Systematic profiling of diagnostic and prognostic value of autophagy-related genes for sarcoma patients.

BACKGROUND: Autophagy-related genes (ARGs) have been confirmed to have an important role in tumorigenesis and tumor microenvironment formation. Nevertheless, a systematic analysis of ARGs and their clinical significance in sarcoma patients is lacking. METHODS: Gene expression files from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) were used to select differentially expressed genes (DEGs). Differentially expressed ARGs (DEARGs) were determined by matching the DEG and HADb gene sets, which were evaluated by functional enrichment analysis. Unsupervised clustering of the identified DEARGs was conducted, and associations with tumor microenvironment (TME), immune checkpoints, and immune cells were analyzed simultaneously. Two prognostic signatures, one for overall survival (OS) and one for disease-free survival (DFS), were established and validated in an independent set. RESULTS: In total, 84 DEARGs and two clusters were identified. TME scores, five immune checkpoints, and several types of immune cells were found to be significantly different between two clusters. Two prognostic signatures incorporating DEARGs showed favorable discrimination and were successfully validated. Two nomograms combining signature and clinical variables were generated. The C-indexes were 0.818 and 0.747 for the OS and DFS nomograms, respectively. CONCLUSION: This comprehensive analyses of the ARG landscape in sarcoma showed novel ARGs related to carcinogenesis and the immune microenvironment. These findings have implications for prognosis and therapeutic responses, which reveal novel potential prognostic biomarkers, promote precision medicine, and provide potential novel targets for immunotherapy.

Surgical treatment of atlantoaxial subluxation by intraoperative skull traction and C1-C2 fixation.

BACKGROUND: Atlantoaxial subluxation (AAS) is a not rare abnormality between the atlas (C1) and axis (C2). For AAS patients with persistent neck pain and neurologic symptoms, surgical intervention is a good choice. Nevertheless, there were still few reports about the use of intraoperative skull traction and different fixation methods in treatment of AAS. METHODS: From January 2012 to December 2018, a total of 86 cases were admitted to our hospital and diagnosed as AAS. All the patients received atlantoaxial reduction with the help of intraoperative skull traction and C1-C2 fixation. Clinical and radiological parameters were collected through chart review. RESULTS: There were 86 cases included in this study. The mean operative time was 153.9 ± 73.9 min, and the mean amount of intraoperative blood loss was 219.1 ± 195.6 ml. 81 patients underwent posterior reduction, internal fixation and fusion. 5 patients underwent anterior release, followed by posterior internal fixation and fusion. 82 patients got satisfactory postoperative outcomes while complications occurred in 4 patients. Significant neurologic improvement was observed in these patients. Bone fusion was achieved on the midline sagittal reconstructed CT images at the latest follow-up in all these patients except 1 case. All the patients were followed up for 34.84 ± 15.86 months at average (range 12-60 months). The mean ADI value was 7.55 ± 1.67 mm at average preoperatively, and improved to 4.03 ± 1.21 mm postoperatively, and to 4.21 ± 0.99 mm at the latest follow-up. The mean A-A angle was 15.48 ± 9.82 degrees at average preoperatively, and improved to 21.61 ± 10.43 degrees postoperatively, and to 19.73 ± 8.13 degrees at the latest follow-up. The mean A-A height was 35.61 ± 7.66 mm at average preoperatively, and improved to 40.08 ± 8.5 mm postoperatively, and to 38.83 ± 6.97 mm at the latest follow-up. There were complications in 4 patients, including pedicle misplacement, pedicle screw fracture, infection and one death. CONCLUSION: Intraoperative skull traction can effectively facilitate the surgical procedures for ASS caused by different etiologies. Further research will be needed to investigate the safety and effectiveness of this method in the future.

Deep learning-based automated high-accuracy location and identification of fresh vertebral compression fractures from spinal radiographs: a multicenter cohort study.

Background: Digital radiography (DR) is a common and widely available examination. However, spinal DR cannot detect bone marrow edema, therefore, determining vertebral compression fractures (VCFs), especially fresh VCFs, remains challenging for clinicians. Methods: We trained, validated, and externally tested the deep residual network (DRN) model that automated the detection and identification of fresh VCFs from spinal DR images. A total of 1,747 participants from five institutions were enrolled in this study and divided into the training cohort, validation cohort and external test cohorts (YHDH and BMUH cohorts). We evaluated the performance of DRN model based on the area under the receiver operating characteristic curve (AUC), feature attention maps, sensitivity, specificity, and accuracy. We compared it with five other deep learning models and validated and tested the model internally and externally and explored whether it remains highly accurate for an external test cohort. In addition, the influence of old VCFs on the performance of the DRN model was assessed. Results: The AUC was 0.99, 0.89, and 0.88 in the validation, YHDH, and BMUH cohorts, respectively, for the DRN model for detecting and discriminating fresh VCFs. The accuracies were 81.45% and 72.90%, sensitivities were 84.75% and 91.43%, and specificities were 80.25% and 63.89% in the YHDH and BMUH cohorts, respectively. The DRN model generated correct activation on the fresh VCFs and accurate peak responses on the area of the target vertebral body parts and demonstrated better feature representation learning and classification performance. The AUC was 0.90 (95% confidence interval [CI] 0.84-0.95) and 0.84 (95% CI 0.72-0.93) in the non-old VCFs and old VCFs groups, respectively, in the YHDH cohort (p = 0.067). The AUC was 0.89 (95% CI 0.84-0.94) and 0.85 (95% CI 0.72-0.95) in the non-old VCFs and old VCFs groups, respectively, in the BMUH cohort (p = 0.051). Conclusion: In present study, we developed the DRN model for automated diagnosis and identification of fresh VCFs from spinal DR images. The DRN model can provide interpretable attention maps to support the excellent prediction results, which is the key that most clinicians care about when using the model to assist decision-making.

Dual-Nozzle 3D Printed Nano-Hydroxyapatite Scaffold Loaded with Vancomycin Sustained-Release Microspheres for Enhancing Bone Regeneration.

Background: Successful treatment of infectious bone defect remains a major challenge in the orthopaedic field. At present, the conventional treatment for infectious bone defects is surgical debridement and long-term systemic antibiotic use. It is necessary to develop a new strategy to achieve effective bone regeneration and local anti-infection for infectious bone defects. Methods: Firstly, vancomycin / poly (lactic acid-glycolic acid) sustained release microspheres (VAN/PLGA-MS) were prepared. Then, through the dual-nozzle 3D printing technology, VAN/PLGA-MS was uniformly loaded into the pores of nano-hydroxyapatite (n-HA) and polylactic acid (PLA) scaffolds printed in a certain proportion, and a composite scaffold (VAN/MS-PLA/n-HA) was designed, which can not only promote bone repair but also resist local infection. Finally, the performance of the composite scaffold was evaluated by in vivo and in vitro biological evaluation. Results: The in vitro release test of microspheres showed that the release of VAN/PLGA-MS was relatively stable from the second day, and the average daily release concentration was about 15.75 µg/mL, which was higher than the minimum concentration specified in the guidelines. The bacteriostatic test in vitro showed that VAN/PLGA-MS had obvious inhibitory effect on Staphylococcus aureus ATCC-29213. Biological evaluation of VAN/MS-PLA/n-HA scaffolds in vitro showed that it can promote the proliferation of adipose stem cells. In vivo biological evaluation showed that VAN/MS-PLA/n-HA scaffold could significantly promote bone regeneration. Conclusion: Our research shows that VAN/MS-PLA/n-HA scaffolds have satisfying biomechanical properties, effectively inhibit the growth of Staphylococcus aureus, with good biocompatibility, and effectiveness on repairing bone defects. The VAN/MS-PLA/n-HA scaffold provide the clinic with an application prospect in bone tissue engineering.

Extensive Spinal Epidural Abscess Resulting in Complete Paraplegia Treated by Selective Laminectomies and Irrigation.

BACKGROUND: Spinal epidural abscess (SEA) is an uncommon clinical entity that is often subject to delayed diagnosis and suboptimal treatment. Untreated disease leads to compression of the spinal cord, resulting in devastating complications. CASE PRESENTATION: A 56-year-old man visited our hospital for progressive lower back and lower extremity pain of several days' duration. Significant pyrexia (39.5°C) and elevated C-reactive protein (89.2 mg/L) were detected during admission, but no positive neurological examination findings were observed. Magnetic resonance imaging revealed pyogenic discitis at L3-4. Despite the administration of directed antibiotic therapy, the patient's condition rapidly deteriorated, culminating in complete paraplegia secondary to an extensive SEA from L4 to C7. Emergency spinal decompression surgery was canceled due to his poor clinical condition and refusal of informed consent. After further deterioration, he consented to two-level selective laminectomies and irrigation. CONCLUSIONS: In contrast with prior case reports, this case illustrates the natural history of an extensive SEA during conservative and late surgical treatment. Early diagnosis and timely surgical decompression are of great importance for extensive SEA.

Attention Gate Based Dual-Pathway Network for Vertebra Segmentation of X-Ray Spine Images.

Automatic spine and vertebra segmentation from X-ray spine images is a critical and challenging problem in many computer-aid spinal image analysis and disease diagnosis applications. In this paper, a two-stage automatic segmentation framework for spine X-ray images is proposed, which can firstly locate the spine regions (including backbone, sacrum and ilium) in the coarse stage and then identify eighteen vertebrae (i.e., cervical vertebra 7, thoracic vertebra 1-12 and lumbar vertebra 1-5) with isolate and clear boundary in the fine stage. A novel Attention Gate based dual-pathway Network (AGNet) composed of context and edge pathways is designed to extract semantic and boundary information for segmentation of both spine and vertebra regions. Multi-scale supervision mechanism is applied to explore comprehensive features and an Edge aware Fusion Mechanism (EFM) is proposed to fuse features extracted from the two pathways. Some other image processing skills, such as centralized backbone clipping, patch cropping and convex hull detection are introduced to further refine the vertebra segmentation results. Experimental validations on spine X-ray images dataset and vertebrae dataset suggest that the proposed AGNet achieves superior performance compared with state-of-the-art segmentation methods, and the coarse-to-fine framework can be implemented in real spinal diagnosis systems.

Retropharyngeal Reduction Plate for Atlantoaxial Dislocation: A Cadaveric Test and Morphometric Trajectory Analysis.

OBJECTIVE: To evaluate the placement feasibility and safety of the newly designed retropharyngeal reduction plate by cadaveric test and to perform morphometric trajectory analysis. METHODS: The five cadaveric specimens with intact atlantoaxial joint were enrolled in this study. They were used for simulating the placement process and evaluating the placement feasibility of the retropharyngeal reduction plate. The atlantoaxial dislocation (AAD) of five cadaveric specimens were obtained by proper external force after dissecting ligaments. The retropharyngeal reduction plate was placed on atlantoaxial joint of cadaveric specimens. The X-ray and three-dimensional (3D) spiral CT were used for evaluating the placement safety of retropharyngeal reduction plate. The DICOM data was obtained after 3D spiral CT scanning for the morphometric trajectory analysis. RESULTS: The reduction plates were successfully placed on the atlantoaxial joint of five cadaveric specimens through the retropharyngeal approach, respectively. The X-ray and 3D spiral CT showed the accurate screw implantation and satisfying plate placement. The length of the left/right atlas screw trajectory (L/RAT) was, respectively, 1.73 ± 0.01 cm (LAT) and 1.71 ± 0.02 cm (RAT). The length of odontoid screw trajectory (OST) was 1.38 ± 0.02 cm. The length of the left/right axis screw trajectory (L/RAXT) was, respectively, 1.67 ± 0.02 cm (LAXT) and 1.67 ± 0.01 cm (RAXT). There was no statistical significance between left side and right side in terms of AT and AXT (P > 0.05). The angles of atlas screw trajectory angle (ASTA), axis screw trajectory angle (AXSTA), and odontoid screw trajectory angle (OSTA) were 38.04° ± 2.03°, 56.92° ± 2.66°, and 34.78° ± 2.87°, respectively. CONCLUSION: The cadaveric test showed that the retropharyngeal reduction plate is feasible to place on the atlantoaxial joint, which is also a safe treatment choice for atlantoaxial dislocation. The meticulous preoperative planning of screw trajectory based on individual differences was also vital to using this technique.

Establishment of an Autophagy-Related Clinical Prognosis Model for Predicting the Overall Survival of Osteosarcoma.

PURPOSE: Osteosarcoma is the most common primary and highly invasive bone tumor in children and adolescents. The purpose of this study is to construct a multi-gene expression feature related to autophagy, which can be used to predict the prognosis of patients with osteosarcoma. Materials and methods. The clinical and gene expression data of patients with osteosarcoma were obtained from the target database. Enrichment analysis of autophagy-related genes related to overall survival (OS-related ARGs) screened by univariate Cox regression was used to determine OS-related ARGs function and signal pathway. In addition, the selected OS-related ARGs were incorporated into multivariate Cox regression to construct prognostic signature for the overall survival (OS) of osteosarcoma. Use the dataset obtained from the GEO database to verify the signature. Besides, gene set enrichment analysis (GSEA) were applied to further elucidate the molecular mechanisms. Finally, the nomogram is established by combining the risk signature with the clinical characteristics. RESULTS: Our study eventually included 85 patients. Survival analysis showed that patients with low riskScore had better OS. In addition, 16 genes were included in OS-related ARGs. We also generate a prognosis signature based on two OS-related ARGs. The signature can significantly divide patients into low-risk groups and high-risk groups, and has been verified in the data set of GEO. Subsequently, the riskScore, primary tumor site and metastasis status were identified as independent prognostic factors for OS and a nomogram were generated. The C-index of nomogram is 0.789 (95% CI: 0.703~0.875), ROC curve and calibration chart shows that nomogram has a good consistency between prediction and observation of patients. CONCLUSIONS: ARGs was related to the prognosis of osteosarcoma and can be used as a biomarker of prognosis in patients with osteosarcoma. Nomogram can be used to predict OS of patients and improve treatment strategies.

Identification of Iron Metabolism-Related Gene Signatures for Predicting the Prognosis of Patients With Sarcomas.

Iron is one of the essential trace elements in the human body. An increasing amount of evidence indicates that the imbalance of iron metabolism is related to the occurrence and development of cancer. Here, we obtained the gene expression and clinical data of sarcoma patients from TCGA and the GEO database. The prognostic value of iron metabolism-related genes (IMRGs) in patients with sarcoma and the relationship between these genes and the immune microenvironment were studied by comprehensive bioinformatics analyses. Two signatures based on IMRGs were generated for the overall survival (OS) and disease-free survival (DFS) of sarcoma patients. At 3, 5, and 7 years, the areas under the curve (AUCs) of the OS signature were 0.708, 0.713, and 0.688, respectively. The AUCs of the DFS signature at 3, 5, and 7 years were 0.717, 0.689, and 0.702, respectively. Kaplan-Meier survival analysis indicated that the prognosis of high-risk patients was worse than that of low-risk patients. In addition, immunological analysis showed that there were different patterns of immune cell infiltration among patients in different clusters. Finally, we constructed two nomograms that can be used to predict the OS and DFS of sarcoma patients. The C-index was 0.766 (95% CI: 0.697-0.835) and 0.763 (95% CI: 0.706-0.820) for the OS and DFS nomograms, respectively. Both the ROC curves and the calibration plots showed that the two nomograms have good predictive performance. In summary, we constructed two IMRG-based prognostic models that can effectively predict the OS and DFS of sarcoma patients.