Improved Skip-Gram Based on Graph Structure Information.

Applying the Skip-gram to graph representation learning has become a widely researched topic in recent years. Prior works usually focus on the migration application of the Skip-gram model, while Skip-gram in graph representation learning, initially applied to word embedding, is left insufficiently explored. To compensate for the shortcoming, we analyze the difference between word embedding and graph embedding and reveal the principle of graph representation learning through a case study to explain the essential idea of graph embedding intuitively. Through the case study and in-depth understanding of graph embeddings, we propose Graph Skip-gram, an extension of the Skip-gram model using graph structure information. Graph Skip-gram can be combined with a variety of algorithms for excellent adaptability. Inspired by word embeddings in natural language processing, we design a novel feature fusion algorithm to fuse node vectors based on node vector similarity. We fully articulate the ideas of our approach on a small network and provide extensive experimental comparisons, including multiple classification tasks and link prediction tasks, demonstrating that our proposed approach is more applicable to graph representation learning.

A New Fast Control Strategy of Terminal Sliding Mode with Nonlinear Extended State Observer for Voltage Source Inverter.

To overcome the sensitivity of voltage source inverters (VSIs) to parameter perturbations and their susceptibility to load variations, a fast terminal sliding mode control (FTSMC) method is proposed as the core and combined with an improved nonlinear extended state observer (NLESO) to resist aggregate system perturbations. Firstly, a mathematical model of the dynamics of a single-phase voltage type inverter is constructed using a state-space averaging approach. Secondly, an NLESO is designed to estimate the lumped uncertainty using the saturation properties of hyperbolic tangent functions. Finally, a sliding mode control method with a fast terminal attractor is proposed to improve the dynamic tracking of the system. It is shown that the NLESO guarantees convergence of the estimation error and effectively preserves the initial derivative peak. The FTSMC enables the output voltage with high tracking accuracy and low total harmonic distortion and enhances the anti-disturbance ability.

An Efficient End-to-End Multitask Network Architecture for Defect Inspection.

Recently, computer vision-based methods have been successfully applied in many industrial fields. Nevertheless, automated detection of steel surface defects remains a challenge due to the complexity of surface defects. To solve this problem, many models have been proposed, but these models are not good enough to detect all defects. After analyzing the previous research, we believe that the single-task network cannot fully meet the actual detection needs owing to its own characteristics. To address this problem, an end-to-end multi-task network has been proposed. It consists of one encoder and two decoders. The encoder is used for feature extraction, and the two decoders are used for object detection and semantic segmentation, respectively. In an effort to deal with the challenge of changing defect scales, we propose the Depthwise Separable Atrous Spatial Pyramid Pooling module. This module can obtain dense multi-scale features at a very low computational cost. After that, Residually Connected Depthwise Separable Atrous Convolutional Blocks are used to extract spatial information under low computation for better segmentation prediction. Furthermore, we investigate the impact of training strategies on network performance. The performance of the network can be optimized by adopting the strategy of training the segmentation task first and using the deep supervision training method. At length, the advantages of object detection and semantic segmentation are tactfully combined. Our model achieves mIOU 79.37% and mAP@0.5 78.38% on the NEU dataset. Comparative experiments demonstrate that this method has apparent advantages over other models. Meanwhile, the speed of detection amount to 85.6 FPS on a single GPU, which is acceptable in the practical detection process.

An Improved Density Peak Clustering Algorithm for Multi-Density Data.

Density peak clustering is the latest classic density-based clustering algorithm, which can directly find the cluster center without iteration. The algorithm needs to determine a unique parameter, so the selection of parameters is particularly important. However, for multi-density data, when one parameter cannot satisfy all data, clustering often cannot achieve good results. Moreover, the subjective selection of cluster centers through decision diagrams is often not very convincing, and there are also certain errors. In view of the above problems, in order to achieve better clustering of multi-density data, this paper improves the density peak clustering algorithm. Aiming at the selection of parameter dc, the K-nearest neighbor idea is used to sort the neighbor distance of each data, draw a line graph of the K-nearest neighbor distance, and find the global bifurcation point to divide the data with different densities. Aiming at the selection of cluster centers, the local density and distance of each data point in each data division is found, a γ map is drawn, the average value of the γ height difference is calculated, and through two screenings the largest discontinuity point is found to automatically determine the cluster center and the number of cluster centers. The divided datasets are clustered by the DPC algorithm, and then the clustering results are perfected and integrated by using the cluster fusion rules. Finally, a variety of experiments are designed from various perspectives on various artificial simulated datasets and UCI real datasets, which demonstrate the superiority of the F-DPC algorithm in terms of clustering effect, clustering quality, and number of samples.

A New SCAE-MT Classification Model for Hyperspectral Remote Sensing Images.

Hyperspectral remote sensing images (HRSI) have the characteristics of foreign objects with the same spectrum. As it is difficult to label samples manually, the hyperspectral remote sensing images are understood to be typical "small sample" datasets. Deep neural networks can effectively extract the deep features from the HRSI, but the classification accuracy mainly depends on the training label samples. Therefore, the stacked convolutional autoencoder network and transfer learning strategy are employed in order to design a new stacked convolutional autoencoder network model transfer (SCAE-MT) for the purposes of classifying the HRSI in this paper. In the proposed classification method, the stacked convolutional au-to-encoding network is employed in order to effectively extract the deep features from the HRSI. Then, the transfer learning strategy is applied to design a stacked convolutional autoencoder network model transfer under the small and limited training samples. The SCAE-MT model is used to propose a new HRSI classification method in order to solve the small samples of the HRSI. In this study, in order to prove the effectiveness of the proposed classification method, two HRSI datasets were chosen. In order to verify the effectiveness of the methods, the overall classification accuracy (OA) of the convolutional self-coding network classification method (CAE), the stack convolutional self-coding network classification method (SCAE), and the SCAE-MT method under 5%, 10%, and 15% training sets are calculated. When compared with the CAE and SCAE models in 5%, 10%, and 15% training datasets, the overall accuracy (OA) of the SCAE-MT method was improved by 2.71%, 3.33%, and 3.07% (on average), respectively. The SCAE-MT method is, thus, clearly superior to the other methods and also shows a good classification performance.

DocR-BERT: Document-Level R-BERT for Chemical-Induced Disease Relation Extraction via Gaussian Probability Distribution.

Chemical-induced disease (CID) relation extraction from biomedical articles plays an important role in disease treatment and drug development. Existing methods are insufficient for capturing complete document level semantic information due to ignoring semantic information of entities in different sentences. In this work, we proposed an effective document-level relation extraction model to automatically extract intra-/inter-sentential CID relations from articles. Firstly, our model employed BERT to generate contextual semantic representations of the title, abstract and shortest dependency paths (SDPs). Secondly, to enhance the semantic representation of the whole document, cross attention with self-attention (named cross2self-attention) between abstract, title and SDPs was proposed to learn the mutual semantic information. Thirdly, to distinguish the importance of the target entity in different sentences, the Gaussian probability distribution was utilized to compute the weights of the co-occurrence sentence and its adjacent entity sentences. More complete semantic information of the target entity is collected from all entities occurring in the document via our presented document-level R-BERT (DocR-BERT). Finally, the related representations were concatenated and fed into the softmax function to extract CIDs. We evaluated the model on the CDR corpus provided by BioCreative V. The proposed model without external resources is superior in performance as compared with other state-of-the-art models (our model achieves 53.5%, 70%, and 63.7% of the F1-score on inter-/intra-sentential and overall CDR dataset). The experimental results indicate that cross2self-attention, the Gaussian probability distribution and DocR-BERT can effectively improve the CID extraction performance. Furthermore, the mutual semantic information learned by the cross self-attention from abstract towards title can significantly influence the extraction performance of document-level biomedical relation extraction tasks.

Pathophysiological roles of autophagy and aldo-keto reductases in development of doxorubicin resistance in gastrointestinal cancer cells.

Here, we show that incubation of three human gastrointestinal cancer cell lines (HCT15, LoVo and MKN45) with doxorubicin (DOX) provokes autophagy through facilitating production of reactive oxygen species (ROS). HCT15 cell treatment with DOX resulted in up-regulation of Beclin1, down-regulation of Bcl2, activation of AMPK and JNK, and Akt inactivation, all of which were restored by pretreating with an antioxidant N-acetyl-l-cysteine. These data suggest that all the autophagy-related alterations evoked by DOX result from the ROS production. In the DOX-resistant cancer cells, degree of autophagy elicited by DOX was milder than the parental cells, and DOX treatment hardly activated the ROS-dependent apoptotic signals [formation of 4-hydroxy-2-nonenal (HNE), cytochrome-c release into cytosol, and activation of JNK and caspase-3], inferring an inverse correlation between cellular antioxidant capacity and autophagy induction by DOX. Monitoring of expression levels of aldo-keto reductases (AKRs) in the parental and DOX-resistant cells revealed an up-regulation of AKR1B10 and/or AKR1C3 with acquiring the DOX resistance. Knockdown and inhibition of AKR1B10 or AKR1C3 in these cells enhanced DOX-elicited autophagy. Measurement of DOX-reductase activity and HNE-sensitivity assay also suggested that both AKR1B10 (via high HNE-reductase activity) and AKR1C3 (via low HNE-reductase and DOX-reductase activities) are involved in the development of DOX resistance. Combination of inhibitors of autophagy and the two AKRs overcame DOX resistance and cross-resistance of gastrointestinal cancer cells with resistance development to DOX or cis-diamminedichloroplatinum. Therefore, concomitant treatment with the inhibitors may be effective as an adjuvant therapy for elevating DOX sensitivity of gastrointestinal cancer cells.

Cullin-4B E3 ubiquitin ligase mediates Apaf-1 ubiquitination to regulate caspase-9 activity.

Apoptotic protease-activating factor 1 (Apaf-1) is a component of apoptosome, which regulates caspase-9 activity. In addition to apoptosis, Apaf-1 plays critical roles in the intra-S-phase checkpoint; therefore, impaired expression of Apaf-1 has been demonstrated in chemotherapy-resistant malignant melanoma and nuclear translocation of Apaf-1 has represented a favorable prognosis of patients with non-small cell lung cancer. In contrast, increased levels of Apaf-1 protein are observed in the brain in Huntington's disease. The regulation of Apaf-1 protein is not yet fully understood. In this study, we show that etoposide triggers the interaction of Apaf-1 with Cullin-4B, resulting in enhanced Apaf-1 ubiquitination. Ubiquitinated Apaf-1, which was degraded in healthy cells, binds p62 and forms aggregates in the cytosol. This complex of ubiquitinated Apaf-1 and p62 induces caspase-9 activation following MG132 treatment of HEK293T cells that stably express bcl-xl. These results show that ubiquitinated Apaf-1 may activate caspase-9 under conditions of proteasome impairment.

Expanded polyglutamine embedded in the endoplasmic reticulum causes membrane distortion and coincides with Bax insertion.

The endoplasmic reticulum (ER) is important in various cellular functions, such as secretary and membrane protein biosynthesis, lipid synthesis, and calcium storage. ER stress, including membrane distortion, is associated with many diseases such as Huntington's disease. In particular, nuclear envelope distortion is related to neuronal cell death associated with polyglutamine. However, the mechanism by which polyglutamine causes ER membrane distortion remains unclear. We used electron microscopy, fluorescence protease protection assay, and alkaline treatment to analyze the localization of polyglutamine in cells. We characterized polyglutamine embedded in the ER membrane and noted an effect on morphology, including the dilation of ER luminal space and elongation of ER-mitochondria contact sites, in addition to the distortion of the nuclear envelope. The polyglutamine embedded in the ER membrane was observed at the same time as Bax insertion. These results demonstrated that the ER membrane may be a target of polyglutamine, which triggers cell death through Bax.

Mastication as a Stress-Coping Behavior.

Exposure to chronic stress induces various physical and mental effects that may ultimately lead to disease. Stress-related disease has become a global health problem. Mastication (chewing) is an effective behavior for coping with stress, likely due to the alterations chewing causes in the activity of the hypothalamic-pituitary-adrenal axis and autonomic nervous system. Mastication under stressful conditions attenuates stress-induced increases in plasma corticosterone and catecholamines, as well as the expression of stress-related substances, such as neurotrophic factors and nitric oxide. Further, chewing reduces stress-induced changes in central nervous system morphology, especially in the hippocampus and hypothalamus. In rodents, chewing or biting on wooden sticks during exposure to various stressors reduces stress-induced gastric ulcer formation and attenuates spatial cognitive dysfunction, anxiety-like behavior, and bone loss. In humans, some studies demonstrate that chewing gum during exposure to stress decreases plasma and salivary cortisol levels and reduces mental stress, although other studies report no such effect. Here, we discuss the neuronal mechanisms that underline the interactions between masticatory function and stress-coping behaviors in animals and humans.

Chewing Maintains Hippocampus-Dependent Cognitive Function.

Mastication (chewing) is important not only for food intake, but also for preserving and promoting the general health. Recent studies have showed that mastication helps to maintain cognitive functions in the hippocampus, a central nervous system region vital for spatial memory and learning. The purpose of this paper is to review the recent progress of the association between mastication and the hippocampus-dependent cognitive function. There are multiple neural circuits connecting the masticatory organs and the hippocampus. Both animal and human studies indicated that cognitive functioning is influenced by mastication. Masticatory dysfunction is associated with the hippocampal morphological impairments and the hippocampus-dependent spatial memory deficits, especially in elderly. Mastication is an effective behavior for maintaining the hippocampus-dependent cognitive performance, which deteriorates with aging. Therefore, chewing may represent a useful approach in preserving and promoting the hippocampus-dependent cognitive function in older people. We also discussed several possible mechanisms involved in the interaction between mastication and the hippocampal neurogenesis and the future directions for this unique fascinating research.

Tooth loss early in life accelerates age-related bone deterioration in mice.

Both osteoporosis and tooth loss are health concerns that affect many older people. Osteoporosis is a common skeletal disease of the elderly, characterized by low bone mass and microstructural deterioration of bone tissue. Chronic mild stress is a risk factor for osteoporosis. Many studies showed that tooth loss induced neurological alterations through activation of a stress hormone, corticosterone, in mice. In this study, we tested the hypothesis that tooth loss early in life may accelerate age-related bone deterioration using a mouse model. Male senescence-accelerated mouse strain P8 (SAMP8) mice were randomly divided into control and toothless groups. Removal of the upper molar teeth was performed at one month of age. Bone response was evaluated at 2, 5 and 9 months of age. Tooth loss early in life caused a significant increase in circulating corticosterone level with age. Osteoblast bone formation was suppressed and osteoclast bone resorption was activated in the toothless mice. Trabecular bone volume fraction of the vertebra and femur was decreased in the toothless mice with age. The bone quality was reduced in the toothless mice at 5 and 9 months of age, compared with the age-matched control mice. These findings indicate that tooth loss early in life impairs the dynamic homeostasis of the bone formation and bone resorption, leading to reduced bone strength with age. Long-term tooth loss may have a cumulative detrimental effect on bone health. It is important to take appropriate measures to treat tooth loss in older people for preventing and/or treating senile osteoporosis.

The osteocyte plays multiple roles in bone remodeling and mineral homeostasis.

Osteocytes are the most abundant cells in bone and are the major orchestrators of bone remodeling and mineral homeostasis. They possess a specialized cellular morphology and a unique molecular feature. Osteocytes are a stellate shape with numerous long, slender dendritic processes. The osteocyte cell body resides in the bone matrix of the lacuna and the dendritic processes extend within the canaliculi to adjacent osteocytes and other cells on the bone surface. Osteocytes form extensive intercellular network to sense and respond to environmental mechanical stimulus by the lacunar-canalicular system and gap junction. Osteocytes are long-lived bone cells. They can undergo apoptosis, which may have specific regulatory effects on osteoclastic bone resorption. Osteocytes can secrete several molecules, including sclerostin, receptor activator of nuclear factor κB ligand and fibroblast growth factor 23 to regulate osteoblastic bone formation, osteoclastic bone resorption and mineral homeostasis. A deeper understanding of the complex mechanisms that mediate the control of osteoblast and osteoclast function by osteocytes may identify new osteocyte-derived molecules as potential pharmacological targets for treating osteoporosis and other skeletal diseases.

Protective roles of aldo-keto reductase 1B10 and autophagy against toxicity induced by p-quinone metabolites of tert-butylhydroquinone in lung cancer A549 cells.

tert-Butylhydroquinone (BHQ), an antioxidant used as a food additive, exhibits an anticancer effect at low doses, but is carcinogenic in rodents at high doses. BHQ is metabolized into cytotoxic tert-butylquinone (TBQ), which is further converted to 6-tert-butyl-2,3-epoxy-4-hydroxy-5-cyclohexen-1-one (TBEH) through 6-tert-butyl-2,3-epoxy-4-benzoquinone (TBE). Both TBQ and TBE are cytotoxic, but their toxic mechanisms have not been fully characterized. In this study, we have investigated the toxic mechanisms of TBQ and TBE, and the defense system against the two p-quinones using lung cancer A549 cells. TBQ and TBE, but not BHQ and TBEH, showed cytotoxicity to A549 cells. Neither caspase-3 activation nor an increase in the expression of endoplasmic reticulum stress-associating target genes was observed. TBQ and TBE reacted with reduced glutathione, and significantly decreased the glutathione level in A549 cells, suggesting that the cytotoxicity of the p-quinones is caused by their high electrophilicity reacting with biomolecules. The A549 cells treated with the p-quinones also showed increased levels of autophagic vacuoles and LC3-II protein, which are specific autophagy markers. An autophagy inhibitor, 3-methyladenine (3MA), decreased the LC3-II production by the p-quinones, but enhanced the cytotoxicity induced by TBQ and TBE, suggesting that autophagy contributes to alleviating the p-quinone-triggered cytotoxicity. In addition, the TBE-induced cytotoxicity and autophagy activation in the cells were significantly suppressed by overexpression of aldo-keto reductase (AKR)1B10 that efficiently reduces TBE into TBEH, and were augmented by pretreatment with a potent AKR1B10 inhibitor, C1. The effects of 3MA and C1 on the TBE-induced cytotoxicity were additive. The data provides evidence for the first time that autophagy and AKR1B10 contribute to the defense system against the cytotoxicity caused by the electrophilic p-quinone metabolites of BHQ.

Bone three-dimensional microstructural features of the common osteoporotic fracture sites.

Osteoporosis is a common metabolic skeletal disorder characterized by decreased bone mass and deteriorated bone structure, leading to increased susceptibility to fractures. With aging population, osteoporotic fractures are of global health and socioeconomic importance. The three-dimensional microstructural information of the common osteoporosis-related fracture sites, including vertebra, femoral neck and distal radius, is a key for fully understanding osteoporosis pathogenesis and predicting the fracture risk. Low vertebral bone mineral density (BMD) is correlated with increased fracture of the spine. Vertebral BMD decreases from cervical to lumbar spine, with the lowest BMD at the third lumbar vertebra. Trabecular bone mass of the vertebrae is much lower than that of the peripheral bone. Cancellous bone of the vertebral body has a complex heterogeneous three-dimensional microstructure, with lower bone volume in the central and anterior superior regions. Trabecular bone quality is a key element to maintain the vertebral strength. The increased fragility of osteoporotic femoral neck is attributed to low cancellous bone volume and high compact porosity. Compared with age-matched controls, increased cortical porosity is observed at the femoral neck in osteoporotic fracture patients. Distal radius demonstrates spatial inhomogeneous characteristic in cortical microstructure. The medial region of the distal radius displays the highest cortical porosity compared with the lateral, anterior and posterior regions. Bone strength of the distal radius is mainly determined by cortical porosity, which deteriorates with advancing age.

Diabetes mellitus aggravates hemorrhagic transformation after ischemic stroke via mitochondrial defects leading to endothelial apoptosis.

Diabetes is a crucial risk factor for stroke and is associated with increased frequency and poor prognosis. Although endothelial dysfunction is a known contributor of stroke, the underlying mechanisms have not been elucidated. The aim of this study was to elucidate the mechanism by which chronic hyperglycemia may contribute to the worsened prognosis following stroke, especially focusing on mitochondrial alterations. We examined the effect of hyperglycemia on hemorrhagic transformation at 24 hours after middle cerebral artery occlusion (MCAO) in streptozotocin (STZ) -induced diabetic mice. We also examined the effects of high-glucose exposure for 6 days on cell death, mitochondrial functions and morphology in human brain microvascular endothelial cells (HBMVECs) or human endothelial cells derived from induced pluripotent stem cells (iCell endothelial cells). Hyperglycemia aggravated hemorrhagic transformation, but not infarction following stroke. High-glucose exposure increased apoptosis, capase-3 activity, and release of apoptosis inducing factor (AIF) and cytochrome c in HBMVECs as well as affected mitochondrial functions (decreased cell proliferation, ATP contents, mitochondrial membrane potential, and increased matrix metalloproteinase (MMP)-9 activity, but not reactive oxygen species production). Furthermore, morphological aberration of mitochondria was observed in diabetic cells (a great deal of fragmentation, vacuolation, and cristae disruption). A similar phenomena were seen also in iCell endothelial cells. In conclusion, chronic hyperglycemia aggravated hemorrhagic transformation after stroke through mitochondrial dysfunction and morphological alteration, partially via MMP-9 activation, leading to caspase-dependent apoptosis of endothelial cells of diabetic mice. Mitochondria-targeting therapy may be a clinically innovative therapeutic strategy for diabetic complications in the future.

Morphology of the lingual papillae in the fishing cat.

We examined the dorsal lingual surface of an adult fishing cat (Prionailurus viverrinus) by scanning electron microscopy. The filiform papillae on the lingual apex had several pointed processes. The connective tissue core of the filiform papillae resembleda a well in shape. The filiform papillae on the anterior part of the lingual body were large and cylindrical in shape. The connective tissue core of the filiform papillae consisted of a large conical papilla. The filiform papillae on the central part of the lingual body were large and conical. The connective tissue core of the filiform papillae consisted of a large main process and some secondary processes. The connective tissue core of the fungiform papillae did not have processes. The vallate papillae were surrounded by a groove and a pad. The top of the connective tissue core of the vallate papillae had a rough surface with no spines.

Morphology of the lingual papillae in the brush-tailed rat kangaroo.

We examined the dorsal lingual surface of an adult brush-tailed rat kangaroo (Bettongia penicillata) by scanning electron microscopy. The filiform and fungiform papillae on the lingual apex and body consisted of a main papilla and secondary papillae. The connective tissue core of the filiform papillae on the lingual apex was cylindrical in shape with a crushed top. The connective tissue core of the filiform papillae on the lingual body had one large and several small processes. The fungiform papillae were round in shape. The connective tissue core of the fungiform papillae had several depressions on its top. The surface of the vallate papillae was rough and the papillae were surrounded by a groove and a pad. Several long conical papillae derived from the posterolateral margin of the tongue where foliate papillae have been shown to be distributed in many other animal species. The long conical papillae were very similar to those of the koala and opossum.

Chewing ameliorates chronic mild stress-induced bone loss in senescence-accelerated mouse (SAMP8), a murine model of senile osteoporosis.

Chronic mild stress is a risk factor for osteoporosis and chewing inhibits the stress response. We examined the effect of chewing on chronic stress-induced bone loss and bone microstructural deterioration in mice. The senescence-accelerated mouse strain P8 (SAMP8) was randomly divided into control, stress, and stress with chewing groups of fifteen animals each. Mice in the stress and stress with chewing groups were placed in a ventilated restraint tube for 60minutes, twice a day for 4weeks. The restrained mice were simultaneously subjected daily to one of the following stressors: water immersion, physical shaking and flashing lights. Mice in the stress with chewing group were allowed to chew a wooden stick during the experimental period. After the experiment, the bone response was evaluated using quantitative micro computed tomography, bone histomorphometry, and biochemical markers. Exposure of SAMP8 mice to chronic stress resulted in significant increase of the blood corticosterone and noradrenaline levels, and adrenal weight. The bone resorption was activated and the bone formation was suppressed. Trabecular bone volume and trabecular number were decreased in both the vertebra and distal femur of the stress group. Chewing under chronic stress prevented the increase in the blood corticosterone and noradrenaline levels, attenuated the reduced bone formation and increased bone resorption, improved the trabecular bone loss and bone microstructural deterioration induced by chronic mild stress. These findings indicate that chewing can ameliorate chronic stress-induced bone loss in SAMP8 mice. Thus, chewing may represent a useful method preventing and/or treating chronic stress-related osteoporosis.