Profound skeletal muscle loss can lead to severe disability and cosmetic deformities. Mesenchymal stem cell (MSC)-derived exosomes have shown potential as an effective therapeutic tool for tissue regeneration. This study aimed to determine the regenerative capacity of MSC-derived exosomes for skeletal muscle regeneration. Exosomes were isolated from human adipose tissue-derived MSCs (AD-MSCs). The effects of MSC-derived exosomes on satellite cells were investigated using cell viability, relevant genes, and protein analyses. Moreover, NOD-SCID mice were used and randomly assigned to the healthy control (n = 4), muscle defect (n = 6), and muscle defect + exosome (n = 6) groups. Muscle defects were created using a biopsy punch on the quadriceps of the hind limb. Four weeks after the surgery, the quadriceps muscles were harvested, weighed, and histologically analyzed. MSC-derived exosome treatment increased the proliferation and expression of myocyte-related genes, and immunofluorescence analysis for myogenin revealed a similar trend. Histologically, MSC-derived exosome-treated mice showed relatively preserved shapes and sizes of the muscle bundles. Immunohistochemical staining revealed greater expression of myogenin and myoblast determination protein 1 in the MSC-derived exosome-treated group. These results indicate that exosomes extracted from AD-MSCs have the therapeutic potential for skeletal muscle regeneration.

Ascites cytology is a cost-effective test for metastatic colorectal cancer (CRC) in the abdominal cavity. However, metastatic carcinoma of the peritoneum is difficult to diagnose based on biopsy findings, and ascitic aspiration cytology has a low sensitivity and specificity and a high inter-observer variability. The aim of the present study was to apply artificial intelligence (AI) to classify benign and malignant cells in ascites cytology patch images of metastatic CRC using a deep convolutional neural network. Datasets were collected from The OPEN AI Dataset Project, a nationwide cytology dataset for AI research. The numbers of patch images used for training, validation, and testing were 56,560, 7068, and 6534, respectively. We evaluated 1041 patch images of benign and metastatic CRC in the ascitic fluid to compare the performance of pathologists and an AI algorithm, and to examine whether the diagnostic accuracy of pathologists improved with the assistance of AI. This AI method showed an accuracy, a sensitivity, and a specificity of 93.74%, 87.76%, and 99.75%, respectively, for the differential diagnosis of malignant and benign ascites. The diagnostic accuracy and sensitivity of the pathologist with the assistance of the proposed AI method increased from 86.8% to 90.5% and from 73.3% to 79.3%, respectively. The proposed deep learning method may assist pathologists with different levels of experience in diagnosing metastatic CRC cells of ascites.

Kim SW, et al. J Korean Assoc Oral Maxillofac Surg. 2018 Oct;44(5):242-247. https://doi.org/10.5125/jkaoms.2018.44.5.242

An important objective of vascularized tissue regeneration is to develop agents for osteonecrosis. We aimed to identify the pro-angiogenic and osteogenic efficacy of adipose tissue-derived (AD) pericytes combined with Nel-like protein-1 (NELL-1) to investigate the therapeutic effects on osteonecrosis. Tube formation and cell migration were assessed to determine the pro-angiogenic efficacy. Vessel formation was evaluated in vivo using the chorioallantoic membrane assay. A mouse model with a 2.5 mm necrotic bone fragment in the femoral shaft was used as a substitute for osteonecrosis in humans. Bone formation was assessed radiographically (plain radiographs, three-dimensional images, and quantitative analyses), and histomorphometric analyses were performed. To identify factors related to the effects of NELL-1, analysis using microarrays, qRT-PCR, and Western blotting was performed. The results for pro-angiogenic efficacy evaluation identified synergistic effects of pericytes and NELL-1 on tube formation, cell migration, and vessel formation. For osteogenic efficacy analysis, the mouse model for osteonecrosis was treated in combination with pericytes and NELL-1, and the results showed maximum bone formation using radiographic images and quantitative analyses, compared with other treatment groups and showed robust bone and vessel formation using histomorphometric analysis. We identified an association between FGF2 and the effects of NELL-1 using array-based analysis. Thus, combinatorial therapy using AD pericytes and NELL-1 may have potential as a novel treatment for osteonecrosis.

Yu Kyung Jun, Nayoung Kim, Hyuk Yoon, Ji Hyun Park, Hyung Kyung Kim, Yonghoon Choi, Ji Ae Lee, Cheol Min Shin, Young Soo Park, Dong Ho Lee. Gut and Liver -0001;0:. https://doi.org/10.5009/gnl230283