Abstract Raloxifene is an FDA approved agent used to treat bone loss and decrease fracture risk. In clinical trials and animal studies, raloxifene reduces fracture risk and improves bone mechanical ...properties, but the mechanisms of action remain unclear because these benefits occur largely independent of changes to bone mass. Using a novel experimental approach, machined bone beams, both from mature male canine and human male donors, were depleted of living cells and then exposed to raloxifene ex vivo. Our data show that ex vivo exposure of non-viable bone to raloxifene improves intrinsic toughness, both in canine and human cortical bone beams tested by 4-point bending. These effects are cell-independent and appear to be mediated by an increase in matrix bound water, assessed using basic gravimetric weighing and sophisticated ultrashort echo time magnetic resonance imaging. The hydroxyl groups ( OH) on raloxifene were shown to be important in both the water and toughness increases. Wide and small angle X-ray scattering patterns during 4-pt bending show that raloxifene alters the transfer of load between the collagen matrix and the mineral crystals, placing lower strains on the mineral, and allowing greater overall deformation prior to failure. Collectively, these findings provide a possible mechanistic explanation for the therapeutic effect of raloxifene and more importantly identify a cell-independent mechanism that can be utilized for novel pharmacological approaches for enhancing bone strength.
Considering that serious hand function damage will greatly affect the daily life of patients, its recovery mainly depends on the regular inspection and manual training of medical staff, and medical ...monitoring based on bioelectric signals can largely replace manual re-examination as autonomous rehabilitation technology. So, for the rationality of feature selection and the diversity of classifier design in the gesture recognition process based on electromyography (EMG) signals, this paper proposes a hand medical monitoring system based on feature selection method of feature subset average recognition rate and optimal machine learning algorithm selection, which mainly depends on the prediction of hand movement. At the same time, since most experiments are conducted in different non-public proprietary databases, the comparison between various gesture recognition methods can only be analyzed to a certain extent. Therefore, this paper uses the DB1 dataset in the large publicly available NinaPro database and combines with presently well-known 11 time-domain (TD) features and 5 frequency domain (FD) features, then uses the support vector machine (SVM) classifier to comparative analysis total 136 feature combinations under various feature numbers. Under the premise of ensuring the overall recognition rate of electromyography gesture, this method will be able to reduce the number of features in feature set, according to the change of the average remove redundant features, and construct an optimal reduced EMG feature set. Finally, through the four common hand motion classifiers based on machine learning: SVM, back propagation neural network, linear discriminant analysis, and K-nearest neighbor, this paper tests and verifies the separability of the optimal reduced EMG feature set, and based on this, selects the optimal hand motion classifier to build the optimal hand motion recognition system, improve the hand medical monitoring system, and provide technical reference for the construction of real-time medical monitoring system.
In the production and construction of industry, safety accidents caused by unsafe behaviors of staff often occur. In a complex construction site scene, due to improper operations by personnel, huge ...safety risks will be buried in the entire production process. The use of deep learning algorithms to replace manual monitoring of site safety regulations is a powerful guarantee for sticking to the line of safety in production. First, the improved YOLO v3 algorithm is used to output the predicted anchor box of the target object, and then pixel feature statistics are performed on the anchor box, and the weight coefficients are respectively multiplied to output the confidence of the standard wearing of the helmet in each predicted anchor box area, according to the empirical threshold determine whether workers meet the standards for wearing helmets. Experimental results show that the helmet wearing detection algorithm based on deep learning in this paper increases the feature map scale, optimizes the prior dimensional algorithm of specific helmet dataset, and improves the loss function, and then combines image processing pixel feature statistics to accurately detect whether the helmet is worn by the standard. The final result is that mAP reaches 93.1% and FPS reaches 55 f/s. In the helmet recognition task, compared to the original YOLO v3 algorithm, mAP is increased by 3.5% and FPS is increased by 3 f/s. It shows that the improved detection algorithm has a better effect on the detection speed and accuracy of the helmet detection task.
The brain is the largest and most complex structure in the central nervous system. It dominates all activities in the body, and the lesions in the human body are also reflected in the brain signal. ...In this paper, the image method is used to assist the brain signal to detect the human lesion. Due to the particularity of medical images, there is no common segmentation method for any medical image, and there is no objective standard to judge whether the segmentation is effective. Medical image segmentation technology is still a bottleneck restricting the development and the application of other related technologies in medical image processing. Based on the above reasons, this paper proposes an improved region growing algorithm based on the fuzzy theory and region growing algorithm. The algorithm is used to segment the medical images of the liver and chest X-ray of different human organs. The improved algorithm uses a threshold segmentation algorithm to assist in the automatic selection of seed points and improves the region growing rules, then morphological post-processing is used to improve the segmentation effect. The experimental results show that the improved region growing algorithm has better segmentation effect under two different organs, which proves that the algorithm has certain applicability, and its accuracy and segmentation quality are better than the traditional region growing algorithm. This algorithm combines the advantages of the threshold method and traditional region growing method. It is feasible in algorithm and has certain application value.
In the field of human-computer interaction, vision-based gesture recognition methods are widely studied. However, its recognition effect depends to a large extent on the performance of the ...recognition algorithm. The skeletonization algorithm and convolutional neural network (CNN) for the recognition algorithm reduce the impact of shooting angle and environment on recognition effect, and improve the accuracy of gesture recognition in complex environments. According to the influence of the shooting angle on the same gesture recognition, the skeletonization algorithm is optimized based on the layer-by-layer stripping concept, so that the key node information in the hand skeleton diagram is extracted. The gesture direction is determined by the spatial coordinate axis of the hand. Based on this, gesture segmentation is implemented to overcome the influence of the environment on the recognition effect. In order to further improve the accuracy of gesture recognition, the ASK gesture database is used to train the convolutional neural network model. The experimental results show that compared with SVM method, dictionary learning + sparse representation, CNN method and other methods, the recognition rate reaches 96.01%.
Abstract Objective Depression is one of the most common mental illnesses. The reliability and the validity of the Patient Health Questionnaire (PHQ)-9, a depression screening tool, have not been ...examined in the general population in China. Thus, this study evaluated the reliability and the validity of the Chinese version of the PHQ-9 in detecting major depression in residents of a Chinese community. Methods A total of 1045 participants from a Shanghai community were enrolled in our study. Participants completed the Chinese versions of the PHQ-9, the Self-Rating Depression Scale (SDS), the 36-item Short Form Health Survey (SF-36), and the Mini International Neuropsychiatric Interview. One hundred participants were randomly selected to complete the PHQ-9 again 2 weeks after the initial assessment. The reliability, the validity and the receiver operating characteristic (ROC) curve of the PHQ-9 were analyzed. Results Cronbach's alpha for the internal consistency reliability of the Chinese version of the PHQ-9 was 0.86 for the entire scale. The correlation coefficient for the 2-week test–retest of the total score was 0.86. The PHQ-9 scale correlated positively with the SDS ( r =0.29, p <0.001) and correlated negatively with all subscale scores of the SF-36 (correlation coefficients ranged from − 0.11 to − 0.47, p <0.001). The area under the curve of the ROC was 0.92 (95% confidence interval: 0.86–0.97). A cutoff score of 7 or higher on the PHQ-9 had a sensitivity of 0.86 and a specificity of 0.86. Conclusions In the general Chinese population, the Chinese version of the PHQ-9 is a valid and efficient tool for screening depression, with a recommended cutoff score of 7 or more.
More and more studies have shown that circular RNAs (circRNAs) play a critical regulatory role in many cancers. However, the potential molecular mechanism of circRNAs in prostate cancer (PCa) remains ...largely unknown.
Differentially expressed circRNAs were identified by RNA sequencing. The expression of hsa_circ_0003258 was evaluated using quantitative real-time PCR and RNA in situ hybridization. The impacts of hsa_circ_0003258 on the metastasis of PCa cells were investigated by a series of in vitro and in vivo assays. Lastly, the underlying mechanism of hsa_circ_0003258 was revealed by Western blot, biotin-labeled RNA pulldown, RNA immunoprecipitation, luciferase assays and rescue experiments.
Increased expression of hsa_circ_0003258 was found in PCa tissues and was associated with advanced TNM stage and ISUP grade. Overexpression of hsa_circ_0003258 promoted PCa cell migration by inducing epithelial mesenchymal transformation (EMT) in vitro as well as tumor metastasis in vivo, while knockdown of hsa_circ_0003258 exerts the opposite effect. Mechanistically, hsa_circ_0003258 could elevate the expression of Rho GTPase activating protein 5 (ARHGAP5) via sponging miR-653-5p. In addition, hsa_circ_0003258 physically binds to insulin like growth factor 2 mRNA binding protein 3 (IGF2BP3) in the cytoplasm and enhanced HDAC4 mRNA stability, in which it activates ERK signalling pathway, then triggers EMT programming and finally accelerates the metastasis of PCa.
Upregulation of hsa_circ_0003258 drives tumor progression through both hsa_circ_0003258/miR-653-5p/ARHGAP5 axis and hsa_circ_0003258/IGF2BP3 /HDAC4 axis. Hsa_circ_0003258 may act as a promising biomarker for metastasis of PCa and an attractive target for PCa intervention.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Caudal autotomy is a phenomenon observed in many reptile taxa, and tail loss is a pivotal functional trait for reptiles, with potentially negative implications for organism fitness due to its ...influence on locomotion. Some lizard species can regenerate a lost tail, which sometimes can lead to the development of more than one tail (i.e., abnormal tail regeneration) in the process. However, little is currently known about the impact of abnormal tail regeneration on locomotor performance. In this study, we document abnormal tail regeneration in Eremias yarkandensis, a reptile species native to northwestern China. Additionally, we investigated the sprint speed and endurance performance of these lizards. This study provides the first report on abnormal tail regeneration and its locomotor performance on a Chinese reptile. We suggest that the abnormal regeneration of tails may contribute to the accumulation of food reserves in the species. In light of our findings, we propose that herpetologists continue to share their sporadic observations and assess the locomotor performance of species experiencing abnormal tail regeneration, further expanding our understanding of this intriguing phenomenon.
Little is currently known about the impact of abnormal tail regeneration on locomotor performance. In this study, we document abnormal tail regeneration in Eremias yarkandensis, a reptile species native to northwestern China.
Due to the complexity issue of the hand gesture recognition feature extraction, for example the variation of the light and background. In this paper, the convolution neural network is applied to the ...recognition of gestures, and the characteristics of convolution neural network are used to avoid the feature extraction process, reduce the number of parameters needs to be trained, and finally achieve the purpose of unsupervised learning. Error back propagation algorithm, is loaded into the convolution neural network algorithm, modify the threshold and weights of neural network to reduce the error of the model. In the classifier, the support vector machine that is added to optimize the classification function of the convolution neural network to improve the validity and robustness of the whole model.
Fucoidan, a sulfated polysaccharide purified from brown algae, has a variety of immune-modulation effects, including promoting antigen uptake and enhancing anti-viral and anti-tumor effects. However, ...the effect of fucoidan in vivo, especially its adjuvant effect on in vivo anti-tumor immune responses, was not fully investigated. In this study, we investigated the effect of fucoidan on the function of spleen dendritic cells (DCs) and its adjuvant effect in vivo. Systemic administration of fucoidan induced up-regulation of CD40, CD80 and CD86 expression and production of IL-6, IL-12 and TNF-α in spleen cDCs. Fucoidan also promoted the generation of IFN-γ-producing Th1 and Tc1 cells in an IL-12-dependent manner. When used as an adjuvant in vivo with ovalbumin (OVA) antigen, fucoidan promoted OVA-specific antibody production and primed IFN-γ production in OVA-specific T cells. Moreover, fucoidan enhanced OVA-induced up-regulation of MHC class I and II on spleen cDCs and strongly prompted the proliferation of OVA-specific CD4 and CD8 T cells. Finally, OVA immunization with fucoidan as adjuvant protected mice from the challenge with B16-OVA tumor cells. Taken together, these results suggest that fucoidan can function as an adjuvant to induce Th1 immune response and CTL activation, which may be useful in tumor vaccine development.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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