Hemiarthroplasty vs. internal fixation for nondisplaced femoral neck fracture in mainland China: a cost-effectiveness analysis.

Objective: Nondisplaced femoral neck fractures constitute a substantial portion of these injuries. The optimal treatment strategy between internal fixation (IF) and hemiarthroplasty (HA) remains debated, particularly concerning cost-effectiveness. Methods: We conducted a cost-effectiveness analysis using a Markov decision model to compare HA and IF in treating nondisplaced femoral neck fractures in elderly patients in China. The analysis was performed from a payer perspective with a 5-year time horizon. Costs were measured in 2020 USD, and effectiveness was measured in quality-adjusted life-years (QALYs). Sensitivity analyses, including one-way and probabilistic analyses, were conducted to assess the robustness of the results. The willingness-to-pay threshold for incremental cost-effectiveness ratio (ICER) was set at $11,083/QALY following the Chinese gross domestic product in 2020. Results: HA demonstrated higher cumulative QALYs (2.94) compared to IF (2.75) but at a higher total cost ($13,324 vs. $12,167), resulting in an ICER of $6,128.52/QALY. The one-way sensitivity analysis identified the costs of HA and IF as the most influential factors. Probabilistic sensitivity analysis indicated that HA was more effective in 69.3% of simulations, with an ICER below the willingness-to-pay threshold of $11,083 in 58.8% of simulations. Conclusions: HA is a cost-effective alternative to IF for treating nondisplaced femoral neck fractures in elderly patients in mainland China.

Paeoniflorin suppresses ferroptosis after traumatic brain injury by antagonizing P53 acetylation.

BACKGROUND: Traumatic brain injury (TBI) could induce multiple forms of cell death, ferroptosis, a novel form of cell death distinct from apoptosis and autophagy, plays an important role in disease progression in TBI. Therapies targeting ferroptosis are beneficial for recovery from TBI. Paeoniflorin (Pae) is a water-soluble monoterpene glycoside and the active ingredient of Paeonia lactiflora pall. It has been shown to exert anti-inflammatory and antioxidant effects. However The effects and mechanisms of paeoniflorin on secondary injury after TBI are unknown. PURPOSE: To investigate the mechanism by which Pae regulates ferroptosis after TBI. METHODS: The TBI mouse model and cortical primary neurons were utilized to study the protective effect of paeoniflorin on the brain tissue after TBI. The neuronal cell ferroptosis model was established by treating cortical primary neurons with erastin. Liproxstatin-1(Lip-1) was used as a positive control drug. Immunofluorescence staining, Nissl staining, biochemical analyses, pharmacological analyses, and western blot were used to evaluate the effects of paeoniflorin on TBI. RESULTS: Pae significantly ameliorated neuronal damage after TBI, inhibited mitochondrial damage, increased glutathione peroxidase 4 (GPX4) activity, decreased malondialdehyde (MDA) production, restored neurological function and inhibited cerebral edema. Pae promotes the degradation of P53 in the form of proteasome, promotes its ubiquitination, and reduces the stability of P53 by inhibiting its acetylation, thus alleviating the P53-mediated inhibition of cystine/glutamate antiporter solute carrier family 7 member 11 (SLC7A11) by P53. CONCLUSION: Pae inhibits ferroptosis by promoting P53 ubiquitination out of the nucleus, inhibiting P53 acetylation, and modulating the SLC7A11-GPX4 pathway.

[Effect of chronic periodontitis on quality of life and severity in patients with bronchiectasis].

PURPOSE: To investigate the effects of chronic periodontitis on the quality of life and severity of the disease in patients with bronchiectasis. METHODS: A total of 80 bronchiectasis patients admitted to The Fourth Hospital of Changsha between April 2021 and April 2023 were randomly selected. Patients were divided into two groups according to whether they had moderate to severe chronic periodontitis: bronchiectasis with periodontitis group (n=45) and bronchiectasis without periodontitis group (n=35). The Qualify of Life Questionnaire for Bronchiectasi(QoL-B) was used to assess patients' quality. The severity of the disease was assessed using the Bronchiectasis Severity Index (BSI), and serum levels of hypersensitive C-reactive protein (hsCRP), tumor necrosis factor alpha(TNF-alpha), and interleukin-6(IL-6) were detected. SPSS 20.0 software package was used for data analysis. RESULTS: The QoL-B score of bronchiectasis with periodontitis group was significantly lower than that of bronchiectasis without periodontitis group, and the BSI score was significantly higher than that of bronchiectasis without periodontitis group(P＜0.05). The levels of hs-CRP, TNF-alpha and IL-6 in bronchiectasis with periodontitis were significantly higher than those in bronchiectasis without periodontitis group(P＜0.05). CONCLUSIONS: Chronic periodontitis shows significant adverse effects on both quality of life and disease severity in patients with bronchiectasis, which may be related to the common mechanism of inflammatory response between the two kinds of diseases.

SSM-Net: Semi-supervised multi-task network for joint lesion segmentation and classification from pancreatic EUS images.

Pancreatic cancer does not show specific symptoms, which makes the diagnosis of early stages difficult with established image-based screening methods and therefore has the worst prognosis among all cancers. Although endoscopic ultrasonography (EUS) has a key role in diagnostic algorithms for pancreatic diseases, B-mode imaging of the pancreas can be affected by confounders such as chronic pancreatitis, which can make both pancreatic lesion segmentation and classification laborious and highly specialized. To address these challenges, this work proposes a semi-supervised multi-task network (SSM-Net) to leverage unlabeled and labeled EUS images for joint pancreatic lesion classification and segmentation. Specifically, we first devise a saliency-aware representation learning module (SRLM) on a large number of unlabeled images to train a feature extraction encoder network for labeled images by computing a contrastive loss with a semantic saliency map, which is obtained by our spectral residual module (SRM). Moreover, for labeled EUS images, we devise channel attention blocks (CABs) to refine the features extracted from the pre-trained encoder on unlabeled images for segmenting lesions, and then devise a merged global attention module (MGAM) and a feature similarity loss (FSL) for obtaining a lesion classification result. We collect a large-scale EUS-based pancreas image dataset (LS-EUSPI) consisting of 9,555 pathologically proven labeled EUS images (499 patients from four categories) and 15,500 unlabeled EUS images. Experimental results on the LS-EUSPI dataset and a public thyroid gland lesion dataset show that our SSM-Net clearly outperforms state-of-the-art methods.

[Intraoperative slide rail CT assistance in percutaneous sacroiliac joint screws for the treatment of pelvic posterior ring injury].

OBJECTIVE: To compare the clinical efficacy of intraoperative slide rail CT combined with C-arm X-ray assistance and just C-arm for percutaneous screw in the treatment of pelvic posterior ring injury. METHODS: A retrospective analysis was performed on the patient data of 76 patients with posterior pelvic ring injury admitted to the Department of Orthopedic Trauma from December 2018 to February 2022. Among them, 39 patients in the CT group were treated with C-arm combined with slide rail CT-assisted inline fixation including 23 males and 16 females with an average age of (44.98±7.33) years old;and the other 37 patients in the C-arm group were treated with intraline fixation treatment under only C-arm fluoroscopy including 24 males and 13 females with an average age of (44.37±10.82) years old. Among them, 42 patients with anterior ring fractures were treated with percutaneous inferior iliac spines with internal fixation (INFIX) or suprapubic support screws to fix the anterior pelvic ring. Postoperative follow-up time, operation time, complications of the two groups were compared. Results of Matta reduction criteria, Majed efficacy evaluation, the CT grading and the rate of secondary surgical revision were compared. RESULTS: The nailing time of (32.63±7.33) min in CT group was shorter than that of (52.95±10.64) min in C-arm group (t=-9.739, P<0.05). The follow-up time between CT group (11.97±1.86) months and C-arm group (12.03±1.71) months were not statistically significant(P>0.05). The postoperative complication rates between two groups were not statistically significant (χ2=0.159, P>0.05). Results of Matta reduction criteria (Z=2.79, P<0.05), Majeed efficacy evaluation(Z=2.79, P<0.05), CT grading (Z=2.83, P<0.05) in CT group were better than those in C-arm group(P<0.05); the secondary surgical revision rate in the CT group was significantly lower than that in the C-arm group (χ2=5.641, P<0.05). CONCLUSION: Compared with traditional C-arm fluoroscopy, intraoperative slide rail CT combined with C-arm assisted percutaneous sacroiliac joint screw placement surgery has the characteristics of short operation time, high accuracy and safety, and significant decrease in postoperative secondary revision rate, and is one of the effective methods for re-establishing the stability of the posterior ring of pelvic fracture.

Improvements to a GLCM-based machine-learning approach for quantifying posterior capsule opacification.

BACKGROUND: Posterior capsular opacification (PCO) is a common complication following cataract surgery that leads to visual disturbances and decreased quality of vision. The aim of our study was to employ a machine-learning methodology to characterize and validate enhancements applied to the grey-level co-occurrence matrix (GLCM) while assessing its validity in comparison to clinical evaluations for evaluating PCO. METHODS: One hundred patients diagnosed with age-related cataracts who were scheduled for phacoemulsification surgery were included in the study. Following mydriasis, anterior segment photographs were captured using a high-resolution photographic system. The GLCM was utilized as the feature extractor, and a supported vector machine as the regressor. Three variations, namely, GLCM, GLCM+C (+axial information), and GLCM+V (+regional voting), were analyzed. The reference value for regression was determined by averaging clinical scores obtained through subjective analysis. The relationships between the predicted PCO outcome scores and the ground truth were assessed using Pearson correlation analysis and a Bland-Altman plot, while agreement between them was assessed through the Bland-Altman plot. RESULTS: Relative to the ground truth, the GLCM, GLCM+C, and GLCM+V methods exhibited correlation coefficients of 0.706, 0.768, and 0.829, respectively. The relationship between the PCO score predicted by the GLCM+V method and the ground truth was statistically significant (p < 0.001). Furthermore, the GLCM+V method demonstrated competitive performance comparable to that of two experienced clinicians (r = 0.825, 0.843) and superior to that of two junior clinicians (r = 0.786, 0.756). Notably, a high level of agreement was observed between predictions and the ground truth, without significant evidence of proportional bias (p > 0.05). CONCLUSIONS: Overall, our findings suggest that a machine-learning approach incorporating the GLCM, specifically the GLCM+V method, holds promise as an objective and reliable tool for assessing PCO progression. Further studies in larger patient cohorts are warranted to validate these findings and explore their potential clinical applications.

DSMT-Net: Dual Self-Supervised Multi-Operator Transformation for Multi-Source Endoscopic Ultrasound Diagnosis.

Pancreatic cancer has the worst prognosis of all cancers. The clinical application of endoscopic ultrasound (EUS) for the assessment of pancreatic cancer risk and of deep learning for the classification of EUS images have been hindered by inter-grader variability and labeling capability. One of the key reasons for these difficulties is that EUS images are obtained from multiple sources with varying resolutions, effective regions, and interference signals, making the distribution of the data highly variable and negatively impacting the performance of deep learning models. Additionally, manual labeling of images is time-consuming and requires significant effort, leading to the desire to effectively utilize a large amount of unlabeled data for network training. To address these challenges, this study proposes the Dual Self-supervised Multi-Operator Transformation Network (DSMT-Net) for multi-source EUS diagnosis. The DSMT-Net includes a multi-operator transformation approach to standardize the extraction of regions of interest in EUS images and eliminate irrelevant pixels. Furthermore, a transformer-based dual self-supervised network is designed to integrate unlabeled EUS images for pre-training the representation model, which can be transferred to supervised tasks such as classification, detection, and segmentation. A large-scale EUS-based pancreas image dataset (LEPset) has been collected, including 3,500 pathologically proven labeled EUS images (from pancreatic and non-pancreatic cancers) and 8,000 unlabeled EUS images for model development. The self-supervised method has also been applied to breast cancer diagnosis and was compared to state-of-the-art deep learning models on both datasets. The results demonstrate that the DSMT-Net significantly improves the accuracy of pancreatic and breast cancer diagnosis.

The inverse association between fasting blood glucose and the occurrence of gallbladder cancer in type 2 diabetes mellitus patients: a case-control study.

OBJECTIVE: This study aimed to explore the correlation between diabetes mellitus (DM) and gallbladder cancer (GBC) in an epidemiological setting. METHODS: The study summarized the clinical and laboratory data of 2210 GBC Chinese patients in the authors' hospital. A total of 17 influencing factors for GBC, including gender, body mass index (BMI), fasting blood glucose (FBG), fasting insulin (FINS), the homeostasis model assessment of insulin resistance (HOMA-IR), retinol-binding protein 4 (RBP4), and lipid indexes were analyzed using unconditional logistic regression analysis. RESULTS: Based on the results of univariate logistic regression, the risk of GBC was significantly and positively correlated with serum triglyceride, low-density lipoprotein, FINS, HOMA-IR, being female, BMI, DM, non-alcoholic fatty liver disease, and gallbladder stone disease (GSD), and significantly negatively correlated with high-density lipoprotein and FBG concentrations in serum, as well as hypertension. According to multivariate analysis, FINS was significantly positively associated with GBC risk, while DM showed an insignificant negative association; FBG was also not important. The most significant independent factor of GBC risk in patients with DM was HOMA-IR. Fasting blood glucose levels showed a significant negative relationship with GBC in patients with DM. In addition, this study indicated a significantly negative association between serum RBP levels and GBC. CONCLUSIONS: The findings of the current study revealed that the efficient treatment of insulin resistance is an important approach for decreasing GBC risk, as opposed to lowering blood sugar only, particularly in patients with DM. Interestingly, FBG may have had an inverse association with the development of GBC in patients with type 2 DM. Of note, the study found that a dramatic initial drop in RBP may help predict the occurrence of GBC.

Preparation, characteristics and cytotoxicity of green synthesized selenium nanoparticles using Paenibacillus motobuensis LY5201 isolated from the local specialty food of longevity area.

Selenium is an essential micronutrient element. For the extremely biotoxic of selenite, Selenium nanoparticles (SeNPs) is gaining increasing interest. In this work, a selenium-enriched strain with highly selenite-resistant (up to 173 mmol/L) was isolated from the local specialty food of longevity area and identified as Paenibacillus motobuensis (P. motobuensis) LY5201. Most of the SeNPs were accumulated extracellular. SeNPs were around spherical with a diameter of approximately 100 nm. The X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy showed that the purified SeNPs consisted of selenium and proteins. Our results suggested that P. motobuensis LY5201could be a suitable and robust biocatalyst for SeNPs synthesis. In addition, the cytotoxicity effect and the anti-invasive activity of SeNPs on the HepG2 showed an inhibitory effect on HepG2, indicating that SeNPs could be used as a potential anticancer drug.

Focusing on the amount of immediate changes in spinopelvic radiographic parameters to predict the amount of mid-term improvement of quality of life in adult degenerative scoliosis patients with surgery.

INTRODUCTION: Surgery is still an effective treatment option for adult degenerative scoliosis (ADS), but how to predict patients' significant amount of the improvement in quality of life remains unclear. The previous studies included an inhomogeneous population. This study aimed to report the results about concentrating on the amount of immediate changes in spinopelvic radiographic parameters to predict the amount of mid-term improvement in quality of life in ADS patients. MATERIALS AND METHODS: Pre-operative and immediately post-operative radiographic parameters included Cobb angle, coronal vertical axis (CVA), sagittal vertical axis (SVA), lumbar lordosis (LL), thoracic kyphosis (TK), pelvic tilt (PT), sacral slope (SS), pelvic incidence (PI) and LL/PI matching (PI-LL). Quality of life scores were evaluated pre-operatively and at the final follow-up using Oswestry Disability Index (ODI) and visual analogue scale (VAS). The amount of immediate changes in spinopelvic radiographic parameters (Δ) and the amount of mid-term improvement in quality of life (Δ) were defined, respectively. RESULTS: Patients showed significant change in radiographic parameters, ODI and VAS pre- and post-surgery, except CVA and PI. Univariate analysis showed a significant correlation between ΔTK, ΔLL, ΔCVA and the amount of mid-term improvement in quality of life, but multivariate analysis did not get a significant result. Univariate and multivariate analyses showed that ΔSVA was still a significant predictor of ΔVAS and ΔODI. The changes in the other radiographic parameters were not significant. The equations were developed by linear regression: ΔODI = 0.162 × ΔSVA - 21.592, ΔVAS = 0.034 × ΔSVA - 2.828. In the ROC curve for ΔSVA in the detection of a strong ΔODI or ΔVAS, the cut-off value of ΔSVA was - 19.855 mm and - 15.405 mm, respectively. CONCLUSIONS: This study shows that ΔSVA can predict the amount of mid-term improvement in quality of life in ADS patients. The changes in the other radiographic parameters were not significant. Two equations were yielded to estimate ΔODI and ΔVAS. ΔSVA has respective cut-off value to predict ΔODI and ΔVAS.

An overview of artificial intelligence in diabetic retinopathy and other ocular diseases.

Artificial intelligence (AI), also known as machine intelligence, is a branch of science that empowers machines using human intelligence. AI refers to the technology of rendering human intelligence through computer programs. From healthcare to the precise prevention, diagnosis, and management of diseases, AI is progressing rapidly in various interdisciplinary fields, including ophthalmology. Ophthalmology is at the forefront of AI in medicine because the diagnosis of ocular diseases heavy reliance on imaging. Recently, deep learning-based AI screening and prediction models have been applied to the most common visual impairment and blindness diseases, including glaucoma, cataract, age-related macular degeneration (ARMD), and diabetic retinopathy (DR). The success of AI in medicine is primarily attributed to the development of deep learning algorithms, which are computational models composed of multiple layers of simulated neurons. These models can learn the representations of data at multiple levels of abstraction. The Inception-v3 algorithm and transfer learning concept have been applied in DR and ARMD to reuse fundus image features learned from natural images (non-medical images) to train an AI system with a fraction of the commonly used training data (<1%). The trained AI system achieved performance comparable to that of human experts in classifying ARMD and diabetic macular edema on optical coherence tomography images. In this study, we highlight the fundamental concepts of AI and its application in these four major ocular diseases and further discuss the current challenges, as well as the prospects in ophthalmology.

Intraoperative CT-assisted sacroiliac screws fixation for the treatment of posterior pelvic ring injury: a comparative study with conventional intraoperative imaging.

Pelvic injuries refer to the disruption of the inherent structural and mechanical integrity of the pelvic ring. Sacroiliac screw fixation technique is often applied for the treatment of posterior pelvic ring injury, which is prone to the iatrogenic injury. This study will compare the intraoperative and postoperative variables of patients underwent sacroiliac screw fixation with intraoperative CT and conventional imaging to evaluate the effect. Thirty-two patients with posterior pelvic ring injury treated by sacroiliac screw fixation from January 2019 to December 2020 were enrolled in this retrospective study. All patients were divided into two groups according to the different assistance of intraoperative imaging. Subsequently, the correlative data were compared and analysed statistically. Twelves cases were assigned to intraoperative CT group, and the remaining twenty cases were assigned to conventional group. There was no significant difference in duration of surgery, fracture healing time, time to ambulation, complications, and Matta radiological score. There was statistically significant difference (p < 0.05) in sacroiliac screws insertion time, length of incision, intraoperative blood loss, quality of screws position, and adjusted Majeed functional score, especially in the sexual intercourse part. With the assistance of intraoperative CT, a less misposition and functional impairment could be achieved, and a more satisfactory curative effect could be developed. Sacroiliac screws fixation with intraoperative CT is a more accurate and ideal method to treat posterior pelvic ring injuries.

Does preoperative morphology of multifidus influence the surgical outcomes of stand-alone lateral lumbar interbody fusion for lumbar spondylolisthesis?

OBJECTIVES: To investigate whether the preoperative morphology of multifidus influences the surgical outcomes of stand-alone lateral lumbar interbody fusion (LLIF) for lumbar spondylolisthesis. PATIENTS AND METHODS: Fifty-eight patients with lumbar spondylolisthesis who underwent single-level, stand-alone LLIF at the L4-5 level were included and followed up for at least 12 months. Preoperative axial cross-sectional area (CSA) and fat infiltration rate (FIR) of multifidus on MRI scans were measured using the ImageJ software. The CSA ratio and FIR were calculated and classified into three grades. Preoperative and final visual analogue scale (VAS) scores for back pain and leg pain, Oswestry Disability Index (ODI) scores were recorded. Cage subsidence and fusion were also evaluated at the final follow-up. Correlations between VAS scores, ODI scores, obvious cage subsidence and fusion rate with the CSA ratio and FIR were analyzed. RESULTS: There were significant correlations between preoperative and final VAS scores for back pain and ODI scores with the CSA ratio and FIR. There was an overall trend towards improvements in back pain and lumbar function in patients with superior morphology of multifidus. In addition, obvious cage subsidence was found to be associated with lower preoperative CSA ratios and higher FIR, whereas fusion rate was only correlated with FIR. CONCLUSIONS: The preoperative morphology of multifidus influenced the surgical outcomes of stand-alone LLIF for lumbar spondylolisthesis. Patients with superior morphology of multifidus showed better outcomes following stand-alone LLIF.

Sacroiliac screws fixation navigated with three-dimensional printing personalized guide template for the treatment of posterior pelvic ring injury: A case report.

Objective: Pelvic injuries refer to the disruption of the inherent structural and mechanical integrity of the pelvic ring. Sacroiliac screw fixation technique is often used for the treatment of posterior pelvic ring injury, which is prone to the iatrogenic injury. Various attempts were proposed to avoid iatrogenic injuries, while the executing processes are usually too cumbersome. The patient-personalized guide template based on 3D printing technology has been considered as a promising method, which can achieve lower deviation and higher accuracy in a simple and convenient way. We reported the first case of posterior pelvic ring injury using 3D printing personalized guide template with the verification of intraoperative CT. Methods: The subject was a 74-year-old female with posterior pelvic ring injury. Two patient-specific guide templates were customized based on 3D printing technology, one for S1 and the other for S2. We used the guide templates for navigation to place the sacroiliac screws. The placement of screws was verified by intraoperative CT. Intraoperative and postoperative variables were collected. Results: The technique helped us successfully insert the sacroiliac screws into the safe zone. The intraoperative blood loss was 23.03 ml, and the duration of operation was 62 min. The exposure dose during CT scanning was 7.025 mSv. The assessment of screws position was excellent. Furthermore, there was no sign of any functional impairment postoperatively. Conclusion: Sacroiliac screws fixation with the assistance of 3D printing personalized guide template under the verification of intraoperative CT may be a promising method to treat posterior pelvic ring injuries.

USP12 promotes breast cancer angiogenesis by maintaining midkine stability.

Deubiquitinases (DUBs) have important biological functions, but their roles in breast cancer metastasis are not completely clear. In this study, through screening a series of DUBs related to breast cancer distant metastasis-free survival (DMFS) in the Kaplan-Meier Plotter database, we identified ubiquitin-specific protease 12 (USP12) as a key deubiquitinating enzyme for breast cancer metastasis. We confirmed this via an orthotopic mouse lung metastasis model. We revealed that the DMFS of breast cancer patients with high USP12 was worse than that of others. Knockdown of USP12 decreased the lung metastasis ability of 4T1 cells, while USP12 overexpression increased the lung metastasis ability of these cells in vivo. Furthermore, our results showed that the supernatant from USP12-overexpressing breast cancer cells could promote angiogenesis according to human umbilical vein endothelial cell (HUVEC) migration and tube formation assays. Subsequently, we identified midkine (MDK) as one of its substrates. USP12 could directly interact with MDK, decrease its polyubiquitination and increase its protein stability in cells. Overexpression of MDK rescued the loss of angiogenesis ability mediated by knockdown of USP12 in breast cancer cells in vitro and in vivo. There was a strong positive relationship between USP12 and MDK protein expression in clinical breast cancer samples. Consistent with the pattern for USP12, high MDK expression predicted lower DMFS and overall survival (OS) in breast cancer. Collectively, our study identified that USP12 is responsible for deubiquitinating and stabilizing MDK and leads to metastasis by promoting angiogenesis. Therefore, the USP12-MDK axis could serve as a potential target for the therapeutic treatment of breast cancer metastasis.

Potential genes and pathways associated with heterotopic ossification derived from analyses of gene expression profiles.

BACKGROUND: Heterotopic ossification (HO) represents pathological lesions that refer to the development of heterotopic bone in extraskeletal tissues around joints. This study investigates the genetic characteristics of bone marrow mesenchymal stem cells (BMSCs) from HO tissues and explores the potential pathways involved in this ailment. METHODS: Gene expression profiles (GSE94683) were obtained from the Gene Expression Omnibus (GEO), including 9 normal specimens and 7 HO specimens, and differentially expressed genes (DEGs) were identified. Then, protein-protein interaction (PPI) networks and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for further analysis. RESULTS: In total, 275 DEGs were differentially expressed, of which 153 were upregulated and 122 were downregulated. In the biological process (BP) category, the majority of DEGs, including EFNB3, UNC5C, TMEFF2, PTH2, KIT, FGF13, and WISP3, were intensively enriched in aspects of cell signal transmission, including axon guidance, negative regulation of cell migration, peptidyl-tyrosine phosphorylation, and cell-cell signaling. Moreover, KEGG analysis indicated that the majority of DEGs, including EFNB3, UNC5C, FGF13, MAPK10, DDIT3, KIT, COL4A4, and DKK2, were primarily involved in the mitogen-activated protein kinase (MAPK) signaling pathway, Ras signaling pathway, phosphatidylinositol-3-kinase/protein kinase B (PI3K/Akt) signaling pathway, and Wnt signaling pathway. Ten hub genes were identified, including CX3CL1, CXCL1, ADAMTS3, ADAMTS16, ADAMTSL2, ADAMTSL3, ADAMTSL5, PENK, GPR18, and CALB2. CONCLUSIONS: This study presented novel insight into the pathogenesis of HO. Ten hub genes and most of the DEGs intensively involved in enrichment analyses may be new candidate targets for the prevention and treatment of HO in the future.