Target-Aware Tracking with Long-Term Context Attention

Most deep trackers still follow the guidance of the siamese paradigms and use a template that contains only the target without any contextual information, which makes it difficult for the tracker to cope with large appearance changes, rapid target movement, and attraction from similar objects. To alleviate the above problem, we propose a long-term context attention (LCA) module that can perform extensive information fusion on the target and its context from long-term frames, and calculate the target correlation while enhancing target features. The complete contextual information contains the location of the target as well as the state around the target. LCA uses the target state from the previous frame to exclude the interference of similar objects and complex backgrounds, thus accurately locating the target and enabling the tracker to obtain higher robustness and regression accuracy. By embedding the LCA module in Transformer, we build a powerful online tracker with a target-aware backbone, termed as TATrack. In addition, we propose a dynamic online update algorithm based on the classification confidence of historical information without additional calculation burden. Our tracker achieves state-of-the-art performance on multiple benchmarks, with 71.1% AUC, 89.3% NP, and 73.0% AO on LaSOT, TrackingNet, and GOT-10k. The code and trained models are available on https://github.com/hekaijie123/TATrack

Promoting musculoskeletal system soft tissue regeneration by biomaterial-mediated modulation of macrophage polarization

Musculoskeletal disorders are common in clinical practice. Repairing critical-sized defects in musculoskeletal systems remains a challenge for researchers and surgeons, requiring the application of tissue engineering biomaterials. Successful application depends on the response of the host tissue to the biomaterial and specific healing process of each anatomical structure. The commonly-held view is that biomaterials should be biocompatible to minimize local host immune response. However, a growing number of studies have shown that active modulation of the immune cells, particularly macrophages, via biomaterials is an effective way to control immune response and promote tissue regeneration as well as biomaterial integration. Therefore, we critically review the role of macrophages in the repair of injured musculoskeletal system soft tissues, which have relatively poor regenerative capacities, as well as discuss further enhancement of target tissue regeneration via modulation of macrophage polarization by biomaterial-mediated immunomodulation (biomaterial properties and delivery systems). This active regulation approach rather than passive-evade strategy maximizes the potential of biomaterials to promote musculoskeletal system soft tissue regeneration and provides alternative therapeutic options for repairing critical-sized defects

Stem cell-based therapeutic strategies for rotator cuff tendinopathy

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

Realization of a power-efficient transmitter based on integrated artificial neural network

In wireless devices, a transmitter normally consumes most of power due to its power amplifier (PA), especially in the applications such as radar, base station, and mobile phone. It is highly desirable to design a transmitter that can emit signals smartly, i.e., the power emission is exactly based on the emitting distance required and the target. Such a design can save huge amount of power as there are almost countless wireless devices in use currently. In this paper, an intelligent radio-frequency transmitter integrated with artificial neural network (ANN) is implemented. The intelligent transmitter consists of an ANN module, a frequency generation module, and a switch-mode PA. The integrated three-layered fully connected ANN can be offline trained to smartly classify input data according to the required power and assign the transmission channel. Furthermore, with the integrated ANN, the average power consumption of the PA is reduced to 34.3 mW, which is 46.5 % lower than PA without the ANN. With the intelligent transmitter, wireless devices can save a large amount of energy in their operations.Published versio

Animal model for tendinopathy

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

An Off-the-Shelf Tissue Engineered Cartilage Composed of Optimally Sized Pellets of Cartilage Progenitor/Stem Cells

Articular cartilage focal lesion remains an intractable challenge in sports medicine, and autologous chondrocytes' implantation (ACI) is one of the most commonly utilized treatment modality for this ailment. However, the current ACI technique requires two surgical steps which increases patients' morbidity and incurs additional medical costs. In the present study, we developed a one-step cryopreserved off-the-shelf ACI tissue-engineered (TE) cartilage by seeding pellets of spheroidal cartilage stem/progenitor cells (CSPCs) on a silk scaffold. The pellets were developed through a hanging-drop method, and the incubation time of 1 day could efficiently produce spheroidal pellets without any adverse influence on the cell activity. The pellet size was also optimized. Under chondrogenic induction, pellets consisting of 40 000 CSPCs were found to exhibit the most abundant cartilage matrix deposition and the highest mRNA expression levels of SOX9, aggrecan, and COL2A1, as compared with pellets consisting of 10 000, 100 000, or 200 000 CSPCs. Scaffolds seeded with CSPCs pellets containing 40 000 cells could be preserved in liquid nitrogen with the viability, migration, and chondrogenic ability remaining unaffected for as long as 3 months. When implanted in a rat trochlear cartilage defect model for 3 months, the ready-to-use, cryopreserved TE cartilage yielded fully cartilage reconstruction, which was comparable with the uncryopreserved control. Hence, our study provided preliminary data that our off-the-shell TE cartilage with optimally sized CSPCs pellets seeded within silk scaffolds exhibited strong cartilage repair capacity, which provided a convenient and promising one-step surgical approach to ACI