Smed Schmidt (sizetoast75)

In this article, we reviewed studies on exosomes in the eye, with a special emphasis on RB. We also reviewed miRNAs expressed in RB tumor, serum, and cell lines and analyzed the targets of these miRNAs from the proteins identified in the RB tumor exosomes. hsa-miR-494 and hsa-miR-9, upregulated and downregulated, respectively in RB, have the maximum number of targets. Although oppositely regulated, they share the same targets in the proteins identified in RB tumor exosomes. Overall this review provides the up-to-date progress in the area of eye exosome research, with an emphasis on RB.Postmenopausal women tend to be susceptible to primary osteoporosis due to its association with oestrogen deficiency. There is emerging evidence that an unhealthy dietary pattern drives an increase in the risk of postmenopausal osteoporosis (PO), whereas a healthy dietary pattern may decrease its occurrence. In this narrative literature review, we sought to review the role of nutrient and dietary patterns in the pathogenesis of PO. Therefore, we searched and reported all research articles from 2001 to May 2020 in Web of Science, Cinahl and Scopus that have researched a relationship between nutrient and/or dietary patterns and postmenopausal osteoporosis. Nutrients such as calcium, phosphorus, magnesium and vitamin D have been proven to be beneficial for bone health. Meanwhile, for the dietary patterns, foods such as dairy products especially milk, fibre and protein-rich foods, e.g., meat were directly linked to a positive association with bone mineral density (BMD). Likewise, fruits, vegetables and probiotic and prebiotic foods were reported for its positive relationship with BMD. Therefore, aside from physical activity, nutrition and diet in adequate proportions are suggested to be an important tool for ameliorating osteoporosis and bone health issues in older age.Deep learning is currently the mainstream method of object detection. Faster region-based convolutional neural network (Faster R-CNN) has a pivotal position in deep learning. It has impressive detection effects in ordinary scenes. However, under special conditions, there can still be unsatisfactory detection performance, such as the object having problems like occlusion, deformation, or small size. This paper proposes a novel and improved algorithm based on the Faster R-CNN framework combined with the Faster R-CNN algorithm with skip pooling and fusion of contextual information. This algorithm can improve the detection performance under special conditions on the basis of Faster R-CNN. The improvement mainly has three parts The first part adds a context information feature extraction model after the conv5_3 of the convolutional layer; the second part adds skip pooling so that the former can fully obtain the contextual information of the object, especially for situations where the object is occluded and deformed; and the third part replaces the region proposal network (RPN) with a more efficient guided anchor RPN (GA-RPN), which can maintain the recall rate while improving the detection performance. The latter can obtain more detailed information from different feature layers of the deep neural network algorithm, and is especially aimed at scenes with small objects. Compared with Faster R-CNN, you only look once series (such as YOLOv3), single shot detector (such as SSD512), and other object detection algorithms, the algorithm proposed in this paper has an average improvement of 6.857% on the mean average precision (mAP) evaluation index while maintaining a certain recall rate. This strongly proves that the proposed method has higher detection rate and detection efficiency in this case.S-Carboxymethyl-L-cysteine (CMC) is an antioxidant and mucolytic commonly prescribed to patients with chronic obstructive pulmonary disease. In humans, CMC is rapidly metabolized to S-carboxymethyl-L-cysteine sulfoxide (CMCO). In this study, we assessed structural and functional similarities between CMC