Multiparametric MRI-based radiomics nomogram for predicting malignant transformation of sinonasal inverted papilloma

AIM

To investigate the feasibility of a radiomics nomogram model for predicting malignant transformation in sinonasal inverted papilloma (IP) based on radiomic signature and clinical risk factors.

MATERIALS AND METHODS

This single institutional retrospective review included a total of 143 patients with IP and 75 patients with IP with malignant transformation to squamous cell carcinoma (IP-SCC). All patients underwent surgical pathology and had preoperative magnetic resonance imaging (MRI) and computed tomography (CT) sinus studies between June 2014 and February 2022. Radiomics features were extracted from contrast-enhanced T1-weighted images (CE-T1WI), T2-weighted images (T2WI), and apparent diffusion coefficient (ADC) maps. The least absolute shrinkage and selection operator (LASSO) were performed to select the features extracted from the sequences mentioned above. Independent clinical risk factors were identified by multivariate logistic regression analysis. Radiomics nomogram was constructed by incorporating independent clinical risk factors and radiomics signature. Based on discrimination and calibration, the diagnostic performance of the nomogram was evaluated.

RESULTS

Twelve radiomics features were selected to develop the radiomics model with an area under the curve (AUC) of 0.987 and 0.989, respectively. Epistaxis (p=0.011), T2 equal signal (p=0.003), extranasal invasion (p<0.001), and loss of convoluted cerebriform pattern (p=0.002) were identified as independent clinical predictors. The radiomics nomogram model showed excellent calibration and discrimination (AUC: 0.993, 95% confidence interval [CI]: 0.985-1.00 and 0.990, 95% CI: 0.974-1.00) in the training and validation sets, respectively.

CONCLUSION

The nomogram that the combined radiomics signature and clinical risk factors showed a satisfactory ability to predict IP-SCC.

Factors associated with nocturnal and diurnal glycemic variability in patients with type 2 diabetes: a cross-sectional study

PURPOSE

There is little information on factors that influence the glycemic variability (GV) during the nocturnal and diurnal periods. We aimed to examine the relationship between clinical factors and GV during these two periods.

METHODS

This cross-sectional study included 134 patients with type 2 diabetes. 24-h changes in blood glucose were recorded by a continuous glucose monitoring system. Nocturnal and diurnal GV were assessed by standard deviation of blood glucose (SDBG), coefficient of variation (CV), and mean amplitude of glycemic excursions (MAGE), respectively. Robust regression analyses were performed to identify the factors associated with GV. Restricted cubic splines were used to determine dose-response relationship.

RESULTS

During the nocturnal period, age and glycemic level at 12:00 A.M. were positively associated with GV, whereas alanine aminotransferase was negatively associated with GV. During the diurnal period, homeostatic model assessment 2-insulin sensitivity (HOMA2-S) was positively associated with GV, whereas insulin secretion-sensitivity index-2 (ISSI2) was negatively associated with GV. Additionally, we found a J-shape association between the glycemic level at 12:00 A.M. and MAGE, with 9.0 mmol/L blood glucose level as a cutoff point. Similar nonlinear associations were found between ISSI2 and SDBG, and between ISSI2 and MAGE, with ISSI2 value of 175 as a cutoff point.

CONCLUSION

Factors associated with GV were different between nocturnal and diurnal periods. The cutoff points we found in this study may provide the therapeutic targets for beta-cell function and pre-sleep glycemic level in clinical practice.

Lymphatic endothelial transcription factor Tbx1 promotes an immunosuppressive microenvironment to facilitate post-myocardial infarction repair

The heart is an autoimmune-prone organ. It is crucial for the heart to keep injury-induced autoimmunity in check to avoid autoimmune-mediated inflammatory disease. However, little is known about how injury-induced autoimmunity is constrained in hearts. Here, we reveal an unknown intramyocardial immunosuppressive program driven by Tbx1, a DiGeorge syndrome disease gene that encodes a T-box transcription factor (TF). We found induced profound lymphangiogenic and immunomodulatory gene expression changes in lymphatic endothelial cells (LECs) after myocardial infarction (MI). The activated LECs penetrated the infarcted area and functioned as intramyocardial immune hubs to increase the numbers of tolerogenic dendritic cells (tDCs) and regulatory T (Treg) cells through the chemokine Ccl21 and integrin Icam1, thereby inhibiting the expansion of autoreactive CD8+ T cells and promoting reparative macrophage expansion to facilitate post-MI repair. Mimicking its timing and implementation may be an additional approach to treating autoimmunity-mediated cardiac diseases.

Sparse-to-Local-Dense Matching for Geometry-Guided Correspondence Estimation

Establishing reliable correspondences between two views is one of the most important components of various vision tasks. This paper proposes a novel sparse-to-local-dense (S2LD) matching method to conduct fully differentiable correspondence estimation with the prior from epipolar geometry. The sparse-to-local-dense matching asymmetrically establishes correspondences with consistent sub-pixel coordinates while reducing the computation of matching. The salient features are explicitly located, and the description is conditioned on both views with the global receptive field provided by the attention mechanism. The correspondences are progressively established in multiple levels to reduce the underlying re-projection error. We further propose a 3D noise-aware regularizer with differentiable triangulation. Additional guidance from 3D space is encoded by the regularizer in training to handle the supervision noise caused by the errors in camera poses and depth maps. The proposed method demonstrates outstanding matching accuracy and geometric estimation capability on multiple datasets and tasks.

The mechanical effect of geometric design of attachments in invisible orthodontics

INTRODUCTION

In invisible orthodontics, attachments are used with aligners to better control tooth movement. However, to what extent the geometry of the attachment can affect the biomechanical properties of the aligner is unknown. This study aimed to determine the biomechanical effect of attachment geometry on orthodontic force and moment using 3-dimensional finite element analysis.

METHODS

A 3-dimensional model of mandibular teeth, periodontal ligaments, and the bone complex was employed. Rectangular attachments with systematic size variations were applied to the model with corresponding aligners. Fifteen pairs were created to move the lateral incisor, canine, first premolar, and second molar mesially for 0.15 mm, respectively. The resulting orthodontic forces and moments were analyzed to compare the effect of attachment size.

RESULTS

Expansion in the attachment size showed a continuous increase in force and moment. Considering the attachment size, the moment increased more than the force, resulting in a slightly higher moment-to-force ratio. Expanding the length, width, or thickness of the rectangular attachment by 0.50 mm increases the force and moment up to 23 cN and 244 cN-mm, respectively. The force direction was closer to the desired movement direction with larger attachment sizes.

CONCLUSIONS

Based on the experimental results, the constructed model successfully simulates the effect of the size of attachments. The larger the size of the attachment, the greater the force and moment, and the better the force direction. The appropriate force and moment for a particular clinical patient can be obtained by choosing the right attachment size.

Joint-Confidence-guided Multi-Task Learning for 3D Reconstruction and Understanding from Monocular Camera

3D reconstruction and understanding from monocular camera is a key issue in computer vision. Recent learning-based approaches, especially multi-task learning, significantly achieve the performance of the related tasks. However a few works still have limitation in drawing loss-spatial-aware information. In this paper, we propose a novel Joint-confidence-guided network (JCNet) to simultaneously predict depth, semantic labels, surface normal, and joint confidence map for corresponding loss functions. In details, we design a Joint Confidence Fusion and Refinement (JCFR) module to achieve multi-task feature fusion in the unified independent space, which can also absorb the geometric-semantic structure feature in the joint confidence map. We use confidence-guided uncertainty generated by the joint confidence map to supervise the multi-task prediction across the spatial and channel dimensions. To alleviate the training attention imbalance among different loss functions or spatial regions, the Stochastic Trust Mechanism (STM) is designed to stochastically modify the elements of joint confidence map in the training phase. Finally, we design a calibrating operation to alternately optimize the joint confidence branch and the other parts of JCNet to avoid overfiting. The proposed methods achieve state-of-the-art performance in both geometric-semantic prediction and uncertainty estimation on NYU-Depth V2 and Cityscapes.

Fully automated cardiac MRI segmentation using dilated residual network

PURPOSE

Cardiac ventricle segmentation from cine magnetic resonance imaging (CMRI) is a recognized modality for the noninvasive assessment of cardiovascular pathologies. Deep learning based algorithms achieved state-of-the-art result performance from CMRI cardiac ventricle segmentation. However, most approaches received less attention at the bottom layer of UNet, where main features are lost due to pixel degradation. To increase performance, it is important to handle the bottleneck layer of UNet properly. Considering this problem, we enhanced the performance of main features at the bottom layer of network.

METHOD

We developed a fully automatic pipeline for segmenting the right ventricle (RV), myocardium (MYO), and left ventricle (LV) by incorporating short-axis CMRI sequence images. We propose a dilated residual network (DRN) to capture the features at full resolution in the bottleneck of UNet. Thus, it significantly increases spatial and temporal information and maintains the localization accuracy. A data-augmentation technique is employed to avoid overfitting and class imbalance problems. Finally, output from each expanding path is added pixel-wise to improve the training response.

RESULTS

We used and evaluated our proposed method on automatic cardiac diagnosis challenge (ACDC). The test set consists of 50 patient records. The overall dice similarity coefficient (DSC) we achieved for our model is 0.924 ± 0.03, 0.907 ± 0.01, and 0.949 ± 0.05 for RV, MYO, and LV, respectively. Similarly, we obtained hausdorff distance (HD) scores of 10.09 ± 0.01, 7.25 ± 0.05, and 6.86 ± 0.02 mm for RV, MYO, and LV, respectively. The results show superior performance and outperformed state-of-the-art methods in terms of accuracy and reached expert-level segmentation. Consequently, the overall DSC and HD result improved by 1.0% and 1.5%, respectively.

CONCLUSION

We designed a dilated residual UNet (DRN) for cardiac ventricle segmentation using short-axis CMRI. Our method has the advantage of restoring and capturing spatial and temporal information by expanding the receptive field without degrading the image main features in the bottleneck of UNet. Our method is highly accurate and quick, taking 0.28 s on average to process 2D MR images. Also, the network was designed to work on predictions of individual MR images to segment the ventricular region, for which our model outperforms many state-of-the-art methods.

LSTformer: Long Short-term Transformer for Real Time Respiratory Prediction

Since the tumor moves with the patient's breathing movement in clinical surgery, the real-time prediction of respiratory movement is required to improve the efficacy of radiotherapy. Some RNN-based respiratory management methods have been proposed for this purpose. However, these existing RNN-based methods often suffer from the degradation of generalization performance for a long-term window (such as 600ms) because of the structural consistency constraints. In this paper, we propose an innovative Long Short-term Transformer (LSTformer) for long-term real-time accurate respiratory prediction. Specifically, a novel Long-term Information Enhancement module (LIE) is proposed to solve the performance degradation under a long window by increasing the long-term memory of latent variables. A lightweight Transformer Encoder (LTE) is proposed to satisfy the real-time requirement via simplifying the architecture and limiting the number of layers. In addition, we propose an application-oriented data augmentation strategy to generalize our LSTformer to practical application scenarios, especially robotic radiotherapy. Extensive experiments on our augmented dataset and publicly available dataset demonstrate the state-of-the-art performance of our method on the premise of satisfying the real-time demand.

[Analysis of changes in self-efficacy and its influencing factors in type 2 diabetic patients after community-based self-management group intervention]

Objective: To analyze the changes in self-efficacy and its influencing factors in type 2 diabetic patients after community-based self-management group intervention. Methods: From August to November 2014, a 3-month community-based self-management intervention study of type 2 diabetes patients was implemented in Fangshan District, Beijing. 510 patients were recruited through posters, household inquiries and telephone notification and then were randomly divided into intervention group (260 patients) and control group (250 patients). Finally, 500 patients completed the study, including 259 in the intervention group and 241 in the control group. Self-efficacy score was measured through face-to-face interview at different time points, including pre-intervention, post-intervention, 2 years after the intervention and 5 years after the intervention, respectively. A two-level random coefficient model was fitted to analyze the long-term trend of self-efficacy and its relationship with group intervention. Results: Individual-level educational attainment, disease duration as well as their treatment plans had a positive correlation with self-efficacy of type 2 diabetic patients while gender and age did not affect their self-efficacy. Patients with junior middle school education, senior high school education and university and above education had 4.66 (P<0.05), 6.40 (P<0.05) and 11.02 (P<0.05) points higher than those with primary education, respectively. The self-efficacy of diabetic patients increased by 0.23 (P<0.05) for each additional course year. The effect of treatment plan on self-efficacy was mainly reflected in the self-efficacy of taking medication or insulin injection as prescribed and blood glucose monitoring. After controlling for the confounding factors, i.e., gender, age, disease duration, educational attainment, and treatment plan, self-efficacy scores at the post-intervention increased in both groups compared to those at the pre-intervention. The intervention group had 7.95 points higher than the control group (P<0.05). After the intervention, the self-efficacy scores of both groups decreased year by year while the intervention group declined faster, with 5.41 points (P<0.05) at 2 years after the intervention and 8.94 points (P<0.05) at 5 years after the intervention. Conclusion: Community-based self-management group intervention could improve the self-efficacy of type 2 diabetic patients while the self-efficacy decreases year by year in the absence of follow-up intervention.

Intelligent cataract surgery supervision and evaluation via deep learning

PURPOSE

To assess the performance of a deep learning (DL) algorithm for evaluating and supervising cataract extraction using phacoemulsification with intraocular lens (IOL) implantation based on cataract surgery (CS) videos.

MATERIALS AND METHODS

DeepSurgery was trained using 186 standard CS videos to recognize 12 CS steps and was validated in two datasets that contained 50 and 21 CS videos, respectively. A supervision test including 50 CS videos was used to assess the DeepSurgery guidance and alert function. In addition, a real-time test containing 54 CSs was used to compare the DeepSurgery grading performance to an expert panel and residents.

RESULTS

DeepSurgery achieved stable performance for all 12 recognition steps, including the duration between two pairs of adjacent steps in internal validation with an ACC of 95.06% and external validations with ACCs of 88.77% and 88.34%. DeepSurgery also recognized the chronology of surgical steps and alerted surgeons to order of incorrect steps. Six main steps are automatically and simultaneously quantified during the evaluation process (centesimal system). In a real-time comparative test, the DeepSurgery step recognition performance was robust (ACC of 90.30%). In addition, DeepSurgery and an expert panel achieved comparable performance when assessing the surgical steps (kappa ranged from 0.58 to 0.77).

CONCLUSIONS

DeepSurgery represents a potential approach to provide a real-time supervision and an objective surgical evaluation system for routine CS and to improve surgical outcomes.

Incidence and risk factors of female urinary incontinence: a 4-year longitudinal study among 24 985 adult women in China

OBJECTIVE

To estimate the incidence of urinary incontinence (UI), including its subtypes stress UI (SUI), urgency UI (UUI) and mixed UI (MUI), and to examine risk factors for de novo SUI and UUI in Chinese women.

DESIGN

Nationwide longitudinal study.

SETTING

Six geographic regions of China.

PARTICIPANTS

Women aged ≥20 years old were included using a multistage, stratified, cluster sampling method.

METHODS

This study was conducted between May 2014 and March 2016, with follow up in 2018. Data on demographics, medical history, lifestyle and physiological and anthropometric information were collected.

MAIN OUTCOME MEASUREMENTS

Incidence, rate ratio (RR).

RESULTS

Analyses included 24 985 women (mean age 41.9 years).The follow-up response rate was 55.5%, median follow-up time was 3.7 years. The standardised incidences of UI, SUI, UUI and MUI were 21.2, 13.1, 3.0 and 5.1 per 1000 person-years, respectively. Risk factors for de novo SUI included delivery pattern (vaginal spontaneous delivery RR 2.12, 95% CI 1.62-2.78 and instrumental delivery RR 3.30, 95% CI 1.99-5.45), high body mass index (BMI) (overweight RR 1.52, 95% CI 1.33-1.74 and obesity RR 1.67, 95% CI 1.32-2.11), cigarette smoking (RR 1.54, 95% CI 1.12-2.12), chronic cough (RR 1.44, 95% CI 1.17-1.76), diabetes (RR 1.33, 95% CI 1.10-1.60) and older age (50-59 years RR 1.49, 95% CI 1.16-1.90 and 60-69 years RR 1.61, 95% CI 1.22-2.13).The risk factors significantly associated with de novo UUI were age (RR increased from 1.21, 95% CI 0.74-1.99, at 30-39 years to 6.3, 95% CI 3.85-10.30, at >70 years) and diabetes (RR 1.48, 95% CI 1.05-2.09).

CONCLUSIONS

The incidence of female UI is 21.2 per 1000 person-years in China. Delivery (vaginal spontaneous delivery, instrumental delivery), high BMI, cigarette smoking, chronic cough, diabetes and older age were risk factors.

TWEETABLE ABSTRACT

The incidence of female urinary incontinence was 21.2 per 1000 person-years in China. Delivery, BMI, diabetes and old age are risk factors.

[Evaluation on the quality of 236 National Demonstration Areas for comprehensive prevention and control of chronic diseases betweem 2017 and 2019]

Objective: To evaluate the quality of the National Demonstration Area for Comprehensive Prevention and Control of NCDs (referred to as "the Demonstration Area"). Methods: Based on the evaluation scores of the Demonstration Area field survey from 2017 to 2019, we counted the scores of each indicator, comparing the scores among indicators and regions. x±s was used to describe the scores. The 95%CI of the score was used to test the statistical difference among regions. Each score was converted into a hundred-mark system to compare the scores among indicators. Results: Of 236 Demonstration Areas, the total score was 83.5. The scores of the first-level indicator listed from high to low appeared as Integrating System of NCD Prevention and Control (92.8), Policy Perfection (90.3), Building Supportive Environment for NCD Prevention and Control (88.4), Implementation of Health Education and Health Promotion (87.4), Whole-course Management of NCDs (78.1), Innovation and Guidance (76.5), Surveillance and Evaluation (75.1). Total scores were higher in the east (259.2±18.8) comparing to the middle (243.2±15.2) or the west (245.4±19.7) regions. Conclusions: Substantial variations on the quality in the Demonstration Area existed across different regions in China. These disparities are important to the government when developing health policies and allocating resources. Whole-course Management of NCDs, Surveillance and Evaluation, and Innovation and Guidance in the Demonstration Area also needs to be improved.

Imaging orbital ferromagnetism in a moiré Chern insulator

Electrons in moiré flat band systems can spontaneously break time-reversal symmetry, giving rise to a quantized anomalous Hall effect. In this study, we use a superconducting quantum interference device to image stray magnetic fields in twisted bilayer graphene aligned to hexagonal boron nitride. We find a magnetization of several Bohr magnetons per charge carrier, demonstrating that the magnetism is primarily orbital in nature. Our measurements reveal a large change in the magnetization as the chemical potential is swept across the quantum anomalous Hall gap, consistent with the expected contribution of chiral edge states to the magnetization of an orbital Chern insulator. Mapping the spatial evolution of field-driven magnetic reversal, we find a series of reproducible micrometer-scale domains pinned to structural disorder.

A nationwide population-based survey on the prevalence and risk factors of symptomatic pelvic organ prolapse in adult women in China - a pelvic organ prolapse quantification system-based study

Objective

To determine the prevalence, risk factors and burden of symptomatic pelvic organ prolapse (POP) in adult Chinese women.

Design

A nationwide cross‐sectional study.

Setting

Six geographic regions of mainland China.

Participants

Women aged ≥20 years old were included using a multistage, stratified, cluster sampling method from February 2014 through March 2016.

Methods

We conducted a nationwide epidemiological survey. ‘Symptomatic POP’ was determined by a screening questionnaire and physical examination.

Main outcome measurements

Prevalence, odds ratio (OR).

Results

A total of 55 477 women (response rate, 92.5%; mean age, 45.1 years old) were included. The prevalence of symptomatic POP was 9.6% (95% CI 9.3–9.8%) and it increased with age in each stage (P < 0.05). Symptomatic POP‐Q stage II, which mainly involved anterior compartment prolapse, was the most common (7.52%). Minor/moderate burden of symptomatic POP was the most common, with a prevalence of 9.7% (95% CI 9.5–10.0%). The odds for each type of symptomatic POP increased with age (>50 vs 20‐29 years old in symptomatic POP‐Q stage II or higher, OR increased from 1.34 [95% CI 1.32–1.45] to 7.34 [95% CI 4.34–12.41]) and multiple vaginal deliveries (multiparous [≥3] vs nulliparous in symptomatic POP‐Q stage II or higher, OR increased from 1.91 [1.71–2.13] to 2.78 [2.13–3.64]).

Conclusions

We found a lower prevalence of symptomatic POP than that found in other surveys. The main type of symptomatic POP was anterior compartment prolapse, indicating that it should be considered first. Older age and multiple vaginal deliveries increased the odds of each type of symptomatic POP.

Tweetable abstract

The prevalence of female symptomatic pelvic organ prolapse (POP) was 9.6% in China. It is related to old age and multiple vaginal deliveries.

The prevalence of female symptomatic pelvic organ prolapse (POP) was 9.6% in China. It is related to old age and multiple vaginal deliveries.

Synovial mesenchymal stem cells effectively alleviate osteoarthritis through promoting the proliferation and differentiation of meniscus chondrocytes

OBJECTIVE

To investigate the relationship between the meniscal defect area and OA progression and explore the effect and mechanism of SMSCs cell therapy in knee osteoarthritis (OA) rat model.

MATERIALS AND METHODS

For animal experiments, knee osteoarthritis (OA) model was constructed in Sprague Dawley (SD) rats by removing the medial meniscus of the right knee. Synovial mesenchymal stem cells (SMSCs) were engrafted by injecting into the right knee cavity. For in vitro experiments, CCK-8 assay was performed to evaluate the proliferation and differentiation of BMSCs and ATDC5 cells after co-cultured with SMSCs. qRT-PCR analysis was performed to detect the expressions of chondrogenic genes in BMSCs and ATDC5 cells after co-cultured with SMSCs. Western blot analysis was conducted to detect the phosphorylations of c-Jun N-terminal kinase (JNK) and extracellular regulated protein kinases (ERK) in MAPK signaling of BMSCs and ATDC5 cells. Enzyme-linked immunosorbent assay (ELISA) was performed to detect the serum levels of interleukin (IL)-1β, IL-1β, IL-6, IL-18 and C-reactive protein (CRP).

RESULTS

Results showed that meniscus damaged area is positively correlated to serum inflammatory factor levels. In vitro study showed that the proliferation and differentiation of BMSCs and ATDC5 cells were promoted after co-cultured with SMSCs. By co-culturing with SMSCs, the MAPK signaling pathway was activated and the expression of chondrogenic markers such as aggrecan (acan), SRY-related high mobility group-box gene 9 (sox9) and Type II collagen a1 (col2a1), was up-regulated both in BMSCs and ATDC5 cells. In vivo study showed SMSCs cell therapy significantly decreased serum inflammatory factor levels and protected cartilage by upregulating the expression of chondrogenic genes of meniscus chondrocytes derived from OA rats.

CONCLUSIONS

For the first time, we found the positive correlation between meniscal defect area and OA progression and demonstrated the effect and mechanism of SMSCs cell therapy in knee osteoarthritis (OA) treatment.

Segment-Based Disparity Refinement With Occlusion Handling for Stereo Matching

In this paper, we propose a disparity refinement method that directly refines the winner-take-all (WTA) disparity map by exploring its statistical significance. According to the primary steps of the segment-based stereo matching, the reference image is over-segmented into superpixels and a disparity plane is fitted for each superpixel by an improved random sample consensus (RANSAC). We design a two-layer optimization to refine the disparity plane. In the global optimization, mean disparities of superpixels are estimated by Markov random field (MRF) inference, and then, a 3D neighborhood system is derived from the mean disparities for occlusion handling. In the local optimization, a probability model exploiting Bayesian inference and Bayesian prediction is adopted and achieves second-order smoothness implicitly among 3D neighbors. The two-layer optimization is a pure disparity refinement method because no correlation information between stereo image pairs is demanded during the refinement. Experimental results on the Middlebury and KITTI datasets demonstrate that the proposed method can perform accurate stereo matching with a faster speed and handle the occlusion effectively. It can be indicated that the "matching cost computation + disparity refinement" framework is a possible solution to produce accurate disparity map at low computational cost.

Simulation of orthodontic force of archwire applied to full dentition using virtual bracket displacement method

OBJECTIVE

Orthodontic force simulation of tooth provides important guidance for clinical orthodontic treatment. However, previous studies did not involve the simulation of orthodontic force of archwire applied to full dentition. This study aimed to develop a method to simulate orthodontic force of tooth produced by loading a continuous archwire to full dentition using finite element method.

METHOD

A three-dimensional tooth-periodontal ligament-bone complex model of mandible was reconstructed from computed tomography images, and models of brackets and archwire were built. The simulation was completed through two steps. First, node displacements of archwire before and after loading were estimated through moving virtual brackets to drive archwire deformation. Second, the obtained node displacements were loaded to implement the loading of archwire, and orthodontic force was calculated. An orthodontic force tester (OFT) was used to measure orthodontic force in vitro for the validation.

RESULTS

After the simulation convergence, archwire was successfully loaded to brackets, and orthodontic force of teeth was obtained. Compared with the measured orthodontic force using the OFT, the absolute difference of the simulation results ranged from 0.5 to 22.7 cN for force component and ranged from 2.2 to 80.0 cN•mm for moment component, respectively. The relative difference of the simulation results ranged from 2.5% to 11.0% for force component, and ranged from 0.6% to 14.7% for moment component, respectively.

CONCLUSIONS

The developed orthodontic force simulation method based on virtual bracket displacement can be used to simulate orthodontic force provided by the archwire applied to full dentition.

Effects of oat protein supplementation on skeletal muscle damage, inflammation and performance recovery following downhill running in untrained collegiate men

The positive influence of animal-based protein supplementation during muscle-damaging exercise has been widely studied. However, the effects of plant-based proteins remain unclear and require further clarification. This study investigated the protective role of oat protein against exercise induced muscle damage (EIMD), subsequent inflammation, and loss of performance induced by downhill running. Subjects consumed either oat protein (25 g protein) or a placebo for 14 days prior to a downhill running test and then for 4 days thereafter. Treatments with oat protein for 19 days markedly alleviated eccentric exercise induced skeletal muscle soreness, and reduced the elevation of plasma IL-6 concentrations and serum creatine kinase, myoglobin and C reactive protein contents. In addition, oat protein supplementation significantly inhibited limb edema following damaging exercise, and the adverse effects on muscle strength, knee-joint range of motion, and vertical jump performance were lessened. Furthermore, the administration of oat protein facilitated recovery from exhaustive downhill running in this study. These findings demonstrated that oat protein supplementation has the potential to alleviate the negative effects of eccentric exercise in untrained young males.

An epidemiologic study of pelvic organ prolapse in postmenopausal women: a population-based sample in China

OBJECTIVE

This study aimed to assess the prevalence and factors associated with symptomatic pelvic organ prolapse (POP) in a representative sample of postmenopausal Chinese women.

METHODS

A total of 20,008 postmenopausal Chinese women were recruited to this cross-sectional study between February 2014 and March 2016. The prevalence of symptomatic POP, defined as any stage II or higher POP resulting in symptoms, was assessed using questionnaires and physical examinations. Multivariable logistic regression was used to assess factors associated with symptomatic POP.

RESULTS

Among all women with natural menopause included in the study (mean age =61.98 ± 10.62 years), 2962 of 20,008 women (14.80%, 95% confidence interval [CI] 14.3-15.3%) had symptomatic POP. In the multivariate analysis, women were more likely to have symptomatic POP if aged 50-59 years (adjusted odds ratio [AOR] 1.322, 95% CI 1.123-1.560), 60-69 years (AOR 1.603, 95% CI 1.352-1.907), or above 70 years (AOR 1.824, 95% CI 1.158-2.197), compared with women aged 40-49 years. Having delivered two times (AOR 1.145, 95% CI 1.105-1.292) or three or more times (AOR 1.384, 95% CI 1.214-1.578) was significantly associated with symptomatic POP. Compared with normal weight women, overweight women (AOR 1.365, 95% CI 1.247-1.494) and obese women (AOR 1.548, 95% CI 1.344-1.780) were more likely to have POP. Living in an urban area, smoking, alcohol consumption, cough, constipation, mental labor, physical disease, and gynecological diseases were also associated with symptomatic POP.

CONCLUSIONS

Symptomatic POP affects nearly 15% of postmenopausal women in China. The prevalence of symptomatic POP increases significantly with age, body mass index, and parity.

Diagnostic guidelines for the histological particle algorithm in the periprosthetic neo-synovial tissue

BACKGROUND

The identification of implant wear particles and non-implant related particles and the characterization of the inflammatory responses in the periprosthetic neo-synovial membrane, bone, and the synovial-like interface membrane (SLIM) play an important role for the evaluation of clinical outcome, correlation with radiological and implant retrieval studies, and understanding of the biological pathways contributing to implant failures in joint arthroplasty. The purpose of this study is to present a comprehensive histological particle algorithm (HPA) as a practical guide to particle identification at routine light microscopy examination.

METHODS

The cases used for particle analysis were selected retrospectively from the archives of two institutions and were representative of the implant wear and non-implant related particle spectrum. All particle categories were described according to their size, shape, colour and properties observed at light microscopy, under polarized light, and after histochemical stains when necessary. A unified range of particle size, defined as a measure of length only, is proposed for the wear particles with five classes for polyethylene (PE) particles and four classes for conventional and corrosion metallic particles and ceramic particles.

RESULTS

All implant wear and non-implant related particles were described and illustrated in detail by category. A particle scoring system for the periprosthetic tissue/SLIM is proposed as follows: 1) Wear particle identification at light microscopy with a two-step analysis at low (× 25, × 40, and × 100) and high magnification (× 200 and × 400); 2) Identification of the predominant wear particle type with size determination; 3) The presence of non-implant related endogenous and/or foreign particles. A guide for a comprehensive pathology report is also provided with sections for macroscopic and microscopic description, and diagnosis.

CONCLUSIONS

The HPA should be considered a standard for the histological analysis of periprosthetic neo-synovial membrane, bone, and SLIM. It provides a basic, standardized tool for the identification of implant wear and non-implant related particles at routine light microscopy examination and aims at reducing intra-observer and inter-observer variability to provide a common platform for multicentric implant retrieval/radiological/histological studies and valuable data for the risk assessment of implant performance for regional and national implant registries and government agencies.

Mild Hypothermia Protects Renal Function in Ischemia-reperfusion Kidney: An Experimental Study in Mice

Mild hypothermia reduces the damage caused by hypoxia and oxidative stress, but how this happens is not very clear. Mice were anesthetized and their core body temperature was maintained at 38 ± 0.5°C and 32 ± 0.5°C. The renal artery and renal veins were blocked for 35 minutes and reperfusion was performed. Twenty-four hours later, serum was obtained to detect the concentrations of creatinine. The expression of CIRP, TRX, Bcl-2, and Bax were detected in tissue samples using Western blot. Apoptosis was measured using terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling and the apoptosis rates were calculated. SOD and MDA were detected to determine the extent of oxidative damage in different groups. The concentration of creatinine in the NC group was 2.11 ± 0.39 mg/dL. Compared to the IR group, the concentration of creatinine decreased in MH+IR group and showed a significant statistical difference (8.74 ± 1.38 mg/dL vs 15.36 ± 2.13 mg/dL, P < .01); the apoptosis rate also decreased with statistical significance (15.02 ± 1.45% vs 37.02 ± 5.70%, P < .01). Compared to the IR group, the expression of CIRP, TRX, and the Bcl-2/Bax ratio significantly increased in the MH+IR group. The SOD activity in the MH+IR group increased (26.90 ± 4.41 U/mgprot vs 16.85 ± 2.41 U/mgprot, P < .05) and the MDA level decreased (0.76 ± 0.18 nmol/mgprot vs 1.37 ± 0.32 nmol/mgprot, P < .05) compared to those of the IR group. Mild hypothermia protects mice kidneys from ischemia-reperfusion damage by reducing oxidative stress injury and apoptosis.

Myocardial ischaemia reperfusion injury: the challenge of translating ischaemic and anaesthetic protection from animal models to humans

Myocardial ischaemia reperfusion injury is the leading cause of death in patients with cardiovascular disease. Interventions such as ischaemic pre and postconditioning protect against myocardial ischaemia reperfusion injury. Certain anaesthesia drugs and opioids can produce the same effects, which led to an initial flurry of excitement given the extensive use of these drugs in surgery. The underlying mechanisms have since been extensively studied in experimental animal models but attempts to translate these findings to clinical settings have resulted in contradictory results. There are a number of reasons for this such as dose response, the intensity of the ischaemic stimulus applied, the duration of ischaemia and lost or diminished cardioprotection in common co-morbidities such as diabetes and senescence. This review focuses on current knowledge regarding myocardial ischaemia reperfusion injury and cardioprotective interventions both in experimental animal studies and in clinical trials.

A potential strategy for counteracting age-related sarcopenia: preliminary evidence of combined exercise training and leucine supplementation

Previous research has demonstrated the positive effects of concurrent/combined aerobic and resistance exercise or leucine supplementation on skeletal muscle protein synthesis (MPS) and hypertrophy in aging organisms. However, the effects of a multimodal intervention which combines both aerobic and resistance exercise and leucine supplementation has not been fully elucidated. Eighteen month old and 2 month old C57BL/6 mice were assigned to aging control (AC, n = 8), aging and multimodal intervention (AMI, n = 8) and young control (YC, n = 8). Mice in the YC and AC groups were fed an alanine-rich diet (3.4%), and mice in the AMI group received an isonitrogenous leucine-supplemented (5%) diet in combination with combined aerobic (30 minutes swimming) and resistance exercise training (incremental jumping submersed in water with overload corresponding to 40%-50% body weight) for a total of 4 weeks. The gastrocnemius muscles were dissected for western blotting detection (signaling proteins involved in MPS) and the ex vivo determination of protein synthesis and protein content. The muscle strength of the hind limbs was measured pre-experiment and repeated once per week on Sunday for 4 weeks. Mice in the AC and AMI groups showed lower ex vivo protein synthesis, protein content, expression of signaling proteins involved in MPS, maximal grip strength but higher plasma cortisol compared with the YC group post intervention. When compared to AC mice, the multimodal treatment led to lower activity of Sestrin2, higher expression of PI3K III and the phosphorylation of mTOR, p70S6K and 4E-BP1, as well as higher plasma leucine, wet gastrocnemius muscle weight and muscle weight to body weight ratio. Furthermore, the multimodal intervention induced more pronounced anabolic response such as higher ex vivo protein synthesis rate, total protein content, and myofibrillar fractions in gastrocnemius muscle, and greater maximum grip strength. The present research shows that a multimodal intervention including combined both aerobic and resistance exercise training and 5% leucine supplementation has the potential to maintain skeletal muscle protein synthesis and attenuate losses in muscular strength during the aging process.

A central pattern generator approach to footstep transition for biped navigation

Existing sampling-based footstep planning method for biped navigation used an intermediate static posture for footstep transition. However, when adopting this approach, the robot is sensitive to modeling error and external environments, and also the transition between different gait patterns is unnatural. This article presents a central pattern generator approach to footstep transition for biped navigation. First, this approach decomposes the biped walking motion into five motion types and designs central pattern generator network for all joints of legs accordingly. Then, the central pattern generator parameters are simplified and the relationship between these parameters and footstep transition is formulated. By modifying the central pattern generator parameters, different walking gaits can be obtained. With sensing feedbacks, self-adaption walking on irregular terrains, such as walking on unknown sloped terrains and flat floor with tiny obstacles, is realized. Experiments were conducted both in simulator and on a physical biped robot. Results have shown that the proposed approach is able to generate gesture transition trajectory for biped robot navigation and realize a self-adaption walking for irregular terrains.

[Three-dimensional tooth model reconstruction based on fusion of dental computed tomography images and laser-scanned images]

Complete three-dimensional(3D) tooth model provides essential information to assist orthodontists for diagnosis and treatment planning. Currently, 3D tooth model is mainly obtained by segmentation and reconstruction from dental computed tomography(CT) images. However, the accuracy of 3D tooth model reconstructed from dental CT images is low and not applicable for invisalign design. And another serious problem also occurs, i.e. frequentative dental CT scan during different intervals of orthodontic treatment often leads to radiation to the patients. Hence, this paper proposed a method to reconstruct tooth model based on fusion of dental CT images and laser-scanned images. A complete3 D tooth model was reconstructed with the registration and fusion between the root reconstructed from dental CT images and the crown reconstructed from laser-scanned images. The crown of the complete 3D tooth model reconstructed with the proposed method has higher accuracy. Moreover, in order to reconstruct complete 3D tooth model of each orthodontic treatment interval, only one pre-treatment CT scan is needed and in the orthodontic treatment process only the laser-scan is required. Therefore, radiation to the patients can be reduced significantly.

Individual tooth segmentation from CT images scanned with contacts of maxillary and mandible teeth

BACKGROUND AND OBJECTIVE

Tooth segmentation from computed tomography (CT) images is a fundamental step in generating the three-dimensional models of tooth for computer-aided orthodontic treatment. Individual tooth segmentation from CT images scanned with contacts of maxillary and mandible teeth is especially challenging, and no method has been reported previously. This study aimed to develop a method for individual tooth segmentation from these images.

METHODS

Tooth contours of maxilla and mandible are first segmented from the volumetric CT images slice-by-slice. For each slice, a line is extracted using the Radon transform to separate neighboring teeth, and each tooth contour is then segmented by a level set model from the corresponding side of the line. Then, each maxillary tooth whose contours overlap with that of mandible ones is detected, and a mesh model is reconstructed from all the contours of these maxillary and mandible teeth with contour overlap. The reconstructed mesh model is segmented using threshold and fast marching watershed method to separate the touched maxillary and mandible teeth. Finally, the separated tooth models are restored to fill the holes to obtain complete tooth models. The proposed method was tested on CT images of ten subjects scanned with natural contacts of maxillary and mandible teeth.

RESULTS

For all the tested images, individual tooth regions are extracted successfully, and the segmentation accuracy and efficiency of the proposed method is promising.

CONCLUSIONS

The proposed method is effective to segment individual tooth from CT images scanned with contacts of maxillary and mandible teeth.

A motion sensing-based framework for robotic manipulation

To data, outside of the controlled environments, robots normally perform manipulation tasks operating with human. This pattern requires the robot operators with high technical skills training for varied teach-pendant operating system. Motion sensing technology, which enables human-machine interaction in a novel and natural interface using gestures, has crucially inspired us to adopt this user-friendly and straightforward operation mode on robotic manipulation. Thus, in this paper, we presented a motion sensing-based framework for robotic manipulation, which recognizes gesture commands captured from motion sensing input device and drives the action of robots. For compatibility, a general hardware interface layer was also developed in the framework. Simulation and physical experiments have been conducted for preliminary validation. The results have shown that the proposed framework is an effective approach for general robotic manipulation with motion sensing control.

Molar axis estimation from computed tomography images

Estimation of tooth axis is needed for some clinical dental treatment. Existing methods require to segment the tooth volume from Computed Tomography (CT) images, and then estimate the axis from the tooth volume. However, they may fail during estimating molar axis due to that the tooth segmentation from CT images is challenging and current segmentation methods may get poor segmentation results especially for these molars with angle which will result in the failure of axis estimation. To resolve this problem, this paper proposes a new method for molar axis estimation from CT images. The key innovation point is that: instead of estimating the 3D axis of each molar from the segmented volume, the method estimates the 3D axis from two projection images. The method includes three steps. (1) The 3D images of each molar are projected to two 2D image planes. (2) The molar contour are segmented and the contour's 2D axis are extracted in each 2D projection image. Principal Component Analysis (PCA) and a modified symmetry axis detection algorithm are employed to extract the 2D axis from the segmented molar contour. (3) A 3D molar axis is obtained by combining the two 2D axes. Experimental results verified that the proposed method was effective to estimate the axis of molar from CT images.

Orthodontic force simulation of Tooth-PDL-Bone Complex under archwire loading

Orthodontic force simulation is very important for the guidance of clinical orthodontic treatment. Previous works were mainly conducted by directly loading the force on a single or a few teeth. However, in clinic, the orthodontic force is provided by loading orthodontic appliances, and there currently is no appropriate way to measure the force on the teeth provided by the loaded appliances. This study presents a method to simulate the orthodontic force of a whole Tooth-Periodontal Ligament-Bone Complex (TPBC) by directly loading the archwire to the dentition applying the finite element method. A 3D TPBC model was reconstructed from CT images, and models of brackets and the archwire were also built. The loading procedure of the archwire was implemented by simulating the deformation and displacement of the archwire before and after the loading, and the stress of the archwire induced by the deformation and displacement was obtained. Then, the stress was applied to the brackets, and the corresponding orthodontic force of the TPBC was simulated. By applying the method, archwire designed according to the planned dentition shape was loaded successfully to the original dentition, and the orthodontic force of the TPBC was obtained.