Background. Long-term extensive use of glucocorticoids will lead to hormonal necrosis of the femoral head, and osteoblasts play an important role in the prevention of osteonecrosis. However, there is no complete cure for necrosis of the femoral head. Mesenchymal stem cell- (MSCs-) derived exosomes are widely used for the repair of various tissue lesions. Therefore, the aim of this study was to investigate the mechanism of dexamethasone- (DEX-) induced osteoblast apoptosis and the therapeutic effect of human umbilical cord MSC- (hucMSC-) derived exosome mimetic vesicles (EMVs) on osteoblast-induced apoptosis by DEX. Methods. The viability and apoptosis of primary MC3T3-E1 cells were determined by the Cell Counting Kit-8 (CCK-8), FITC-Annexin V/PI staining and immunoblot. The intracellular levels of reactive oxygen species (ROS) after DEX treatment were measured by 2, 7 -dichlorodihydrofluorescein diacetate (DCFH-DA) staining. In this study, hucMSC-EMVs and N-acetyl-l-cysteine (NAC) were used as therapeutic measures. The expression of B-cell lymphoma 2-associated X, Bcl 2, HO-1, and nuclear factor erythroid-derived 2-like 2 and MAPK- signaling pathway in osteogenic cell MC3T3-E1 cells treated with Dex was analyzed by the immunoblotting. Results. DEX significantly induced osteoblasts MC3T3-E1 apoptosis and ROS accumulation. MAPK-signaling pathway was activated in MC3T3-E1 after DEX treatment. hucMSC-EMVs intervention significantly downregulated DEX-induced MAPK-signaling pathway activation and ROS accumulation. In addition, hucMSC-EMVs can reduce the apoptosis levels in osteoblast MC3T3-E1 cells induced by DEX. Conclusions. Our study confirmed that hucMSC-EMVs regulates MAPK-signaling pathway and ROS levels to inhibit DEX-induced osteoblast apoptosis.

Introduction: Neuroblastoma (NB) is one of the most common extracranial solid malignant tumors in children. The 5-year survival rate of high-risk or refractory NB is less than 50%. Therefore, developing new effective therapeutics for NB remains an urgent challenge. Materials and Methods: Based on the NB dataset TARGET-NBL in the TCGA database, the prognosis-related genes were analyzed using univariate cox regression (p < 0.01). The protein network interaction of prognostic genes was analyzed using STRING to obtain 150 hub genes with HR > 1 and 150 hub genes with HR < 1. The Connectivity Map database was used to predict a therapeutic drug: BI-D1870, a ribosomal S6 kinase inhibitor. The inhibitory effect of BI-D1870 on NB was investigated through in vivo and in vitro experiments, and its inhibitory mechanism was explored. Results: Both the in vivo and in vitro experiments showed that BI-D1870 could inhibit tumor proliferation and induce tumor apoptosis. Furthermore, we proved that BI-D1870 caused G2/M phase arrest and mitosis damage in cells. RNA-seq of cells showed that BI-D1870 may inhibit the growth of NB by inhibiting the PI3K-Akt-mTOR axis. Western blot and immunofluorescence testing showed that BI-D1870 inhibited the PI3K-Akt-mTORC1 signal pathway to regulate the phosphorylation of RPS6 and 4E BP1 proteins, inhibit protein translation, and inhibit microtubule formation, thus preventing mitotic proliferation and inducing apoptosis. Conclusions: This study provides strong support that BI-D1870 may be a potential adjuvant therapy for NB.

Objective: Mucinous breast cancer (MBC) is a kind of breast cancer (BC), which is rare in clinic, mainly for women, because of the low incidence rate, so there is no unified standard treatment protocol. Elderly patients have a poor prognosis due to their combined comorbidities. This study aims to investigate the effect of surgery and chemoradiotherapy on the prognosis of elderly female MBC patients and construct nomograms for predicting the OS and CSS in elderly female MBC patients.Methods: Data for female MBC patients over 65 years are obtained from the Surveillance, Epidemiology and End Results (SEER) database, patients were divided into two groups: the training set and the validation set. External validation data of the prediction model were provided by Kunming Hospital of Traditional Chinese Medicine. We used Cox regression modeling, which was used to identify independent risk factors affecting patient prognosis. After avoiding confounding bias according to the multifactorial Cox regression model, we used these screened statistically significant results to construct column‐line plots. The performance of the model was tested using the consistency index (c‐index), the calibration curve, and the area under the operating characteristic curve of the receiver (AUC). Subsequently, we used decision curve analysis (DCA) to examine the potential clinical value of our nomograms.Results: A total of 8103 elderly MBC female patients were extracted from the database SEER and were assigned to the training and validation set, randomly. A total of 83 patients from Kunming Hospital of Traditional Chinese Medicine were used in the external verification set. After multifactorial Cox regression analysis, we found that age, race, T‐stage, M‐stage, surgical approach, radiotherapy, and tumor size were independent risk factors for OS in elderly MBC patients. Similarly, independent risk factors of CSS included age, marital status, N stage, M stage, surgical approach, chemotherapy, and tumor size. The C‐index for the OS training, validation, and external verification set were 0.731 (95%CI 0.715–0.747), 0.738 (95%CI 0.724–0.752), and 0.809 (95%CI 0.731–0.8874). The C‐index of the training set, the validation set, and external verification set for CSS were 0.786 (95%CI 0.747–0.825), 0.776 (95%CI 0.737–0.815), and 0.84 (95%CI0.754–0.926), respectively. The AUC, calibration curves and DCA also showed good accuracy.Conclusions: In this study, we construct a new nomogram to predict the prognosis of elderly patients with MBC. The nomograms have undergone internal and external validation and have been confirmed to have good clinical applicability. At the same time, we found that for elderly female MBC patients, surgery and radiotherapy significantly benefit their survival, but chemotherapy is not conducive to patient survival.

This study aimed to develop nomograms to accurately predict the overall survival (OS) and cancer-specific survival (CSS) of non-metastatic bladder cancer (BC) patients. Clinicopathological information of 260,412 non-metastatic BC patients was downloaded from the Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2020. LASSO method and Cox proportional hazard regression analysis were utilized to discover the independent risk factors, which were used to develop nomograms. The accuracy and discrimination of models were tested by the consistency index (C-index), the area under the subject operating characteristic curve (AUC) and the calibration curve. Decision curve analysis (DCA) was used to test the clinical value of nomograms compared with the TNM staging system. Nomograms predicting OS and CSS were constructed after identifying independent prognostic factors. The C-index of the training, internal validation and external validation cohort for OS was 0.722 (95%CI: 0.720–0.724), 0.723 (95%CI: 0.721–0.725) and 0.744 (95%CI: 0.677–0.811). The C-index of the training, internal validation and external validation cohort for CSS was 0.794 (95%CI: 0.792–0.796), 0.793 (95%CI: 0.789–0.797) and 0.879 (95%CI: 0.814–0.944). The AUC and the calibration curves showed good accuracy and discriminability. The DCA showed favorable clinical potential value of nomograms. Kaplan–Meier curve and log-rank test uncovered statistically significance survival difference between high- and low-risk groups. We developed nomograms to predict OS and CSS for non-metastatic BC patients. The models have been internally and externally validated with accuracy and discrimination and can assist clinicians to make better clinical decisions.