Development and Validation of a Predictive Model for the Prognosis of Complications of Supracondylar Fractures of The Humerus in Children

Objective: Informing patient consultations and healthcare choices, clinical predictive models can offer patients tailored projections of the outcome. The most frequent elbow fractures in children are supracondylar humerus fractures, and clinical prediction models were still largely underutilized in these cases. By developing and verifying a prediction model to lower the risk of postoperative problems in children with supracondylar humerus fractures, this research sought to evaluate independent risk variables connected with the incidence of complications of supracondylar humerus fractures in children. Methods: We retrospectively studied 411 children with supracondylar humerus fractures treated surgically at our hospital from 2015 to 2019, and explored the independent risk factors affecting the prognosis of supracondylar humerus fractures in children in the study group using univariate and multifactorial Cox regression analysis, respectively. In addition, a prediction model based on the independent factors was constructed, a nomogram was made and data from the two cohorts were used to verify the feasibility and reliability of the model and visualize the data. Results: Height, older than eight years, weight, nerve damage, fracture type and with joystick technology of the child as independent risk factors influenced the prognosis of pediatric supracondylar humerus fractures in the modeling constructed by the training cohort, respectively. The results of the validation cohort were further screened for older than eight years, nerve injury and fracture type as independent prognostic factors. Conclusions: We were able to construct a predictive model based on a large genuine data sample, and clinical characteristics in this model could be used as independent predictors for reducing the occurrence of postoperative complications in supracondylar fractures. Combining basic vital signs and clinical risk factors into a simple and clear nomogram was more likely to result in the best treatment plan

Amphiphilic AIEgen-polymer aggregates: Design, self-assembly and biomedical applications

Aggregation-induced emission (AIE) is a phenomenon in which fluorescence is enhanced rather than quenched upon molecular assembly. AIE fluorogens (AIEgens) are flexible, conjugated systems that are limited in their dynamics when assembled, which improves their fluorescent properties. This intriguing feature has been incorporated in many different molecular assemblies and has been extended to nanoparticles composed of amphiphilic polymer building blocks. The integration of the fascinating AIE design principle with versatile polymer chemistry opens up new frontiers to approach and solve intrinsic obstacles of conventional fluorescent materials in nanoscience, including the aggregation-caused quenching effect. Furthermore, this integration has drawn significant attention from the nanomedicine community, due to the additional advantages of nanoparticles comprising AIEgenic molecules, such as emission brightness and fluorescence stability. In this regard, a range of AIEgenic amphiphilic polymers have been developed, displaying enhanced emission in the self-assembly/aggregated state. AIEgenic assemblies are regarded as attractive nanomaterials with inherent fluorescence, which display promising features in a biomedical context, for instance in biosensing, cell/tissue imaging and tracking, as well as (photo) therapeutics. In this review, we describe recent strategies for the design and synthesis of novel types of AIEgenic amphiphilic polymers via facile approaches including direct conjugation to natural/synthetic polymers, polymerization, post-polymerization and supramolecular host−guest interactions. Their self-assembly behavior and biomedical potential will be discussed

Blockchain-enabled Wireless IoT Networks with Multiple Communication Connections

Blockchain-enabled wireless network has been recognized as an emerging network architecture to be widely employed into the Internet of Things (IoT) ecosystems for establishing trust and consensus mechanisms without the involvement of a third party. However, the uncertainty and vulnerability of wireless channels among the IoT nodes may pose a serious challenge to facilitate the deployment of blockchain in wireless networks. In this paper, we first present a generic system model for blockchain enabled wireless networks with multiple communication connections, where the number of communication connections between a client IoT node and the blockchain full nodes can be any arbitrary positive integer to satisfy different security requirements. Based on the proposed spatial-temporal network model, we theoretically calculate the transmission successful probability and the required communication throughput to support a wireless blockchain network. Finally, simulation results validate the accuracy of our theoretical analysis

End-to-End Fovea Localisation in Colour Fundus Images with a Hierarchical Deep Regression Network

Accurately locating the fovea is a prerequisite for developing computer aided diagnosis (CAD) of retinal diseases. In colour fundus images of the retina, the fovea is a fuzzy region lacking prominent visual features and this makes it difficult to directly locate the fovea. While traditional methods rely on explicitly extracting image features from the surrounding structures such as the optic disc and various vessels to infer the position of the fovea, deep learning based regression technique can implicitly model the relation between the fovea and other nearby anatomical structures to determine the location of the fovea in an end-to-end fashion. Although promising, using deep learning for fovea localisation also has many unsolved challenges. In this paper, we present a new end-to-end fovea localisation method based on a hierarchical coarse-to-fine deep regression neural network. The innovative features of the new method include a multi-scale feature fusion technique and a self-attention technique to exploit location, semantic, and contextual information in an integrated framework, a multi-field-of-view (multi-FOV) feature fusion technique for context-aware feature learning and a Gaussian-shiftcropping method for augmenting effective training data. We present extensive experimental results on two public databases and show that our new method achieved state of- the-art performances. We also present a comprehensive ablation study and analysis to demonstrate the technical soundness and effectiveness of the overall framework and its various constituent components

PO-256 Influences of Exercise on Circulating Irisin in Overweight or Obese Individuals: a system review

Objective Irisin is a newly identified myokine, which is mainly secreted by skeleton muscle, adipose and cerebellar. It is shown to be related to some physiology process. The aim of this study is to evaluate the influence of exercise on circulating irisin concentrations in overweight or obese individuals Methods Searches were performed on nine online electronic databases including PubMed, EMbase, The Cochrane Library, web of science, Ebsco, CNKI, VIP, CBM and Wan-Fang Data databases. The search items were irisin, fibronectin type Ⅲ domain-containing protein 5, FNDC5, exercise, training, physical activity, obesity, overweight, obese, body mass index, BMI, adiposity and fat. Randomized controlled trials (RCT) or clinical controlled trials about the effect of exercise on circulating irisin concentrations in overweight or obese individuals in English or Chinese were eligible for the study. The trials compare exercise intervention with no intervention, or combined interventions of exercise and other with other intervention(s), and the exercise intervention is not one acute time. Besides, the trial objects belong to overweight or obese regardless of the judgement’s indicator. According to the criteria, the data extracted by two research independently. If there was disagreement, discussion between all the authors were used to settle. The risk of bias among the included studies was assessed by the Cochrane Collaboration Risk-of-Bias tool, which consists of seven domains and each one was judged to ‘unclear risk’ ‘low risk’, or ‘high risk’ following the recommendations detailed of the Cochrane handbook. Lastly an analysis about the final studies was done.  Results The search identified a total of 855 possible articles. Of those, 364 were removed as duplicates, and the remaining 491 were screened for the titles and abstracts. The full-texts of 56 trials were retrieved to assess for eligibility. After the evaluation, four articles of RCTs were retained for the final system review from the year of 2015 to 2017, producing 6 study estimates. The assessments class of methods quantality of them are A. All the research subjects are more than 18 years old, and in one study subjects are men, men and women in two, women in three. The types of exercise intervention are dissimilar, such as strengthen or endurance exercise (including high intensity interval training, HIIT). In the duration of exercise, three studies are 8 weeks, and two for 12 weeks, one for 24 weeks. In circulating irisin, the detection methods of all is enzyme-linked immunosorbent assay, and three are in plasm, three in serum. Furthermore, the concentration unit in five studies is ng/ml, and one is µg/ml. Bonefate suggests that aerobic exercise with the frequency of 3 times per week for 24 week maintains plasma FNDC5/irisin of middle-age obese men, same as 8 weeks aerobic exercise for overweight/obese adults by Kim, but three is an opposite result from Wu, which proved that aerobic exercise of twelve weeks ascends serum irisin of young obese women. HIIT of eight or twelve weeks ascends serum irisin in sedentary obese women or young obese women according to Tofighi or Wu suggestion. Moreover, resistance exercise of 8 weeks significantly increases plasma irisin of overweight/obese adults From Kim’s study. Conclusions The study about effect of exercise on circulating irisin levels in overweight or obese individuals is not sufficient to come to a positive result, although the quality assessments of current evidences are high. Basing on the available literatures, exercise can maintain or improve circulating irisin levels in overweight or obese individuals. The effect needs to be illustrated by further RCTs with large sample size. &nbsp

Inherently Fluorescent Peanut-Shaped Polymersomes for Active Cargo Transportation

Nanomotors have been extensively explored for various applications in nanomedicine, especially in cargo transportation. Motile properties enable them to deliver pharmaceutical ingredients more efficiently to the targeted site. However, it still remains a challenge to design motor systems that are therapeutically active and can also be effectively traced when taken up by cells. Here, we designed a nanomotor with integrated fluorescence and therapeutic potential based on biodegradable polymersomes equipped with aggregation-induced emission (AIE) agents. The AIE segments provided the polymersomes with autofluorescence, facilitating the visualization of cell uptake. Furthermore, the membrane structure enabled the reshaping of the AIE polymersomes into asymmetric, peanut-shaped polymersomes. Upon laser irradiation, these peanut polymersomes not only displayed fluorescence, but also produced reactive oxygen species (ROS). Because of their specific shape, the ROS gradient induced motility in these particles. As ROS is also used for cancer cell treatment, the peanut polymersomes not only acted as delivery vehicles but also as therapeutic agents. As an integrated platform, these peanut polymersomes therefore represent an interesting delivery system with biomedical potential.</p

Inherently Fluorescent Peanut-Shaped Polymersomes for Active Cargo Transportation

Nanomotors have been extensively explored for various applications in nanomedicine, especially in cargo transportation. Motile properties enable them to deliver pharmaceutical ingredients more efficiently to the targeted site. However, it still remains a challenge to design motor systems that are therapeutically active and can also be effectively traced when taken up by cells. Here, we designed a nanomotor with integrated fluorescence and therapeutic potential based on biodegradable polymersomes equipped with aggregation-induced emission (AIE) agents. The AIE segments provided the polymersomes with autofluorescence, facilitating the visualization of cell uptake. Furthermore, the membrane structure enabled the reshaping of the AIE polymersomes into asymmetric, peanut-shaped polymersomes. Upon laser irradiation, these peanut polymersomes not only displayed fluorescence, but also produced reactive oxygen species (ROS). Because of their specific shape, the ROS gradient induced motility in these particles. As ROS is also used for cancer cell treatment, the peanut polymersomes not only acted as delivery vehicles but also as therapeutic agents. As an integrated platform, these peanut polymersomes therefore represent an interesting delivery system with biomedical potential.</p