Objective To investigate the analgesic effect and the in vitro anticoagulation activity of Ento-I, along with its protective effect against the formation of collagen- adrenaline induced thrombus. Methods The threshold of pain in mice was deter mined with the method of hot plate. Mice thrombogenesis induced by collagen-epinephrine mixture injected through tail-vein was adopted for observing the mortality, hemiplegia recovery rates, hemiplegia formation time, survival time and time for hemiplegia recovery in mice to evaluate the protective effects of test drugs against thrombus in vivo. Anticoagulation effects of test drugs were detected by measuring the thrombin time (TT), prothrombin time (PT), and activated partial thromboplastin time (APTT) of rabbits with in vitro clotting model. Results The experiment of hot plate for analgesia showed that compared with those of normal control group Ento-I plastic could significantly prolong pain thresholds in mice at 30, 60 and 90 min after final administration (P<0.01). The mortality of collagen-epinephrine induced thrombotic hemiplegia was reduced while its recovery rates were significantly increased for mice administered Ento-I plastic (P<0.05). Compared with clopidogrel group, Ento-I plastic 2 mg/kg could effectively reduce the time for hemiplegia recovery (P<0.05). In addition, compared with substrate matrix group, Ento-I plastic (4.65 mg/kg) could significantly prolong TT, PT, and APTT in rabbit plasma (P<0.05, P<0.05 and P<0.01). Conclusion The Ento-I plastic possesses analgesic effect, anticoagulability and antithrombotic activity, and it may be a promising medicine for the treatment of thrombotic diseases.

There are two modes to display panoramic movies in virtual reality (VR) environment: non-stereoscopic mode (2D) and stereoscopic mode (3D). It has not been fully studied whether there are differences in the activation effect between these two continuous display modes on emotional arousal and what characteristics of the related neural activity are. In this paper, we designed a cognitive psychology experiment in order to compare the effects of VR-2D and VR-3D on emotional arousal by analyzing synchronously collected scalp electroencephalogram signals. We used support vector machine (SVM) to verify the neurophysiological differences between the two modes in VR environment. The results showed that compared with VR-2D films, VR-3D films evoked significantly higher electroencephalogram (EEG) power (mainly reflected in α and β activities). The significantly improved β wave power in VR-3D mode showed that 3D vision brought more intense cortical activity, which might lead to higher arousal. At the same time, the more intense α activity in the occipital region of the brain also suggested that VR-3D films might cause higher visual fatigue. By the means of neurocinematics, this paper demonstrates that EEG activity can well reflect the effects of different vision modes on the characteristics of the viewers' neural activities. The current study provides theoretical support not only for the future exploration of the image language under the VR perspective, but for future VR film shooting methods and human emotion research.
Arousal ; Electroencephalography ; Emotions/physiology* ; Humans ; Motion Pictures ; Virtual Reality

[ Abstract]Automatic and accurate segmentation of lung parenchyma is essential for assisted diagnosis of lung cancer. In recent years, researchers in the field of deep learning have proposed a number of improved lung parenchyma segmentation methods based on U-Net. However, the existing segmentation methods ignore the complementary fusion of semantic information in the feature map between different layers and fail to distinguish the importance of different spaces and channels in the feature map. To solve this problem, this paper proposes the double scale parallel attention (DSPA) network (DSPA-Net) architecture, and introduces the DSPA module and the atrous spatial pyramid pooling (ASPP) module in the "encoder-decoder" structure. Among them, the DSPA module aggregates the semantic information of feature maps of different levels while obtaining accurate space and channel information of feature map with the help of cooperative attention (CA). The ASPP module uses multiple parallel convolution kernels with different void rates to obtain feature maps containing multi-scale information under different receptive fields. The two modules address multi-scale information processing in feature maps of different levels and in feature maps of the same level, respectively. We conducted experimental verification on the Kaggle competition dataset. The experimental results prove that the network architecture has obvious advantages compared with the current mainstream segmentation network. The values of dice similarity coefficient (DSC) and intersection on union (IoU) reached 0.972 ± 0.002 and 0.945 ± 0.004, respectively. This paper achieves automatic and accurate segmentation of lung parenchyma and provides a reference for the application of attentional mechanisms and multi-scale information in the field of lung parenchyma segmentation.
Algorithms ; Image Processing, Computer-Assisted/methods* ; Lung/diagnostic imaging* ; Neural Networks, Computer ; Tomography, X-Ray Computed/methods*

The surgical installation accuracy of the components in unicompartmental knee arthroplasty (UKA) is an important factor affecting the joint function and the implant life. Taking the ratio of the medial-lateral position of the femoral component relative to the tibial insert (a/A) as a parameter, and considering nine installation conditions of the femoral component, this study established the musculoskeletal multibody dynamics models of UKA to simulate the patients' walking gait, and investigated the influences of the medial-lateral installation positions of the femoral component in UKA on the contact force, joint motion and ligament force of the knee joint. The results showed that, with the increase of a/A ratio, the medial contact force of the UKA implant was decreased and the lateral contact force of the cartilage was increased; the varus rotation, external rotation and posterior translation of the knee joint were increased; and the anterior cruciate ligament force, posterior cruciate ligament force and medial collateral ligament force were decreased. The medial-lateral installation positions of the femoral component in UKA had little effect on knee flexion-extension movement and lateral collateral ligament force. When the a/A ratio was less than or equalled to 0.375, the femoral component collided with the tibia. In order to prevent the overload on the medial implant and lateral cartilage, the excessive ligament force, and the collision between the femoral component and the tibia, it is suggested that the a/A ratio should be controlled within the range of 0.427-0.688 when the femoral component is installed in UKA. This study provides a reference for the accurate installation of the femoral component in UKA.
Humans ; Arthroplasty, Replacement, Knee ; Knee Joint/surgery* ; Knee Prosthesis ; Gait ; Rotation

OBJECTIVETo study the order and degree of muscular affection in patients with Duchenne muscular dystrophy (DMD) during the course of disease.

METHODSMultiplex ligation dependent probe amplification (MLPA) was used to detect potential mutation of dystrophin gene. Magnetic resonance imaging (MRI) was used to scan the anteromedial aspect of thigh muscles.

RESULTSAll of the 6 patients were found to have deletion or duplication mutations. The order of affection has been gluteus maximus, adductor magnus, quadriceps femoris, rectus femoris and biceps muscle of the thigh, while semimembranous muscle, semitendinosus, sartorius muscle and musculus gracilis are selectively affected and in a decreasing order.

CONCLUSIONMRI can reflect the order, extent and degree of skeletal muscle involvement in patients with DMD, and can reflect pathological changes of damaged skeletal muscle at each stage, which may provide an important means for patient examination and diagnosis. No apparent correlation between the severity of disease and the nature of mutations was noted.

Adolescent ; Child ; Child, Preschool ; Dystrophin ; genetics ; Female ; Humans ; Magnetic Resonance Imaging ; Male ; Muscle, Skeletal ; diagnostic imaging ; Muscular Dystrophy, Duchenne ; diagnosis ; diagnostic imaging ; genetics ; Mutation ; Radiography ; Sequence Deletion

Computer-aided diagnosis (CAD) systems play a very important role in modern medical diagnosis and treatment systems, but their performance is limited by training samples. However, the training samples are affected by factors such as imaging cost, labeling cost and involving patient privacy, resulting in insufficient diversity of training images and difficulty in data obtaining. Therefore, how to efficiently and cost-effectively augment existing medical image datasets has become a research hotspot. In this paper, the research progress on medical image dataset expansion methods is reviewed based on relevant literatures at home and abroad. First, the expansion methods based on geometric transformation and generative adversarial networks are compared and analyzed, and then improvement of the augmentation methods based on generative adversarial networks are emphasized. Finally, some urgent problems in the field of medical image dataset expansion are discussed and the future development trend is prospected.
Humans ; Diagnosis, Computer-Assisted ; Diagnostic Imaging ; Datasets as Topic

We reported a 32 years female patient in whom lung metastasis from breast cancer was presented as solitary pulmonary pure ground-glass opacity (GGO) lesion. The patient received rational preoperative examinations and surgery though the preoperative diagnosis was not accurate. Because of different therapy strategies and purposes, it is crucial to make distinction of atypical metastases from primary cancers. Thus, for patients with a history of malignancy, possible metastasis should be taken into consideration if new GGO was found on the CT. Besides this, the follow-up interval of CT should be shortened appropriately, preoperative examinations and surgical procedures should be made according to the suggestions of multidisciplinary team.

Medical image segmentation based on deep learning has become a powerful tool in the field of medical image processing. Due to the special nature of medical images, image segmentation algorithms based on deep learning face problems such as sample imbalance, edge blur, false positive, false negative, etc. In view of these problems, researchers mostly improve the network structure, but rarely improve from the unstructured aspect. The loss function is an important part of the segmentation method based on deep learning. The improvement of the loss function can improve the segmentation effect of the network from the root, and the loss function is independent of the network structure, which can be used in various network models and segmentation tasks in plug and play. Starting from the difficulties in medical image segmentation, this paper first introduces the loss function and improvement strategies to solve the problems of sample imbalance, edge blur, false positive and false negative. Then the difficulties encountered in the improvement of the current loss function are analyzed. Finally, the future research directions are prospected. This paper provides a reference for the reasonable selection, improvement or innovation of loss function, and guides the direction for the follow-up research of loss function.
Algorithms ; Image Processing, Computer-Assisted

To explore the influence of bionic texture coronary stents on hemodynamics, a type of bioabsorbable polylactic acid coronary stents was designed, for which a finite element analysis method was used to carry out simulation analysis on blood flow field after the implantation of bionic texture stents with three different shapes (rectangle, triangle and trapezoid), thus revealing the influence of groove shape and size on hemodynamics, and identifying the optimal solution of bionic texture groove. The results showed that the influence of bionic texture grooves of different shapes and sizes on the lower wall shear stress region had a certain regularity. Specifically, the improvement effect of grooves above 0.06 mm on blood flow characteristics was poor, and the effect of grooves below 0.06 mm was good. Furthermore, the smaller the size is, the better the improvement effect is, and the 0.02 mm triangular groove had the best improvement effect. Based on the results of this study, it is expected that bionic texture stents have provided a new method for reducing in-stent restenosis.
Bionics ; Computer Simulation ; Coronary Vessels ; Hemodynamics/physiology* ; Models, Cardiovascular ; Stents ; Stress, Mechanical

Considering the small differences between different types in the diabetic retinopathy (DR) grading task, a retinopathy grading algorithm based on cross-layer bilinear pooling is proposed. Firstly, the input image is cropped according to the Hough circle transform (HCT), and then the image contrast is improved by the preprocessing method; then the squeeze excitation group residual network (SEResNeXt) is used as the backbone of the model, and a cross-layer bilinear pooling module is introduced for classification. Finally, a random puzzle generator is introduced in the training process for progressive training, and the center loss (CL) and focal loss (FL) methods are used to further improve the effect of the final classification. The quadratic weighted Kappa (QWK) is 90.84% in the Indian Diabetic Retinopathy Image Dataset (IDRiD), and the area under the receiver operating characteristic curve (AUC) in the Messidor-2 dataset (Messidor-2) is 88.54%. Experiments show that the algorithm proposed in this paper has a certain application value in the field of diabetic retina grading.
Humans ; Diabetic Retinopathy/diagnostic imaging* ; Algorithms ; ROC Curve ; Diabetes Mellitus