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Ewing's sarcoma is a high-grade malignancy bone and soft tissue tumor that most commonly occurs in children and adolescents. Although the overall prognosis of Ewing's sarcoma has improved, the 5-year survival rate has not improved significantly. The study aimed to determine the risk factors independently associated with the prognosis of Ewing's sarcoma and to construct a nomogram to predict patient survival. Patients diagnosed with Ewing's sarcoma were collected from the Surveillance, Epidemiology, and End Results program database between 2004 and 2015 and further divided into training and validation cohort. Univariate and multivariate Cox regression analyses were used to identify meaningful independent prognostic factors. The nomogram was used to predict 3- and 5-year overall survival (OS) and cancer-specific survival (CSS). Finally, the nomogram was verified internally and externally through the training and validation cohorts, and the predictive capability was evaluated using the receiver operating characteristic (ROC) curve, C-index, and calibration curve and compared with that of the 7th TNM stage. A total of 1120 patients were divided into training (n = 713) and validation (n = 407) cohorts. Based on the multivariate analysis of the training cohort, a nomogram that integrated age, tumor size, primary site, N stage, and M stage was constructed (P < 0.05). The predicted C-indexes of OS and CSS of the training cohort were 0.744 (95% CI 0.717–0.771) and 0.743 (95% CI 0.715–0.770), respectively. However, the TNM stage had a C-index of 0.695 (95% CI 0.666–0.724) and 0.698 (95% CI 0.669–0.727) for predicting OS and CSS, respectively. The nomogram showed higher C-indexes than those in the TNM stage. Furthermore, the internal and external calibration curves showed good consistency between the predicted and observed values. Age, tumor size, primary site, N stage, and M stage are independent risk factors affecting the OS and CSS in Ewing’s sarcoma patients. Compared with the 7th TNM staging, the nomogram consisting of these factors was more accurate for risk assessment and survival prediction in patients with Ewing’s sarcoma, thus providing a novel reliable tool for risk assessment and survival prediction in Ewing’s sarcoma patients.

Background The transoral atlantoaxial reduction plate (TARP) is an effective advance in the treatment of atlantoaxial dislocation (AAD) and can enable the performance of anterior atlantoaxial release, reduction, decompression, and internal fixation in a one-stage operation. However, accurate transoral C2 pedicle insertion (C2TOPI) remains a challenge. The aim of this study is to develop a grouped patient-specific drill template (PDT) specifically for AAD with complete reduction and, furthermore, to compare its efficacy and accuracy in facilitating C2TOPI. Methods After CT scanning, ten cadaveric C2 specimens were randomly assigned to two groups (the PDT and freehand group). A grouped PDT specifically for AAD with complete reduction was designed and manufactured. C2TOPI was performed using the PDT or the fluoroscopy-guided freehand technique. Postoperative CT scans were subsequently performed to analyze the deviations at the centroid of the cross section at the midpoint of the pedicle. Screw position grades were also assessed in both groups. Results Compared to the freehand group, the PDT group had a significantly shorter surgery time ( p < 0.001). Significant differences between the two groups were observed in the absolute value of the deviations at the centroid of the pedicle on either the axial or sagittal planes ( p < 0.05). No significant difference was found in the screw positions between the two groups ( p > 0.05); however, two unacceptable breaches (20%) occurred in the freehand group. Conclusion A specifically designed PDT could provide an accurate and easy-to-apply method for C2TOPI in AAD with complete reduction.

Objective: The purpose of this study was to analyze the risk factors for limb fracture non-union in order to improve non-union prevention and early detection.Methods: A total of 223 patients with non-union after surgery for limb fractures performed at our institution from January 2005 to June 2017 were included as the case group, while a computer-generated random list was created to select 446 patients with successful bone healing after surgery for limb fractures who were treated during the same period as the control group, thus achieving a ratio of 1:2. The medical records of these patients were reviewed retrospectively. Age, sex, body mass index, obesity, smoking, alcohol, diabetes, hypertension, osteoporosis, fracture type, multiple fractures, non-steroidal anti-inflammatory drugs (NSAIDs) use, delayed weight bearing, internal fixation failure, and infection data were analyzed and compared between the two groups. A multivariate logistic regression model was constructed to determine relevant factors associated with non-union.Results: After comparison between two groups by univariate analysis and multivariate logistic regression, we found some risk factors associated that osteoporosis (odds ratio [OR] = 3.16, 95% confidence interval [CI]: 2.05–4.89, p &lt; 0.001), open fracture (OR = 2.71, 95%CI: 1.72–4.27, p &lt; 0.001), NSAIDs use (OR = 2.04, 95%CI: 1.24–3.37, p = 0.005), delayed weight bearing (OR = 1.72, 95%CI: 1.08–2.74, p = 0.023), failed internal fixation (OR = 5.93, 95%CI: 2.85–12.36, p &lt; 0.001), and infection (OR = 6.77, 95%CI: 2.92–15.69, p &lt; 0.001) were independent risk factors for non-union after surgery for limb fractures.Conclusions: Osteoporosis, open fracture type, NSAIDs use, delayed weight bearing, failed internal fixation, and infection were found to be the main causes of bone non-union; clinicians should, therefore, take targeted measures to intervene in high-risk groups early.

Post-operative infections in orthopaedic implants are severe complications that require urgent solutions. Although conventional antibiotics limit bacterial biofilm formation, they ignore the bone loss caused by osteoclast formation during post-operative orthopaedic implant-related infections. Fortunately, enoxacin exerts both antibacterial and osteoclast inhibitory effects, playing a role in limiting infection and preventing bone loss. However, enoxacin lacks specificity in bone tissue and low bioavailability-related adverse effects, which hinders translational practice. Here, we developed a nanosystem (Eno@MSN-D) based on enoxacin (Eno)-loaded mesoporous silica nanoparticles (MSN), decorated with the eight repeating sequences of aspartate (D-Asp8), and coated with polyethylene glycol The release results suggested that Eno@MSN-D exhibits a high sensitivity to acidic environment. Moreover, this Eno@MSN-D delivery nanosystem exhibited both antibacterial and anti-osteoclast properties in vitro. The cytotoxicity assay revealed no cytotoxicity at the low concentration (20 μg/ml) and Eno@MSN-D inhibited RANKL-induced osteoclast differentiation. Importantly, Eno@MSN-D allowed the targeted release of enoxacin in infected bone tissue. Bone morphometric analysis and histopathology assays demonstrated that Eno@MSN-D has antibacterial and antiosteoclastic effects in vivo, thereby preventing implant-related infections and bone loss. Overall, our study highlights the significance of novel biomaterials that offer new alternatives to treat and prevent orthopaedic Staphylococcus aureus-related implantation infections and bone loss.

Disruption of extracellular matrix (ECM) homeostasis and subchondral bone remodeling play significant roles in osteoarthritis (OA) pathogenesis. Vindoline (Vin), an indole alkaloid extracted from the medicinal plant Catharanthus roseus, possesses anti-inflammatory properties. According to previous studies, inflammation is closely associated with osteoclast differentiation and the disorders of the homeostasis between ECM. Although Vin has demonstrated effective anti-inflammatory properties, its effects on the progression of OA remain unclear. We hypothesized that Vin may suppress the progress of OA by suppressing osteoclastogenesis and stabilizing ECM of articular cartilage. Therefore, we investigated the effects and molecular mechanisms of Vin as a treatment for OA in vitro and in vivo. In the present study, we found that Vin significantly suppressed RANKL-induced osteoclast formation and obviously stabilized the disorders of the ECM homeostasis stimulated by IL-1β in a dose-dependent manner. The mRNA expressions of osteoclast-specific genes were inhibited by Vin treatment. Vin also suppressed IL-1β-induced mRNA expressions of catabolism and protected the mRNA expressions of anabolism. Moreover, Vin notably inhibited the activation of RANKL-induced and IL-1β-induced NF-κB and ERK pathways. In vivo, Vin played a protective role by inhibiting osteoclast formation and stabilizing cartilage ECM in destabilization of the medial meniscus (DMM)-induced OA mice. Collectively, our observations provide a molecular-level basis for Vin’s potential in the treatment of OA.

Background: Oxidative stress plays a critical role in tumorigenesis, tumor development, and resistance to therapy. A systematic analysis of the interactions between antioxidant gene expression and the prognosis of patients with sarcoma is lacking but urgently needed. Methods: Gene expression and clinical data of patients with sarcoma were derived from The Cancer Genome Atlas Sarcoma (training cohort) and Gene Expression Omnibus (validation cohorts) databases. Least absolute shrinkage, selection operator regression, and Cox regression were used to develop prognostic signatures for overall survival (OS) and disease-free survival (DFS). Based on the signatures and clinical features, two nomograms for predicting 2-, 4-, and 6-year OS and DFS were established. Results: On the basis of the training cohort, we identified five-gene (CHAC2, GPX5, GSTK1, PXDN, and S100A9) and six-gene (GGTLC2, GLO1, GPX7, GSTK1, GSTM5, and IPCEF1) signatures for predicting OS and DFS, respectively, in patients with sarcoma. Kaplan-Meier survival analysis of the training and validation cohorts revealed that patients in the high-risk group had a significantly poorer prognosis than those in the low-risk group. On the basis of the signatures and other independent risk factors, we established two models for predicting OS and DFS that showed excellent calibration and discrimination. For the convenience of clinical application, we built web-based calculators (OS: https://quankun.shinyapps.io/sarcOS/; DFS: https://quankun.shinyapps.io/sarcDFS/). Conclusions: The antioxidant gene signature models established in this study can be novel prognostic predictors for sarcoma.