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Purpose: The purpose of this study was to evaluate the outcomes of displaced, multi-fragmentary patella fractures in elderly patients treated with anterior plating and cerclage wires. Patients and methods: Between 2018 and 2020, patients aged at least 60 years old undergoing anterior plating and circumferential wiring for displaced, multi-fragmentary patella fractures with a minimum of 12 months follow-up were included. Fragments were reduced and circumferentially stabilized by loop wires, followed by multi-planar fixation with an anterior locking plate and multi-directional screws. Postoperative outcomes were evaluated with the Böstman scores and range of motion. Patients were also asked about symptomatic hardware as well as satisfaction with postoperative outcomes. Results: Sixteen patients with an average age of 71.8 ± 9.3 years old were followed up for an average follow-up was 25.1 ± 8.2 months. At the latest follow-up, the average Böstman scores were 27.2 ± 3.4, and active knee flexion was 123 ± 14°. Two patients complained pinpoint implant irritation and underwent implant removal. Another underwent implant removal due to cultural reasons. Fifteen patients were satisfied with the operative outcomes, and one was unsatisfied due to intermittent patellofemoral pain. Cerclage wire breakage was noted in nine patients on postoperative radiographs, but none elicited pinpoint pain. No wound complications, infections, nonunion or loss of reduction were observed. Conclusions: Anterior locking plates and cerclage wires in tandem provide reliable multi-planar fixation for displaced, multi-fragmentary patellar fractures in elderly patients and resulted in favorable clinical outcomes. [ABSTRACT FROM AUTHOR]

For multilayer perceptron (MLP), the initial weights will significantly influence its performance. Based on the enhanced fractional derivative extend from convex optimization, this paper proposes a fractional gradient descent (RFGD) algorithm robust to the initial weights of MLP. We analyze the effectiveness of the RFGD algorithm. The convergence of the RFGD algorithm is also analyzed. The computational complexity of the RFGD algorithm is generally larger than that of the gradient descent (GD) algorithm but smaller than that of the Adam, Padam, AdaBelief, and AdaDiff algorithms. Numerical experiments show that the RFGD algorithm has strong robustness to the order of fractional calculus which is the only added parameter compared to the GD algorithm. More importantly, compared to the GD, Adam, Padam, AdaBelief, and AdaDiff algorithms, the experimental results show that the RFGD algorithm has the best robust performance for the initial weights of MLP. Meanwhile, the correctness of the theoretical analysis is verified. [ABSTRACT FROM AUTHOR]

It is valuable and meaningful to suppress impulsive noise in system identification. Existing algorithms usually only consider impulsive noise with small frequency and amplitude. Furthermore, few researchers pay attention to the tracking performance of these algorithms. This paper builds a framework based on the deep deterministic policy gradient (DDPG) algorithm with the ability to explore and correct. The enhanced fractional derivative is introduced to further improve the performance of this reinforcement learning-based framework. Thus a fractional least mean square filter algorithm based on reinforcement learning (FrlMS) is proposed. The stability of the FrlMS algorithm is analyzed. Compared with the competing algorithms, the simulation experiments in system identification show that the FrlMS algorithm has satisfactory tracking performance in the face of impulsive noise, especially when the frequency and (or) amplitude are (is) large. [ABSTRACT FROM AUTHOR]

Complex-valued neural network is a kind of learning model which can deal with problems in complex domain. Fully complex extreme learning machine (CELM) is a much faster training algorithm than the complex backpropagation (CBP) scheme. However, it is at the cost of using more hidden nodes to obtain the comparable performance. An upper-layer-solution-aware algorithm has been proposed for training single-hidden layer feedforward neural networks, which performs much better than its counterparts, pseudo-inverse learning (PIL)/extreme learning machine and gradient decent-based backpropagation neural networks. Consequently, there exist two challenges that need to be dealt with: 1) How to combine the advantages of CBP and CELM to develop a novel complex learning algorithm? and 2) What is the convergent behavior of the presented algorithm? In this article, an input weights dependent complex-valued (IWDCV) learning algorithm based on Wirtinger calculus has been proposed, which effectively solves the nonanalytic problem of the common activation functions during training neural networks. In addition, the monotonicity of the error function and the deterministic convergence of the proposed model have been strictly proved, which theoretically guarantee the efficiency and effectiveness of the given model, IWDCV. Finally, for real and complex-valued problems, a variety of simulations have been done to demonstrate the comparable performance of the proposed algorithm which support the theoretical observations as well. [ABSTRACT FROM AUTHOR]

Mesenchymal stem cell‐derived small extracellular vesicles (MSC‐sEVs) possess a great therapeutical potential for osteoarthritis (OA) treatment. However, the steric and electrostatic hindrance of cartilage matrix leads to very limited distribution of MSC‐sEVs in cartilage and low bioavailability of MSC‐sEVs after intra‐articular injection. To overcome this, a strategy to reverse the surface charge of MSC‐sEVs by modifying the MSC‐sEVs with a novel cationic amphiphilic macromolecule namely ε‐polylysine‐polyethylene‐distearyl phosphatidylethanolamine (PPD) was developed in this study. Through incubation with 100 μg/ml PPD, positively charged MSC‐sEVs (PPD‐sEVs) were obtained, and the modification process showed nearly no disturbance to the integrity and contents of sEVs and exhibited good stability under the interference of anionic macromolecules. A more effective cellular uptake and homeostasis modulation ability of PPD‐sEVs than unmodified MSC‐sEVs to chondrocytes was demonstrated. More importantly, PPD‐sEVs demonstrated significantly enhanced cartilage uptake, cartilage penetration, and joint retention capacity as compared to MSC‐sEVs. Intra‐articular injection of PPD‐sEVs into a mouse OA model showed significantly improved bioavailability than MSC‐sEVs, which resulted in enhanced therapeutic efficacy with reduced injection frequency. In general, this study provides a facile and effective strategy to improve the intra‐articular bioavailability of MSC‐sEVs and has a great potential to accelerate the clinical practice of MSC‐sEVs based OA therapy. [ABSTRACT FROM AUTHOR]

Elman recurrent network is a representative model with feedback mechanism. Although gradient descent method has been widely used to train Elman network, it frequently leads to slow convergence. According to optimization theory, conjugate gradient method is an alternative strategy in searching the descent direction during training. In this paper, an efficient conjugate gradient method has been presented to reach the optimal solution in two ways: (1) constructing a more effective conjugate coefficient, (2) determining adaptive learning rates in terms of the generalized Armijo search method. Experiments show that the performance of the new algorithm is superior to traditional algorithms, such as gradient descent method and conjugate gradient method. In particular, the new algorithm has better performance than the evolutionary algorithm. Finally, we prove the weak and strong convergence of the presented algorithm, i.e., the gradient norm of the error function with respect to the weight vectors converges to zero and the weight sequence approaches a fixed optimal point. [ABSTRACT FROM AUTHOR]

Osteoarthritis (OA) is a common degenerative joint disease which currently lacks of effective agents. It is therefore urgent and necessary to seek an effective approach that can inhibit inflammation and promote cartilage matrix homeostasis. Cartilage progenitor cells (CPCs) are identified as a cell population of superficial zone in articular cartilage which possess strong migration ability, proliferative capacity, and chondrogenic potential. Recently, the application of CPCs may represent a novel cell therapy strategy for OA treatment. There is growing evidence that extracellular vesicles (EVs) are primary mediators of the benefits of stem cell-based therapy. In this study, we explored the protective effects of CPCs-derived EVs (CPCs-EVs) on IL-1β-induced chondrocytes. We found CPCs-EVs exhibited chondro-protective effects in vitro. Furthermore, our study demonstrated that CPCs-EVs promoted matrix anabolism and inhibited inflammatory response at least partially via blocking STAT3 activation. In addition, liquid chromatography-tandem mass spectrometry analysis identified 991 proteins encapsulated in CPCs-EVs. By bioinformatics analysis, we showed that STAT3 regulatory proteins were enriched in CPCs-EVs and could be transported to chondrocytes. To promoting the protective function of CPCs-EVs in vivo, CPCs-EVs were modified with cationic peptide ε-polylysine-polyethylene-distearyl phosphatidylethanolamine (PPD) for surface charge reverse. In posttraumatic OA mice, our results showed PPD modified CPCs-EVs (PPD-EVs) effectively inhibited extracellular matrix catabolism and attenuated cartilage degeneration. Moreover, PPD-EVs down-regulated inflammatory factors expressions and reduced OA-related pain in OA mice. In ex-vivo cultured OA cartilage explants, PPD-EVs successfully promoted matrix anabolism and inhibited inflammation. Collectively, CPCs-EVs-based cell-free therapy is a promising strategy for OA treatment. [ABSTRACT FROM AUTHOR]

Find the global optimal solution of the model is one promising research topic in computational intelligent community. Dependent on analogies to natural processes, the evolutionary swarm intelligent algorithms are widely used for solving global optimization problems which directed by the fitness values. In this paper, we propose one efficient fractional global learning machine (Fragmachine) which includes two stages (descending and ascending) to determine the optimal search path. The neural network model is used to approach the given fitness value. Specifically, for the descending stage, the integer gradient of the network output with respect the current location is employed to find the next descending point, while for the ascending stage, the fractional gradient is implemented to climb and escape from the local optimal point. We further propose one adaptive learning rate during training which relies on both the current gradient (integer or fractional) information and the fitness value. Finally, a series of numerical experiments verify the effectiveness of the proposed algorithm, Fragmachine. [ABSTRACT FROM AUTHOR]

Background: Kashin–Beck disease (KBD) is an endemic, chronic osteoarthropathy that seriously affects joint function and can lead to severe knee deformity. Osteotomy is considered to be one of the effective methods for the treatment of this disease. Therefore, we designed a novel type of osteotomy named combined proximal tibial osteotomy (CPTO), which combines the characteristics of opening‐wedge high tibial osteotomy and tibial condylar valgus osteotomy. Case presentation: We report the case of a 48‐year‐old male with knee pain and varus deformity who was diagnosed with KBD and varus knee osteoarthritis (Kellgren–Lawrence stage IV). Considering the patient's relatively young age, a varus deformity of the right knee of 16.79°, and an intra‐articular instability, we performed a CPTO treatment. In this procedure, we performed an L‐shaped osteotomy from the medial edge of the proximal tibia to the intercondylar eminence and an osteotomy from the medial side of the proximal tibia to the lateral side through the same incision, to adjust the leg alignment and the congruity of the joint by valgus correction. At 29 months follow‐up, this patient achieved satisfactory results, with a varus right knee of 2.87°. There was significant improvement in his right knee function, pain, and joint stability. Conclusions: CPTO may be an acceptable treatment for KBD patients with severe knee varus deformity and intra‐articular instability. It can be considered as an alternative treatment, especially for patients with advanced osteoarthritis needing knee preservation. [ABSTRACT FROM AUTHOR]

Background: Knee osteoarthritis (OA) is a leading cause of global disability. According to current guidelines, exercise is the most recommended and important non-surgical treatment for knee OA. However, the best type of exercise for this condition remains unclear. Evidence has shown that traditional Chinese exercises may be more effective. Therefore, the current prospective, two-armed, single-center randomized controlled trial (RCT) aimed to identify an effective physiotherapy for knee OA.Methods/design: In total, 114 patients with painful knee OA will be recruited from the orthopedic outpatient department of Shanghai Jiao Tong University Affiliated Sixth People's Hospital. To compare the therapeutic effect of two different home-based exercise programs, the participants will be randomly assigned into the experimental group (leg swing exercise) or the control group (quadriceps strengthening exercise). Each participant in both groups will be required to attend five individual sessions with a physiotherapist who will teach the exercise program and monitor progress. Participants will be instructed to perform the exercises at home every day for 12 weeks. Clinical outcomes will be assessed at baseline and 12 and 24 weeks after starting the intervention. The primary outcomes are average overall knee pain and physical function in daily life. The secondary outcomes include other measures of knee pain, physical function, patient-perceived satisfactory improvement, health-related quality of life, physical activity and performance, muscle strength of the lower limb, and adherence.Discussion: This study will provide more evidence on the effects of traditional Chinese exercise on improving physical function and relieving joint pain among patients with knee OA. If proven effective, leg swing exercise can be used as a non-surgical treatment for knee OA in the future.Trial Registration: Chinese Clinical Trial Registry ChiCTR2000039005 . Registered on 13 October 2020. [ABSTRACT FROM AUTHOR]

Lateral intra-articular varus osteotomy is an L-shaped osteotomy of the lateral tibial condyle to correct mild knee valgus and lateral plateau malunion of the proximal tibia. In order to minimize injury, it was modified to preserve the posterolateral cortex and the upper tibiofibular joint. The aim of this study was to evaluate the stability of modified lateral intra-articular varus osteotomy by comparing the biomechanical strength with lateral intra-articular varus osteotomy. Twenty-four synthetic tibia models were divided into 2 groups based on osteotomy type. Each model was then fixed with 2 commonly used plate systems. Biomechanical tests were conducted to measure parameters including construct stiffness, wedge displacement, and the number of failed specimens, and the results were compared among different groups. No significant difference was found in construct stiffness among all groups (P > 0.05). There was also no significant difference in wedge displacement among all groups (P > 0.05). When an axial load of 1500 N was applied, the number of failed specimens showed no significant difference among all groups (P > 0.05). The main failure pattern was additional fracture lines on the lateral tibial plateau. The findings indicate that there was no significant difference in stability between the 2 groups under the tested loading conditions. Furthermore, it appears that preserving the posterolateral cortex may have no impact on biomechanical stability. • Biomechanical study of lateral high tibia osteotomy with synthetic bones. • Modified lateral intra-articular varus osteotomy construct is stable. • Modified osteotomy has comparable reliability compared to traditional osteotomy. [ABSTRACT FROM AUTHOR]