Effect of recombinant human bone morphogenetic protein 2/poly-lactide-co-glycolic acid (rhBMP-2/PLGA) with core decompression on repair of rabbit femoral head necrosis

ABSTRACTObjectiveTo observe the effect of recombinant human bone morphogenetic protein 2/poly-lactide-co-glycolic acid (rhBMP-2/PLGA) with core decompression on repair of rabbit femoral head necrosis.MethodBilateral femoral head necrosis models of rabbit were established by steroid injection. A total of 48 rabbits (96 femoral head necrosis) were randomly divided into 4 groups: Group A, control group with12 rabbits, 24 femoral head necrosis; Group B, treated with rhBMP-2/PLGA implantation after core depression, with 12 rabbits, 24 femoral head necrosis; Group C, treated with rhBMP-2 implantation after core depression, with 12 rabbits, 24 femoral head necrosis; Group D treated with core depression group without implantation, with 12 rabbits, 24 femoral head necrosis. All animals were sacrificed after 12 weeks. The ability of repairing bone defect was evaluated by X-ray radiograph. Bone mineral density analysis of the defect regions were used to evaluate the level of ossification. The morphologic change and bone formation was assessed by HE staining. The angiogenesis was evaluated by VEGF immunohistochemistry.ResultsThe osteogenetic ability and quality of femoral head necrosis in group B were better than those of other groups after 12 weeks by X-ray radiograph and morphologic investigation. And the angiogenesis in group B was better than other groups. Group C had similar osteogenetic quality of femoral head necrosis and angiogenesis with group D.ConclusionThe treatment of rhBMP-2/PLGA implantation after core depression can promote the repair of rabbit femoral head necrosis. It is a promising and efficient synthetic bone material to treat the femoral head necrosis

A Four-Stage Data Augmentation Approach to ResNet-Conformer Based Acoustic Modeling for Sound Event Localization and Detection

In this paper, we propose a novel four-stage data augmentation approach to ResNet-Conformer based acoustic modeling for sound event localization and detection (SELD). First, we explore two spatial augmentation techniques, namely audio channel swapping (ACS) and multi-channel simulation (MCS), to deal with data sparsity in SELD. ACS and MDS focus on augmenting the limited training data with expanding direction of arrival (DOA) representations such that the acoustic models trained with the augmented data are robust to localization variations of acoustic sources. Next, time-domain mixing (TDM) and time-frequency masking (TFM) are also investigated to deal with overlapping sound events and data diversity. Finally, ACS, MCS, TDM and TFM are combined in a step-by-step manner to form an effective four-stage data augmentation scheme. Tested on the Detection and Classification of Acoustic Scenes and Events (DCASE) 2020 data sets, our proposed augmentation approach greatly improves the system performance, ranking our submitted system in the first place in the SELD task of DCASE 2020 Challenge. Furthermore, we employ a ResNet-Conformer architecture to model both global and local context dependencies of an audio sequence to yield further gains over those architectures used in the DCASE 2020 SELD evaluations.Comment: 12 pages, 8 figure

{μ-N-[(Diphenyl­phosphino)meth­yl]pyridin-2-amine-κ2 N 1:P}bis­{[2-(2,2′-bipyridin-6-yl)phenyl-κ3 N,N′,C 1]platinum(II)} bis­(perchlorate)

The title compound, [Pt2(C16H11N2)2(C18H17N2P)](ClO4)2, contains two PtII atoms, bridged by an N-[(diphenyl­phosphino)meth­yl]pyridin-2-amine (dppmp) ligand. One Pt atom is coordinated by one P atom from the dppmp ligand, and one C atom and two N atoms from a 6-phenyl-2,2′-bipyridine (pbpy) ligand in a square-planar geometry. The other Pt atom is coordinated by one N atom from the dppmp ligand, and one C atom and two N atoms from another pbpy ligand in a square-planar geometry. There are intra­molecular π–π inter­actions between the pbpy ligands, with a centroid–centroid distance of 3.62 (1) Å between two pyridyl rings. The oxygen atoms of both perchlorate anions are disordered, each over two different positions [occupanicies 0.49 (3)/0.51 (3) and 0.48 (2)/0.52 (2)]

Dictionary learning LASSO for feature selection with application to hepatocellular carcinoma grading using contrast enhanced magnetic resonance imaging

IntroductionThe successful use of machine learning (ML) for medical diagnostic purposes has prompted myriad applications in cancer image analysis. Particularly for hepatocellular carcinoma (HCC) grading, there has been a surge of interest in ML-based selection of the discriminative features from high-dimensional magnetic resonance imaging (MRI) radiomics data. As one of the most commonly used ML-based selection methods, the least absolute shrinkage and selection operator (LASSO) has high discriminative power of the essential feature based on linear representation between input features and output labels. However, most LASSO methods directly explore the original training data rather than effectively exploiting the most informative features of radiomics data for HCC grading. To overcome this limitation, this study marks the first attempt to propose a feature selection method based on LASSO with dictionary learning, where a dictionary is learned from the training features, using the Fisher ratio to maximize the discriminative information in the feature.MethodsThis study proposes a LASSO method with dictionary learning to ensure the accuracy and discrimination of feature selection. Specifically, based on the Fisher ratio score, each radiomic feature is classified into two groups: the high-information and the low-information group. Then, a dictionary is learned through an optimal mapping matrix to enhance the high-information part and suppress the low discriminative information for the task of HCC grading. Finally, we select the most discrimination features according to the LASSO coefficients based on the learned dictionary.Results and discussionThe experimental results based on two classifiers (KNN and SVM) showed that the proposed method yielded accuracy gains, compared favorably with another 5 state-of-the-practice feature selection methods

A Survey of Executive Compensation Contracts in China’s Listed Companies

We analyze 228 executive compensation contracts voluntarily disclosed by Chinese listed firms and find that central-government-controlled companies disclose more information in executive compensation contracts than local-government-controlled and non-government-controlled companies. Cash-based payments are the main form of executive compensation, whereas equity-based payments are seldom used by Chinese listed companies. On average, there are no significant differences in the value of basic salaries and performance-based compensation in executive compensation contracts. But, compared with their counterparts in non-government-controlled companies, executives in government-controlled companies are given more incentive compensation. Accounting earnings are typically used in executive compensation contracts, with few firms using stock returns to evaluate their executives. However, the use of non-financial measures has increased significantly since 2007