gebhart/patrepeval huggingface dataset:
Functional Characterization of Bacteria Isolated from Ancient Arctic Soil Exposes Diverse Resistance Mechanisms to Modern Antibiotics (2015)

Using functional metagenomics to study the resistomes of bacterial communities isolated from different layers of the Canadian high Arctic permafrost, we show that microbial communities harbored diverse resistance mechanisms at least 5,000 years ago. Among bacteria sampled from the ancient layers of a permafrost core, we isolated eight genes conferring clinical levels of resistance against aminoglycoside, β-lactam and tetracycline antibiotics that are naturally produced by microorganisms. Among these resistance genes, four also conferred resistance against amikacin, a modern semi-synthetic antibiotic that does not naturally occur in microorganisms. In bacteria sampled from the overlaying active layer, we isolated ten different genes conferring resistance to all six antibiotics tested in this study, including aminoglycoside, β-lactam and tetracycline variants that are naturally produced by microorganisms as well as semi-synthetic variants produced in the laboratory. On average, we found that resistance genes found in permafrost bacteria conferred lower levels of resistance against clinically relevant antibiotics than resistance genes sampled from the active layer. Our results demonstrate that antibiotic resistance genes were functionally diverse prior to the anthropogenic use of antibiotics, contributing to the evolution of natural reservoirs of resistance genes.
EGR3 as a potential susceptibility gene for schizophrenia in Korea (2010)

Early growth response (EGR) genes play critical roles in signal transduction in the brain, which is involved in neuronal activation, brain development, and synaptic plasticity. EGR genes, including EGR2, EGR3, and EGR4, showed significant association with schizophrenia in Japanese schizophrenic pedigrees. In particular, EGR3, which resides at the chromosomal location 8p21.3, was suggested to be a potential susceptibility gene in schizophrenia based on a study of Japanese cases. However, this requires further replication with an independent sample set. We investigated the association of the EGR3 and EGR2 genes, which were suggested as potential susceptibility genes for schizophrenia supported by both genetic association and postmortem brain expression studies, with schizophrenia in Korean patients. Along with 350 healthy individuals, 244 schizophrenic patients were analyzed. Among the four examined single-nucleotide polymorphisms (SNPs) of EGR3 (rs1008949, rs7009708, rs35201266, and rs3750192), SNP rs35201266 in intron 1 of the EGR3 gene showed a significant association with schizophrenia (P = 0.0008, χ(2) = 11.156, OR = 1.493), which withstands multiple testing correction. In addition, the "T-G-C-G" haplotype of EGR3 was under-represented in the patients with schizophrenia (P = 0.0073, χ(2) = 7.188, OR = 0.697). However, an association between the SNPs of EGR2 (rs2295814 and rs2297488) and schizophrenia was not found. These findings are consistent with the previous genetic association of the EGR3 gene in Japanese cohorts, which is the first replication concerning the association of EGR3 with schizophrenia in an independent cohort. Taken together, EGR3 could be suggested as a compelling susceptibility gene in schizophrenia.
Cross-view Asymmetric Metric Learning for Unsupervised Person Re-identification (2017)

While metric learning is important for Person re-identification (RE-ID), a significant problem in visual surveillance for cross-view pedestrian matching, existing metric models for RE-ID are mostly based on supervised learning that requires quantities of labeled samples in all pairs of camera views for training. However, this limits their scalabilities to realistic applications, in which a large amount of data over multiple disjoint camera views is available but not labelled. To overcome the problem, we propose unsupervised asymmetric metric learning for unsupervised RE-ID. Our model aims to learn an asymmetric metric, i.e., specific projection for each view, based on asymmetric clustering on cross-view person images. Our model finds a shared space where view-specific bias is alleviated and thus better matching performance can be achieved. Extensive experiments have been conducted on a baseline and five large-scale RE-ID datasets to demonstrate the effectiveness of the proposed model. Through the comparison, we show that our model works much more suitable for unsupervised RE-ID compared to classical unsupervised metric learning models. We also compare with existing unsupervised RE-ID methods, and our model outperforms them with notable margins. Specifically, we report the results on large-scale unlabelled RE-ID dataset, which is important but unfortunately less concerned in literatures.
Immunoglobulins: 25 Years of Immunoinformatics and IMGT-ONTOLOGY (2014)

IMGT®, the international ImMunoGeneTics information system® (CNRS and Montpellier University) is the global reference in immunogenetics and immunoinformatics. By its creation in 1989, IMGT® marked the advent of immunoinformatics, which emerged at the interface between immunogenetics and bioinformatics. IMGT® is specialized in the immunoglobulins (IG) or antibodies, T cell receptors (TR), major histocompatibility (MH), and IgSF and MhSF superfamilies. IMGT® has been built on the IMGT-ONTOLOGY axioms and concepts, which bridged the gap between genes, sequences and three-dimensional (3D) structures. The concepts include the IMGT® standardized keywords (identification), IMGT® standardized labels (description), IMGT® standardized nomenclature (classification), IMGT unique numbering and IMGT Colliers de Perles (numerotation). IMGT® comprises seven databases, 15,000 pages of web resources and 17 tools. IMGT® tools and databases provide a high-quality analysis of the IG from fish to humans, for basic, veterinary and medical research, and for antibody engineering and humanization. They include, as examples: IMGT/V-QUEST and IMGT/JunctionAnalysis for nucleotide sequence analysis and their high-throughput version IMGT/HighV-QUEST for next generation sequencing, IMGT/DomainGapAlign for amino acid sequence analysis of IG domains, IMGT/3Dstructure-DB for 3D structures, contact analysis and paratope/epitope interactions of IG/antigen complexes, and the IMGT/mAb-DB interface for therapeutic antibodies and fusion proteins for immunological applications (FPIA).
Quantum codes of minimum distance two (1997)

It is reasonable to expect the theory of quantum codes to be simplified in the case of codes of minimum distance 2; thus, it makes sense to examine such codes in the hopes that techniques that prove effective there will generalize. With this in mind, we present a number of results on codes of minimum distance 2. We first compute the linear programming bound on the dimension of such a code, then show that this bound can only be attained when the code either is of even length, or is of length 3 or 5. We next consider questions of uniqueness, showing that the optimal code of length 2 or 4 is unique (implying that the well-known one-qubit-in-five single-error correcting code is unique), and presenting nonadditive optimal codes of all greater even lengths. Finally, we compute the full automorphism group of the more important distance 2 codes, allowing us to determine the full automorphism group of any GF(4)-linear code.
Development of Nanoparticle Libraries for Biosensing (2005)

Magnetic and magnetofluorescent nanoparticles have become important materials for biological applications especially for sensing, separation, and imaging. To achieve target specificity, these nanomaterials are often covalently modified with binding proteins such as antibodies or proteins. Here we report on the creation of nanoparticle libraries that achieve specificity through multivalent modification with small molecules. We explore different synthetic routes to attach small molecules with anhydride, amine, hydroxyl carboxyl, thiol, and epoxy handles. We show that the derived nanomaterials have unique biological functions, possess different behaviors in cell screens, and can be used as substrates for biological screens.
Advancing beyond current generation dye-sensitized solar cells (2008)

The most efficient dye-sensitized solar cells (DSSCs) have had essentially the same configuration (nanoparticle TiO2 sensitized with [Ru(4,4′-dicarboxy-2,2′-bipyridine)2(NCS)2] in contact with I3−/I−) for the last 17 years. In this article we outline the strategies for improving each of the three major photo-relevant components of a DSSC, review literature reports consistent with these strategies and suggest future directions. Finally we explore the potential of future generation DSSCs for advancing energy-conversion performance.
Antitumor activity of ZD1694 (tomudex) against human head and neck cancer in nude mouse models: role of dosing schedule and plasma thymidine. (1999)

We studied the antitumor activity and toxicity of ZD1694 (tomudex), a specific inhibitor of thymidylate synthase (TS), in nude mice bearing human head and neck squamous cell carcinoma A253 and FaDu xenografts. Mice were treated by single i.v. push (i.v. x 1), i.v. push once a week for 3 weeks (weekly x 3), and i.v. push once a day for 5 days (daily x 5), and the maximum tolerated doses (MTDs) of ZD1694 were 300 mg/kg, 60 mg/kg/week, and 30 mg/kg/day, respectively. ZD1694 was moderately active against both A253 and FaDu xenografts. Antitumor activity was schedule-dependent in both tumors: weekly x 3 > or = i.v. x 1 >> daily x 5. In contrast, the rank order of toxicity was daily x 5 >> weekly x 3 > or = i.v. x 1. ZD1694 at the MTD produced 20% complete tumor regression and 20% partial tumor regression (PR) with i.v. x 1 and weekly x 3 schedules and 12-day tumor growth delay with daily x 5 schedule against FaDu xenografts. No complete tumor regression was achieved with ZD1694 with any schedule against A253; a 20% PR, 40% PR, and 10-day tumor growth delay were observed with i.v. x 1, weekly x 3, and daily x 5 schedules, respectively. The data indicate that ZD1694 was slightly more effective against FaDu than against A253. Of interest and potential clinical importance was the observation that ZD1694 was still active at doses lower than the MTD (> or =1/3 MTD), which showed a high therapeutic index and wide safety margin. Study of ZD1694 compared with 5-fluorouracil and 5-fluoro-2'-deoxyuridine at the MTD revealed that the antitumor activity of ZD1694 was comparable with or superior to 5-fluorouracil and 5-fluoro-2'-deoxyuridine against both A253 and FaDu xenografts, with less toxicity. High plasma thymidine in mouse relative to human (approximately 1.3 microM and <0.1 microM, respectively) may complicate the study of antitumor activity and toxicity of TS inhibitors with human tumor xenografts grown in the mouse. To test this hypothesis, we preadministered methoxypolyethyleneglycol-conjugated thymidine phosphorylase (MPEG-TPase; 2500 units/kg/dose) to reduce mouse plasma thymidine, then treated with various doses of ZD1694 using the daily x 5 or i.v. x 1 schedules in the A253 tumor model. MPEG-TPase significantly increased the toxicity of ZD1694; the MTD of ZD1694 plus MPEG-TPase was reduced 3- and 10-fold compared with ZD1694 alone for i.v x 1 and daily x 5 schedules, respectively. However, preadministration of MPEG-TPase did not potentiate the antitumor activity of ZD1694 with either schedule. The data indicate that the study of TS inhibitors in rodent models may not be suitable for predicting a safe dose for clinical study. However, rodent models, particularly human tumor xenografts, are still useful models for evaluation of antitumor activity and schedule selection for TS inhibitors.
Identification of a signaling complex involving CD2, ζ chain and p59fyn in T lymphocytes (1994)

CD2 is a cell surface receptor molecule which has been implicated in cell-cell adhesion and signaling functions in T lymphocytes and natural killer cells. The mechanism by which extracellular stimuli induce CD2-regulated signal transduction events is largely unknown. However, there is increasing evidence that in cells of hematopoietic origin several receptor-mediated signaling mechanisms involve transmembrane polypeptides related to the CD3 zeta chain and the activation of protein tyrosine kinases. We have therefore investigated the potential involvement of zeta chain and src family protein tyrosine kinases in signal transduction pathways initiated by CD2. Using in vitro kinase assays on CD2 immunoprecipitates from detergent lysates of T lymphocytes, we identified a complex consisting of CD2, zeta chain and the src family kinases p59fyn and p56lck. Furthermore, using double indirect immunofluorescence combined with capping techniques, we have revealed such complexes in viable T lymphocytes. These findings provide evidence for a multimolecular signaling complex consisting of at least CD2, zeta chain and p59fyn in T lymphocytes and suggest a critical role for this complex in the initiation of CD2-mediated cellular activation by regulating the activation of intracellular signaling molecules.
GraphLab: A New Framework for Parallel Machine Learning (2010)

Designing and implementing efficient, provably correct parallel machine learning (ML) algorithms is challenging. Existing high-level parallel abstractions like MapReduce are insufficiently expressive while low-level tools like MPI and Pthreads leave ML experts repeatedly solving the same design challenges. By targeting common patterns in ML, we developed GraphLab, which improves upon abstractions like MapReduce by compactly expressing asynchronous iterative algorithms with sparse computational dependencies while ensuring data consistency and achieving a high degree of parallel performance. We demonstrate the expressiveness of the GraphLab framework by designing and implementing parallel versions of belief propagation, Gibbs sampling, Co-EM, Lasso and Compressed Sensing. We show that using GraphLab we can achieve excellent parallel performance on large scale real-world problems.
Demonstration of Allelic Exchange in the Slow-Growing Bacterium Mycobacterium avium subsp. paratuberculosis , and Generation of Mutants with Deletions at the pknG, relA , and lsr2 Loci (2008)

Mycobacterium avium subsp. paratuberculosis is the causative pathogen of Johne's disease, a chronic inflammatory wasting disease in ruminants. This disease has been difficult to control because of the lack of an effective vaccine. To address this need, we adapted a specialized transduction system originally developed for M. tuberculosis and modified it to improve the efficiency of allelic exchange in order to generate site-directed mutations in preselected M. avium subsp. paratuberculosis genes. With our novel optimized method, the allelic exchange frequency was 78 to 100% and the transduction frequency was 1.1 x 10(-7) to 2.9 x 10(-7). Three genes were selected for mutagenesis: pknG and relA, which are genes that are known to be important virulence factors in M. tuberculosis and M. bovis, and lsr2, a gene regulating lipid biosynthesis and antibiotic resistance. Mutants were successfully generated with a virulent strain of M. avium subsp. paratuberculosis (M. avium subsp. paratuberculosis K10) and with a recombinant K10 strain expressing the green fluorescent protein gene, gfp. The improved efficiency of disruption of selected genes in M. avium subsp. paratuberculosis should accelerate development of additional mutants for vaccine testing and functional studies.
C‐Terminal Ladder Sequencing by an Approach Combining Chemical Degradation with Analysis by Matrix‐Assisted‐Laser‐Desorption Ionization Mass Spectrometry (1997)

A chemical procedure for the degradation of peptides and analysis by matrix-assisted-laser-desorption ionization mass spectrometry (MALDI-MS) was used for C-terminal sequence determination. The method allowed us to determine up to eight amino acid residues in the lower picomole range by mass analysis without any repetitions of the degradation nor any extraction or purification of the truncated peptide chains. The C-terminal degradation of all 20 common amino acid residues was proved by applying this method. Extended C-terminal sequence information from enzymatic digests using carboxypeptidase P was obtained by combining the enzymatic with the chemical mass spectrometric approach. Furthermore the amino acids lysine and glutamine, with the same masses, were distinguishable due to the formation of acetyl-lysine in the chemical process.
Nature of the immunogenic moiety recognized by the human T cell proliferating in response to tetanus toxoid antigen (1981)

This study was undertaken to investigate the nature of the immunogenic moiety recognized by the human T cell which proliferates in response to tetanus toxoid (TT) antigen. Immunosorbent-purified anti-TT IgG antibodies failed, even when added in great excess, to inhibit T cell proliferation in response to TT. Urea-denatured (UD) TT antigen containing less than 1% native TT, as assessed by its reactivity with antibodies raised against native TT, triggered proliferation in T cells to an extent equal to that seen with native TT. The proliferative response to UDTT was seen only in T cells obtained from donors immune to TT and was inhibited by antisera to DRw antigens of the cell donor. T cells responding to TT and to UDTT essentially overlapped because exposure to 5'-bromo-2-deoxyuridine and light of T cells prestimulated with TT or UDTT abolished the specific response to both forms of the TT antigen but not to phytohemagglutinin or to Monilia antigen. It is concluded that proliferating human T cells recognize determinants which differ from those that elicit an antibody response and which may arise as a result of antigen processing by macrophages. The implications of these present results on the nature of the human T cell receptor for antigen are discussed.
Development of Peptide Antagonists for the Androgen Receptor Using Combinatorial Peptide Phage Display (2005)

Abstract Under the auspices of the Nuclear Receptor Signaling Atlas (NURSA) , we have undertaken to evaluate the feasibility of targeting nuclear receptor-coactivator surfaces for new drug discovery. The underlying objective of this approach is to provide the research community with reagents that can be used to modulate the transcriptional activity of nuclear receptors. Using combinatorial peptide phage display, we have been able to develop peptide antagonists that target specific nuclear receptor (NR)-coactivator binding surfaces. It can be appreciated that reagents of this nature will be of use in the study of orphan nuclear receptors for whom classical ligands have not yet been identified. In addition, because the interaction of coactivators with the receptor is an obligate step for NR transcriptional activity, it is anticipated that peptides that block these interactions will enable the definition of the biological and pharmacological significance of individual NR-coactivator interactions. In this report, we describe the use of this approach to develop antagonists of the androgen receptor by targeting its coactivator-binding pocket and their use to study the coactivator-binding surface of this receptor. Based on our findings, we believe that molecules that function by disrupting the androgen receptor-cofactor interactions will have use in the treatment of prostate cancer.
Cell type-specific control of human neuronectin secretion by polypeptide mediators and phorbol ester. (1989)

Neuronectin (NEC1) is a human extracellular matrix (ECM) protein expressed with a unique rostrocaudal pattern in white matter of the normal adult central nervous system. In addition, NEC1 is expressed in normal fetal and adult smooth muscle, along certain epithelial-mesenchymal junctions, and transiently in developing fetal cartilage. Region-specific induction of NEC1 is found in dermal wounds and in the reactive stroma of actinic keratoses, psoriatic skin lesions, and a range of malignant tumors. One explanation for these diverse tissue patterns is that cells capable of producing NEC1 are widely distributed in neural and mesenchymal tissues, but they become NEC1 producers only when induced by region-specific differentiation signals. In this study, we used cultured human cells to show that several regulatory polypeptides, including fibroblast growth factors, tumor necrosis factor, platelet-derived growth factor, nerve growth factor, and transforming growth factor-beta (TGF-beta), as well as 12-O-tetradecanoyl phorbol-13-acetate (TPA), modulate NEC1 secretion, with distinct patterns of inducing and inhibitory activities in different neural and mesenchymal cell types. TPA and TGF-beta act both as inducers and inhibitors of NEC1 secretion, depending on the target cell. These effects are specific for NEC1 and are not seen for several other secreted and membrane proteins studied. We suggest that NEC1 expression comes under different modes of extrinsic control in different cell lineages and in response to tissue injury and neoplasia.
[The effect of fluoridated phenylethanolamines on hyperglycemia induced by catecholamines in the rat]. (1975)

10 compounds from the 2.4- and 3.4-difluorinated phenylethanol-amines series were tested for their antagonistic action against a hyperglycemia induced by catecholamines in rats, and the ED50 and AD50 values were determined. All the substances acted beta-adrenolytically, with the glycogenolysis enhanced by isoproterenol being blocked more potently by 3.4-difluorophenylethanolamines than by the corresponding 2.4-difluoroderivatives. An exception in the series is 2.4-difluoro-n-butylnoradrenalin, which acts 10fold more beta-adrenolytically than the 3.4-difluoroderivative, and has 3 times the effect of the comparative substance dichloroisoproterenol.
Pre-processing of Social Media Posts (2018)

Social media has become a slogan in emotion and sentiment analysis. In today’s era Social media networking sites are almost used by everyone. Social media users share their feelings, thoughts, and experiences with other people by short messages. Short messages are composed of emoticons, slangs, noises, irrelevancies and words. Thus, preprocessing becomes the challenging task for Sentiment analysis. This experiment is performed to evaluate the impact of pre-processing on social data for sentiment classification particularly for slang words. This paper focused on identification of important slang words and to evaluate their impact on sentiment analysis of social media posts. The proposed scheme collects bigrams, trigrams of slang and exploits different features for better results of sentiment classification. N-grams are used for bindings and conditional random fields (CRF) to determine the importance of slang words. Experiments declare that this proposed scheme increases the accuracy of Sentiment analysis. Keywords : Pre-processing, normalization, sentiment analysis Cite this Article Rafiya Jan, Afaq Alam Khan. Preprocessing of Social Media Posts. Recent Trends in Programming Languages. 2018; 5(1): 14–18p.