Rapidly expanding giant neurofibroma of the back with intratumoral hematoma: a case report and literature review.

Neurofibromatosis type I is a common genetic disease that can lead to disfigurement, neurological and functional disorders. However, it is rare to meet the case which a huge mass is formed rapidly after neurofibroma ruptures. This case report describes a rare case of a 52-year-old female with a rapidly expanding mass on her back and mild anemia as the main symptoms. Physical examination showed a huge mass on the back and a surface ulceration with the diameter of 6 cm. Imaging examination revealed the abundant blood supply to the lesion. We performed preoperative arterial embolization, and surgical resection on the fifth day after embolization. After operation, proper blood transfusion and vacuum sealing drainage (VSD) were given. Through 9-months follow-up study, the incision of the patient recovered well and there was no sign of tumor recurrence. Therefore, this case report provides clinicians with valuable experience in the treatment for rapidly expanding neurofibroma.

Cerium Oxide Nanoparticles Promote Osteoplastic Precursor Differentiation by Activating the Wnt Pathway.

Osteoplastic precursors are critical for fracture repair and bone homeostasis maintenance. Cerium oxide nanoparticles (CeO2 NPs) can promote the osteogenic differentiation of mesenchymal stem cells and secrete vascular endothelial growth factors. However, little is known about its role in precursor osteoblasts; therefore, we further investigated the effect and mechanism of CeO2 NPs in precursor osteoblasts. Cell counting kit-8 analysis was utilized to detect the toxicity of CeO2 NPs on MC3T3-E1 mouse osteogenic precursor cells. Then, alizarin red S staining was employed to assess the degree of extracellular matrix mineralization, and quantitative real-time polymerase chain reaction analysis was performed to measure the levels of osteogenesis-related genes. To identify differentially expressed genes, mRNA-sequencing was performed. Subsequently, GO and KEGG analyses were deployed to identify the major downstream pathways, whereas Western blot was used for verification. CeO2 NPs significantly enhanced the ability of MC3T3-E1 precursor osteoblasts to enhance matrix mineralization and increased the expression of osteogenic genes such as runt-related transcription factor 2, collagen Iα1, and osteocalcin. Pathway analysis revealed that CeO2 NPs enhanced the nuclear translocation of ß-catenin and activated the Wnt pathway by promoting family with sequence similarity 53 member B/simplet expression, while Western blot analysis indicated the same results. After using a Wnt pathway inhibitor (KYA1797K), the simulative effect of CeO2 NPs was abolished. This study revealed that CeO2 NPs promoted MC3T3-E1 precursor osteoblast differentiation by activating the Wnt pathway.

The Protective Effect of Selenium Nanoparticles in Osteoarthritis: In vitro and in vivo Studies.

Introduction: Osteoarthritis (OA) is a common chronic joint disease characterized by articular cartilage degeneration. OA usually manifests as joint pain, limited mobility, and joint effusion. Currently, the primary OA treatment is non-steroidal anti-inflammatory drugs (NSAIDs). Although they can alleviate the disease's clinical symptoms and signs, the drugs have some side effects. Selenium nanoparticles (SeNPs) may be an alternative to relieve OA symptoms. Materials and Results: We confirmed the anti-inflammatory effect of selenium nanoparticles (SeNPs) in vitro and in vivo experiments for OA disease in this study. In vitro experiments, we found that SeNPs could significantly reduce the expression of nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), the major inflammatory factors, and had significant anti-inflammatory and anti-arthritic effects. SeNPs can inhibit reactive oxygen species (ROS) production and increased glutathione peroxidase (GPx) activity in interleukin-1beta (IL-1ß)-stimulated cells. Additionally, SeNPs down-regulated matrix metalloproteinase-13 (MMP-13) and thrombospondin motifs 5 (ADAMTS-5) expressions, while up-regulated type II collagen (COL-2) and aggrecan (ACAN) expressions stimulated by IL-1ß. The findings also indicated that SeNPs may exert their effects through suppressing the NF-κB p65 and p38/MAPK pathways. In vivo experiments, the prevention of OA development brought on by SeNPs was demonstrated using a DMM model. Discussion: Our results suggest that SeNPs may be a potential anti-inflammatory agent for treating OA.

Association of smoking and osteoarthritis in US (NHANES 1999-2018).

Little is currently known about the effect of smoking on osteoarthritis (OA). This study aimed to investigate the relationship between smoking and OA in the United States (US) general population. Cross-sectional study. Level of evidence, 3. 40,201 eligible participants from the National Health and Nutrition Examination Survey 1999-2018 were included and divided into OA and non-arthritis groups. Participants demographics and characteristics were compared between the two groups. Then the participants were divided into non-smokers, former smokers, and current smokers based on their smoking status, also demographics and characteristics among the three groups were compared. Multivariable logistic regression was used to determine the relationship between smoking and OA. The current and former smoking rate in the OA group (53.0%) was significantly higher than that in the non-arthritis group (42.5%; p < 0.001). Multivariable regression analysis including body mass index (BMI), age, sex, race, education level, hypertension, diabetes, asthma and cardiovascular disease showed that smoking was an association for OA. This large national study highlights a positive association between smoking and OA prevalence in the general US population. It is necessary to further study the relationship between smoking and OA in order to determine the specific mechanism of smoking on OA.

Animal model for tendinopathy.

Background: Tendinopathy is a common motor system disease that leads to pain and reduced function. Despite its prevalence, our mechanistic understanding is incomplete, leading to limited efficacy of treatment options. Animal models contribute significantly to our understanding of tendinopathy and some therapeutic options. However, the inadequacies of animal models are also evident, largely due to differences in anatomical structure and the complexity of human tendinopathy. Different animal models reproduce different aspects of human tendinopathy and are therefore suitable for different scenarios. This review aims to summarize the existing animal models of tendinopathy and to determine the situations in which each model is appropriate for use, including exploring disease mechanisms and evaluating therapeutic effects. Methods: We reviewed relevant literature in the PubMed database from January 2000 to December 2022 using the specific terms ((tendinopathy) OR (tendinitis)) AND (model) AND ((mice) OR (rat) OR (rabbit) OR (lapin) OR (dog) OR (canine) OR (sheep) OR (goat) OR (horse) OR (equine) OR (pig) OR (swine) OR (primate)). This review summarized different methods for establishing animal models of tendinopathy and classified them according to the pathogenesis they simulate. We then discussed the advantages and disadvantages of each model, and based on this, identified the situations in which each model was suitable for application. Results: For studies that aim to study the pathophysiology of tendinopathy, naturally occurring models, treadmill models, subacromial impingement models and metabolic models are ideal. They are closest to the natural process of tendinopathy in humans. For studies that aim to evaluate the efficacy of possible treatments, the selection should be made according to the pathogenesis simulated by the modeling method. Existing tendinopathy models can be classified into six types according to the pathogenesis they simulate: extracellular matrix synthesis-decomposition imbalance, inflammation, oxidative stress, metabolic disorder, traumatism and mechanical load. Conclusions: The critical factor affecting the translational value of research results is whether the selected model is matched with the research purpose. There is no single optimal model for inducing tendinopathy, and researchers must select the model that is most appropriate for the study they are conducting. The translational potential of this article: The critical factor affecting the translational value of research results is whether the animal model used is compatible with the research purpose. This paper provides a rationale and practical guide for the establishment and selection of animal models of tendinopathy, which is helpful to improve the clinical transformation ability of existing models and develop new models.

Stem cell-based therapeutic strategies for rotator cuff tendinopathy.

Rotator cuff tendinopathy is a common musculoskeletal disorder that imposes significant health and economic burden. Stem cell therapy has brought hope for tendon healing in patients with final stage rotator cuff tendinopathy. Some clinical trials have confirmed the effectiveness of stem cell therapy for rotator cuff tendinopathy, but its application has not been promoted and approved. There are still many issues that should be solved prior to using stem cell therapy in clinical applications. The optimal source and dose of stem cells for rotator cuff tendinopathy should be determined. We also proposed novel prospective approaches that can overcome cell population heterogeneity and standardize patient types for stem cell applications. The translational potential of this article: This review explores the optimal sources of stem cells for rotator cuff tendinopathy and the principles for selecting stem cell dosages. Key strategies are provided for stem cell population standardization and recipient selection.

Preoperative Simulation and Three-Dimensional Model for the Operative Treatment of Forearm Double Fracture: A Randomized Controlled Clinical Trial.

BACKGROUND: To assess the safety and efficacy of preoperative simulation and three-dimensional (3D) models in the treatment of ulnoradial diaphyses fracture. It was hypothesized that preoperative simulation and 3D printing might significantly shorten the mean operative time, intraoperative bleeding, and intraoperative fluoroscopy. MATERIAL AND METHODS: Forty patients with forearm double fracture were divided into 3D printing group and conventional surgery group. Preoperative simulation and 3D printing were performed on patients in the 3D printing group to examine implant reduction and placement as well as preoperative plate/screw size. The operation time, intraoperative bleeding, and frequency of fluoroscopies were recorded. RESULTS: In the conventional surgery group, the operative time, intraoperative bleeding, and the frequency of fluoroscopy were 106.2 ± 15.92 min, 61.45 ± 11.33 ml and 5.65 ± 1.23 times, whereas in the 3D printing group, values of all the three parameters were better than those of the conventional surgery group (91.3 ± 14.85 min, 48.6 ± 10.39 ml and 3.85 ± 1.04 times, respectively). The forearm pronation and supination of the 3D printing group improved to 79.55 ± 5.12° and 76.80 ± 3.96°, respectively. In the conventional surgery group, patients also had significant improvement in these indicators, which improved to 78.60 ± 5.18° and 75.4 ± 5.30°. CONCLUSIONS: The results showed that preoperative simulation and 3D printing can enhance the safety as well as personalization of the surgical process during the treatment of forearm double fracture and therefore holds potential for future application in clinical practice. TRIAL REGISTRY: Name of the registry: This study was registered in the Chinese Clinical Trial Registry; Trial registration number: ChiCTR2100045790.

The Effect of Autologous Adipose-Derived Stromal Vascular Fractions on Cartilage Regeneration Was Quantitatively Evaluated Based on the 3D-FS-SPGR Sequence: A Clinical Trial Study.

BACKGROUND: Numerous reports confirmed the safety and clinical efficacy of autologous adipose-derived stromal vascular fractions (SVF), which have recently been used to treat osteoarthritis (OA). However, there is still no consensus as to whether SVF can promote cartilage regeneration. Herein, the purpose of our study was to evaluate the effectiveness of SVF versus hyaluronic acid (HA) in cartilage regeneration by establishing a cartilage model based on the three-dimensional fat-suppressed spoiled gradient recalled echo (3D-FS-SPGR) sequence. METHODS: Patients with symptomatic OA were recruited in our research, who were randomized into two groups. Meanwhile, patients in Kellgren-Lawrence (K-L) grades 2 and 3 were distinguished in each group. In the test group, patients received SVF injections of the knee, while patients in the control group received the same dose of HA. Each patient underwent the 3D-FS-SPGR sequence to establish a cartilage model at baseline, 6 months, and 12 months, respectively. The cartilage was characterized into six regions, and relevant parameters of the cartilage model were counted. Clinical and radiographic scores were recorded in one-year follow-up. RESULTS: In all regions, the thickness and volume of cartilage defect and the volume of healthy cartilage were improved to some extent in the test group, especially the medial femoral condyle (MF) and medial tibial condyle (MT). In grades 2 and 3, the thickness and volume of cartilage defect decreased by 0.92 ± 0.18 mm and 1.03 ± 0.23 mm and 84.00 ± 32.30 mm3 and 130.30 ± 49.56 mm3 in MF and by 0.96 ± 0.22 mm and 0.99 ± 0.14 mm and 64.18 ± 21.40 mm3 and 95.11 ± 19.93 mm3 in MT, respectively. No such phenomenon was observed in the control group. Meanwhile, the SVF-treated knees showed significant improvement in clinical and radiographic scores at 12 months. Nevertheless, these scores of the control group became worse at 12-month follow-up visit. CONCLUSION: Taken together, this study shows that intra-articular injection of SVF markedly improved the clinical symptoms without adverse events, thereby repairing the damaged articular cartilage through cartilage regeneration.

Advanced Nanofiber-Based Scaffolds for Achilles Tendon Regenerative Engineering.

The Achilles tendon (AT) is responsible for running, jumping, and standing. The AT injuries are very common in the population. In the adult population (21-60 years), the incidence of AT injuries is approximately 2.35 per 1,000 people. It negatively impacts people's quality of life and increases the medical burden. Due to its low cellularity and vascular deficiency, AT has a poor healing ability. Therefore, AT injury healing has attracted a lot of attention from researchers. Current AT injury treatment options cannot effectively restore the mechanical structure and function of AT, which promotes the development of AT regenerative tissue engineering. Various nanofiber-based scaffolds are currently being explored due to their structural similarity to natural tendon and their ability to promote tissue regeneration. This review discusses current methods of AT regeneration, recent advances in the fabrication and enhancement of nanofiber-based scaffolds, and the development and use of multiscale nanofiber-based scaffolds for AT regeneration.

Advanced injectable hydrogels for cartilage tissue engineering.

The rapid development of tissue engineering makes it an effective strategy for repairing cartilage defects. The significant advantages of injectable hydrogels for cartilage injury include the properties of natural extracellular matrix (ECM), good biocompatibility, and strong plasticity to adapt to irregular cartilage defect surfaces. These inherent properties make injectable hydrogels a promising tool for cartilage tissue engineering. This paper reviews the research progress on advanced injectable hydrogels. The cross-linking method and structure of injectable hydrogels are thoroughly discussed. Furthermore, polymers, cells, and stimulators commonly used in the preparation of injectable hydrogels are thoroughly reviewed. Finally, we summarize the research progress of the latest advanced hydrogels for cartilage repair and the future challenges for injectable hydrogels.

Bone metastasis risk and prognosis assessment models for kidney cancer based on machine learning.

Background: Bone metastasis is a common adverse event in kidney cancer, often resulting in poor survival. However, tools for predicting KCBM and assessing survival after KCBM have not performed well. Methods: The study uses machine learning to build models for assessing kidney cancer bone metastasis risk, prognosis, and performance evaluation. We selected 71,414 kidney cancer patients from SEER database between 2010 and 2016. Additionally, 963 patients with kidney cancer from an independent medical center were chosen to validate the performance. In the next step, eight different machine learning methods were applied to develop KCBM diagnosis and prognosis models while the risk factors were identified from univariate and multivariate logistic regression and the prognosis factors were analyzed through Kaplan-Meier survival curve and Cox proportional hazards regression. The performance of the models was compared with current models, including the logistic regression model and the AJCC TNM staging model, applying receiver operating characteristics, decision curve analysis, and the calculation of accuracy and sensitivity in both internal and independent external cohorts. Results: Our prognosis model achieved an AUC of 0.8269 (95%CI: 0.8083-0.8425) in the internal validation cohort and 0.9123 (95%CI: 0.8979-0.9261) in the external validation cohort. In addition, we tested the performance of the extreme gradient boosting model through decision curve analysis curve, Precision-Recall curve, and Brier score and two models exhibited excellent performance. Conclusion: Our developed models can accurately predict the risk and prognosis of KCBM and contribute to helping improve decision-making.

Osteoporosis, fracture and survival: Application of machine learning in breast cancer prediction models.

The risk of osteoporosis in breast cancer patients is higher than that in healthy populations. The fracture and death rates increase after patients are diagnosed with osteoporosis. We aimed to develop machine learning-based models to predict the risk of osteoporosis as well as the relative fracture occurrence and prognosis. We selected 749 breast cancer patients from two independent Chinese centers and applied six different methods of machine learning to develop osteoporosis, fracture and survival risk assessment models. The performance of the models was compared with that of current models, such as FRAX, OSTA and TNM, by applying ROC, DCA curve analysis, and the calculation of accuracy and sensitivity in both internal and independent external cohorts. Three models were developed. The XGB model demonstrated the best discriminatory performance among the models. Internal and external validation revealed that the AUCs of the osteoporosis model were 0.86 and 0.87, compared with the FRAX model (0.84 and 0.72)/OSTA model (0.77 and 0.66), respectively. The fracture model had high AUCs in the internal and external cohorts of 0.93 and 0.92, which were higher than those of the FRAX model (0.89 and 0.86). The survival model was also assessed and showed high reliability via internal and external validation (AUC of 0.96 and 0.95), which was better than that of the TNM model (AUCs of 0.87 and 0.87). Our models offer a solid approach to help improve decision making.

Identification of Novel Mutations in the EXT1 and EXT2 Genes of Chinese Patients with Hereditary Multiple Osteochondromas.

Aim: To detect mutations in the EXT1 and EXT2 genes in four Chinese families with hereditary multiple osteochondromas (HMO). HMO is an autosomal dominant disorder characterized by the overgrowth of multiple cartilage-capped bones in the metaphysis of long bones and flat bones. Methods: Polymerase chain reaction-based amplification followed by DNA sequencing of the complete coding sequences of EXT1 and EXT2 was performed for four Chinese families with HMO. Results: The mutant allele was found in six patients: three mutations were found in EXT1 and two in EXT2. A novel frameshift mutation, which generates a premature stop codon at codon 586 and causes partial loss of the glycosyltransferase domain, was detected in exon 9 of EXT1 (F579Yfs*8). We hypothesize that F579Yfs*8 is a pathogenic mutation. Two novel missense mutations (G339S and V545D) were found in EXT1. The variant c.1634T>A (V545D) is apparently benign. In addition we found a novel deletion mutation in EXT2, c.856_864 del TTCCTCCTG, which results in the deletion of 286Phe, 287Leu, and 288Leu, that is likely pathogenic. Finally, we identified a likely benign variant in exon 13 of EXT2. c.2035-41T>C (rs3740878). Conclusions: We found three novel, potentially pathogenic mutations in EXT1 and EXT2, including a novel frameshift mutation. More importantly, our study results have expanded the spectrum of EXT mutations conducive to the genetic diagnosis and counseling of patients with HMO.

The application prospect of metal/metal oxide nanoparticles in the treatment of osteoarthritis.

The current understanding of osteoarthritis is developing from a mechanical disease caused by cartilage wear to a complex biological response involving inflammation, oxidative stress and other aspects. Nanoparticles are widely used in drug delivery due to its good stability in vivo and cell uptake efficiency. In addition to the above advantages, metal/metal oxide NPs, such as cerium oxide and manganese dioxide, can also simulate the activity of antioxidant enzymes and catalyze the degradation of superoxide anions and hydrogen peroxide. Degrading of metal/metal oxide nanoparticles releases metal ions, which may slow down the progression of osteoarthritis by inhibiting inflammation, promoting cartilage repair and inhibiting cartilage ossification. In present review, we focused on recent research works concerning osteoarthritis treating with metal/metal oxide nanoparticles, and introduced some potential nanoparticles that may have therapeutic effects.

Immunopolarization-regulated 3D printed-electrospun fibrous scaffolds for bone regeneration.

Three-dimension (3D)-printed bioscaffolds are precise and personalized for bone regeneration. However, customized 3D scaffolds may activate the immune response in vivo and consequently impede bone formation. In this study, with layer-by-layer deposition and electrospinning technology to control the physical structure, 3D-printed PCL scaffolds with PLLA electrospun microfibrous (3D-M-EF) and nanofibrous (3D-N-EF) composites were constructed, and their immunomodulatory effect and the subsequent osteogenic effects were explored. Compared to 3D-N-EF scaffolds, 3D-M-EF scaffolds polarized more RAW264.7 cells toward alternatively activated macrophages (M2), as demonstrated by increased M2 and deceased classically activated macrophage (M1) phenotypic marker expression in the cells. In addition, the 3D-M-EF scaffolds shifted RAW264.7 cells to the M2 phenotype through PI3K/AKT signaling and enhanced VEGF and BMP-2 expression. Conditional medium from the RAW264.7 cells seeded in 3D-M-EF scaffolds promoted osteogenesis of MC3T3-E1 cells. Furthermore, in vivo study of repairing rat calvarial defects, the 3D-M-EF scaffolds increased the polarization of M2 macrophages, enhanced angiogenesis, and accelerated new bone formation. Collectively, our data suggested that well-designed 3D-M-EF scaffolds are favorable for osteogenesis through regulation of M2 polarization. Therefore, it is potential to utilize the physical structure of 3D-printed scaffolds to manipulate the osteoimmune environment to promote bone regeneration.

Nomogram Predicts Risk and Prognostic Factors for Bone Metastasis of Pancreatic Cancer: A Population-Based Analysis.

Background: The overall survival (OS) of pancreatic cancer (PC) patients with bone metastasis (BM) is extremely low, and it is pretty hard to treat bone metastasis. However, there are currently no effective nomograms to predict the diagnosis and prognosis of pancreatic cancer with bone metastasis (PCBM). Therefore, it is of great significance to establish effective predictive models to guide clinical practice. Methods: We screened patients from Surveillance Epidemiology and End Results (SEER) database between 2010 and 2016. The independent risk factors of PCBM were identified from univariable and multivariable logistic regression analyses, and univariate and multivariate Cox proportional hazards regression analyses were used to determine independent prognostic factors affecting the prognosis of PCBM. In addition, two nomograms were constructed to predict the risk and prognosis of PCBM. We used the area under the curve (AUC), C-index and calibration curve to determine the predictive accuracy and discriminability of nomograms. The decision curve analysis (DCA) and Kaplan-Meier(K-M) survival curves were employed to further confirm the clinical effectiveness of the nomogram. Results: Multivariable logistic regression analyses revealed that risk factors of PCBM included age, primary site, histological subtype, N stage, radiotherapy, surgery, brain metastasis, lung metastasis, and liver metastasis. Using Cox regression analyses, we found that independent prognostic factors of PCBM were age, race, grade, histological subtype, surgery, chemotherapy, and lung metastasis. We utilized nomograms to visually express data analysis results. The C-index of training cohort was 0.795 (95%CI: 0.758-0.832), whereas that of internal validation cohort was 0.800 (95%CI: 0.739-0.862), and the external validation cohort was 0.787 (95%CI: 0.746-0.828). Based on AUC of receiver operating characteristic (ROC) analysis, calibration plots, and decision curve analysis (DCA), we concluded that the risk and prognosis model of PCBM exhibits excellent performance. Conclusion: Nomogram is sufficiently accurate to predict the risk and prognostic factors of PCBM, allowing for individualized clinical decisions for future clinical work.

Novel Mutations in Chinese Patients with Multiple Osteochondromas Identified Using Whole Exome Sequencing.

Background: Multiple osteochondromas (MO) are an autosomal-dominant disease characterized by the growth of multiple cartilage-capped prominences in the growth plate region of the metaphysis in long and flat bones. Materials and Methods: To detect genetic mutations related to MO, a three-generation Chinese family with MO was evaluated using whole exome sequencing for mutation screening. The candidate pathogenic mutation was validated by Sanger sequencing. Results: A novel frameshift (NM_000401.3:c.1321del:p.Leu441TrpfsTer28) in exon 8 of the exotosin 2 (EXT2) gene was identified in two affected individuals. Codons 441 and 468 in the EXT2 gene are highly conserved among vertebrates as demonstrated by multiple sequence alignment. The c.1321 del C resulted in an amino acid change at codon 441, which generated a premature stop codon at position 468, causing complete loss of the glycosyltransferase domain. Conclusions: A novel frameshift mutation c.1321delC detected in the EXT2 gene may help in prenatal genetic screening and early diagnosis of MO.

Development and Prospect of Intra-Articular Injection in the Treatment of Osteoarthritis: A Review.

Osteoarthritis (OA) is a common degenerative disease that affects the vast majority of the elderly and may eventually embark on the road of the total knee arthroplasty (TKA), although controversy still exists in the medical community about the best therapies for osteoarthritis. Compared with physical therapy, oral analgesics and other non-operative treatments, intra-articular injection is more safe and effective. Moreover, intra-articular injection is much less invasive and has fewer adverse reactions than surgical treatment. This article reviews mechanism, benefits and adverse reactions of corticosteroids (CS), hyaluronic acid (HA), platelet-rich plasma (PRP), mesenchymal stem cell (MSCs), stromal vascular fraction (SVF) and other new therapies (for example: gene therapy). The application prospect of intra-articular injection was analyzed according to the recent progress in drug research.