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Abstract Background This study aimed to assess the efficacy of a novel spinal osteotomy technique, the posterior trans-intervertebral osteotomy with anterior support, in individuals diagnosed with ankylosing spondylitis. This study utilized computer software to simulate the osteotomy procedure, predict orthopedic outcomes, and assist in preoperative planning. Methods Four patients with ankylosing spondylitis underwent posterior trans-intervertebral osteotomy with anterior support that post-operative follow-up of more than 1 year. Osteotomy was performed using the intervertebral space approach with the cage placed anteriorly in the intervertebral space to improve the correction. Perioperative clinical symptoms, imaging data, and surgical factors were also documented. Results Patients who underwent posterior trans-intervertebral osteotomy with anterior support achieved good clinical results with favorable correction rates and minimal estimated blood loss. The average preoperative, postoperative and follow-up Cobb angles were 90.5° (range: 86–96°), 43.5° (range: 34–52°) and 46.25°(range: 37–55°), respectively. The average estimated blood loss was 500 mL (range: 300–800 mL). Patients with preoperative deficits improved their neurological status, and no complications were observed throughout the postoperative period. Pain, self-image, and mental health in the SRS-22 demonstrated significant improvement at the final follow-up compared to preoperative values. The satisfaction with management score was 3.25 ± 0.65. Conclusions Posterior trans-intervertebral osteotomy with an anterior support procedure was performed through the intervertebral space and subsequent implantation of a cage within the transpedicular space, effectively addressing the constraints associated with the conventional trans-intervertebral osteotomy method. Our preliminary findings indicate that posterior trans-intervertebral osteotomy with anterior support is potentially more secure than the conventional method for correcting ankylosing spondylitis kyphosis.

A multi-objective pedestrian tracking method based on you only look once-v8 (YOLOv8) and the improved simple online and real time tracking with a deep association metric (DeepSORT) was proposed with the purpose of coping with the issues of local occlusion and ID dynamic transformation that frequently arise when tracking target pedestrians in real complex traffic scenarios. To begin with, in order to enhance the feature extraction network's capacity to learn target feature information in busy traffic situations, the detector implemented the YOLOv8 method with a high level of small-scale feature expression. In addition, the omni-scale network (OSNet) feature extraction network was then put on top of DeepSORT in order to accomplish real-time synchronized target tracking. This increases the effectiveness of picture edge recognition by dynamically fusing the collected feature information at various scales. Furthermore, a new adaptive forgetting smoothing Kalman filtering algorithm (FSA) was created to adapt to the nonlinear condition of the pedestrian trajectory in the traffic scene in order to address the issue of poor prediction attributed to the linear state equation of Kalman filtering once more. Afterward, the original intersection over union (IOU) association matching algorithm of DeepSORT was replaced by the complete-intersection over union (CIOU) association matching algorithm to fundamentally reduce the target pedestrians' omission and misdetection situation and to improve the accuracy of data matching. Eventually, the generalized trajectory feature extractor model (GFModel) was developed to tightly merge the local and global information through the average pooling operation in order to get precise tracking results and further decrease the impact of numerous disturbances on target tracking. The fusion algorithm of YOLOv8 and improved DeepSORT method based on OSNet, FSA and GFModel was named YOFGD. According to the experimental findings, YOFGD's ultimate accuracy can reach 77.9% and its speed can reach 55.8 frames per second (FPS), which is more than enough to fulfill the demands of real-world scenarios.

Abstract Background The purpose of this study was to report our surgical experience in patients with lumbosacral degenerative diseases who underwent posterior decompression and interbody fusion fixed with cortical bone trajectory screw and sacral alar screw, which is known as low-profile posterior lumbosacral interbody fusion (LP-PLSIF). Methods Patients with lumbosacral degenerative disease who underwent LP-PLSIF and traditional PLSIF (control group) internally fixed with pedicle screws were included retrospectively. Patients’ demographic data, operative parameters, and perioperative complications were recorded and analyzed. Results A total of 18 patients were enrolled in this study, which included 9 patients (5 male and 4 female) who underwent LP-PLSIF, and 9 patients (4 male and 5 female) who underwent traditional PLSIF. There wasn’t a significant difference in the average age between the two groups, 56.78 ± 10.92 years in the LP-PLSIF group and 60.22 ± 8.21 years in the PLSIF group (p = 0.460). The bone mineral density (BMD) of the two groups of patients were -2.00 ± 0.26 T and -2.13 ± 0.19 T, respectively (P = 0.239). The mean postoperative follow-up time was 12.7 months (range, 12–14 months). The mean operation time was 142.78 ± 11.21 min and 156.11 ± 13.41 min in the LP-PLSIF group and PLSIF group respectively (P

Abstract Recently, discriminative machine learning models have been widely used to predict various attributes from Electron Backscatter Diffraction (EBSD) patterns. However, there has never been any generative model developed for EBSD pattern simulation. On one hand, the training of generative models is much harder than that of discriminative ones; On the other hand, numerous variables affecting EBSD pattern formation make the input space high-dimensional and its relationship with the distribution of backscattered electrons complicated. In this study, we propose a framework (EBSD-CVAE/GAN) with great flexibility and scalability to realize parametric simulation of EBSD patterns. Compared with the frequently used forward model, EBSD-CVAE/GAN can take variables more than just orientation and generate corresponding EBSD patterns in a single run. The accuracy and quality of generated patterns are systematically evaluated. The model does not only summarize a distribution of backscattered electrons at a higher level, but also mitigates data scarcity in this field.

Osteosarcoma (OS) therapy faces many challenges, especially the poor survival rate once metastasis occurs. Therefore, it is crucial to explore new OS treatment strategies that can efficiently inhibit OS metastasis. Bioactive nanoparticles such as zinc oxide nanoparticles (ZnO NPs) can efficiently inhibit OS growth, however, the effect and mechanisms of them on tumor metastasis are still not clear. In this study, we firstly prepared well-dispersed ZnO NPs and proved that ZnO NPs can inhibit OS metastasis-related malignant behaviors including migration, invasion, and epithelial-mesenchymal transition (EMT). RNA-Seqs found that differentially expressed genes (DEGs) in ZnO NP-treated OS cells were enriched in wingless/integrated (Wnt) and hypoxia-inducible factor-1 (HIF-1) signaling pathway. We further proved that Zn2+ released from ZnO NPs induced downregulation of β-catenin expression via HIF-1α/BNIP3/LC3B-mediated mitophagy pathway. ZnO NPs combined with ICG-001, a β-catenin inhibitor, showed a synergistic inhibitory effect on OS lung metastasis and a longer survival time. In addition, tissue microarray (TMA) of OS patients also detected much higher β-catenin expression which indicated the role of β-catenin in OS development. In summary, our current study not only proved that ZnO NPs can inhibit OS metastasis by degrading β-catenin in HIF-1α/BNIP3/LC3B-mediated mitophagy pathway, but also provided a far-reaching potential of ZnO NPs in clinical OS treatment with metastasis.

BackgroundRecent studies have reported better predictive performance of triglyceride glucose (TyG) index for cardiovascular events in women, however, whether this association persists in postmenopausal women is inconclusive. We investigated the association between TyG index and H-type hypertension (HHT) in postmenopausal women.Methods1,301 eligible women with hypertension were included in this cross-sectional study. Concomitant homocysteine levels >10 μmol/L were defined as H-type hypertension. The TyG index was calculated as ln [triglycerides (mg/dl) × fasting glucose (mg/dl)/2]. Multivariable logistic regression models and restricted cubic spline models were used to assess the association between TyG index and H-type hypertension in postmenopausal women, and subgroup analyses were performed for potential confounders.ResultsOf the 1,301 hypertensive patients, 634 (48.7%) participants had H-type hypertension. In each adjusted model, TyG index was significantly associated with the risk of H-type hypertension. each 1-unit increase in TyG index was associated with an increased risk of H-type hypertension in all participants (OR = 1.6; 95% CI, 1.3–2.0; P

Scoliosis is a three-dimensional structural deformity of the spine; more than 80% of scoliosis has no specific pathogenesis but is understood to be closely related to genetic, hormonal, and environmental factors. In recent years, the epigenetic alterations observed in scoliosis have been analyzed in numerous studies to determine the pathogenesis and progression of this condition, however, there is currently no comprehensive review of the epigenetic factors to date. We searched PubMed, Embase, and Web of Science databases for relative studies without language and date restrictions in March 2023. Twenty-five studies were included in this review and analyzed from the four main aspects of epigenetic alteration: DNA methylation, non-coding RNAs, histone modifications, and chromatin remodeling. The relationship between DNA methylation, non-coding RNAs, and scoliosis was considerably reported in the literature, and the corresponding related signaling pathways and novel biomarkers observed in scoliosis provide insights into innovative prevention and treatment strategies. However, the role of histone modifications is rarely reported in scoliosis, and few studies have investigated the relationship between scoliosis and chromatin remodeling. Therefore, these related fields need to be further explored to elucidate the overall effects of epigenetics in scoliosis.

The use of robots in various industries is evolving from mechanization to intelligence and precision. These systems often comprise parts made of different materials and thus require accurate and comprehensive target identification. While humans perceive the world through a highly diverse perceptual system and can rapidly identify deformable objects through vision and touch to prevent slipping or excessive deformation during grasping, robot recognition technology mainly relies on visual sensors, which lack critical information such as object material, leading to incomplete cognition. Therefore, multimodal information fusion is believed to be key to the development of robot recognition. Firstly, a method of converting tactile sequences to images is proposed to deal with the obstacles of information exchange between different modalities for vision and touch, which overcomes the problems of the noise and instability of tactile data. Subsequently, a visual-tactile fusion network framework based on an adaptive dropout algorithm is constructed, together with an optimal joint mechanism between visual information and tactile information established, to solve the problem of mutual exclusion or unbalanced fusion in traditional fusion methods. Finally, experiments show that the proposed method effectively improves robot recognition ability, and the classification accuracy is as high as 99.3%.

BackgroundPrevious studies have explored the relationship between body fat percentage (BFP) and hypertension or homocysteine. However, evidence on the constancy of the association remains inconclusive in postmenopausal women. The aim of this study was to investigate the association between BFP and H-type hypertension in postmenopausal women.MethodsThis cross-sectional study included 1,597 eligible female patients with hypertension. Homocysteine levels ≥10 mmol/L were defined as H-type hypertension. BFP was calculated by measuring patients' physical parameters. Subjects were divided into 4 groups according to quartiles of BFP (Q1: 33.4% or lower, Q2: 33.4–36.1%, Q3: 36.1–39.1%, Q4: >39.1%). We used restricted cubic spline regression models and logistic regression analysis to assess the relationship between BFP and H-type hypertension. Additional subgroup analysis was performed for this study.ResultsAmong 1,597 hypertensive patients, 955 (59.8%) participants had H-type hypertension. There were significant differences between the two groups in age, BMI, educational background, marital status, exercise status, drinking history, WC, TG, LDL, Scr, BUN, and eGFR (P < 0.05). The prevalence of H-type hypertension in the Q1 to Q4 groups was 24.9, 25.1, 24.9, and 25.1%, respectively. After adjusting for relevant factors, we found that the risk of H-type hypertension in the Q4 group had a significantly higher than the Q1 group (OR = 3.2, 95% CI: 1.3–7.5).ConclusionBFP was positively associated with the risk of H-type hypertension in postmenopausal women. Postmenopausal women should control body fat to prevent hypertension.

Background: We aim to examine the relationship between age at menarche and hyperhomocysteinemia in women in Hunan Province. Methods: Participants were required to complete a questionnaire that included age at menarche, lifestyle habits, other baseline information, and blood biochemical parameters in a cross-sectional study. The association between hyperhomocysteinemia and age at menarche was examined by Multivariable adjusted logistic regression. Results: A cohort of 2008 women with a mean age of 60.11 years (aged from 18.0 to 88.0 years) was included in this study. After adjustment for confounding factors such as age, the results showed that the risk of hyperhomocysteinemia among women whose age at menarche were over 16 years was 2.543 (1.849, 3.469) times higher than the risk among women whose age at atmenarche were less than 14 years, and 2.656 (1.882, 3.748) times more likely to have hypertension than women with menarche at 14 years. Besides, the odds ratios of diabetes, hyperlipidemia, and obesity were elevated in women older than 16 years of age at menarche (OR = 1.924, p < 0.001; OR = 1.491, p = 0.014; OR = 1.670, p = 0.022). Conclusions: Our findings suggest that late menarche tends to be associated with a high risk of hyperhomocysteinemia and its associated set of diseases such as hypertension, diabetes, hyperlipidemia, and obesity in women in Hunan, China. This association tends to differ across birth cohorts. Therefore, adequate attention of menarcheal age may be able to predict diseases in elderly females.