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The host innate immune response to viral infection often involves the activation of type I interferons. Not surprisingly, many viruses have evolved various mechanisms to disable the interferon pathway and evade the antiviral response involving innate immunity. Rabbit hemorrhagic disease (RHD) is caused by RHD virus (RHDV), but whether it can antagonize the production of host interferon to establish infection has not been investigated. In this study, we found that during RHDV infection, the expressions of interferon and the interferon-stimulated gene were not activated. We constructed eukaryotic expression plasmids of all RHDV proteins, and found that RHDV 3C protein inhibited poly(I:C)-induced interferon expressions. Using siRNA to interfere with the expressions of TLR3 and MDA5, we found that the MDA5 signal pathway was used by the 3C protein to inhibit poly(I:C)-induced interferon expression. This effect was mediated by cleaving the interferon promoter stimulated 1 (IPS-1) protein. Finally, our study showed that interferon was effective against RHDV infection. In summary, our findings showed that the RHDV 3C protein was a new interferon antagonist. These results increase our understanding of the escape mechanism from innate immunity mediated by the RHDV 3C protein.

Obesity is caused by imbalanced energy intake and expenditure. The excessive energy intake and storage in adipose tissues is associated with many diseases. Several studies have demonstrated that VEGFB deficiency induces obese phenotypes. However, roles of VEGFB isoforms VEGFB167 and VEGFB186 in adipose tissue development and function are still not clear. In this study, genetic mouse models of adipose-specific VEGFB167 and VEGFB186 overexpression (aP2-Vegfb167tg/+ and aP2-Vegfb186tg/+) were generated and their biologic roles were investigated. On regular chow, adipose-specific VEGFB186 is negatively associated with white adipose tissues (WAT) and positively regulates brown adipose tissues (BAT). VEGFB186 up-regulates energy metabolism and metabolism-associated genes. In contrast, VEGFB167 has nominal roles in adipose development and function. On high fat diet, VEGFB186 expression can reverse the phenotypes of VEGFB deletion. VEGFB186 overexpression up-regulates BAT-associated genes and down-regulates WAT-associated genes. VEGFB186 and VEGFB167 have very distinct roles in regulation of adipose development and energy metabolism. As a key regulator of adipose tissue development and energy metabolism, VEGFB186 may be a target for obesity prevention and treatment.

Atherosclerosis, a chronic inflammatory disease that often leads to myocardial infarction and stroke, is mainly caused by lipid accumulation. Eukaryotic initiation factor 6 (Eif6) is a rate-limiting factor in protein translation of transcription factors necessary for lipogenesis. To determine whether Eif6 affects atherosclerosis, Eif6+/- mice were crossed into Apoe-/- background. Apoe-/-/Eif6+/- mice on high fat diet showed significant reduction in atherosclerotic lesions and necrotic core content in aortic root sections in comparison with Apoe-/- mice. RNA-Seq was used to investigate the effect of Eif6 in aorta. Deficiency of Eif6 shows broad effect on cell metabolism. Expression of genes for fatty acid synthesis including Fatty acid synthase (Fasn), Elovl3, Elovl6 and Acaca are down-regulated in aortas. Importantly, Fasn is decreased in macrophages. Results suggest that Eif6 deficiency may decrease atherosclerosis through inhibition of Fasn and lipids metabolism in macrophages.

The host innate immune response to viral infection often involves the activation of type I interferons (IFNs). Not surprisingly, many viruses have evolved various mechanisms to disable the IFN pathway and evade the antiviral response involving innate immunity. Rabbit hemorrhagic disease (RHD) is caused by RHD virus (RHDV), but whether it can antagonize the production of host IFN to establish infection has not been investigated. In this study, we found that during RHDV infection, the expressions of IFN and the interferon-stimulated gene were not activated. We constructed eukaryotic expression plasmids of all RHDV proteins, and found that RHDV 3C protein inhibited poly(I:C)-induced IFN expressions. Using siRNA to interfere with the expressions of TLR3 and MDA5, we found that the MDA5 signal pathway was used by the 3C protein to inhibit poly(I:C)-induced IFNs expression. This effect was mediated by cleaving the interferon promoter stimulated 1 (IPS-1) protein. Finally, our study showed that IFN was effective against RHDV infection. In summary, our findings showed that RHDV 3C protein was a new interferon antagonist. These results increased our understanding of the escape mechanism from innate immunity mediated by the RHDV 3C protein.

VEGFB has high sequence homology and shares receptor VEGFR1 with VEGFA and PlGF. However, its function is poorly understood. Using VEGFA repression (VegfaDown), VEGFB knockout (Vegfb−/−) and VEGFB over expression (aP2-Vegfb167, aP2-Vegfb186) mouse models, we identified VEGFB167 as a strong promoter of tumor growth. Universal Vegfb inactivation significantly retards tumor growth and metastasis of B16 and U14 cancer cells. VEGFB deletion led to an inactivation of VEGFR1 pathway, blocking of tumor-associated macrophage transformation towards M1 phenotype and creation of a microenvironment that represses tumor growth and metastasis. Genetic VEGFA repression showed reduced inhibitory effect on U14 and no effect on B16 tumor growth in comparison to VEGFB. The inhibitory effect by inactivating VEGFB on tumor growth and tumor cell metastasis is significantly better than VEGFA. The study demonstrates VEGFB is an oncogene and drug target for VEGFB-sensitive cancers.

Background: The intestinal bacterial community has an important role in maintaining human health. Dysbiosis is a key inducer of many chronic diseases including obesity and diabetes. Kunming mice are frequently used as a model of human disease and yet little is known about the bacterial microbiome resident to the gastrointestinal tract. Results: We undertook metagenomic sequencing of the luminal contents of the stomach, duodenum, jejunum, ileum, cecum, colon, and rectum of Kunming mice. Firmicutes was the dominant bacterial phylum of each intestinal tract and Lactobacillus the dominant genus. However, the bacterial composition differed among the seven intestinal tracts of Kunming mice. Compared with the small intestine, the large intestine bacterial community of Kunming mice is more stable and diverse. Conclusions: To our knowledge, ours is the first study to systematically describe the gastrointestinal bacterial composition of Kunming mice. Our findings provide a better understanding of the bacterial composition of Kunming mice and serves as a foundation for the study of precision medicine. Normal 0 false false false EN-US ZH-CN X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.5pt; mso-bidi-font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-font-kerning:1.0pt; mso-fareast-language:ZH-CN;}

Background：Atherosclerosis is a chronic inflammatory disease, caused by accumulation of lipid-laden and inflammatory macrophages in the artery wall. Understanding its molecular mechanisms and developing novel therapeutic targets to promote atherosclerotic regression is an important clinical goal.Methods : ApoE-/- and eIF6+/-/ApoE-/- mice were fed Western diet (WD) for 16 weeks. Molecular biology technology were performed to analyze the differences between them.Results: The mechanism by which Eukaryotic initiation factor 6 (eIF6) affects macrophages and atherosclerosis remains to be elucidated. Western blotting and real-time polymerase chain reaction (PCR ) analysis indicated significantly higher expression levels of eIF6 than those in the control in RAW264.7 cells induced by Lipopolysaccharide (LPS) and Interleukin-4 (IL4). We constructed eIF6+/-/ApoE-/- mice, the hematoxylin (HE) and Oil Red O staining analysis indicated that these mice showed a significant decrease in atherosclerotic lesion formation increased anti-inflammatory cell content in aortas, and reduced necrotic core content compared with ApoE-/- mice on a western diet for 16 weeks. eIF6 deficiency suppressed foam cell formation and promoted the anti-inflammatory macrophage phenotype in primary macrophages. More anti-inflammatory populations were observed in blood and atherosclerotic aortas of eIF6+/- ApoE-/- mice by flow cytometry. Immunofluorescent staining analysis obtained the same results.Conclusions: eIF6 deficiency protects against atherosclerosis by promoting the anti-inflammatory macrophage phenotype and reducing macrophage uptake of low-density lipoprotein (LDL), indicating that new insight into eIF6 may reveal a potential novel therapeutic target for the resolution of inflammation in atherosclerosis.

A negative lymph node (NLN) count has been shown to have a significant impact on the prognosis of many types of cancer. However, its prognostic value for jejunoileal neuroendocrine tumors (NETs) remains unclear. In this study, we investigated the prognostic value of NLN count in patients with resected jejunoileal NETs diagnosed between 1988 and 2014. The data were retrieved from the Surveillance, Epidemiology and End Results database. The X-tile program was used to determine the cutoff value of the NLN count. Univariate and multivariate Cox proportional hazards models were used to assess the prognostic value of NLN count on survival. Harrell concordance index was used to compare the prognostic validity of NLN count with two current prognostic systems. The optimal cutoff point of the NLN count was 8. Kaplan–Meier analysis revealed a progressively worse overall survival (OS) with an NLN count ≤8 compared with an NLN count > 8 (P

Whether regional lymph node involvement exerts significant effect on the prognosis still remains obscure for pancreatic neuroendocrine tumors. To clarify this association and identify predictors for lymph node involvement, we studied the data of patients aged >18 years with regional lymph node involvement histologically confirmed pancreatic neuroendocrine tumors from 2004 to 2014 in the Surveillance, Epidemiology, and End Results database (http://seer.cancer.gov/about). We evaluated Lymph node involvement as a prognostic factor by Cox regression. We reduced 9 variables of demographic and tumor characteristics to 5 potential predictors using least absolute shrinkage and selection operator (LASSO) regression model. We further constructed a lymph node involvement model by logistic regression. The model was verified by the verification set, and the visual expression of the model was realized by a nomogram. A total of 1545 cases of pancreatic neuroendocrine tumors were included in our study. Lymph node positivity was significantly associated with disease-specific survival (P < 0.001). Younger patients (P < 0.05), patients with tumors in the pancreatic head (P < 0.05), patients at high American Joint Committee on Cancer T stage (P < 0.001), and patients of an undifferentiated status (P < 0.05) showed a significantly higher possibility of developing lymph node involvement. The reliability of this model was verified by cross-validation between the training and testing set, and we obtained good discrimination and calibration power. This model also showed great performance in C-index and area under receiver operating characteristic curve. Lymph node positivity was an important negative prognostic predictor for pancreatic neuroendocrine tumor. We developed a lymph node involvement model based on the predictors including age, marital status, primary site, T status, and tumor grade. Key words: Surveillance; Epidemiology; and End Results database; logistic regression; lymph node involvement; nomogram; pancreatic neuroendocrine tumors

The heme oxygenase (HO) system is an important regulatory arm of the intrinsic cytoprotective and anti-inflammatory system. HO-2 plays an important role in regulating inflammation following injury. The aim of this study was to evaluate the effect of HO-2 overexpression on inflammatory responses. A skin transplantation model, involving the application of skin grafts from wild-type or HO-2 overexpressing mice to BALB/c mice, was used for investigation. HO-2 overexpression suppressed the production of pro-inflammatory cytokines (IL-1β, TNF-α, and IL-6) in macrophages compared to that in macrophages obtained from control mice. HO-2 overexpression also significantly prolonged the survival of allografted skin. Our findings suggest that HO-2 attenuates inflammatory responses and effectively prolongs skin graft survival.

Purpose: Liver cancer is insensitive to chemotherapy. Sorafenib is currently the standard treatment for patients with advanced diseases, with mild survival extension and several intolerable drug-related side effects. The establishment of new treatments is an unmet clinical need. The aim of our study was to assess the efficacy and safety of apatinib, a novel antiangiogenic drug, in the treatment of patients with liver cancer. Materials and Methods: Patients with unresectable or relapsed liver cancer were included in a single center, retrospective, observational study and treated with apatinib until progressive disease or unacceptable toxicity. Results: 32 patients were reviewed from January 2015 to March 2017. No complete response (CR) occurred, 5 patients (16%) showed partial response (PR), 14 patients (44%) had stable disease (SD), 13 patients (41%) had progressive disease (PD), with disease control rate of 60%. Median progression-free survival (PFS) was 5 months (95% confidence interval [CI]: 4.3-6.1 months) for hepatocellular carcinoma (HCC) and 3 months (95% CI: 2.5-4.2 months) for intrahepatic cholangiocarcinoma (ICC). The median overall survival (OS) was 13 months (95% CI: 12.4-14.1 months) for HCC and 5 months (95% CI: 4.5-6.2 months) for ICC, respectively. The most common adverse effects (AEs) were proteinuria (31%), secondary hypertension (28%) and liver dysfunction (13%). Conclusion: Apatinib treatment was an effective for patients with liver cancer. The toxicities were mild and tolerable.

Objectives This study aimed to reveal the regulatory roles of microRNAs in head and neck squamous cell carcinoma (HNSCC) through comprehensive ceRNA, miRNA-transcription factor (TF)-hub gene network and survival analysis. Materials and methods Expression analysis was performed using the 'edgeR' package based on The Cancer Genome Atlas database. The ceRNA network was screened by intersecting prediction results from miRcode, miRTarBase, miRDB and TargetScan. GSE30784, GSE59102 and GSE107591 from the Gene Expression Omnibus repository were chosen for cross-validation. Hub genes were identified using a protein-protein interaction network constructed by Search Tool for the Retrieval of Interacting Genes. The Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining (TTRUST) was utilized to map the miRNA-TF-Hub gene network. Patient overall survival was analyzed using the ‘survival’ package in R. Structural and functional analysis of miR-204/211 was based on miRbase and RNAstructure. Results A ceRNA network of 178 lncRNAs, 19 miRNAs and 55 mRNAs was generated, and a TF regulatory network with 11 miRNAs, 11 TFs and 18 hub genes was constructed from the 52 hub genes identified through the protein–protein interaction (PPI) network. Survival analysis demonstrated that the dysregulated expression of 11 lncRNAs and 14 mRNAs was highly related to overall survival. Furthermore, miR-204 and miR-211 were significantly involved in the network with identical mature structures, indicating them as key miRNAs in HNSCC. Conclusion This study reveals the comprehensive molecular regulatory networks centralized by miRNAs in HNSCC and uncovers the crucial role of miR-204 and miR-211, which may become potential diagnostic and therapeutic targets.

The rumen contains a highly complex microbial ecosystem that plays an important role in converting solar energy in plants into nutrients for ruminants and generates animal food products, such as meat and milk for humans. Therefore, understanding the effect of the dietary concentrate to forage (C:F) ratio on ruminal microbiota is of great significance for the growth and development of ruminants. In this study, changes in the ruminal bacterial and anaerobic fungal populations of Shaanbei white-cashmere (SWC) goats that were reared under different dietary C:F ratios were evaluated by high-throughput sequencing analysis. It was found that dietary C:F ratio has a significant impact on the composition of the ruminal bacteria in SWC goats. The levels of Actinobacteria and Proteobacteria were significantly increased (P

Atherosclerosis is a chronic inflammatory disease; unstable atherosclerotic plaque rupture, vascular stenosis, or occlusion caused by platelet aggregation and thrombosis lead to acute cardiovascular disease. Atherosclerosis-related inflammation is mediated by proinflammatory cytokines, inflammatory signaling pathways, bioactive lipids, and adhesion molecules. This review discusses the effects of inflammation and the systemic inflammatory signaling pathway on atherosclerosis, the role of related signaling pathways in inflammation, the formation of atherosclerosis plaques, and the prospects of treating atherosclerosis by inhibiting inflammation.

As primary duodenal adenocarcinoma is rare, the prognostic factors of this disease remain insufficiently explored, especially in China. We identified postoperative duodenal adenocarcinoma patients at a Chinese double-center (from 2006 to 2016) or who were registered with the Surveillance, Epidemiology, and End Results (SEER) database (from 2004 to 2014). Clinicopathological features and significant prognostic factors for cancer-specific survival (CSS) were reviewed and analyzed by using univariate and multivariate Cox proportional hazards regression. Then, a nomogram predicting CSS was constructed based on the SEER database and validated externally by using the separate Chinese cohort. Totally, 137 patients from the Chinese double-center and 698 patients from the SEER database were included for analysis. The multivariate analyses showed that age, tumor grade and TNM stage were independent prognostic factors. The nomogram constructed using these factors showed a clear prognostic superiority to the AJCC-TNM classification, 7th ed. (C-index: SEER cohort, 0.693 vs 0.625, P P

The experiment aimed to specifically monitor the passage of lactobacilli in vivo after oral administration. The green fluorescent protein (GFP) gene was cloned downstream from the constitutive p32 promoter from L. lactis subsp. cremoris Wg2. The recombinant expression vector, pLEM415-gfp-p32, was electroporated into Lactobacillus plantarum (L. plantarum) isolated from goat. Green fluorescent protein (GFP) was successfully expressed in L. plantarum. After 2 h post-administration, transformed Lactobacillus could be detectable in all luminal contents. In the rumen, bacteria concentration initially decreased, reached the minimum at 42 h post-oral administration and then increased. However, this concentration decreased constantly in the duodenum. This result indicated that L. plantarum could colonize in the rumen but not in the duodenum.

What is the story of an image? What is the relationship between pictures, language, and information we can extract using state of the art computational recognition systems? In an attempt to address both of these questions, we explore methods for retrieving and generating natural language descriptions for images. Ideally, we would like our generated textual descriptions (captions) to both sound like a person wrote them, and also remain true to the image content. To do this we develop data-driven approaches for image description generation, using retrieval-based techniques to gather either: (a) whole captions associated with a visually similar image, or (b) relevant bits of text (phrases) from a large collection of image + description pairs. In the case of (b), we develop optimization algorithms to merge the retrieved phrases into valid natural language sentences. The end result is two simple, but effective, methods for harnessing the power of big data to produce image captions that are altogether more general, relevant, and human-like than previous attempts.

Curcumin is a major component of turmeric with promising tumor-suppressive activity; however, its underlying molecular mechanisms need to be investigated further. We aimed to investigate the mechan...

Although deep convolutional neural networks (CNNs) have shown remarkable results for feature learning and prediction tasks, many recent studies have demonstrated improved performance by incorporating additional handcrafted features or by fusing predictions from multiple CNNs. Usually, these combinations are implemented via feature concatenation or by averaging output prediction scores from several CNNs. In this paper, we present new approaches for combining different sources of knowledge in deep learning. First, we propose feature amplification, where we use an auxiliary, hand-crafted, feature (e.g. optical flow) to perform spatially varying soft-gating on intermediate CNN feature maps. Second, we present a spatially varying multiplicative fusion method for combining multiple CNNs trained on different sources that results in robust prediction by amplifying or suppressing the feature activations based on their agreement. We test these methods in the context of action recognition where information from spatial and temporal cues is useful, obtaining results that are comparable with state-of-the-art methods and outperform methods using only CNNs and optical flow features.

In this paper, we define a new task, Exact Street to Shop, where our goal is to match a real-world example of a garment item to the same item in an online shop. This is an extremely challenging task due to visual differences between street photos (pictures of people wearing clothing in everyday uncontrolled settings) and online shop photos (pictures of clothing items on people, mannequins, or in isolation, captured by professionals in more controlled settings). We collect a new dataset for this application containing 404,683 shop photos collected from 25 different online retailers and 20,357 street photos, providing a total of 39,479 clothing item matches between street and shop photos. We develop three different methods for Exact Street to Shop retrieval, including two deep learning baseline methods, and a method to learn a similarity measure between the street and shop domains. Experiments demonstrate that our learned similarity significantly outperforms our baselines that use existing deep learning based representations.

Motivated by recent successes on learning feature representations and on learning feature comparison functions, we propose a unified approach to combining both for training a patch matching system. Our system, dubbed Match-Net, consists of a deep convolutional network that extracts features from patches and a network of three fully connected layers that computes a similarity between the extracted features. To ensure experimental repeatability, we train MatchNet on standard datasets and employ an input sampler to augment the training set with synthetic exemplar pairs that reduce overfitting. Once trained, we achieve better computational efficiency during matching by disassembling MatchNet and separately applying the feature computation and similarity networks in two sequential stages. We perform a comprehensive set of experiments on standard datasets to carefully study the contributions of each aspect of MatchNet, with direct comparisons to established methods. Our results confirm that our unified approach improves accuracy over previous state-of-the-art results on patch matching datasets, while reducing the storage requirement for descriptors. We make pre-trained MatchNet publicly available.

The ability of rumen microorganisms to use fibrous plant matter plays an important role in ruminant animals; however, little information about rumen colonization by microbial populations after weaning has been reported. In this study, high-throughput sequencing was used to investigate the establishment of this microbial population in 80 to 110-day-old goats. Illumina sequencing of goat rumen samples yielded 101,356,610 nucleotides that were assembled into 256,868 reads with an average read length of 394 nucleotides. Taxonomic analysis of metagenomic reads indicated that the predominant phyla were distinct at different growth stages. The phyla Firmicutes and Synergistetes were predominant in samples taken from 80 to 100-day-old goats, but Bacteroidetes and Firmicutes became the most abundant phyla in samples from 110-day-old animals. There was a remarkable variation in the microbial populations with age; Firmicutes and Synergistetes decreased after weaning, but Bacteroidetes and Proteobacteria increased from 80 to 110 day of age. These findings suggested that colonization of the rumen by microorganisms is related to their function in the rumen digestive system. These results give a better understanding of the role of rumen microbes and the establishment of the microbial population, which help to maintain the host’s health and improve animal performance.

While previous results from univariate analysis showed that the activity level of the parahippocampal gyrus (PHG) but not the fusiform gyrus (FG) reflects selective maintenance of the cued picture category, present results from multi-voxel pattern analysis (MVPA) showed that the spatial response patterns of both regions can be used to differentiate the selected picture category in working memory. The ventral temporal and occipital areas including the PHG and FG have been shown to be specialized in perceiving and processing different kinds of visual information, though their role in the representation of visual working memory remains unclear. To test whether the PHG and FG show spatial response patterns that reflect selective maintenance of task-relevant visual working memory in comparison with other posterior association regions, we reanalyzed data from a previous fMRI study of visual working memory with a cue inserted during the delay period of a delayed recognition task. Classification of FG and PHG activation patterns for the selected category (face or scene) during the cue phase was well above chance using classifiers trained with fMRI data from the cue or probe phase. Classification of activity in other temporal and occipital regions for the cued picture category during the cue phase was relatively less consistent even though classification of their activity during the probe recognition was comparable with the FG and PHG. In sum, these findings suggest that the FG and PHG carry information relevant to the cued visual category, and their spatial activation patterns during selective maintenance seem to match those during visual recognition.

What do people care about in an image? To drive computational visual recognition toward more human-centric outputs, we need a better understanding of how people perceive and judge the importance of content in images. In this paper, we explore how a number of factors relate to human perception of importance. Proposed factors fall into 3 broad types: 1) factors related to composition, e.g. size, location, 2) factors related to semantics, e.g. category of object or scene, and 3) contextual factors related to the likelihood of attribute-object, or object-scene pairs. We explore these factors using what people describe as a proxy for importance. Finally, we build models to predict what will be described about an image given either known image content, or image content estimated automatically by recognition systems.