Endoscopic double line suture repair technique for repairing Iatrogenic dural tear: a technical case report.

PURPOSE: Introducing a suture repair technology, endoscopic double line suture repair technique, for iatrogenic dural injury during Percutaneous Endoscopic Lumbar Discectomy (PELD) surgery. METHODS: A patient with dural injury and cauda equina herniation during PELD surgery was treated with endoscopic double line suture repair technique. RESULTS: A patient with dural injury and cauda equina nerve herniation during PELD surgery was successfully treated using double-line suture technique. After the repair, no obvious cerebrospinal fluid leakage and cauda equina nerve re-herniation was seen. During the postoperative observation period, the wound healed well and there were no complications related to cerebrospinal leakage. During the follow-up period (1 year), the patient reported significant symptom relief and no complications. CONCLUSION: This novel dural repair technology is safe and effective and can be used to treat dural injuries during PELD surgery.

Mining bone metastasis related key genes of prostate cancer from the STING pathway based on machine learning.

Background: Prostate cancer (PCa) is the second most prevalent malignant tumor in male, and bone metastasis occurs in about 70% of patients with advanced disease. The STING pathway, an innate immune signaling mechanism, has been shown to play a key role in tumorigenesis, metastasis, and cancerous bone pain. Hence, exploring regulatory mechanism of STING in PCa bone metastasis will bring novel opportunities for treating PCa bone metastasis. Methods: First, key genes were screened from STING-related genes (SRGs) based on random forest algorithm and their predictive performance was evaluated. Subsequently, a comprehensive analysis of key genes was performed to explore their roles in prostate carcinogenesis, metastasis and tumor immunity. Next, cellular experiments were performed to verify the role of RELA in proliferation and migration in PCa cells, meanwhile, based on immunohistochemistry, we verified the difference of RELA expression between PCa primary foci and bone metastasis. Finally, based on the key genes to construct an accurate and reliable nomogram, and mined targeting drugs of key genes. Results: In this study, three key genes for bone metastasis were mined from SRGs based on the random forest algorithm. Evaluation analysis showed that the key genes had excellent prediction performance, and it also showed that the key genes played a key role in carcinogenesis, metastasis and tumor immunity in PCa by comprehensive analysis. In addition, cellular experiments and immunohistochemistry confirmed that overexpression of RELA significantly inhibited the proliferation and migration of PCa cells, and RELA was significantly low-expression in bone metastasis. Finally, the constructed nomogram showed excellent predictive performance in Receiver Operating Characteristic (ROC, AUC = 0.99) curve, calibration curve, and Decision Curve Analysis (DCA) curve; and the targeted drugs showed good molecular docking effects. Conclusion: In sum, this study not only provides a new theoretical basis for the mechanism of PCa bone metastasis, but also provides novel therapeutic targets and novel diagnostic tools for advanced PCa treatment.

Association between serum polyunsaturated fatty acids and bone mineral density in US adults: NHANES 2011-2014.

Objective: The purpose of this study was to investigate the association between serum polyunsaturated fatty acids (PUFAs) and bone mineral density (BMD). Methods: We performed a cross-sectional study based on data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014. The weighted multiple linear regression model was utilized to determine the association between serum PUFAs and BMD. Further smoothed curve fitting and threshold effect analysis were conducted. Finally, we performed a subgroup analysis. Results: In total, 1979 participants aged 20-59 years were enrolled. After adjusting for all covariates, we found that serum docosapentaenoic acid (DPA) was positively associated with head BMD (ß = 0.0015, 95% Cl: 0.0004, 0.0026, P = 0.008296) and lumbar spine BMD (ß = 0.0005, 95% Cl: 0.0000, 0.0010, P = 0.036093), and serum eicosadienoic acid (EDA) was negatively associated with thoracic spine BMD (ß = -0.0008, 95% Cl: -0.0016, -0.0000, P = 0.045355). Smoothed curve fitting revealed a nonlinear positive association between serum DPA and lumbar spine BMD. Threshold effect analysis indicated that the threshold of serum DPA was 81.4 µmol/L. Subgroup analysis revealed a positive correlation between serum DPA and head BMD in the subgroup aged 50-59 years (ß = 0.0025, 95% Cl: 0.0002, 0.0049, P = 0.035249) and females (ß = 0.0026, 95% Cl: 0.0008, 0.0044, P = 0.005005). There was a positive relationship between serum DPA and lumbar spine BMD in females (ß = 0.0008, 95% Cl: 0.0001, 0.0015, P = 0.017900) and a negative association between serum EDA and thoracic spine BMD in the subgroup aged 30-39 years (ß = -0.0016, 95% Cl: -0.0031, -0.0001, P = 0.041331), males (ß = -0.0012, 95% Cl: -0.0023, -0.0001, P = 0.039364) and other races (ß = -0.0021, 95% Cl: -0.0037, -0.0006, P = 0.008059). Conclusion: This study demonstrated a linear positive relationship between serum DPA and head BMD, a nonlinear positive association between serum DPA and lumbar spine BMD, and a linear negative correlation between serum EDA and thoracic spine BMD in US adults.

Development and validation of a novel necroptosis-related gene signature for predicting prognosis and therapeutic response in Ewing sarcoma.

Ewing sarcoma (ES) is the second most common malignant bone tumor in children and has a poor prognosis due to early metastasis and easy recurrence. Necroptosis is a newly discovered cell death method, and its critical role in tumor immunity and therapy has attracted widespread attention. Thus, the emergence of necroptosis may provide bright prospects for the treatment of ES and deserves our further study. Here, based on the random forest algorithm, we identified 6 key necroptosis-related genes (NRGs) and used them to construct an NRG signature with excellent predictive performance. Subsequent analysis showed that NRGs were closely associated with ES tumor immunity, and the signature was also good at predicting immunotherapy and chemotherapy response. Next, a comprehensive analysis of key genes showed that RIPK1, JAK1, and CHMP7 were potential therapeutic targets. The Cancer Dependency Map (DepMap) results showed that CHMP7 is associated with ES cell growth, and the Gene Set Cancer Analysis (GSCALite) results revealed that the JAK1 mutation frequency was the highest. The expression of 3 genes was all negatively correlated with methylation and positively with copy number variation (CNV). Finally, an accurate nomogram was constructed with this signature and clinical traits. In short, this study constructed an accurate prognostic signature and identified 3 novel therapeutic targets against ES.

Exploration of the Shared Hub Genes and Biological Mechanism in Osteoporosis and Type 2 Diabetes Mellitus based on Machine Learning.

A substantial amount of evidence suggests a close relationship between osteoporosis (OP) and Type 2 Diabetes Mellitus (T2DM), but the mechanisms involved remain unknown. Therefore, we conducted this study with the aim of screening for hub genes common to both diseases and conducting a preliminary exploration of common regulatory mechanisms. In the present study, we first screened genes significantly associated with OP and T2DM by the univariate logistic regression algorithm. And then, based on cross-analysis and random forest algorithm, we obtained three hub genes (ACAA2, GATAD2A, and VPS35) and validated the critical roles and predictive performance of the three genes in both diseases by differential expression analysis, receiver operating characteristic (ROC) curves, and genome wide association study (GWAS) analysis. Finally, based on gene set enrichment analysis (GSEA) and the construction of the miRNA-mRNA regulatory network, we conducted a preliminary exploration of the co-regulatory mechanisms of three hub genes in two diseases. In conclusion, this study provides promising biomarkers for predicting and treating both diseases and offers novel directions for exploring the common regulatory mechanisms of both diseases.

Preoperative Magnetic Resonance Imaging Signal Intensity Classification Is Associated With Clinical Presentation and Surgical Outcomes in Myelopathy Caused by Thoracic Ossification of Ligamentum Flavum: A Multicenter Study.

STUDY DESIGN: Retrospective Cohort Study. OBJECTIVES: To explore whether classification of the increased signal intensity (ISI) on magnetic resonance imaging (MRI) correlates with clinical presentations and outcomes in symptomatic thoracic ossification of ligamentum flavum (T-OLF) patients. METHODS: All patients with symptomatic T-OLF who underwent laminectomy at four institutions were reviewed. The ISI on preoperative T2-weighted MRI was divided into 3 groups, Grade 0, none; Grade 1, light (obscure); and Grade 2, intense (bright). Neurological function before surgery and at follow-up was evaluated by the revised Japanese Orthopedic Association (JOA) score. Patients' demographics, clinical manifestations, and surgical outcomes were compared. RESULTS: A total of 94 patients were involved. Preoperative MRI showed 32 patients in Grade 0, 39 patients in Grade 1, and 23 patients in Grade 2. Low extremities numbness, weakness, and clinical signs were less frequent in Grade 0 patients. The grade of ISI was correlated with the duration of symptoms and cord compression. Grade 0 patients had a better preoperative JOA score than those with ISI changes, while Grade 2 patients showed worse neurological recovery, longer duration of operation, more intraoperative blood loss, and a higher incidence of perioperative complications. CONCLUSION: The classification of ISI is an effective parameter for preoperatively assessing cord compression, clinical severity, and surgical outcomes in T-OLF patients. Grade 0 patients have relatively mild neurological impairment but are more likely to be misdiagnosed. Grade 2 indicates the worst clinical impairment and neurological recovery, and implies a risky and challenging surgery.

Is Helicobacter pylori infection associated with osteoporosis? a systematic review and meta-analysis.

INTRODUCTION: This study used systematic review and meta-analysis to evaluate the association between Helicobacter pylori infection and osteoporosis. MATERIALS AND METHODS: PubMed, Ovid and Web of Science were searched to include observational studies published in English comparing bone mineral density changes between Helicobacter pylori-positive and -negative participants. The quality of the included literature was assessed using the Newcastle-Ottawa Quality Assessment Scale (NOS). R software was used for meta-analysis, and odds ratio (OR) and 95% confidence interval (CI) were calculated to evaluate the relationship between Helicobacter pylori infection and osteoporosis. RESULTS: Twenty-two studies involving 24,176 participants were included in the study. Our meta-analysis showed that Helicobacter pylori infection was significantly associated with the risk of osteoporosis (OR: 1.12, 95%CI: 1.03, 1.22). Participants infected with the CagA-positive Helicobacter pylori strain were more likely to develop osteoporosis (OR = 1.42, 95%CI: 1.09; 1.85). CONCLUSION: Infection with Helicobacter pylori, particularly the CagA-positive strain, has been associated with an increased risk of osteoporosis. The bone health of Helicobacter pylori-positive patients deserves more attention.

The application of tranexamic acid in joint arthroplasty: A 20-year bibliometric analysis.

Background: With the arrival of the era of the aging population, the amount of joint arthroplasty surgery keeps rising, and the articles related to the application of tranexamic acid (TXA) in joint arthroplasty (we called the application of tranexamic acid in joint arthroplasty as TIA in this study) also show a blowout growth. Therefore, we conducted a bibliometric analysis of TIA-related publications to identify the main research trends and hot spots in this field in the last 20 years. Methods: In this study, publications in the field of TIA from January 1, 2002 to December 31, 2021 were searched in the Web of Science Core Collection (WoSCC). A total of 1,013 publications were evaluated for specific characteristics with Microsoft Excel software, CiteSpace, VOSviewer, and Online Analysis Platform of Literature Metrology (http://bibliometric.com/). Results: A total of 1,013 TIA-related articles were included in this study, and the number of articles in this field has increased yearly over the past 20 years. The USA and China dominated in the field of TIA. The Sichuan University published the most TIA-related articles among all the institutions. Of all the authors, Professor Pei was the most productive author with 64 articles. The lack of international cooperation was a significant problem in this field during the past 20 years. Furthermore, the results of the co-citation analysis and citation bursts analysis revealed that the safety and effectiveness of TIA and the optimal use strategy were the main trends and hotspots for the current and future. Conclusion: This bibliometric study reviewed the evolution trend of TIA research, and identified the countries, institutions, authors and journals that have made significant contributions to this field in the past 20 years, as well as the limitations and deficiencies in this field. In addition, this study revealed that the effectiveness and safety of TIA and the optimal use strategy was the current or future research trend and hotspot in this field.

Harnessing hyaluronic acid for the treatment of osteoarthritis: A bibliometric analysis.

Background: Osteoarthritis (OA) is a common disease which usually occurs in middle-aged and elderly people. Hyaluronic acid (HA) has been widely used to treat OA and related researches on the efficacy and safety of HA in the treatment of OA have been published. Therefore, the purpose of this research was to investigate the subject characteristics of harnessing HA for the treatment of OA and to analyse the relevant trends and hotspots by using a bibliometric approach. Methods: The articles published from 1 January 2002 to 31 December 2021 were searched in the Web of Science Core Collection (WoSCC) and the relevant information of HA for the treatment of OA was extracted after screening. Then, a total of 2438 publications were analysed by using Microsoft Excel, CiteSpace 5.8.R3, VOSviewer 1.6.18 and the Online Analysis Platform of Literature Metrology (http://bibliometric.com/). Results: A total of 2438 articles were finally included for analysis. The number of publications increased year by year. A total of 83 coutries and 3319 institutions published 2438 manuscripts in the field of use HA for the treatment of OA. The most productive country was United States with total 689 publications and League of European Research Universities Leru (Belgium) was the leading institution with total 126 publicatios. In terms of authors, the most prominent author was KrausVB, who published 28 papers with the highest H-index (19). In addition, Osteoarthritis and Cartilage had the highest number of publications (152 articles) and the highest number of citations (6450 citations). The co-cited references analysis indicated that the article published by McAlindon in 2014 had the most highest number of citations (91co-citations). What's more, most research hotspots focused on the efficacy and safety of HA, and regenerative medicine researches such as platelet-rich plasma (PRP) and mesenchymal stem cells (MSCs) have attracted more and more attentions of researchers. Conclusion: This study visually analyzed the historical evolution and future trends of HA for the treatment of OA, and discussed the research priorities. At present, there are still different views on the efficacy of HA for the treatment of OA. Gradually, research hotspots of this field have focused on the regenerative medicine.

Global publication trends and research hotspots of curcumin application in tumor: A 20-year bibliometric approach.

Malignant tumor is a disease caused by the imbalance of cell growth and proliferation mechanism, which seriously threatens human health and life safety. However, side effects and drug resistance are the key factors that limit the efficacy of anti-tumor drugs. Therefore, it is urgent and necessary to explore and unearth natural, safe and effective chemosensitizers in tumor researches. Curcumin is the main active ingredient in Curcuma, which has anti-inflammatory, anti-inflammatory and anti-oxidation effects, and has inhibitory effects on a variety of cancers. Bibliometric analysis is a scientific and quantitative method to assess the published articles, which can help researchers to find the development trends and the research hotspots of a specific research field, providing the development of future research for researchers. This study searched the Web Science Core Collection (woscc) for publications related to curcumin and tumors from January 1, 2001 to December 31, 2021. The specific characteristics of 1707 publications were analyzed by using Microsoft Excel software, CiteSpace, Vosviewer and online analysis platform of literature metrology. China had the largest number of published articles, with 579 publications. Aggarwal BB's articles total citations and average citations were the most. PLoS One had the largest number of publications, with 32 publications. The current research focuses on "nanoparticles", "delivery", "micells" and "doxorubicin". At present, nano based drug delivery system to improve the bioavailability of curcumin and thus to treat tumors will be the focus of future research.

A Novel Ferroptosis-Related Gene Signature for Prognosis Prediction in Ewing Sarcoma.

Ferroptosis, as a form of programmed cell death independent of apoptosis, has been demonstrated that plays a major role in tumorigenesis and cancer treatment. A comprehensive analysis of ferroptosis-related genes (FRGs) may lead to a novel choice for the treatment of Ewing sarcoma (ES). Here, 148 differentially expressed FRGs (DEFRGs) were identified between normal and ES tissue. And the GO and KEGG analyses of DEFRGs indicated that these genes were enriched in cancer and immune-related signaling pathways. Then, the GSE17679 cohort was randomly divided into train and test cohorts. Based on the train cohort, AURKA, RGS4, and RIPK1 were identified as key genes through the univariate Cox regression analysis, the random survival forest algorithm, and the multivariate Cox regression analysis and utilized to establish a prognostic FRG signature. The validation results demonstrated that the gene signature has not only excellent prediction performance and generalization ability but is also good at predicting the response of immunotherapy and chemotherapy. Subsequent analysis indicated that all 3 key genes play key roles in tumor immunity and prognosis of ES. Of these, AURKA was highly associated with EWSR1, which was verified by a single-cell dataset (GSE130019). Therefore, the 3 genes may be potential therapeutic targets for ES. At the end of this study, we also constructed an accurate nomogram that helps clinicians to assess the survival time of ES patients. In conclusion, our study constructed an excellent gene signature, which is helpful in improving the prognosis of ES patients.

Construct and Validate a Predictive Model for Surgical Site Infection after Posterior Lumbar Interbody Fusion Based on Machine Learning Algorithm.

Purpose: Surgical site infection is one of the serious complications after lumbar fusion. Early prediction and timely intervention can reduce the harm to patients. The aims of this study were to construct and validate a machine learning model for predicting surgical site infection after posterior lumbar interbody fusion, to screen out the most important risk factors for surgical site infection, and to explore whether synthetic minority oversampling technique could improve the model performance. Method: This study reviewed 584 patients who underwent posterior lumbar interbody fusion for degenerative lumbar disease at our center from January 2019 to August 2021. Clinical information and laboratory test data were collected from the electronic medical records. The original dataset was divided into training set and validation set in a 1 : 1 ratio. Seven machine learning algorithms were used to develop predictive models; the training set of each model was resampled using synthetic minority oversampling technique. Finally, the model performance was assessed in the validation set. Results: Of the 584 patients, 33 (5.65%) occurred surgical site infection. Stepwise logistic regression showed that preoperative albumin level (OR 0.659, 95% CI 0.563-0.756), diabetes (OR 9.129, 95% CI 3.816-23.126), intraoperative dural tear (OR 8.436, 95% CI 2.729-25.334), and rheumatic disease (OR 8.471, 95% CI 1.743-39.567) were significant predictors associated with surgical site infection. The performance of the AdaBoost Classification Trees model was the best among the seven machine learning models, and synthetic minority oversampling technique improved the performance of all models. Conclusion: The prediction model we constructed based on machine learning and synthetic minority oversampling technique can accurately predict surgical site infection, which is conducive to clinical decision-making and optimization of perioperative management.

Rapid measurement of thoracolumbar kyphosis with the integrated inclinometer of a smartphone: a validity and reliability study.

The objective of this study was to evaluate the accuracy, reliability, and time requirements of two methods for measuring thoracolumbar kyphosis: a conventional method using a picture archiving and communication system (PACS) and this new method using the integrated inclinometer of a smartphone. The thoracolumbar kyphotic angles of one hundred consecutive patients were measured by a PACS and this novel smartphone method. The measured angles were analysed by multiple statistical methods, and the two measurement tools were compared in terms of accuracy, reliability, and time requirements. The mean result of thoracolumbar kyphosis measured by the PACS was 21.43 ± 12.96°, and the mean value measured by the smartphone was 21.03 ± 13.01°. A Bland-Altman plot for these two methods showed a mean difference of 0.4°, with the limits of agreement being -2.4° and 3.2°. One-way ANOVA showed no significant difference (F = 0.080, P = 0.999) among measurements by different observers and different methods. The intraclass correlation coefficients (ICCs) of the mean values of four repeated measurements of thoracolumbar kyphosis between these two methods were 0.997 (0.995-0.998), revealing that the two methods were highly correlated. The ICC results showed that the concordance between these two methods was very good for all measurements of thoracolumbar kyphosis, and the inter- and intra-observer reliability of the novel smartphone method were very good. The PACS method (36.95 ± 0.98 s) took significantly longer than the smartphone method (17.68 ± 0.97 s) when compared by an independent-samples t test (P = 0.000). This new method using the integrated inclinometer of a smartphone has satisfactory validity and reliability compared to the PACS method. Additionally, the new method took significantly less time than the PACS method. Measuring with a smartphone is more convenient than using a PACS, which is always rooted in a full-sized computer. In summary, this new method using the integrated inclinometer of a smartphone is rapid, convenient, accurate and reliable when measuring thoracolumbar kyphosis in osteoporotic vertebral compression fracture (OVCF) patients.

Construction of a Prognosis-Related Gene Signature by Weighted Gene Coexpression Network Analysis in Ewing Sarcoma.

BACKGROUND: Ewing sarcoma (ES) is the second most common pediatric bone tumor with a high rate of metastasis, high recurrence, and low survival rate. Therefore, the identification of new biomarkers which can improve the prognosis of ES patients is urgently needed. METHODS: Here, GSE17679 dataset was downloaded from GEO databases. WGCNA method was used to identify one module associating with OVS (overall vital survival) and event. cytoHubba was used to screen out 50 hub genes from the module genes. Then, GSE17679 dataset was randomly divided into train cohort and test cohort. Next, univariate Cox analysis, LASSO regression analysis, and multivariate Cox analysis were conducted on 50 hub genes combined with train cohort data to select pivotal genes. Finally, an optimal 7-gene-based risk assessment model was established, which was verified by test cohort, entire GSE17679, and two independent datasets (GSE63157 and TCGA-SARC). RESULTS: The results of the functional enrichment analysis revealed that the OVS and event-associated module were mainly enriched in the protein transcription, cell proliferation, and cell-cycle control. And the train cohort was divided into high-risk and low-risk subgroups based on the median risk score; the results showed that the survival of the low-risk subgroup was significantly longer than high-risk. ROC analysis revealed that AUC values of 1, 3, and 5-year survival were 0.85, 0.94, and 0.88, and Kaplan-Meier analysis also revealed that P value < 0.0001, indicating that this model was accurate, which was also verified in the test, entire cohort, and two independent datasets (GSE63157 and TCGA-SARC). Then, we performed a comprehensive analysis (differential expression analysis, correlation analysis and survival analysis) of seven pivotal genes, and found that four genes (NCAPG, KIF4A, NUF2 and CDC20) plays a more crucial role in the prognosis of ES. CONCLUSION: Taken together, this study established an optimal 7-gene-based risk assessment model and identified 4 potential therapeutic targets, to improve the prognosis of ES patients.

The role of vascular endothelial growth factor as a prognostic and clinicopathological marker in osteosarcoma: a systematic review and meta-analysis.

BACKGROUND: In recent years, numerous investigations have been conducted to determine the clinical significance and critical functions of vascular endothelial growth factor (VEGF) in various malignant cancers. The purpose of this meta-analysis was to comprehensively evaluate the prognostic and clinicopathological value of VEGF in patients with osteosarcoma. METHODS: We performed a systematic literature retrieval of available databases. Odds ratios (ORs) or standard mean difference (SMD) for clinicopathological parameters, hazard ratios (HRs) for overall survival and disease-free survival were calculated to assess the correlation between VEGF expression and prognosis in patients with osteosarcoma. RESULTS: A total of 22 studies with 1144 patients were included in our study. Pooled analyses showed that VEGF overexpression predicted worse overall survival (HR, 2.42; 95% CI, 1.87-3.11, p < 0.001) and disease-free survival (HR, 2.604; 95% CI, 1.698-3.995, p < 0.001), respectively. Furthermore, investigation regarding osteosarcoma clinicopathologic characteristics suggested that high VEGF expression was significantly associated with metastasis (OR, 4.39; 95% CI, 2.77-6.95; p < 0.001), clinical stage (OR, 0.73; 95% CI, 0.62-0.87; p < 0.001), and microvessel density (SMD, 3.33, 95% CI,1.57-5.10, p < 0.001), but not associated with tumor location, gender, age, local recurrence, and chemotherapy response. CONCLUSION: Our meta-analysis findings suggest that elevated VEGF expression may be a predictive biomarker for poor prognosis and adverse clinicopathological characteristics in patients with osteosarcoma.