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您的检索式：作者名="Natalia Usman"
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| 1 | Multipotent stromal cells stimulate liver regeneration by influencing the macrophage polarization in rat显示文摘AIM To investigate the influence of the umbilical cordderived multipotent stromal cells(MSCs) on recovery of the liver after the subtotal resection, that is, removal of 80% of the organ mass, a renowned model of the small-for-size liver remnant syndrome. METHODS The MSCs were obtained from the intervascular tissue of umbilical cords, dissected from rat fetuses, by the explant culture technique. The vital labeling of MSCs with РКН26 was carried out on the 3 rd passage. The subtotal resection was performed on male Sprague-Dawley rats. The experimental group animals received a transplant 106 MSCs infused into the spleen. Hepatocyte proliferation was assessed by counting of either mitotic figures or Ki67-positive cells in microscopic images. MSC differentiation was assessed with antibodies to hepatocyte-specific marker cytokeratin 18(CK18), cholangiocyte-specific protein CK19, smooth muscle cell-specific protein α-SMA, the endothelial cell marker CD31, or the active fibroblast marker FAPα. Total macrophages of the liver were selectively stained in cryosections incubated with antiCD68 antibodies(1:100, Abcam), while the M2 a and M2 c macrophage populations were selectively stained with anti-CD206 antibodies. Expression of interleukin and growth factor genes was evaluated with PCR-RT.RESULTS Intrasplenic allogeneic transplantation of the umbilical cord-derived multipotent stromal cells stimulates reparative processes within the residual liver tissue after subtotal resection(removal of 80% of the organ mass), as indicated by increased rates of hepatocyte proliferation and accelerated organ mass recovery. These effects may result from paracrine influence of the transplanted cells on the resident macrophage population of the liver. The transplantation favors polarization of macrophages to M2 phenotype(the M2-polarized macrophages specifically express CD206; they are known to suppress inflammation and support tissue repair). No differentiation of the transplanted cells into any of the liver cell types have been observed in the study.CONCLUSION We found no direct evidence for the paracrine effect of MSCs on liver regeneration after the subtotal liver resection in rats. However, the paracrine mechanism of the therapeutic activity of transplanted MSC is indirectly indicated by a decrease in the total number of CD68 + macrophages and an increase in the proportion of M2 pro-repair macrophages in the regenerating liver as compared to animals in which the transplantation was only mimicked. | Andrey Elchaninov Timur Fatkhudinov Natalia Usman Irina Arutyunyan Andrey Makarov Anastasia Lokhonina Irina Eremina Viktor Surovtsev Dmitry Goldshtein Galina Bolshakova Valeria Glinkina Gennady Sukhikh | 2018 | World Journal of Hepatology2018，10，2： | 2 |
| 2 | Chest Radiographs Based Pneumothorax Detection Using Federated Learning显示文摘Pneumothorax is a thoracic condition that occurs when a person’s lungs collapse,causing air to enter the pleural cavity,the area close to the lungs and chest wall.The most persistent disease,as well as one that necessitates particular patient care and the privacy of their health records.The radiologists find it challenging to diagnose pneumothorax due to the variations in images.Deep learning-based techniques are commonly employed to solve image categorization and segmentation problems.However,it is challenging to employ it in the medical field due to privacy issues and a lack of data.To address this issue,a federated learning framework based on an Xception neural network model is proposed in this research.The pneumothorax medical image dataset is obtained from the Kaggle repository.Data preprocessing is performed on the used dataset to convert unstructured data into structured information to improve the model’s performance.Min-max normalization technique is used to normalize the data,and the features are extracted from chest Xray images.Then dataset converts into two windows to make two clients for local model training.Xception neural network model is trained on the dataset individually and aggregates model updates from two clients on the server side.To decrease the over-fitting effect,every client analyses the results three times.Client 1 performed better in round 2 with a 79.0%accuracy,and client 2 performed better in round 2 with a 77.0%accuracy.The experimental result shows the effectiveness of the federated learning-based technique on a deep neural network,reaching a 79.28%accuracy while also providing privacy to the patient’s data. | Ahmad Almadhor Arfat Ahmad Khan Chitapong Wechtaisong Iqra Yousaf Natalia Kryvinska Usman Tariq Haithem Ben Chikha | 2023 | Computer Systems Science & Engineering2023，47，11： | 0 |
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