Search

ACLF (Acute on chronic liver failure) is a systemic inflammatory disease. PANoptosis is a newly discovered regulated cell death (RCD) that occurs in the infectious and inflammatory diseases. The purpose of this study is to investigate the presence of PANoptosis in liver failure. We selected articles from PubMed and Web of Science databases to collect data from these articles through bibliometrics, data mining, and other methods, and then integrated and analyzed these data. Then, we used the public dataset (GSE139602) to obtain central differentially expressed genes (DEGs) to perform various bioinformatics analyses to predict the potential biological mechanism of ACLF. Finally, we conducted experiment validation in a model of ACLF with rats. We found that in the same cell model or animal disease model of liver failure, three types of RDC can occur simultaneously. Enrichment analysis showed that RDC and immune signaling pathways are important pathways in ACLF, and DEGs are mainly involved in immune and inflammatory responses, biosynthesis, and metabolic pathways. The vivo experiments in rats have shown that a large release of inflammatory factors and the key proteins of PANoptosis were all detected separately in the ACLF rats. Those data support the existence of PANoptosis in ACLF.

The cytosol-facing outer membrane (OM) of organelles communicates with other cellular compartments to exchange proteins, metabolites and signaling molecules. Cellular surveillance systems also target OM-resident proteins to control organellar homeostasis and ensure cell survival under stress. Using traditional approaches to discover OM proteins and identify their dynamically interacting partners remains challenging. In this study, we developed an OM proximity labeling (OMPL) system using biotin ligase-mediated proximity biotinylation to map the proximity proteome of the OMs of mitochondria, chloroplasts, and peroxisomes in living Arabidopsis (Arabidopsis thaliana) cells. We demonstrate the power of this system with the discovery of cytosolic factors and OM receptor candidates involved in local protein translation and translocation, membrane contact sites, and organelle quality control. This system also performed admirably for the rapid isolation of intact mitochondria and peroxisomes. Our data support the notion that TOM20-3 is a candidate for both a mitochondrial and a chloroplast receptor, and that PEX11D is a candidate for a peroxisome receptor for the coupling of protein translation and import. OMPL-generated OM proximity proteomes are valuable sources of candidates for functional validation and suggest directions for further investigation of important questions in cell biology.

Agrimonia pilosa Ledeb., which belongs to Agrimonia and Rosaceae, is used in traditional Chinese medicine. It exhibits excellent medicinal properties and has been used to treat various diseases, such as tumors, trichomoniasis, vaginitis, diarrhea, and dysentery. Phytochemical studies have revealed that Agrimonia has over 100 secondary metabolites that can be categorized into six classes, i.e., flavonoids, isocoumarins, triterpenes, phloroglucinol derivatives, tannins, and organic acids. This review summarizes recently published literature on the chemical structures of 90 bioactive compounds that have been identified in A. pilosa and examines their pharmacological properties, including their antitumor, anti-inflammatory, antioxidant, antibacterial, and antidiabetic properties, as well as the potential development of parasitic resistance to these chemicals. This review highlights existing knowledge gap and serves as a basis for developing novel preparations of A. pilosa with medicinal value.

With the rapid development of information technology, the society’s demand for innovative talents has become increasingly prominent. The purpose of this study is to optimize the teaching strategies of entrepreneurship education for college students, further cultivate college students’ entrepreneurial ideas, and promote the formation of entrepreneurial values. The problems existing in entrepreneurship education in colleges and universities are studied based on entrepreneurial psychology and attribution theory. A questionnaire survey is conducted on the problems with a high probability of entrepreneurial failure of college students. The heads of new ventures in Xi’an are selected. Then, 300 questionnaires are distributed, and 209 are returned. The survey results are analyzed using failure attribution and failure learning. Suggestions are provided for management strategies of new ventures. The results show that the Corrected Item-Total Correlation (CITC) value of R−1 is 0.65, and the CITC value of R−2 is 0.35. In addition, the Kaiser-Meyer-Olkin (KMO) values of entrepreneurial failure attribution and entrepreneurial failure mode are both greater than 0.7, which indicates that the scale of entrepreneurial failure attribution has good validity and can be used for factor analysis. However, the KMO values of entrepreneurial failure attribution and entrepreneurial failure learning model are both greater than 0.7, and the significance of Bartlett sphericity test is 0.00, which indicates that the survey has good validity. The research has practical application and reference value for the cultivation of college students’ innovative and entrepreneurial ability.

Mitochondrial Ca2+ (mtCa2+) homeostasis is essential to mitochondrial functions. However, how mtCa2+ homeostasis is achieved and the consequences of impaired mtCa2+ homeostasis in plants is poorly understood. Here, we demonstrate a critical role for mitochondrial Ca2+ uniporter (MCU) in the control of mtCa2+ uptake for mtCa2+ homeostasis in planta by characterizing MCU mutants and overexpressed plants. Impaired MCU-controlled mtCa2+ homeostasis (iMUCH) in gain-of-function and loss-of-function MCU plants causes the misregulation of mitochondrial gene expression that triggers mitonuclear protein imbalance. Transcriptome integrated with proteomics analysis reveal activation of multiple compartmental UPR gene expression and decrease of cytosolic translation with selective repression of ribosome and RNA modification protein synthesis upon iMUCH. Intriguingly, TOR signalling is not involved in cytosolic translational response to iMUCH, but the reduction of eIFα phosphorylation is evident under iMUCH induced mitochondrial stress. Thus, our study unveils the essential functions of MCU proteins for mtCa2+ homeostasis, and the involvement of MCU-controlled mtCa2+ homeostasis in mitochondrial stress dependent regulation of protein synthesis for cellular proteostasis that is connected to plant growth and stress resistance.

Mitochondria produce signals besides energy and metabolites that influence plant growth and fitness. However, how mitochondrial signals are relayed to other cellular compartments is largely unknown. By applying poly(A)-site RNA-sequencing (PAS-seq) to wildtype Arabidopsis seedlings and a mutant in the histone demethylase JMJ30 treated with the mitochondrial electron transfer chain inhibitor antimycin A (AA), we identified a previously undefined mitochondrion-to-nucleus communication pathway by which mitochondrial functional state regulates co-transcriptionally alternative polyadenylation (APA) of nuclear mRNA. We observed a global shortening of 3′ untranslated regions (UTRs) as a molecular signature of AA-activated mitochondrial retrograde response (MRR), which contributed in part to translational regulation of auxin response and cell wall biogenesis. JMJ30 regulated AA-induced 3′ UTR shortening, resulting in more transcripts with shortened 3′ UTRs upon AA treatment in a JMJ30 gain-of-function mutant and overexpression lines. We also report on the JMJ30-interacting protein CPSF30, a cleavage and polyadenylation specificity factor that recruits JMJ30 to modulate H3K27me3 status at its target loci. Our study illustrates how epigenetic modification and APA coordinate mitochondrion-to-nucleus communication to allow cells to rapidly respond to changes in mitochondrial functional state and shape plant growth and fitness.One-sentence summaryEpigenetic modification and APA coordinate mitochondrion-to-nucleus communication to allow cells to rapidly respond to changes in mitochondrial functional state and shape plant growth and fitness.

Nonalcoholic fatty liver disease (NAFLD) has become a major public health issue as its progression increases risks of multisystem morbidity and mortality. Recent evidence indicates a more complex relationship between hypertension and NAFLD than previously thought. In this study, a comprehensive literature search was used to gather information supporting the comorbidity phenomenon of hypertension and NAFLD. Then, systems biology approach was applied to identify the potential genes and mechanisms simultaneously associated with hypertension and NAFLD. With the help of protein-protein interaction network-based algorithm, we found that the distance between hypertension and NAFLD was much less than random ones. Sixty-four shared genes of hypertension and NAFLD modules were identified as core genes. Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analysis indicated that some inflammatory, metabolic and endocrine signals were related to the potential biological functions of core genes. More importantly, drugs used to treat cardiovascular diseases, hypertension, hyperlipidemia, inflammatory diseases and depression could be potential therapeutics against hypertension-NAFLD co-occurrence. After analyzing public OMICs data, ALDH1A1 was identified as a potential therapeutic target, without being affected by reverse causality. These findings give a clue for the potential mechanisms of comorbidity of hypertension and NAFLD and highlight the multiple target-therapeutic strategy of NAFLD for future clinical research., Graphical Abstract

With the surge of images in the information era, people demand an effective and accurate way to access meaningful visual information. Accordingly, effective and accurate communication of information has become indispensable. In this article, we propose a content-based approach that automatically generates a clear and informative visual summarization based on design principles and cognitive psychology to represent image collections. We first introduce a novel method to make representative and nonredundant summarizations of image collections, thereby ensuring data cleanliness and emphasizing important information. Then, we propose a tree-based algorithm with a two-step optimization strategy to generate the final layout that operates as follows: (1) an initial layout is created by constructing a tree randomly based on the grouping results of the input image set; (2) the layout is refined through a coarse adjustment in a greedy manner, followed by gradient back propagation drawing on the training procedure of neural networks. We demonstrate the usefulness and effectiveness of our method via extensive experimental results and user studies. Our visual summarization algorithm can precisely and efficiently capture the main content of image collections better than alternative methods or commercial tools.

Tongxinluo (TXL) is one of the most common traditional Chinese medicines and plays a vital role in treating atherosclerosis (AS). Endothelial cell (EC) pyroptosis plays a crucial role in the development of AS. Previous research revealed the inhibitory function of TXL in EC apoptosis and autophagy. However, whether TXL can inhibit the pyroptosis of ECs has not been determined.To explore the influence of TXL on EC pyroptosis and determine its underlying mechanism of action in AS.The TXL components were determined by ultra-performance liquid chromatography coupled with a photodiode array detector. We used ApoETen major components of TXL were detected. The vivo results showed that TXL inhibited the development of AS and decreased EC pyroptosis, the activation of caspase-1, and the release of inflammatory cytokines. The vitro experiments showed that TXL significantly reduced the extent of injury to MAECs by oxidized LDL (ox-LDL). TXL reversed the high expression of gasdermin D and other proteins induced by ox-LDL and had a significant synergistic effect with the caspase-1 inhibitor VX-765. We also confirmed that TXL decreased the accumulation of ROS and the expression levels of its essential regulatory proteins Cox2 and iNOS. When ROS accumulation was reduced, EC pyroptotic damage was reduced accordingly.Our results indicated that TXL inhibited EC pyroptosis in AS. Reducing the accumulation of ROS may be the essential mechanism of AS inhibition by TXL.

Art painting evaluation is sophisticated for a novice with no or limited knowledge on art criticism, and history. In this study, we propose the concept of representativity to evaluate paintings instead of using professional concepts, such as genre, media, and style, which may be confusing to non-professionals. We define the concept of representativity to evaluate quantitatively the extent to which a painting can represent the characteristics of an artists creations. We begin by proposing a novel deep representation of art paintings, which is enhanced by style information through a weighted pooling feature fusion module. In contrast to existing feature extraction approaches, the proposed framework embeds painting styles, and authorship information, and learns specific artwork characteristics in a single framework. Subsequently, we propose a graph-based learning method for representativity learning, which considers intra-category, and extra-category information. In view of the significance of historical factors in the art domain, we introduce the creation time of a painting into the learning process. User studies demonstrate our approach helps the public effectively access the creation characteristics of artists through sorting paintings by representativity from highest to lowest.

Background. Acute-on-chronic liver failure (ACLF) is a clinical syndrome with acute jaundice and coagulation dysfunction caused by various inducements on the basis of chronic liver disease. Western medical treatment is limited. Previous studies have confirmed that Jieduan-Niwan Formula (JDNW Formula), an empirical prescription for the treatment of ACLF, can inhibit inflammation and resist hepatocyte apoptosis. However, potential targets and mechanisms still need to be explored. Methods. In this study, network pharmacological analysis was performed to investigate the key components and potential mechanisms of JDNW Formula treating ACLF. Firstly, we predicted the potential active ingredients of JDNW Formula and the corresponding potential targets through TCMSP, BATMAN-TCM platform, and literature supplement. Then, the ACLF targets database was built using OMIM, DisGeNET, and GeneCard database. Based on the matching targets between JDNW Formula and ACLF, the PPI network was constructed for MCODE analysis and common targets were enriched by Metascape. Furthermore, the ACLF rat model was used to verify the potential mechanism of JDNW Formula in treating ACLF. Results. 132 potential bioactive components of JDNW Formula and 168 common targets were obtained in this study. The enrichment analysis shows that the AMPK signaling pathway was associated with the treating effects of JDNW Formula. Quercetin was hypothesized to be the key bioactive ingredient in JDNW Formula and has a good binding affinity to AMPK based on molecular docking verification. JDNW Formula and quercetin were verified to treat ACLF by regulating the AMPK/PGC-1α signaling pathway as a prediction. Conclusion. The study predicted potential mechanisms of JDNW Formula in the treatment of ACLF, involving downregulation of inflammatory factor expression, antioxidant stress, and inhibition of hepatocyte apoptosis. JDNW Formula may improve mitochondrial quality in ACLF via the AMPK signaling pathway, which serves as a guide for further study.

There is yet no effective drug for Alzheimer’s disease (AD) which is one of the world’s most common neurodegenerative diseases. The Qin-Zhi-Zhu-Dan Formula (QZZD) is derived from a widely used Chinese patent drug–Qing-Kai-Ling Injection. It consists of Radix Scutellariae, Fructus Gardeniae, and Pulvis Fellis Suis. Recent study showed that QZZD and its effective components played important roles in anti-inflammation, antioxidative stress and preventing brain injury. It was noted that QZZD had protective effects on the brain, but the mechanism remained unclear. This study aims to investigate the mechanism of QZZD in the treatment of AD combining network pharmacology approach with experimental validation. In the network pharmacology analysis, a total of 15 active compounds of QZZD and 135 putative targets against AD were first obtained. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were then applied to clarify the biological mechanism. The anti-inflammatory mechanism of QZZD was proved, and a synthetic pathway–TNFR1-ERK1/2-NF-κBp65 signaling pathway was obtained. On the basis of the above discoveries, we further validated the protective effects QZZD on neurons with an APP/PS1 double transgenic mouse model. Weight change of the mice was monitored to assess QZZD’s influence on the digestive system; water maze experiment was used for evaluating the effects on spatial learning and memory; Western blotting and immunohistochemistry analysis were used to detect the predicted key proteins in network pharmacology analysis, including Aβ, IL-6, NF-κBp65, TNFR1, p-ERK1/2, and ERK1/2. We proved that QZZD could improve neuroinflammation and attenuate neuronal death without influencing the digestive system in APP/PS1 double transgenic mice with dementia. Combining animal pharmacodynamic experiments with network pharmacology analysis, we confirmed the importance of inflammation in pathogenesis of AD, clarified the pharmacodynamic characteristics of QZZD in treating AD, and proved its neuroprotective effects through the regulation of TNFR1-ERK1/2-NF-κBp65 signaling pathway, which might provide reference for studies on treatment of AD in the future.

Jieduan-Niwan (JDNW) formula is a traditional Chinese medicine compound created by the famous Chinese medicine expert Professor Qian Ying, and has been used clinically for decades to treat acute-on-chronic liver failure (ACLF) and exhibits remarkable efficacy. However, the exact mechanism remains to be discovered. As an important hepatocyte damage-associated molecular patterns (DAMP) factor, high mobility group box 1 (HMGB1) is a potential therapeutic target as an accelerator of ACLF in the pathogenesis. Therefore, the present study investigated whether JDNW inhibits the overexpression and cytoplasmic translocation of HMGB1 in ACLF liver tissue and alleviates its mediated oxidative stress and apoptosis. In vivo, an immune-induced ACLF rat model was established, and then treated with JDNW for 5, 10, and 15 d. The results showed that a large number of cytoplasmic translocations of HMGB1 occurred in the ACLF group. And there was an increase in the expression of HMGB1 in the M-5 d group. After the intervention of JDNW, the overexpression and translocation of HMGB1 were inhibited. In vitro, D-GaLN caused an increase in the expression and translocation of HMGB1 in L02 cells. Similar to the inhibitor of HMGB1, JDNW serum alleviated this kind of increase. Further tests showed that JDNW attenuated ACLF-related oxidative stress and apoptosis, and the inhibition was associated with the regulation of TLR-4/NF

Distinguishing aesthetically pleasing food photos from others is an important visual analysis task for social media and ranking systems related to food. Nevertheless, aesthetic assessment of food images remains a challenging and relatively unexplored task, largely due to the lack of related food image datasets and practical knowledge. Thus, we present the Gourmet Photography Dataset (GPD), the first large-scale dataset for aesthetic assessment of food photos. It contains 24,000 images with corresponding binary aesthetic labels, covering a large variety of foods and scenes. We also provide a non-stationary regularization method to combat over-fitting and enhance the ability of tuned models to generalize. Quantitative results from extensive experiments, including a generalization ability test, verify that neural networks trained on the GPD achieve comparable performance to human experts on the task of aesthetic assessment. We reveal several valuable findings to support further research and applications related to visual aesthetic analysis of food images. To encourage further research, we have made the GPD publicly available at https://github.com/Openning07/GPA.

Weixin Hou,1– 4 Xiaoyi Wei,1,2 Jiajun Liang,1– 4 Peng Fang,5 Chongyang Ma,1,2 Qiuyun Zhang,1,2,* Yanbin Gao3,4,* 1Department of Hepatology, School of Traditional Chinese Medicine, Capital Medical University, Beijing, People’s Republic of China; 2Department of Hepatology, Beijing Key Laboratory of Traditional Chinese Medicine Collateral Disease Theory Research, Capital Medical University, Beijing, People’s Republic of China; 3Department of Endocrinology, School of Traditional Chinese Medicine, Capital Medical University, Beijing, People’s Republic of China; 4Department of Endocrinology, Beijing Key Laboratory of Traditional Chinese Medicine Collateral Disease Theory Research, Capital Medical University, Beijing, People’s Republic of China; 5Department of Infectious Diseases, First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qiuyun Zhang; Yanbin GaoSchool of Traditional Chinese Medicine, Capital Medical University, No. 10 You An Men Wai, Xi Tou Tiao, Feng Tai District, Beijing, 100069, People’s Republic of ChinaTel +86 10 8391 1638; +86 10 8391 1720Email 19970059@ccmu.edu.cn; gyb@ccmu.edu.cnBackground: Acute-on-chronic liver failure (ACLF) is a critical disease with a high fatality rate. Immune dysfunction and inflammatory responses are key risk factors in ACLF. Pyroptosis is a form of programmed cell death characterized by the release of inflammatory cytokines, which causes the strong inflammatory responses. High mobility group box-1 (HMGB1) could induce pyroptosis and is closely related to ACLF. However, the role of HMGB1-induced hepatocyte pyroptosis in ACLF has never been proposed; whether HMGB1-induced hepatocyte pyroptosis participates in the development of ACLF and the mechanisms involved are barely understood.Purpose: This study aimed to clarify the roles of HMGB1-induced hepatocyte pyroptosis in ACLF and the molecular mechanisms involved.Methods: Wistar rats were randomly divided into five groups, viz.: Normal, ACLF model, HMGB1 inhibitor, Caspase-1 inhibitor, and HMGB1 inhibitor+Caspase-1 inhibitor groups. The ACLF rat model was established using 40% carbon tetrachloride-induced liver fibrosis, followed by D-galactosamine and lipopolysaccharide joint acute attacks. The liver function, coagulation function and pathological damage of rats in each group were evaluated. The biological mechanisms of HMGB1-induced pyroptosis and the release of inflammatory cytokines were investigated using Western blot, quantitative real-time PCR (RT-qPCR), immunofluorescence, enzyme-linked immunosorbent assay (ELISA), and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay.Results: The liver function and coagulation function of ACLF rats were seriously impaired; liver tissue showed massive or submassive necrosis, accompanied by inflammatory cell infiltration; the percentage of pyroptotic hepatocytes significantly increased, and a large number of inflammatory cytokines were released. The expression levels of pyroptosis-related genes and proteins in liver tissues and serum significantly increased. But these phenomenons were improved by the inhibition of HMGB1, and the dual inhibition of HMGB1 and Caspase-1 showed a stronger effect.Conclusion: The findings indicate, for the first time, that pyroptosis is a crucial pathophysiological event of ACLF involved in its pathogenesis, and HMGB1-induced hepatocyte pyroptosis expands inflammatory responses to aggravate ACLF, suggesting that it may be a potential therapeutic target for ACLF treatment.Keywords: HMGB1, pyroptosis, inflammatory response, molecular mechanism of ACLF, ACLF treatment

Background. Acute on chronic liver failure (ACLF) is a syndrome of acute liver failure that occurs on the basis of chronic liver disease, which is characterized by a rapid deterioration in a short period and high mortality. High mobility group box 1 (HMGB1) may be involved in the pathological process of ACLF; its specific role remains to be further elucidated. Our previous studies have shown that quercetin (Que) exerts anti-oxidant and anti-apoptotic effects by inhibiting HMGB1 in vitro. The present study aimed to investigate the effect of Que on liver injury in ACLF rats. Methods. The contents of ALT, AST, TBiL, and PT time of rats in each group were observed. HE staining was used to detect liver pathology. The levels of oxidative stress indicators such as MDA, GSH, and 4-HNE in the rat liver were detected. TUNEL assay was used to detect apoptosis in rat hepatocytes. Immunofluorescence and western blot analysis were performed to explore the protective effect of Que on ACLF rats and the underlying mechanism. Results. The results showed that Que could reduce the increase of serum biochemical indices, improve liver pathology, and reduce liver damage in ACLF rats. Further results confirmed that Que reduced the occurrence of oxidative stress and apoptosis of hepatocytes, and these reactions may aggravate the progress of ACLF. Meanwhile, the results of immunofluorescence and western blotting also confirmed that the expression of HMGB1 and extranuclear translocation in ACLF rat hepatocytes were significantly increased, which was alleviated by the treatment of Que. In addition, when cotreated with glycyrrhizin (Gly), an inhibitor of HMGB1, the inhibition of Que on HMGB1 and its translocation, apoptosis and oxidative stress, and the related proteins of HMGB1-mediated cellular pathway have been significantly enhanced. Conclusion. Thus, Que alleviates liver injury in ACLF rats, and its mechanism may be related to oxidative stress and apoptosis caused by HMGB1 and its translocation.

Developing deep neural networks to generate 3D scenes is a fundamental problem in neural synthesis with immediate applications in architectural CAD, computer graphics, as well as in generating virtual robot training environments. This task is challenging because 3D scenes exhibit diverse patterns, ranging from continuous ones, such as object sizes and the relative poses between pairs of shapes, to discrete patterns, such as occurrence and co-occurrence of objects with symmetrical relationships. This paper introduces a novel neural scene synthesis approach that can capture diverse feature patterns of 3D scenes. Our method combines the strength of both neural network-based and conventional scene synthesis approaches. We use the parametric prior distributions learned from training data, which provide uncertainties of object attributes and relative attributes, to regularize the outputs of feed-forward neural models. Moreover, instead of merely predicting a scene layout, our approach predicts an over-complete set of attributes. This methodology allows us to utilize the underlying consistency constraints among the predicted attributes to prune infeasible predictions. Experimental results show that our approach outperforms existing methods considerably. The generated 3D scenes interpolate the training data faithfully while preserving both continuous and discrete feature patterns., Published at ICCV2021

As a kind of animal medicine, cattle bile has anti-inflammatory, antipyretic and cholagogic effects. The fermentation process of cattle bile is included in the application of many traditional Chinese medicines. In this study, we fermented cattle bile singly and investigated the impact of fermentation on the anti-inflammatory effect of cattle bile, as well as the mechanism of fermented cattle bile on microglia cells. After high temperature sterilization, cattle bile was fermented with Massa Medicata Fermentata (medicated leaven, Shen Qu). We used ultra-high performance liquid chromatography-mass spectrometry/mass spectrometry (UHPLC-MS/MS) to analyze the bile acids of cattle bile and fermented cattle bile. The results showed that 3-dehydrocholic acid, 7-ketolithocholic acid, 12-dehydrocholic acid, 12-Ketolithocholic acid, ursodeoxycholic acid and dehydrolithocholic acid increased more significantly than others; glycocholic acid and glycochenodeoxycholic acid decreased more significantly than others. After fermentation, cattle bile significantly reduced the release of NO and inflammatory factors (TNF-α and IL-1β). Furthermore, the protein expression of TNF-α, IL-1β and iNOS were decreased. In addition, we found that fermented cattle bile could have an anti-inflammatory effect through attenuating the activation of NLRP3 inflammasome. Thus, fermentation can enhance the anti-inflammatory effect of cattle bile. Fermented cattle bile has an anti-inflammatory effect by inhibiting the NLRP3 inflammasome pathway, which can expand the clinical application of cattle bile and provide new thoughts and methods for the application of cattle bile.

Non-alcoholic fatty liver disease (NAFLD) has become the most prevalent liver disease in China. Sinisan (SNS) is a traditional Chinese medicine formula that has been widely used in treating chronic liver diseases, including NAFLD. However, its underlying biological mechanisms are still unclear. In this study, we employed a network pharmacology approach consisting of overlapped terms- (genes or pathway terms-) based analysis, protein-protein interaction (PPI) network-based analysis, and PPI clusters identification. Unlike the previous network pharmacology study, we used the shortest path length-based network proximity algorithm to evaluate the efficacy of SNS against NAFLD. And we also used random walk with restart (RWR) algorithm and Community Cluster (Glay) algorithm to identify important targets and clusters. The screening results showed that the mean shortest path length between genes of SNS and NAFLD was significantly smaller than degree-matched random ones. Six PPI clusters were identified and ten hub targets were obtained, including STAT3, CTNNB1, MAPK1, MAPK3, AGT, NQO1, TOP2A, FDFT1, ALDH4A1, and KCNH2. The experimental study indicated that SNS reduced hyperlipidemia, liver steatosis, and inflammation. Most importantly, JAK2/STAT3 signal was inhibited by SNS treatment and was recognized as the most important signal considering the network pharmacology part. This study provides a systems perspective to study the relationship between Chinese medicines and diseases and helps to discover potential mechanisms by which SNS ameliorates NAFLD.

Acute-on-chronic liver failure (ACLF) is a serious and complicated disease that threatens human health because its pathogenesis is unclear, and the outcome of the current therapies has been less than satisfactory. A national famous doctor of traditional Chinese medicine, Qian Ying, created the Jieduan-Niwan Formula (JDNW), based on his long-term clinical experience. However, despite the good clinical outcome, the biological mechanism by which it works is unknown. In the current study, we established an ACLF rat model by administering human serum albumin (HSA) combined with D-galactosamine (D-GalN) and lipopolysaccharide (LPS) to explore the potential mechanism of JDNW in treating ACLF. The rats were treated with JDNW by administration of the model substances and sacrificed after 4, 8, and 12 h. Then we divided the rats into normal group, model at 4 h, model at 8 h, model at 12 h, JDNW at 4 h, JDNW at 8 h, and JDNW at 12 h. Biochemical and histopathological examinations were performed to compare the rats in different groups. Compared with the ACLF model group, expression levels of alanine transaminase, aspartate aminotransferase, total bilirubin, and TNF-α and IL-6 proteins were reduced in the JDNW group at the corresponding time points, the survival rates of rats were increased, and the pathological condition of the liver was improved. In addition, JDNW treatment improved the ultrastructure of hepatocytes and mitochondria and decreased the hepatocyte apoptosis index. E2F1, P53, P73, Apaf-1, p14ARF, caspase-3, caspase-6, and caspase-7 levels in the JDNW group were distinctly lower than those in the untreated rats. Moreover, Bcl-2 and Mcl-1 levels increased. Thus, JDNW decreases ACLF-induced mortality in rats by modulating the E2F1-mediated intrinsic apoptotic pathway.

Objective: To study the effects of social stress (CS) and social stress combined with high-fat diet on fat mobilization as a candidate mechanism for the induction or aggravation of non-alcoholic fatty liver disease (NAFLD). Methods: Thirty-two male Wistar rats (250 ± 10 g) were randomly allocated to a blank control group (BC), a high-fat diet group (HFD), a CS group, and a combined CS and high-fat diet group (CS + HFD). Rats were sacrificed and tissues were collected after 8 weeks. Liver and body mass were measured and used to calculate the liver index. Serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), and free fatty acids (FFAs) were measured. Liver sections were examined microscopically after oil red O and hematoxylin and eosin staining. The relative mRNA expression of acetyl-CoA carboxylase (ACCase), hydroxymethylglutaryl coenzyme A (HMG-CoA) reductase in liver, and hormone-sensitive lipase (HSL), and adipose triglyceride lipase (ATGL) in subcutaneous adipose tissue, were measured by real-time PCR. The liver concentrations of triglyceride, reactive oxygen species, and ACCase were measured by ELISA and HSL activity was determined using turbidimetry. Results: NAFLD developed in the CS, HFD, and CS + HFD groups, with the most severe NAFLD being in the CS + HFD group. Serum AST, ALT, and FFA, liver index, and hepatic triglyceride, FFA, and tumor necrosis factor-α were significantly higher in both the CS and CS + HFD groups. However, food intake and ACCase mRNA expression were lower. The mRNA expression of HSL and ATGL in adipose tissue was much higher, and HSL activity was higher in the CS group than in the BC group, and in the CS + HFD group than in the HFD group. Conclusion: We have successfully established two models of stress-induced NAFLD, suggesting stress can induce and aggravate NAFLD by promoting fat mobilization through upregulation of HSL and ATGL. Keywords: Non-alcoholic fatty liver disease, Chronic stress, Fat mobilization, Free fatty acid

Recent advances in single-view 3D hair digitization have made the creation of high-quality CG characters scalable and accessible to end-users, enabling new forms of personalized VR and gaming experiences. To handle the complexity and variety of hair structures, most cutting-edge techniques rely on the successful retrieval of a particular hair model from a comprehensive hair database. Not only are the aforementioned data-driven methods storage intensive, but they are also prone to failure for highly unconstrained input images, complicated hairstyles, and failed face detection. Instead of using a large collection of 3D hair models directly, we propose to represent the manifold of 3D hairstyles implicitly through a compact latent space of a volumetric variational autoencoder (VAE). This deep neural network is trained with volumetric orientation field representations of 3D hair models and can synthesize new hairstyles from a compressed code. To enable end-to-end 3D hair inference, we train an additional embedding network to predict the code in the VAE latent space from any input image. Strand-level hairstyles can then be generated from the predicted volumetric representation. Our fully automatic framework does not require any ad-hoc face fitting, intermediate classification and segmentation, or hairstyle database retrieval. Our hair synthesis approach is significantly more robust and can handle a much wider variation of hairstyles than state-of-the-art data-driven hair modeling techniques with challenging inputs, including photos that are low-resolution, overexposured, or contain extreme head poses. The storage requirements are minimal and a 3D hair model can be produced from an image in a second. Our evaluations also show that successful reconstructions are possible from highly stylized cartoon images, non-human subjects, and pictures taken from behind a person. Our approach is particularly well suited for continuous and plausible hair interpolation between very different hairstyles.

Background. Qingdu Decoction (QDD) is a traditional Chinese medicine formula for treating chronic liver injury (CLI). Materials and methods. A network pharmacology combining experimental validation was used to investigate potential mechanisms of QDD against CLI. We firstly screened the bioactive compounds with pharmacology analysis platform of the Chinese medicine system (TCMSP) and gathered the targets of QDD and CLI. Then, we constructed a compound-target network and a protein-protein interaction (PPI) network and enriched core targets in Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways. At last, we used a CLI rat model to confirm the effect and mechanism of QDD against CLI. Enzyme-linked immunosorbent assay (ELISA), western blot (WB), and real-time quantitative polymerase chain reaction (RT-qPCR) were used. Results. 48 bioactive compounds of QDD passed the virtual screening criteria, and 53 overlapping targets were identified as core targets of QDD against CLI. A compound-CLI related target network containing 94 nodes and 263 edges was constructed. KEGG enrichment of core targets contained some pathways related to CLI, such as hepatitis B, tumor necrosis factor (TNF) signaling pathway, apoptosis, hepatitis C, interleukin-17 (IL-17) signaling pathway, and hypoxia-inducible factor (HIF)-1 signaling pathway. Three PPI clusters were identified and enriched in hepatitis B and tumor necrosis factor (TNF) signaling pathway, apoptosis and hepatitis B pathway, and peroxisome pathway, respectively. Animal experiment indicated that QDD decreased serum concentrations of alanine aminotransferase (ALT), aspartate aminotransferase (AST), endotoxin (ET), and IL-17 and increased prothrombin time activity (PTA) level. WB and RT-qPCR analyses indicated that, compared with the model group, the expression of cysteinyl aspartate specific proteinase-9 (caspase-9) protein, caspase-3 protein, B-cell lymphoma-2 associated X protein (Bax) mRNA, and cytochrome c (Cyt c) mRNA was inhibited and the expression of B-cell lymphoma-2 (Bcl-2) mRNA was enhanced in the QDD group. Conclusions. QDD has protective effect against CLI, which may be related to the regulation of hepatocyte apoptosis. This study provides novel insights into exploring potential biological basis and mechanisms of clinically effective formula systematically.

Recent years have witnessed significant progress in 3D hand mesh recovery. Nevertheless, because of the intrinsic 2D-to-3D ambiguity, recovering camera-space 3D information from a single RGB image remains challenging. To tackle this problem, we divide camera-space mesh recovery into two sub-tasks, i.e., root-relative mesh recovery and root recovery. First, joint landmarks and silhouette are extracted from a single input image to provide 2D cues for the 3D tasks. In the root-relative mesh recovery task, we exploit semantic relations among joints to generate a 3D mesh from the extracted 2D cues. Such generated 3D mesh coordinates are expressed relative to a root position, i.e., wrist of the hand. In the root recovery task, the root position is registered to the camera space by aligning the generated 3D mesh back to 2D cues, thereby completing cameraspace 3D mesh recovery. Our pipeline is novel in that (1) it explicitly makes use of known semantic relations among joints and (2) it exploits 1D projections of the silhouette and mesh to achieve robust registration. Extensive experiments on popular datasets such as FreiHAND, RHD, and Human3.6M demonstrate that our approach achieves stateof-the-art performance on both root-relative mesh recovery and root recovery. Our code is publicly available at https://github.com/SeanChenxy/HandMesh., Comment: CVPR2021

In this work, we propose a framework for single-view hand mesh reconstruction, which can simultaneously achieve high reconstruction accuracy, fast inference speed, and temporal coherence. Specifically, for 2D encoding, we propose lightweight yet effective stacked structures. Regarding 3D decoding, we provide an efficient graph operator, namely depth-separable spiral convolution. Moreover, we present a novel feature lifting module for bridging the gap between 2D and 3D representations. This module begins with a map-based position regression (MapReg) block to integrate the merits of both heatmap encoding and position regression paradigms for improved 2D accuracy and temporal coherence. Furthermore, MapReg is followed by pose pooling and pose-to-vertex lifting approaches, which transform 2D pose encodings to semantic features of 3D vertices. Overall, our hand reconstruction framework, called MobRecon, comprises affordable computational costs and miniature model size, which reaches a high inference speed of 83FPS on Apple A14 CPU. Extensive experiments on popular datasets such as FreiHAND, RHD, and HO3Dv2 demonstrate that our MobRecon achieves superior performance on reconstruction accuracy and temporal coherence. Our code is publicly available at https://github.com/SeanChenxy/HandMesh.

Background Liver failure is considered as the inability of the liver to perform its normal synthetic and metabolic function. Our previous data showed that Jieduan-Niwan formula (JDNW) induced liver failure, while its underlying mechanism remains unknown. Methods In the present study, we performed a network pharmacology to analyze the bioactive ingredients and related targets. Compound and target data of JDNW formula were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), and targets related to liver diseases were obtained from DisGeNET database. Information of protein protein interaction were retrieved from STRING database. Network construction and degree calculation were used Cytoscape software. Metascape web-server was used for GO and KEGG pathway enrichment. A microarray data series (GSE72081) was obtained from Gene Expression Omnibus database and analyzed using R project and Connectivity Map. Ledock was used for molecular docking. Results A total of 114 unduplicated active ingredients were identified after ADME screening. After construction of a target-liver disease network, 28 targets were identified for anti-liver failure effect. These targets were significantly enriched in fluid shear stress and atherosclerosis, pathways in cancer, IL-17 signaling pathway, HIF-1 signaling pathway, insulin resistance, toxoplasmosis, prostate cancer, microRNAs in cancer, NF-kappa B signaling pathway, Chemical carcinogenesis, VEGF signaling pathway and complement and coagulation cascades pathways. After analyzing a public microarray data of quercetin, we found biological action of some NFκB inhibitors was similar to quercetin. Molecular docking study showed that quercetin possessed a capability to bind on IKKβ and inhibited NFκB activation. Conclusions JDNW formula treated liver failure via multiple targets and multiple pathways, including NFκB signal. Quercetin was identified as a key bioactive ingredient of JDNW formula and its anti-liver failure effect may involve in NFκB inhibition.

To elucidate the mechanisms underlying the treatment of Alzheimer's disease (AD) with Traditional Chinese Medicine (TCM), by examining the active components, potential targets and synthetic pathways of Bulao Elixir (BLE).The Absorption, Distribution, Metabolism, Excretion (ADME) / Toxicology (T) calculation was used to screen the active components of Bulao Elixir. Based on the TCM Systems Pharmacology Analysis Platform (TCMSP database) and a text mining tool (GoPubMed database), we predicted and screened the active components of Bulao Elixir and its therapeutic targets for AD. Using the Database for Annotation, Visualization and Integrated Discovery (DAVID), we obtained the targets for AD. Cytoscape software was used to establish a network map of the active component-target and target-pathway of Bulao Elixir. Gene function, related biological processes and signaling pathways were analyzed using the DAVID database.Twelve active components were selected from 196 components of Bulao Elixir. Among 2209 targets, 102 effective targets were selected, and 30 important targets were identified via matching with the disease targets. After further analysis, 14 core targets were identified. Enrichment analysis revealed that most of these important targets were involved in multiple biological processes, including apoptosis, inflammatory reactions, and cell regulation cycles. The synthetic pathways for AD treatment were identified after analyzing and confirming the relevant pathways, providing potentially useful information for diagnosis and treatment methods for AD.The current study elucidated the potential treatment mechanisms of Bulao Elixir in AD using network pharmacology, providing a foundation for further clarification of its treatment targets.

Stroke is the second leading cause of death after heart disease globally and cerebral ischemic stroke accounts for approximately 70% of all incident stroke cases. We selected four main compounds from a patent Chinese medicine, Qingkailing (QKL) injection, including baicalin from Scutellaria baicalensis Georgi (Huang Qin), geniposide from Gardenia jasminoides J. Ellis (Zhizi), and cholic acid and hyodeoxycholic acid from Bovis Calculus (Niuhuang) with a ratio of 4.4:0.4:3:2.6 m/m, to develop a more efficacious and safer modern Chinese medicine injection against ischemic stroke, refined QKL (RQKL). In this study, we investigated multiple targets, levels, and pathways of RQKL by using an integrative pharm\acology combining experimental validation approach. In silica study showed that RQKL may regulate PI3K-Akt, estrogen, neurotrophin, HIF-1, MAPK, Hippo, FoxO, TGF-beta, NOD-like receptor, apoptosis, NF-kappa B, Wnt, chemokine, TNF, Toll-like receptor signaling pathways against ischemic stroke. The experimental results showed that RQKL improved neurological function and prevented infract volume and blood-brain-barrier damage. RQKL inhibited microgliosis and astrogliosis, and protected neurons from ischemic/reperfusion injury. RQKL also inhibited cell apoptosis and affecting the ratio of the anti-apoptosis protein B-cell lymphoma-2 (Bcl2) and pro-apoptosis protein Bcl2-associated X protein (Bax). Western blot analysis showed that RQKL activated AKT/PI3K signaling pathway and antibody array showed RQKL inhibited inflammatory response and decreased proinflammatory factor Tnf, Il6, and Il1b, and chemokines Ccl2, Cxcl2, and Cxcl3, and increased anti-inflammatory cytokine Il10. In conclusion, RQKL protected tissue against ischemic stroke through multiple-target, multiple signals, and modulating multiple cell-types in brain. This study not only promoted our understanding of the role of RQKL against ischemic stroke, but also provided a pattern for the study of Chinese medicine combining pharmaceutical Informatics and system biology methods.

To evaluate the effectiveness of Sini powder for the treatment of non-alcoholic fatty liver disease (NAFLD) in rats and the molecular mechanisms involved.A rat model of stress-induced NAFLD was established by a combination of long-term tethering and feeding of a high-fat, high-calorie diet. These rats were then intragastrically administered with either simvastatin, Sini powder, or vehicle for 1 week. The body mass and field test scores for each group were recorded weekly. Serum aspartate aminotransferase and alanine aminotransferase activities, and triglyceride, total cholesterol, and free fatty acid concentrations were measured. Liver tissue histopathology was examined on hematoxylin and eosin-stained paraffin sections and oil red O-stained frozen sections. The hepatic mRNA expression of nuclear factor kappa-B (NF-κB), NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3), apoptosis-associated speck-like protein containing CARD (ASC), and caspase-1 were measured by reverse transcription-polymerase chain reaction (RT-PCR). The hepatic protein concentrations of NF-κB and NLRP3, ASC, caspase-1, interleukin-1β (IL-1β), interleukin-6 (IL-6), and the serum concentrations of IL-1β and IL-6 were measured by enzyme-linked immunosorbent assay.Compared with the Blank group, rats in the Compound model group showed significant pathologic manifestations of NAFLD, and the expression of NF-κB, NLRP3, ASC, caspase-1, IL-1β and IL-6 were significantly higher (all P0.01). Both simvastatin and Sini powder significantly ameliorated the NAFLD pathology and the abnormal expression of NF-κB, NLRP3, ASC, caspase-1, IL-1β, and IL-6 (all P0.01).Sini powder inhibits the inflammatory response in rats with NAFLD, which is mediated by NF-κB/NLRP3, IL-1β, and IL-6, reduces the effects of psychological stress, and improves lipid metabolism. Therefore, Sini powder may be effective for the treatment of stress-related NAFLD through multiple mechanisms.

Object detection has achieved remarkable progress in the past decade. However, the detection of oriented and densely packed objects remains challenging because of following inherent reasons: (1) receptive fields of neurons are all axis-aligned and of the same shape, whereas objects are usually of diverse shapes and align along various directions; (2) detection models are typically trained with generic knowledge and may not generalize well to handle specific objects at test time; (3) the limited dataset hinders the development on this task. To resolve the first two issues, we present a dynamic refinement network that consists of two novel components, i.e., a feature selection module (FSM) and a dynamic refinement head (DRH). Our FSM enables neurons to adjust receptive fields in accordance with the shapes and orientations of target objects, whereas the DRH empowers our model to refine the prediction dynamically in an object-aware manner. To address the limited availability of related benchmarks, we collect an extensive and fully annotated dataset, namely, SKU110K-R, which is relabeled with oriented bounding boxes based on SKU110K. We perform quantitative evaluations on several publicly available benchmarks including DOTA, HRSC2016, SKU110K, and our own SKU110K-R dataset. Experimental results show that our method achieves consistent and substantial gains compared with baseline approaches. The code and dataset are available at https://github.com/Anymake/DRN_CVPR2020., Comment: Accepted by CVPR 2020 as Oral

Multimodal and multi-domain stylization are two important problems in the field of image style transfer. Currently, there are few methods that can perform both multimodal and multi-domain stylization simultaneously. In this paper, we propose a unified framework for multimodal and multi-domain style transfer with the support of both exemplar-based reference and randomly sampled guidance. The key component of our method is a novel style distribution alignment module that eliminates the explicit distribution gaps between various style domains and reduces the risk of mode collapse. The multimodal diversity is ensured by either guidance from multiple images or random style code, while the multi-domain controllability is directly achieved by using a domain label. We validate our proposed framework on painting style transfer with a variety of different artistic styles and genres. Qualitative and quantitative comparisons with state-of-the-art methods demonstrate that our method can generate high-quality results of multi-domain styles and multimodal instances with reference style guidance or random sampled style.

Monocular depth estimation plays a crucial role in 3D recognition and understanding. One key limitation of existing approaches lies in their lack of structural information exploitation, which leads to inaccurate spatial layout, discontinuous surface, and ambiguous boundaries. In this paper, we tackle this problem in three aspects. First, to exploit the spatial relationship of visual features, we propose a structure-aware neural network with spatial attention blocks. These blocks guide the network attention to global structures or local details across different feature layers. Second, we introduce a global focal relative loss for uniform point pairs to enhance spatial constraint in the prediction, and explicitly increase the penalty on errors in depth-wise discontinuous regions, which helps preserve the sharpness of estimation results. Finally, based on analysis of failure cases for prior methods, we collect a new Hard Case (HC) Depth dataset of challenging scenes, such as special lighting conditions, dynamic objects, and tilted camera angles. The new dataset is leveraged by an informed learning curriculum that mixes training examples incrementally to handle diverse data distributions. Experimental results show that our method outperforms state-of-the-art approaches by a large margin in terms of both prediction accuracy on NYUDv2 dataset and generalization performance on unseen datasets.

Ischemic stroke is the most common type of cerebrovascular accident worldwide. It causes long-term disability and death. Qingkailing (QKL) injection is a traditional Chinese patent medicine which has been clinically applied in the treatment of ischemic stroke for nearly thirty years. In the present study, network pharmacology combined with experimentation was used to elucidate the mechanisms of QKL. ADME screening and target prediction identified 62 active compounds and 275 targets for QKL. Topological screening of the protein-protein interaction (PPI) network was used to build a core PPI network consisting of 408 nodes and 17,830 edges. KEGG enrichment indicated that the main signaling pathway implicated in ischemic stroke involved hypoxia-inducible factor-1 (HIF-1). Experimentation showed that QKL alleviated neurological deficits, brain infraction, blood-brain barrier (BBB) leakage, and tight junction degeneration in a mouse ischemic stroke model. Two-photon laser scanning microscopy was used to evaluate BBB permeability and cerebral microvessel structure in living mice. HIF-1α, matrix metalloproteinase-9 (MMP-9), and tight junction proteins such as occludin, zonula occludins-1 (ZO-1), claudin-5, and VE-Cadherin were measured by western blotting. QKL upregulated ZO-1 and downregulated HIF-1α and MMP-9. QKL has a multiapproach, multitarget, and synergistic effect against ischemic stroke.

Ethnopharmacological relevance Baicalin is one of the major bioactive compounds extracted from the root of Scutellaria baicalensis Georgi, which was used to treat cerebral ischemia for thounds of years. However, its biological mechanisms remains to be further explored. Aim of the review This study aims to identify potential biological mechanisms of baicalin against cerebral ischemia combining antibody-based array and bioinformatics analysis. Methods A rat model of middle cerebral artery occlusion (MCAO) was constructed. Sprague-Dawley rats were randomly divided into three groups: control group, ischemic model group, and baicalin 100 mg/kg treatment group respectively. Bederson score and 2, 3, 5-triphenyl tetrazolium chloride (TTC) staining were examined to evaluate the pharmacodynamics of baicalin treatment. Antibody-based array technology, enzyme linked immunosorbent assay (ELISA), western-blot, molecular docking, transcription factor perdiction, hematoxylin and eosin (H&E), and immunofluorescence staining were used to study the regulation of baicalin on inflammatory response after cerebral ischemia in vivo. LPS-induced RAW 264.7 macrophage inflammation model was prepared to observe the anti-inflammatory effect of baicalin in vitro. Results Baicalin (100 mg/kg) reduced neurological injury score, cerebral infarction volume, and necrotic cells in MCAO rats. Baicalin inhibited the expression of CCL2, and reduced the phosphorylation levels of p65, IκBα protein and down-regulated level of CCR2. Besides, baicalin could bond to CCR2 directly, which prevented CCL2 from binding to CCR2. Furthermore, baicalin down-regulated the number of monocytes in the peripheral blood and improved the spleen index post-cerebral ischemia. In vitro, baicalin significantly inhibited the secretion of NO, IL6, TNFα, and CCL2 in macrophages and promoted the secretion of IL13, IFNG, and IL1a. Conclusions Baicalin inhibited cerebral ischemia-induced activation of the NFκB/CCL2/CCR2 pathway with multiple target effect. These data promote the therapeutic utilization of baicalin in preventing cerebral ischemia clinically.

Sampling, grouping, and aggregation are three important components in the multi-scale analysis of point clouds. In this paper, we present a novel data-driven sampler learning strategy for point-wise analysis tasks. Unlike the widely used sampling technique, Farthest Point Sampling (FPS), we propose to learn sampling and downstream applications jointly. Our key insight is that uniform sampling methods like FPS are not always optimal for different tasks: sampling more points around boundary areas can make the point-wise classification easier for segmentation. Towards this end, we propose a novel sampler learning strategy that learns sampling point displacement supervised by task-related ground truth information and can be trained jointly with the underlying tasks. We further demonstrate our methods in various point-wise analysis tasks, including semantic part segmentation, point cloud completion, and keypoint detection. Our experiments show that jointly learning of the sampler and task brings better performance than using FPS in various point-based networks., Comment: 14 pages, 13 figures and 14 tables

3D tensor field design is important in several graphics applications such as procedural noise, solid texturing, and geometry synthesis. Different fields can lead to different visual effects. The topology of a tensor field, such as degenerate tensors, can cause artifacts in these applications. Existing 2D tensor field design systems cannot be used to handle the topology of a 3D tensor field. In this paper, we present to our knowledge the first 3D tensor field design system. At the core of our system is the ability to edit the topology of tensor fields. We demonstrate the power of our design system with applications in solid texturing and geometry synthesis.

The visual richness of computer graphics applications is frequently limited by the difficulty of obtaining high-quality, detailed 3D models. This paper proposes a method for realistically transferring details specifically, displacement maps from existing high-quality 3D models to simple shapes that may be created with easy-to-learn modeling tools. Our key insight is to use metric learning to find a combination of geometric features that successfully predicts detail-map similarities on the source mesh; we use the learned feature combination to drive the detail transfer. The latter uses a variant of multi-resolution non-parametric texture synthesis, augmented by a high-frequency detail transfer step in texture space. We demonstrate that our technique can successfully transfer details among a variety of shapes including furniture and clothing.

Similar objects are ubiquitous and abundant in both natural and artificial scenes. Determining the visual importance of several similar objects in a complex photograph is a challenge for image understanding algorithms. This study aims to define the importance of similar objects in an image and to develop a method that can select the most important instances for an input image from multiple similar objects. This task is challenging because multiple objects must be compared without adequate semantic information. This challenge is addressed by building an image database and designing an interactive system to measure object importance from human observers. This ground truth is used to define a range of features related to the visual importance of similar objects. Then, these features are used in learning-to-rank and random forest to rank similar objects in an image. Importance predictions were validated on 5,922 objects. The most important objects can be identified automatically. The factors related to composition (e.g., size, location, and overlap) are particularly informative, although clarity and color contrast are also important. We demonstrate the usefulness of similar object importance on various applications, including image retargeting, image compression, image re-attentionizing, image admixture, and manipulation of blindness images.

Background Cerebral ischemia is the second-leading cause of death and the main cause of permanent adult disabilities worldwide. Qingkailing (QKL) injection, a patented Chinese medicine approved by the China Food and Drug Administration, has been widely used in clinical practice to treat cerebral ischemia in China. The NOD-like receptor pyrin 3 (NLRP3) inflammasome is activated in cerebral ischemia and thus, is an effective therapeutic target. AMP-activated protein kinase (AMPK) is an important regulator inhibiting NLRP3 inflammasome activation. Methods We investigated the potential of QKL injection to provide neuroprotection after cerebral ischemia in a rat model of middle cerebral artery occlusion (MCAO). Adult male Sprague-Dawley rats (210–230 g) were randomly divided into three groups which consist of sham, MCAO and 3 ml/kg QKL. Rats in the QKL group received intraperitoneal injections of 3 ml/kg QKL, while rats in other groups were given saline in the same volumes. After 90 min ischemia and 24 h reperfusion, neurological function, laser speckle imaging, brain infarction, brain water content and brain blood barrier permeability were examined and cell apoptosis at prefrontal cortex were evaluated 24 h after MCAO, and western blot and real-time quantitative polymerase chain reaction was also researched, respectively. Results Intraperitoneal administration of QKL alleviated neurological deficiencies, cerebral infarction, blood-brain barrier permeability, brain oedema and brain cell apoptosis after MCAO induction. QKL decreased pro-inflammatory cytokines, TNF-α, IL-6 and IL-1β, and increased anti-inflammatory cytokines, IL-4 and IL-10. Furthermore, QKL activated phosphorylated AMPK, decreased oxidative stress and decreased NLRP3 inflammasome activation. Conclusions QKL relieved cerebral ischemia reperfusion injury and suppressed the inflammatory response by inhibiting AMPK-mediated activation of the NLRP3 inflammasome. These results suggest that QKL might have potential in treating brain inflammatory response and attenuating the cerebral ischemia-reperfusion injury.

Taking a satisfactory picture in a low-light environment remains a challenging problem. Low-light imaging mainly suffers from noise due to the low signal-to-noise ratio. Many methods have been proposed for the task of image denoising, but they fail to work under extremely low-light conditions. Recently, deep learning based approaches have been presented that have higher objective quality than traditional methods, but they usually have high computational cost which makes them impractical to use in real-time applications or where the processing power is limited. In this paper, we propose a new residual learning based deep neural network for end-to-end extreme low-light image denoising that can not only significantly reduce the computational cost but also improve the quality over existing methods in both objective and subjective metrics. Specifically, in one setting we achieved 29x speedup with higher PSNR. Subjectively, our method provides better color reproduction and preserves more detailed texture information compared to state-of-the-art methods.

Ischemic stroke is accompanied by high mortality and morbidity rates. At present, there is no effective clinical treatment. Alternatively, traditional Chinese medicine has been widely used in China and Japan for the treatment of ischemic stroke. Baicalin is a flavonoid extracted from Scutellaria baicalensis that has been shown to be effective against ischemic stroke; however, its mechanism has not been fully elucidated. Based on network pharmacology, we explored the potential mechanism of baicalin on a system level. After obtaining baicalin structural information from the PubChem database, an approach combined with literature mining and PharmMapper prediction was used to uncover baicalin targets. Ischemic stroke-related targets were gathered with the help of DrugBank, Online Mendelian Inheritance in Man (OMIM), Genetic Association Database (GAD), and Therapeutic Target Database (TTD). Protein-protein interaction (PPI) networks were constructed through the Cytoscape plugin BisoGenet and analyzed by topological methods. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were carried out via the Database for Annotation, Visualization, and Integrated Discovery (DAVID) server. We obtained a total of 386 potential targets and 5 signaling pathways, including mitogen-activated protein kinase (MAPK), phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT), hypoxia-inducible factor-1 (HIF-1), nuclear factor kappa B (NF-κB), and forkhead box (FOXO) signaling pathways. GO analysis showed that these targets were associated with antiapoptosis, antioxidative stress, anti-inflammation, and other physiopathological processes that are involved in anti-ischemic stroke effects. In summary, the mechanism of baicalin against ischemic stroke involved multiple targets and signaling pathways. Our study provides a network pharmacology framework for future research on traditional Chinese medicine.

Traditional Chinese medicine (TCM) has a longstanding history and has gained widespread clinical applications. San Cao Decoction (SCD) is an experience prescription first formulated by Prof. Duzhou Liu. We previously demonstrated its antihypertensive effects; however, to systematically explain the underlying mechanisms of action, we employed a systems pharmacology approach for pharmacokinetic screening and target prediction by constructing protein-protein interaction networks of hypertension-related and putative SCD-related targets, and Database for Annotation, Visualization, and Integrated Discovery enrichment analysis. We identified 123 active compounds in SCD and 116 hypertension-related targets. Furthermore, the enrichment analysis of the drug-target network showed that SCD acts in a multidimensional manner to regulate PI3K-Akt-endothelial nitric oxide synthase signaling to maintain blood pressure. Our results highlighted the molecular mechanisms of antihypertensive actions of medicinal herbs at a systematic level.

Time-lapse videos usually contain visually appealing content but are often difficult and costly to create. In this paper, we present an end-to-end solution to synthesize a time-lapse video from a single outdoor image using deep neural networks. Our key idea is to train a conditional generative adversarial network based on existing datasets of time-lapse videos and image sequences. We propose a multi-frame joint conditional generation framework to effectively learn the correlation between the illumination change of an outdoor scene and the time of the day. We further present a multi-domain training scheme for robust training of our generative models from two datasets with different distributions and missing timestamp labels. Compared to alternative time-lapse video synthesis algorithms, our method uses the timestamp as the control variable and does not require a reference video to guide the synthesis of the final output. We conduct ablation studies to validate our algorithm and compare with state-of-the-art techniques both qualitatively and quantitatively., Comment: To appear in CVPR 2019