Miracle-dz/UniFAR-FTUs huggingface dataset:
Inorganic Arsenic Activates Reduced NADPH Oxidase in Human Primary Macrophages through a Rho Kinase/p38 Kinase Pathway1

Inorganic arsenic is an immunotoxic environmental contaminant to which millions of humans are chronically exposed. We recently demonstrated that human primary macrophages constituted a critical target for arsenic trioxide (As2O3), an inorganic trivalent form. To specify the effects of arsenic on macrophage phenotype, we investigated in the present study whether As2O3 could regulate the activity of NADPH oxidase, a major superoxide-generating enzymatic system in human phagocytes. Our results show that superoxide levels were significantly increased in a time-dependent manner in blood monocyte-derived macrophages treated with 1 μM As2O3 for 72 h. Concomitantly, As2O3 induced phosphorylation and membrane translocation of the NADPH oxidase subunit p47phox and it also increased translocation of Rac1 and p67phox. Apocynin, a selective inhibitor of NADPH oxidases, prevented both p47phox translocation and superoxide production. NADPH oxidase activation was preceded by phosphorylation of p38-kinase in As2O3-treated macrophages. The p38-kinase inhibitor SB-203580 prevented phosphorylation and translocation of p47phox and subsequent superoxide production. Pretreatment of macrophages with the Rho-kinase inhibitor Y-27632 was found to mimic inhibitory effects of SB-203580 and to prevent As2O3-induced phosphorylation of p38 kinase. Treatment with As2O3 also resulted in an increased secretion of the proinflammatory chemokine CCL18 that was fully inhibited by both apocynin and SB-203580. Taken together, our results demonstrate that As2O3 induced a marked activation of NADPH oxidase in human macrophages, likely through stimulation of a Rho-kinase/p38-kinase pathway, and which may contribute to some of the deleterious effects of inorganic arsenic on macrophage phenotype.
Collaboration and Conflict in the Development of a Computerized Dispatch Facility

Recent research on the social and cultural aspects of systems development work has focused on the work of professional software and systems designers. A complementary approach is to look at the work of end users as systems developers, whose informal systems design work is frequently ignored or undervalued in organizations and by IS researchers. This case study, of an application to facilitate dispatch work in a large organization, describes a history of collaboration and conflict between IS professionals and end users as systems designers. Application development was initiated by end users, the initial programming was carried out by IS professionals in collaboration with end users, and the subsequent implementation and enhancement of the application was shared, and passed back and forth between end users and the organization's IS department over a period of several years. We take a Social Construction of Technology approach to describing this history, examining the mixture of cooperation and conflict between the Dispatch and IS departments in terms of the differing interpretations of the application by the social groups involved in its history. A constructivist approach to studying systems design allows us to recognize the unique expertise end users bring to systems development work, and provides a useful means for describing the political aspects of systems design and implementation over an extended time period.
Joint local and non-local priors for ground-based astronomical image denoising

Ground-based astronomical images usually suffer from the degradation of random noise, which has a negative impact on the subsequent performance. It is expected that local and nonlocal variations are the two sides of the same coin in image modeling. However, most of existing denoising methods focus on modeling the sparsity of local patches or the nonlocal self-similarity information individually, which may result in poor image structure representation ability. To remedy this issue, we propose a unified approach via combining the framelet and the low-rank prior scheme for astronomical image denoising. On one hand, the synthesis-based low-rank prior is employed to reveal the intrinsic low-dimensional subspace (namely the main edges) of the similar patches. On the other hand, the analysis-based framelet prior is introduced to capture the local subtle texture structures. Experimental results validate the effectiveness of this combination, and the proposed method outperforms the state-of-the-art denoising methods.
Identification of a phosphorylation site and functional analysis of conserved aspartic acid residues of OmpR, a transcriptional activator for ompF and ompC in Escherichia coli

In Escherichia coli the OmpR and EnvZ proteins regulate the expression of the outer membrane porin proteins OmpC and OmpF. EnvZ and OmpR belong to a family of sensor/effector protein pairs that control adaptation to a variety of environmental conditions. EnvZ acts as the sensor protein that phosphorylates OmpR, which in turn regulates porin gene expression. The level of phosphorylated OmpR appears to be a determining factor for ompC and ompF regulation. Phosphorylation of OmpR is considered to occur at one or more aspartic acid residues (Asp‐11, Asp‐12 and/or Asp‐55) that are highly conserved among the effector proteins. In this report we biochemically characterized the aspartic acid residue(s) in OmpR that were phosphorylated by EnvZ. Reduction of aspartyl phosphate residues in the amino‐terminal domain of OmpR with [3H]‐NaBH4 indicated that Asp‐55 was a primary site of modification. We further studied the role of the highly conserved aspartate residues by creating OmpR mutants having aspartate to alanine substitutions at positions 11 (D11A), 12 (D12A) and 55 (D55A). Studies of ompF and ompC expression as well as in vivo and in vitro phosphorylation experiments also demonstrated that while Asp‐55 is the primary phosphate acceptor site in OmpR, Asp‐11 may also serve as a phosphorylation site, particularly in the absence of Asp‐55.
Graphical models of protein–protein interaction specificity from correlated mutations and interaction data

Protein–protein interactions are mediated by complementary amino acids defining complementary surfaces. Typically not all members of a family of related proteins interact equally well with all members of a partner family; thus analysis of the sequence record can reveal the complementary amino acid partners that confer interaction specificity. This article develops methods for learning and using probabilistic graphical models of such residue “cross‐coupling” constraints between interacting protein families, based on multiple sequence alignments and information about which pairs of proteins are known to interact. Our models generalize traditional consensus sequence binding motifs, and provide a probabilistic semantics enabling sound evaluation of the plausibility of new possible interactions. Furthermore, predictions made by the models can be explained in terms of the underlying residue interactions. Our approach supports different levels of prior knowledge regarding interactions, including both one‐to‐one (e.g., pairs of proteins from the same organism) and many‐to‐many (e.g., experimentally identified interactions), and we present a technique to account for possible bias in the represented interactions. We apply our approach in studies of PDZ domains and their ligands, fundamental building blocks in a number of protein assemblies. Our algorithms are able to identify biologically interesting cross‐coupling constraints, to successfully identify known interactions, and to make explainable predictions about novel interactions. Proteins 2009. © 2009 Wiley‐Liss, Inc.
binding in an energetic model for glycine riboswitch folding Dissecting electrostatic screening , specific ion binding , and ligand Material Supplemental

Riboswitches are gene-regulating RNAs that are usually found in the 59-untranslated regions of messenger RNA. As the sugarphosphate backbone of RNA is highly negatively charged, the folding and ligand-binding interactions of riboswitches are strongly dependent on the presence of cations. Using small angle X-ray scattering (SAXS) and hydroxyl radical footprinting, we examined the cation dependence of the different folding stages of the glycine-binding riboswitch from Vibrio cholerae. We found that the partial folding of the tandem aptamer of this riboswitch in the absence of glycine is supported by all tested monoand divalent ions, suggesting that this transition is mediated by nonspecific electrostatic screening. Poisson–Boltzmann calculations using SAXS-derived low-resolution structural models allowed us to perform an energetic dissection of this process. The results showed that a model with a constant favorable contribution to folding that is opposed by an unfavorable electrostatic term that varies with ion concentration and valency provides a reasonable quantitative description of the observed folding behavior. Glycine binding, on the other hand, requires specific divalent ions binding based on the observation that Mg, Ca, and Mn facilitated glycine binding, whereas other divalent cations did not. The results provide a case study of how iondependent electrostatic relaxation, specific ion binding, and ligand binding can be coupled to shape the energetic landscape of a riboswitch and can begin to be quantitatively dissected.
Boosting Relation Extraction with Limited Closed-World Knowledge

This paper presents a new approach to improving relation extraction based on minimally supervised learning. By adding some limited closed-world knowledge for confidence estimation of learned rules to the usual seed data, the precision of relation extraction can be considerably improved. Starting from an existing baseline system we demonstrate that utilizing limited closed world knowledge can effectively eliminate "dangerous" or plainly wrong rules during the bootstrapping process. The new method improves the reliability of the confidence estimation and the precision value of the extracted instances. Although recall suffers to a certain degree depending on the domain and the selected settings, the overall performance measured by F-score considerably improves. Finally we validate the adaptability of the best ranking method to a new domain and obtain promising results.
Laser ablation and high precision patterning of biomaterials and intraocular lenses

The use of intraocular lenses (IOL) is the most promising method for restoring excellent vision in cataract surgery. In addition, multifocal intraocular lenses for good distant and near vision are investigated. Several new materials, techniques and patterns are studied for the formation and etching of intraocular lenses in order to improve their optical properties and reduce the diffractive aberrations. As pulsed laser ablation is well established as a universal tool for surface processing of organic polymer materials, this study was focused in using laser ablation with short and ultra short laser pulses for surface modification of PMMA and intraocular lenses, instead of using other conventional techniques. The main advantage of using very short laser pulses, e.g. of ns, ps or fs duration, is that heat diffusion into the polymer material is negligible. As a result high precision patterning of the sample, without thermal damage of the surroundings, becomes possible. In this study, laser ablation was performed using commercially available hydrophobic acrylic IOLs, hydrophilic acrylic IOLs, and PMMA IOLs, with various diopters. We investigated the ablation efficiency and the phenomenology of the etched patterns by testing the ablation rate, versus laser energy fluence, at several wavelengths and the surface modification with atomic force microscopy (AFM), or scanning electron microscopy (SEM). The irradiated polymers have different optical properties, at the applied wavelengths, and therefore, present different ablation behaviour and morphology of the laser ablated crater walls and surrounding surfaces. The experimental results, some theoretical assumptions for mathematical modeling of the relevant ablation mechanisms are discussed.
Crowd crawling: towards collaborative data collection for large-scale online social networks

The emerging research for online social networks (OSNs) requires a huge amount of data. However, OSN sites typically enforce restrictions for data crawling, such as request rate limiting on a per-IP basis. It becomes challenging for an individual research group to collect sufficient data by using its own network resources. In this paper, we introduce and motivate crowd crawling, which allows multiple research groups to efficiently crawl data in a collaborative way. Crowd crawling is carefully designed by addressing several practical challenges including resource diversity of different partners, strict request rate limiting from OSN providers, and data fidelity. We implemented and deployed a crowd crawling prototype on PlanetLab, and demonstrated its performance through evaluations. We have made the datasets crawled in our evaluation publicly available.
Supporting model-based construction of semantic-enabled Web applications

Semantic annotation of Web content is in the core of the current semantic Web activity. The operationalization of the semantic Web raises the challenge on how to systematically integrate semantic annotations into generated Web application pages. In this paper, we present VizCo, a tool for systematically integrating RDF based semantically enriched application domain models into the process of setting up dynamically generated Web application user interfaces and supporting their evolution. The form-based Web pages are annotated based on the underlying domain model. Combined with further mapping tools, VizCo is used in our Web application development framework for coupling the domain model views and, indirectly, the underlying application data with other Web application components, especially with elements of the user interface. In contrast to a direct coupling with the application data an additional semantic layer is introduced. We follow a pragmatic approach that utilizes domain information extracted from application schemata and data as a starting point. Both the domain model and its coupling to the data source can be manually refined and extended. The couplings are dynamically translated into bi-directional data bindings at runtime.
Effects of physiological aging and cerebrovascular risk factors on the hemodynamic response to brain activation: A functional transcranial doppler study

The influence of the vascular system on the coupling of cerebral blood flow (CBF) to focal brain activation during aging is incompletely understood. Using functional transcranial Doppler sonography and a hypercapnic challenge as a marker of intact cerebral vasoreactivity, we determined CBF velocity (CBFV) changes in response to a language and arithmetic task in a group of 43 healthy young subjects (mean age 32 ± 8.6 years), 18 healthy old subjects (mean age 64 ± 9.8 years) and 29 old subjects with risk factors for an atherosclerosis (mean age 69 ± 8.4 years). Despite a similar performance during the cognitive tasks the CBFV changes were significantly lower in the group of old subjects with vascular risk factors compared with the healthy young and old subjects. Similarly, the CBFV changes during hypercapnia were significantly lower in the group of old subjects with vascular risk factors compared with the healthy young and old subjects. In contrast, both cognitive tasks and hypercapnia produced comparable CBFV changes in the group of healthy young and old subjects. These results suggest that the hemodynamic response to neuronal activation is unaffected by aging alone, whereas the presence of cardiovascular risk factors significantly diminishes the capability of cerebral vessels to react to vasodilating stimuli.
Regulation of Nav1.7: A Conserved SCN9A Natural Antisense Transcript Expressed in Dorsal Root Ganglia

The Nav1.7 voltage-gated sodium channel, encoded by SCN9A, is critical for human pain perception yet the transcriptional and post-transcriptional mechanisms that regulate this gene are still incompletely understood. Here, we describe a novel natural antisense transcript (NAT) for SCN9A that is conserved in humans and mice. The NAT has a similar tissue expression pattern to the sense gene and is alternatively spliced within dorsal root ganglia. The human and mouse NATs exist in cis with the sense gene in a tail-to-tail orientation and both share sequences that are complementary to the terminal exon of SCN9A/Scn9a. Overexpression analyses of the human NAT in human embryonic kidney (HEK293A) and human neuroblastoma (SH-SY5Y) cell lines show that it can function to downregulate Nav1.7 mRNA, protein levels and currents. The NAT may play an important role in regulating human pain thresholds and is a potential candidate gene for individuals with chronic pain disorders that map to the SCN9A locus, such as Inherited Primary Erythromelalgia, Paroxysmal Extreme Pain Disorder and Painful Small Fibre Neuropathy, but who do not contain mutations in the sense gene. Our results strongly suggest the SCN9A NAT as a prime candidate for new therapies based upon augmentation of existing antisense RNAs in the treatment of chronic pain conditions in man.
Hybrid biogeography-based optimization for solving vendor managed inventory system

In the modern era of industrialization and globalization, distribution and control of goods are essential aspects for multinational corporations and strategic partners. Vendor managed inventory (VMI) is one of the well-known strategies of merchandizing between supplier and retailer. In this paper, we consider different number of suppliers and retailers to perform business under VMI system and formulate three: single-supplier and single-retailer, single-supplier and multi-retailer, and multi-supplier and multi-retailer VMI systems. The objective is to minimize the total cost of VMI system. Since it is a non-linear integer programming problem, this paper proposes a novel hybrid biogeography-based optimization algorithm to solve it. We enhance the proposed algorithm by embedding stochastic fractal search (SFS) in biogeography-based optimization (BBO). SFS algorithm is a newly developed powerful evolutionary algorithm to find global optimum much faster and efficiently. The diffusion process of SFS improved the exploitation ability of search in BBO. Our proposed algorithm is applied on all three versions of VMI systems under different constraints. We have considered suitable input data for all the different problems and obtained the results. By comparison, we show that the results outperformed for all VMI systems.
Audio-Based Distributional Representations of Meaning Using a Fusion of Feature Encodings

Recently a “Bag-of-Audio-Words” approach was proposed [1] for the combination of lexical features with audio clips in a multimodal semantic representation, i.e., an Audio Distributional Semantic Model (ADSM). An important step towards the creation of ADSMs is the estimation of the semantic distance between clips in the acoustic space, which is especially challenging given the diversity of audio collections. In this work, we investigate the use of different feature encodings in order to address this challenge following a two-step approach. First, an audio clip is categorized with respect to three classes, namely, music, speech and other. Next, the feature encodings are fused according to the posterior probabilities estimated in the previous step. Using a collection of audio clips annotated with tags we derive a mapping between words and audio clips. Based on this mapping and the proposed audio semantic distance, we construct an ADSM model in order to compute the distance between words (lexical semantic similarity task). The proposed model is shown to significantly outperform (23.6% relative improvement in correlation coefficient) the state-of-the-art results reported in the literature.
High Expectations Across Multiple Domains, Peer Norms, and Physical Dating Violence Among California Adolescents

The purpose of this study is, first, to assess whether high expectation messages (from school, home, and community), and peer norms, were associated with physical dating violence victimization (PDV) among a representative sample of California middle and high school students, and second, to assess whether these associations differed by gender and grade level and/or were mediated by self-efficacy. Data from 7th-, 9th-, and 11th-grade respondents of the 2008-2010 California Healthy Kids Survey (CHKS) were analyzed (N = 85,198). CHKS is an anonymous, school-based cross-sectional survey. Logistic regression was used to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for expectations in each domain (school, community, and home), peers norms, and their cumulative effects on physical dating violence victimization. We examined interactions for expectations and for peer norms by gender and grade level, and tested the mediation effect of self-efficacy. Ten percent of students reported experiencing physical dating violence victimization in the past year. Students who reported high overall expectations (in multiple domains) had significantly lower odds of experiencing dating violence (OR = 0.24, CI = [0.20, 0.28]) compared with those who reported very low expectations. This association held across all expectation domains and peer norms when tested in separate models and also when tested together in a single model. High expectations in the home domain and peer norms showed the lowest odds. Associations between high expectations and dating violence were similar across gender and grade levels. Self-efficacy partially mediated the associations between high expectations and dating violence. Suggestions for future research are presented.
Semantic based Web Prefetching using Decision Tree Induction

Access delays on the web are the major issues, users experiencing these days. Web Prefetching has provided tremendous results in decreasing this access delay. Existing methods are based on URL's of the web objects, user access. Use of domain ontology with the semantics can make this process easier and more effective. Semantics basically governs the relationships among objects of interest for the current scenario. Earlier methods also used to prefetch web pages, which were never being accessed. This paper provides a semantic based Prefetching scheme for the web browsers to overcome the limitations of existing systems. Semantic based prefetching uses anchor text as a base for finding out patterns. Anchor text is present in the hyperlinks of web page. With the help of anchor text, ranking of web page that will be received by search engine can also be determined. This scheme applies Decision Tree Induction for computing the probability of the anchor text and finding out patterns to be prefetched. SPRINT is used in the proposed framework as the decision tree induction method. For improving the performance, pruning is also applied on the Decision Tree Induction. The concept is elaborated with the help of example of mining mobile search engine. The experimental results are performed in Matlab 5.0.