Exosomes are small membrane vesicles that measure 20 to 100 nm in diameter and are released by many cell types, including lymphocytes, dendritic cells (DCs) and tumor cells. As efficient messengers in cell-to-cell communication, exosomes released by tumors play an important role in regulating tumor malignancy. Tumor-derived exosomes contain proteins, mRNAs, and miRNAs, which can be delivered between different types of cells and even transferred to distant locations to influence the biological activities of tumors, such as proliferation, invasion and metastasis, immunoregulation, generation of a premetastatic niche and stimulation of angiogenesis. This review highlights advances in the understanding of exosome secretion and the role of exosomes in cancer molecular behavior. Moreover, we also discuss the potential clinical application of exosomes as biomarkers and therapeutic tools. Tumor-derived exosomes may represent a target for therapeutic intervention and for the development of early diagnostic biomarkers.

Background: Colorectal cancer is harmful to the patient's life. The treatment of patients is determined by accurate preoperative staging. Magnetic resonance imaging (MRI) played an important role in the preoperative examination of patients with rectal cancer, and artificial intelligence (AI) in the learning of images made significant achievements in recent years. Introducing AI into MRI recognition, a stable platform for image recognition and judgment can be established in a short period. This study aimed to establish an automatic diagnostic platform for predicting preoperative T staging of rectal cancer through a deep neural network. Methods: A total of 183 rectal cancer patients’ data were collected retrospectively as research objects. Faster region-based convolutional neural networks (Faster R-CNN) were used to build the platform. And the platform was evaluated according to the receiver operating characteristic (ROC) curve. Results: An automatic diagnosis platform for T staging of rectal cancer was established through the study of MRI. The areas under the ROC curve (AUC) were 0.99 in the horizontal plane, 0.97 in the sagittal plane, and 0.98 in the coronal plane. In the horizontal plane, the AUC of T1 stage was 1, AUC of T2 stage was 1, AUC of T3 stage was 1, AUC of T4 stage was 1. In the coronal plane, AUC of T1 stage was 0.96, AUC of T2 stage was 0.97, AUC of T3 stage was 0.97, AUC of T4 stage was 0.97. In the sagittal plane, AUC of T1 stage was 0.95, AUC of T2 stage was 0.99, AUC of T3 stage was 0.96, and AUC of T4 stage was 1.00. Conclusion: Faster R-CNN AI might be an effective and objective method to build the platform for predicting rectal cancer T-staging. Trial registration: chictr.org.cn: ChiCTR1900023575; http://www.chictr.org.cn/showproj.aspx?proj=39665 .

Nicotinamide adenine dinucleotide (NAD+) is a critical metabolite that acts as a cofactor in energy metabolism, and serves as a cosubstrate for non-redox NAD+-dependent enzymes, including sirtuins, CD38 and poly(ADP-ribose) polymerases. NAD+ metabolism can regulate functionality attributes of innate and adaptive immune cells and contribute to inflammatory responses. Thus, the manipulation of NAD+ bioavailability can reshape the courses of immunological diseases. Here, we review the basics of NAD+ biochemistry and its roles in the immune response, and discuss current challenges and the future translational potential of NAD+ research in the development of therapeutics for inflammatory diseases, such as COVID-19.

Introduction: This study evaluated the accuracy of endoscopic ultrasound (EUS) for preoperative staging of rectal cancer and guiding the treatment of transanal endoscopic microsurgery (TEM) in early rectal cancer. Material and methods: One-hundred-twenty-six patients with rectal cancer were staged preoperatively using EUS and the results were compared with postoperative histopathology results. Radical surgeries, including low anterior resection (LAR), abdominal-perineal resection (APR) and Hartmann surgeries, were performed on patients with advanced rectal cancers, and TEM was performed on patients with stage T1. The Kappa statistic was used to determine agreement between EUS-based staging and pathology staging. Results: The overall accuracies of EUS for T and N stage were 90.8% (Kappa ¼ 0.709) and 76.7% (Kappa ¼ 0.419), respectively. The accuracies of EUS for uT1, uT2, uT3, and uT4 stages were 96.8%, 92.1%, 84.1%, and 88.9%, respectively, and for uN0, uN1, and uN2 stages, they were 71.9%, 64.9%, and 93.0%, respectively. Twelve patients underwent TEM and received confirmed pathology results of early rectal cancer. After postoperative follow-up, there were no local recurrences or distant metastases. Conclusion: EUS is a good and comparable technique for postoperative staging of rectal cancer. Moreover, EUS is used as indicator for preoperative staging and tumor assessment strategy when considering TEM.

Background: This study aimed to establish a three-dimensional model of infrapyloric vessels using the Hisense computer-assisted surgery (CAS) system before the operation to understand blood vessel variation types and determine the group 6 lymph node (LN) metastasis status. Methods: One hundred and four gastric cancer patients were randomly assigned to a CAS group and a computed tomography (CT) group. Intraoperative and postoperative complications in the two groups were recorded. The number of group 6 LNs dissected and the metastasis status were compared between the groups. The independent risk factors influencing group 6 LN metastasis were determined by multiple logistic regression analysis. Results: In the 50 CAS group patients, the gastrocolic trunk of Henle was divided into a gastrocolic type (34.0%) and a gastropancreatic colonic type (66.0%); the right gastroepiploic artery was divided into a coarse blood supply type (24.0%) and a fine blood supply type (76.0%); and the relationship between the right gastroepiploic artery and right gastroepiploic vein was divided into an adjacent type (58.0%) and a separated type (42.0%). Although the difference was not significant, the CAS group had fewer cases of intraoperative gastrocolic trunk injury and postoperative pancreatic leakage in trend than the CT group. The CAS group had more dissected LNs (P < 0.001) and metastatic LNs (P ¼ 0.011) than the CT group; meanwhile, it had higher LN metastasis rate and LN metastasis degree in trend than the CT group. According to the multiple logistic regression model, tumor location and TNM stage were significantly correlated with group 6 LN metastases. Conclusions: By establishing a three-dimensional model of the infrapyloric vessels using the Hisense CAS system, we comprehensively determined the anatomic variations in each collateral vessel. The application of the Hisense CAS system significantly improved the number of LNs dissected and the discovery rate of LN metastases without increasing the incidence of complications.