three dimension convolutional neural network (3D-CNN) and faster regions convolutional neural network (Faster R-CNN) techniques in the detection of pulmonary nodules. Then we introduced the application of 2D-CNN, 3D-CNN, multi-stream multi-scale convolutional neural network (MMCNN), deep convolutional generative adversarial networks (DCGAN) and transfer learning technology in classification of pulmonary nodules. Finally, we conducted a comprehensive comparative analysis of different deep learning methods in the detection and classification of pulmonary nodules.
Deep Learning ; Humans ; Multiple Pulmonary Nodules ; Neural Networks, Computer ; Solitary Pulmonary Nodule ; Tomography, X-Ray Computed

Alzheimer's disease (AD) is a leading cause of dementia in the elderly. Mitogen-activated protein kinase phosphatase 1 (MKP-1) plays a neuroprotective role in AD. However, the molecular mechanisms underlying the effects of MKP-1 on AD have not been extensively studied. MicroRNAs (miRNAs) regulate gene expression at the post-transcriptional level, thereby repressing mRNA translation. Here, we reported that the microRNA-429-3p (miR-429-3p) was significantly increased in the brain of APP23/PS45 AD model mice and N2A^APP AD model cells. We further found that miR-429-3p could downregulate MKP-1 expression by directly binding to its 3'-untranslated region (3' UTR). Inhibition of miR-429-3p by its antagomir (A-miR-429) restored the expression of MKP-1 to a control level and consequently reduced the amyloidogenic processing of APP and Aβ accumulation. More importantly, intranasal administration of A-miR-429 successfully ameliorated the deficits of hippocampal CA1 long-term potentiation and spatial learning and memory in AD model mice by suppressing extracellular signal-regulated kinase (ERK1/2)-mediated GluA1 hyperphosphorylation at Ser831 site, thereby increasing the surface expression of GluA1-containing α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs). Together, these results demonstrate that inhibiting miR-429-3p to upregulate MKP-1 effectively improves cognitive and synaptic functions in AD model mice, suggesting that miR-429/MKP-1 pathway may be a novel therapeutic target for AD treatment.