Miracle-dz/UniFAR-FTUs huggingface dataset:
Nitric oxide modulates murine yolk sac vasculogenesis and rescues glucose induced vasculopathy

Nitric oxide (NO) has been demonstrated to mediate events during ovulation, pregnancy, blastocyst invasion and preimplantation embryogenesis. However, less is known about the role of NO during postimplantation development. Therefore, in this study, we explored the effects of NO during vascular development of the murine yolk sac, which begins shortly after implantation. Establishment of the vitelline circulation is crucial for normal embryonic growth and development. Moreover, functional inactivation of the endodermal layer of the yolk sac by environmental insults or genetic manipulations during this period leads to embryonic defects/lethality, as this structure is vital for transport, metabolism and induction of vascular development. In this study, we describe the temporally/spatially regulated distribution of nitric oxide synthase (NOS) isoforms during the three stages of yolk sac vascular development (blood island formation, primary capillary plexus formation and vessel maturation/remodeling) and found NOS expression patterns were diametrically opposed. To pharmacologically manipulate vascular development, an established in vitro system of whole murine embryo culture was employed. During blood island formation, the endoderm produced NO and inhibition of NO (L-NMMA) at this stage resulted in developmental arrest at the primary plexus stage and vasculopathy. Furthermore, administration of a NO donor did not cause abnormal vascular development; however, exogenous NO correlated with increased eNOS and decreased iNOS protein levels. Additionally, a known environmental insult (high glucose) that produces reactive oxygen species (ROS) and induces vasculopathy also altered eNOS/iNOS distribution and induced NO production during yolk sac vascular development. However, administration of a NO donor rescued the high glucose induced vasculopathy, restored the eNOS/iNOS distribution and decreased ROS production. These data suggest that NO acts as an endoderm-derived factor that modulates normal yolk sac vascular development, and decreased NO bioavailability and NO-mediated sequela may underlie high glucose induced vasculopathy.
Purification and Properties of Arabidopsis thaliana COR (Cold-Regulated) Gene Polypeptides COR15am and COR6.6 Expressed in Escherichia coli

Arabidopsis thaliana cold-regulated genes COR15a and COR6.6 encode 15- and 6.6-kD polypeptides, respectively. The COR15a polypeptide is known to be targeted to chloroplasts and, during import, to be processed to a 9.4-kD polypeptide designated COR15am. The COR6.6 polypeptide is thought to be located in the cytosol. The coding sequences for COR15am and COR6.6 were fused to the bacteriophage T7 promoter and expressed in Escherichia coli. The recombinant polypeptides COR15amr and COR6.6r were purified to near homogeneity using a combination of ammonium sulfate fractionation, ion-exchange chromatography, and adsorption chromatography on hydroxyapatite. COR15amr and the major species of COR15am in chloroplasts co-migrated on both two-dimensional O'Farrell gels and nondenaturing polyacrylamide gels. These data corroborate the site of COR15a processing and indicate no difference in charge or quaternary structure between COR15amr and the major species of COR15am in plants. In contrast, the migration patterns of COR6.6r and COR6.6 on two-dimensional gels suggest that a considerable portion of the COR6.6 population in plants is modified. In the accompanying papers (M.S. Webb, S.J. Gilmour, M.F. Thomashow, P.L. Steponkus [1996] Plant Physiology 111: 301–312; M. Uemura, S.J. Gilmour, M.F. Thomashow, P.L. Steponkus [1996] Plant Physiology 111:313–327), the effects of COR15amr and COR6.6r on the cryostability and lyotropic phase behavior of liposomes are examined.
2018 Korean Society for the Study of Obesity Guideline for the Management of Obesity in Korea

Obesity increases the risks of diabetes, hypertension, and cardiovascular diseases, ultimately contributing to mortality. Korean Society for the Study of Obesity (KSSO) was established to improve the management of obesity through research and education; to that end, the Committee of Clinical Practice Guidelines of KSSO reviews systemic evidence using expert panels to develop clinical guidelines. The clinical practice guidelines for obesity were revised in 2018 using National Health Insurance Service Health checkup data from 2006 to 2015. Following these guidelines, we added a category, class III obesity, which includes individuals with body mass index (BMI) ≥35 kg/m2. Agreeing with the International Federation for the Surgery of Obesity and Metabolic Disorders, Asian Pacific Chapter consensus, we determined that bariatric surgery is indicated for Korean patients with BMI ≥35 kg/m2 and for Korean patients with BMI ≥30 kg/m2 who have comorbidities. The new guidelines focus on guiding clinicians and patients to manage obesity more effectively. Our recommendations and treatment algorithms can serve as a guide for the evaluation, prevention, and management of overweight and obesity.
Phospholipase A2 and Its Role in Brain Tissue

Abstract: Phospholipase A2 (PLA2) is the name for the class of lipolytic enzymes that hydrolyze the acyl group from the sn‐2 position of glycerophospholipids, generating free fatty acids and lysophospholipids. The products of the PLA2‐catalyzed reaction can potentially act as second messengers themselves, or be further metabolized to eicosanoids, platelet‐activating factor, and lysophosphatidic acid. All of these are recognized as bioactive lipids that can potentially alter many ongoing cellular processes. The presence of PLA2 in the central nervous system, accompanied by the relatively large quantity of potential substrate, poses an interesting dilemma as to the role PLA2 has during both physiologic and pathologic states. Several different PLA2 enzymes exist in brain, some of which have been partially characterized. They are classified into two subtypes, CA2+‐dependent and Ca2+‐independent, based on their catalytic dependence on Ca2+. Under physiologic conditions, PLA2 may be involved in phospholipid turnover, membrane remodeling, exocytosis, detoxification of phospholipid peroxides, and neurotransmitter release. However, under pathological situations, increased PLA2 activity may result in the loss of essential membrane glycerophospholipids, resulting in altered membrane permeability, ion homeostasis, increased free fatty acid release, and the accumulation of lipid peroxides. These processes, along with loss of ATP, may be responsible for the loss of membrane phospholipid and subsequent neuronal injury found in ischemia, spinal cord injury, and other neurodegenerative diseases. This review outlines the current knowledge of the PLA2 found in the central nervous system and attempts to define the role of PLA2 during both physiologic and pathologic conditions.
Armadillo: harvesting information for the semantic web

Armadillo [1] is an automatic system for producing domainspecific Semantic Web oriented annotation on large repositories. Armadillo is adaptive: learning how to harvest information with minimal user intervention. The first step performed in the learning process is identifying seed terms for examples of information to be extracted. The seeds, provided by the user from existing data or via connection to a web service, are used to learn from different parts of the repository or in the external world (e.g. the Web). An agent spiders the available space and identifies places where such terms occur (documents, databases, etc.). Rules are induced to model the context in which these terms appear. These rules are then used to extract other examples not contained in the initial lexicon but that appear in similar contexts. All new terms must be confirmed before they are accepted and used to re-seed learning. Multiple strategies are used for confirmation, e.g. a new piece of information is accepted if found within different (linguistic or semantic) contexts. Finally all the extracted information is integrated with the existing knowledge base. The methodology relies on the inherent redundancy of large repositories, e.g. the Web or company-wide repositories. By inherent redundancy we mean the fact that information is frequently represented in different forms in distributed resources. Armadillo has similarities to SemTag [2] which automatically generates instance labels from documents on the web. SemTag’s extraction is shallow for the needs of the Semantic Web: e.g. there is no attempt to automatically discover relations among entities. SemTag can be seen as an extension of a search engine towards semantic indexing and retrieval. Armadillo improves on SemTag by integrating extracted data from numerous sources into a knowledge base (KB). Such a KB can then be used both to access information directly (e.g. via a semantic web agent) and to annotate the pages where information was identified. Armadillo’s architecture is based on Semantic Web Services, where each service is associated to parts of the ontology (e.g. a set of concepts and/or relations) and works in an independent way. Each service can use other services (in-
Disclose More and Risk Less: Privacy Preserving Online Social Network Data Sharing

Many third-party services and applications have integrated the login services of popular Online Social Networks, such as Facebook and Google+, and acquired user information to enrich their services by requesting user's permission. Although users can control the information disclosed to the third parties in a certain granularity, there are still serious privacy risks due to the inference attack. Even if users conceal their sensitive information, attackers can infer their secrets by exploiting the correlations among private and public information with background knowledge. To defend against such attacks, we formulate the social network data sharing problem through an optimization-based approach, which maximizes the users’ self-disclosure utility while preserving their privacy. We propose two privacy-preserving social network data sharing methods to counter the inference attack. One is the efficiency-based privacy-preserving disclosure algorithm (EPPD) targeting the high utility, and the other is to convert the original problem into a multi-dimensional knapsack problem (d-KP) using greedy heuristics with a low computational complexity. We use real-world social network datasets to evaluate the performance. From the results, the proposed methods achieve a better performance when compared with the existing ones.
The association between leisure time physical activity and smoking in adolescence: An examination of potential mediating and moderating factors

Background: Although physical activity has been associated negatively with smoking in adolescence, the association is not well understood. Purpose: This study examines the relationship between adolescents’ leisure time physical activity and smoking behavior, while considering BMI, weight concern, sense of coherence, and physically active self-concept as potential mediating and moderating variables. Method: Data were obtained through a postal survey among 3,940 Danes aged 16 to 20. Bivariate and multivariate logistic regressions were performed to identify significant associations as well as mediating and moderating effects. Results: In the bivariate model, leisure time physical activity was negatively associated with smoking; adolescents who were active at least one hour per week were up to half as likely to smoke as inactive adolescents. In the adjusted model, however, the association disappeared. Further analyses revealed that physically active self-concept acted both as a mediator and as a moderator of the studied relationship. Conclusion: The data suggest that participation in leisure time physical activity is indeed inversely associated with adolescent smoking, but only when physical activity is perceived as an important part of the self. Hence, interventions designed to promote physical activity among youth may also aim to boost physically active self-concepts.
Mainstream media behavior analysis on Twitter: a case study on UK general election

With the development of social media tools such as Facebook and Twitter, mainstream media organizations including newspapers and TV media have played an active role in engaging with their audience and strengthening their influence on the recently emerged platforms. In this paper, we analyze the behavior of mainstream media on Twitter and study how they exert their influence to shape public opinion during the UK's 2010 General Election. We first propose an empirical measure to quantify mainstream media bias based on sentiment analysis and show that it correlates better with the actual political bias in the UK media than the pure quantitative measures based on media coverage of various political parties. We then compare the information diffusion patterns from different categories of sources. We found that while mainstream media is good at seeding prominent information cascades, its role in shaping public opinion is being challenged by journalists since tweets from them are more likely to be retweeted and they spread faster and have longer lifespan compared to tweets from mainstream media. Moreover, the political bias of the journalists is a good indicator of the actual election results.
Estimating Canadian Monetary Policy Regimes

Andolfatto and Gomme (2003) find evidence that Canadian monetary policy appears to alternate between high and low money growth rate regimes, and that private-sector belief formation over these unobserved regimes could induce significant persistence in the propagation of monetary policy shocks. In this paper, we examine the sensitivity of these conclusions by re-estimating the data allowing for the possibility of multiple regimes. In doing so, we find evidence of three (rather than two) distinct monetary policy regimes. In particular, we find that one policy regime is characterized by high money growth with moderate variability. The other two policy regimes are characterized by a common low money growth rate; they are distinguished primarily by their variability (high and low). A simulation exercise based on our three-regime model reveals an improvement in accounting for the behavior of the Canadian economy over some episodes; notably, the sharp increase in interest rates and the curtailment of economic activity in the early 1980s.
Isotope Labeling in MS-based Proteomics

A variety of stable isotope labeling techniques have been developed and used in mass spectrometry (MS)-based proteomics, primarily for relative quantitation of changes in protein abundances between two compared samples, but also for qualitative characterization of differentially labeled proteomes. Differential O/O coding relies on the O exchange that takes place at the C-terminal carboxyl group of proteolytic fragments, where two O atoms are typically replaced by two O atoms by enzyme-catalyzed oxygen-exchange in the presence of H2 O. The resulting mass shift between differentially labeled peptide ions permits identification, characterization and quantitation of proteins fromwhich the peptides are proteolytically generated.This review focuses on the utility of O/O labeling within the context of mass spectrometry-based proteome research. Different strategies employing O/O are examined in the context of global comparative proteome profiling, targeted subcellular proteomics, analysis of post-translational modifications and biomarker discovery. Also discussed are analytical issues related to this technique, including variable O exchange along with advantages and disadvantages of O/O labeling in comparison with other isotope-coding techniques.
Zinc-α-2-Glycoprotein: A Candidate Biomarker for Colon Cancer Diagnosis in Chinese Population

Zinc-α-2-glycoprotein (AZGP1) is a 41-kDa secreted glycoprotein, which has been detected in several malignancies. The diagnostic value of AZGP1 in serum of prostate and breast cancer patients has been reported. Analyzing “The Cancer Genome Atlas” data, we found that in colon cancer AZGP1 gene expression was upregulated at transcriptional level. We hypothesized that AZGP1 could be used as a diagnostic marker of colon cancer. First, we confirmed AZGP1 expression was higher in a set of 28 tumor tissues than in normal colonic mucosa tissues by real-time quantitative PCR and western blot in a Chinese population. We verified that serum concentration of AZGP1 was higher in 120 colon cancer patients compared with 40 healthy controls by ELISA (p < 0.001). Then receiver-operating characteristic (ROC) curve analysis was used to evaluate the predictive diagnostic value of AZGP1 in serum. The area under the curve (AUC) of AZGP1 was 0.742 (p < 0.001, 95% confidence interval (CI) = 0.656–0.827) in between the AUC of carcinoembryonic antigen (CEA) and the AUC of CA19-9, suggesting that predictive diagnostic value of AZGP1 is between CEA and Carbohydrate 19-9 (CA19-9). The combination of AZGP1 with traditional serum biomarkers, CEA and CA19-9, could result in better diagnostic results. To further validate the diagnostic value of AZGP1, a tissue microarray containing 190 samples of primary colon cancer tissue paired with normal colonic tissue was analysed and the result showed that AZGP1 was significantly upregulated in 68.4% (130 of 190) of the primary cancer lesions. In contrast, there was a weakly positive staining in 29.5% (56 of 190) of the normal colonic tissue samples (p < 0.001). Leave-one-out cross-validation was performed on the serum data, and showed that the diagnostic value of AZGP1 had 63.3% sensitivity and 65.0% specificity. Combination of AZGP1, CEA and CA19-9 had improved diagnosis value accuracy with 74.2% sensitivity and 72.5% specificity. These results suggest that AZGP1 is a useful diagnostic biomarker in tissues and serum from a Chinese population.
The Formation of Ceramide-1-phosphate during Neutrophil Phagocytosis and Its Role in Liposome Fusion*

Ceramide, a product of agonist-stimulated sphingomyelinase activation, is known to be generated during the phagocytosis of antibody-coated erythrocytes by polymorphonuclear leukocytes. Agonist-stimulated formation of ceramide-1-phosphate is now shown to occur in 32PO4-labeled neutrophils. Ceramide-1-phosphate is formed by a calcium-dependent ceramide kinase, found predominately in the neutrophil plasma membrane. The neutrophil kinase is specific for ceramide because, in contrast to the bacterial diglyceride kinase, ceramide is not phosphorylated under conditions specific for diglyceride phosphorylation. Conversely, 1,2-diacylglycerol does not serve as substrate for the neutrophil ceramide kinase. Ceramide kinase activation occurs in a time-dependent fashion, reaching peak activity 10 min after formyl peptide stimulation and challenge with antibody-coated erythrocytes. The lipid kinase activity is optimal at pH 6.8. Because the formation of the phagolysosome is a critical event in phagocytosis, the effect of ceramide-1-phosphate in promoting the fusion of liposomes was determined. Both the addition of increasing concentrations of sphingomyelinase D and ceramide-1-phosphate promoted liposomal fusion. In summary, ceramide-1-phosphate is formed during phagocytosis through activation of ceramide kinase. Ceramide-1-phosphate may promote phagolysosome formation.
On RIC bounds of Compressed Sensing Matrices for Approximating Sparse Solutions Using ℓq Quasi Norms

This paper follows the recent discussion on the sparse solution recovery with quasi-norms lq, q 2 (0,1) when the sensing matrix possesses a Restricted Isometry Constant δ2k (RIC). Our key tool is an improvement on a version of “the converse of a generalized Cauchy-Schwarz inequality” extended to the setting of quasi-norm. We show that, if δ2k � 1/2, any minimizer of the lq minimization, at least for those q 2 (0,0.9181], is the sparse solution of the corresponding underdetermined linear system. Moreover, if δ2k � 0.4931, the sparse solution can be recovered by any lq,q 2 (0,1) minimization. The values 0.9181 and 0.4931 improves those reported previously in the literature.
The fable of the bees: incentivizing robust revocation decision making in ad hoc networks

In this paper we present a new key-revocation scheme for ad hoc network environments with the following characteristics: Distributed: Our scheme does not require a permanently available central authority. Active: Our scheme incentivizes rational (selfish but honest) nodes to revoke malicious nodes. Robust: Our scheme is resilient against large numbers of colluding malicious nodes (30% of the network for a detection error rate of 15%). Detection error tolerant: Revocation decisions fundamentally rely on intrusion detection systems (IDS). Our scheme is active for any meaningful IDS (IDS error rate 0.5) and robust for an IDS error rate of up to 29%. Several schemes in the literature have two of the above four characteristics (characteristic four is typically not explored). This work is the first to possess all four, making our revocation scheme well-suited for environments such as ad hoc networks, which are very dynamic, have significant bandwidth-constraints, and where many nodes must operate under the continual threat of compromise.
Improvement for distortion resistance of Delaunay triangulation net-based fingerprint templates

Fingerprint template is considered as an effective method to solve the problem of fingerprint protection, and an indispensable key technology in the identification field. Among them, the Delaunay triangulation net-based template is a new type of solution. However, such a triangulation net is greatly affected by the elastic distortion of the fingerprint. In this study, a novel improvement, Delaunay tentacle, is proposed to this issue. Based on the orderly degradation of the Delaunay triangulation net, the Delaunay tentacle, kernel, and centre can be generated in turn. By calculating the deformation of the tentacles, this innovative, improved Delaunay triangulation structure can sense and resist distortion. The proposed algorithm is tested on the Fingerprint Verification Competition databases, and the model is compared with other current similar schemes. Experimental results demonstrate that it has promising performance.
Operations for Learning with Graphical Models

This paper is a multidisciplinary review of empirical, statistical learning from a graphical model perspective. Well-known examples of graphical models include Bayesian networks, directed graphs representing a Markov chain, and undirected networks representing a Markov field. These graphical models are extended to model data analysis and empirical learning using the notation of plates. Graphical operations for simplifying and manipulating a problem are provided including decomposition, differentiation, andthe manipulation of probability models from the exponential family. Two standard algorithm schemas for learning are reviewed in a graphical framework: Gibbs sampling and the expectation maximizationalgorithm. Using these operations and schemas, some popular algorithms can be synthesized from their graphical specification. This includes versions of linear regression, techniques for feed-forward networks, and learning Gaussian and discrete Bayesian networks from data. The paper concludes by sketching some implications for data analysis and summarizing how some popular algorithms fall within the framework presented. The main original contributions here are the decompositiontechniques and the demonstration that graphical models provide a framework for understanding and developing complex learning algorithms.