Polycystic ovary syndrome, blood group & diet: A correlative study in South Indian females

Aim: To find out the co-relation between polycystic ovary syndrome (PCOS) with blood group & diet in South Indian females, between the age-group of (20-30) years. Objectives: Correlative analysis of ABO & Rh system, dietary habits & alcohol consumption with PCOS. Materials & Methods: 100 patients between (20-30) years, diagnosed with PCOS were selected. A standard PCOS questionnaire was given. Blood group & dietary status data were collected. Patients were grouped according to ABO & Rh system considering their diet & alcohol intake (p≤0.05 significant). Result: Our data revealed that the highest risk of PCOS was observed in females with blood group ‘O’ positive followed by ‘B’ positive who were on mixed diet & used to consume alcohol. Our study also suggests that Rh negative individuals didn’t show any association with PCOS. Conclusion: The results of our study suggest that ‘O’ positive females, are more prone to PCOS. Though the relative frequency of B positive individuals are more in India, females with blood group O positive are more susceptible to PCOS, contributing factors being mixed diet & alcohol intake. So, early screening of ‘O’ positive &‘B’ positive females of reproductive age-group in South-India, could be used as a measure for timely diagnosis of PCOS, better management &also prevention of complications. However, further research should be done to investigate the multifaceted mechanisms triggering these effects

What do Deck Chairs and Sun Hats Have in Common? Uncovering Shared Properties in Large Concept Vocabularies

Concepts play a central role in many applications. This includes settings where concepts have to be modelled in the absence of sentence context. Previous work has therefore focused on distilling decontextualised concept embeddings from language models. But concepts can be modelled from different perspectives, whereas concept embeddings typically mostly capture taxonomic structure. To address this issue, we propose a strategy for identifying what different concepts, from a potentially large concept vocabulary, have in common with others. We then represent concepts in terms of the properties they share with the other concepts. To demonstrate the practical usefulness of this way of modelling concepts, we consider the task of ultra-fine entity typing, which is a challenging multi-label classification problem. We show that by augmenting the label set with shared properties, we can improve the performance of the state-of-the-art models for this task.Comment: Accepted for EMNLP 202

Signaling network map of the aryl hydrocarbon receptor

We thank the Department of Biotechnology (DBT), Government of India for research support to the Institute of Bioinformatics, Bangalore. We thank the “Infosys Foundation” for research support to the Institute of Bioinformatics. We thank UK India Education and Research Initiative (UKIERI) for generous grant support. SDY is a recipient of DST-INSPIRE Senior Research Fellowship from Department of Science and Technology (DST), Government of India. AR and JA are recipients of Senior Research Fellowship from Council of Scientific and Industrial Research (CSIR), Government of India. RR is a recipient of Research Associateship from Department of Biotechnology, Government of India

What do deck chairs and sun hats have in common? Uncovering shared properties in large concept vocabularies

Concepts play a central role in many applications. This includes settings where concepts have to be modelled in the absence of sentence context. Previous work has therefore focused on distilling decontextualised concept embeddings from language models. But concepts can be modelled from different perspectives, whereas concept embeddings typically mostly capture taxonomic structure. To address this issue, we propose a strategy for identifying what different concepts, from a potentially large concept vocabulary, have in common with others. We then represent concepts in terms of the properties they share with the other concepts. To demonstrate the practical usefulness of this way of modelling concepts, we consider the task of ultra-fine entity typing, which is a challenging multi-label classification problem. We show that by augmenting the label set with shared properties, we can improve the performance of the state-of-the-art models for this task

Synergistic Antibacterial Effects of Metallic Nanoparticle Combinations

© The Author(s) 2019.Metallic nanoparticles have unique antimicrobial properties that make them suitable for use within medical and pharmaceutical devices to prevent the spread of infection in healthcare. The use of nanoparticles in healthcare is on the increase with silver being used in many devices. However, not all metallic nanoparticles can target and kill all disease-causing bacteria. To overcome this, a combination of several different metallic nanoparticles were used in this study to compare effects of multiple metallic nanoparticles when in combination than when used singly, as single elemental nanoparticles (SENPs), against two common hospital acquired pathogens (Staphylococcus aureus and Pseudomonas. aeruginosa). Flow cytometry LIVE/DEAD assay was used to determine rates of cell death within a bacterial population when exposed to the nanoparticles. Results were analysed using linear models to compare effectiveness of three different metallic nanoparticles, tungsten carbide (WC), silver (Ag) and copper (Cu), in combination and separately. Results show that when the nanoparticles are placed in combination (NPCs), antimicrobial effects significantly increase than when compared with SENPs (P < 0.01). This study demonstrates that certain metallic nanoparticles can be used in combination to improve the antimicrobial efficiency in destroying morphologically distinct pathogens within the healthcare and pharmaceutical industry.Peer reviewe

Proactive and politically skilled professionals: What is the relationship with affective occupational commitment?

The aim of this study is to extend research on employee affective commitment in three ways: (1) instead of organizational commitment the focus is on occupational commitment; (2) the role of proactive personality on affective occupational commitment is examined; and (3) occupational satisfaction is examined as a mediator and political skills as moderator in the relationship between proactive personality and affective occupational commitment. Two connected studies, one in a hospital located in the private sector and one in a university located in the public sector, are carried out in Pakistan, drawing on a total sample of over 400 employees. The results show that proactive personality is positively related to affective occupational commitment, and that occupational satisfaction partly mediates the relationship between proactive personality and affective occupational commitment. No effect is found for a moderator effect of political skills in the relationship between proactive personality and affective occupational commitment. Political skills however moderate the relationship between proactive personality and affective organizational commitment

Genomewide identification of \u3ci\u3ePseudomonas syringae\u3c/i\u3e pv.\u3ci\u3etomato\u3c/i\u3e DC3000 promoters controlled by the HrpL alternative sigma factor

The ability of Pseudomonas syringae pv. tomato DC3000 to parasitize tomato and Arabidopsis thaliana depends on genes activated by the HrpL alternative sigma factor. To support various functional genomic analyses of DC3000, and specifically, to identify genes involved in pathogenesis, we developed a draft sequence of DC3000 and used an iterative process involving computational and gene expression techniques to identify virulence-implicated genes downstream of HrpLresponsive promoters. Hypersensitive response and pathogenicity (Hrp) promoters are known to control genes encoding the Hrp (type III protein secretion) machinery and a few type III effector proteins in DC3000. This process involved (i) identification of 9 new virulenceimplicated genes in the Hrp regulon by miniTn5gus mutagenesis, (ii) development of a hidden Markov model (HMM) trained with known and transposon-identified Hrp promoter sequences, (iii) HMM identification of promoters upstream of 12 additional virulence-implicated genes, and (iv) microarray and RNA blot analyses of the HrpLdependent expression of a representative subset of these DC3000 genes. We found that the Hrp regulon encodes candidates for 4 additional type III secretion machinery accessory factors, homologs of the effector proteins HopPsyA, AvrPpiB1 (2 copies), AvrPpiC2, AvrPphD (2 copies), AvrPphE, AvrPphF, and AvrXv3, and genes associated with the production or metabolism of virulence factors unrelated to the Hrp type III secretion system, including syringomycin synthetase (SyrE), N-(indole-3-acetyl)-L-lysine synthetase (IaaL), and a subsidiary regulon controlling coronatine production. Additional candidate effector genes, hopPtoA2, hopPtoB2, and an avrRps4 homolog, were preceded by Hrp promoter-like sequences, but these had HMM expectation values of relatively low significance and were not detectably activated by HrpL

Accretion of Planetary Material onto Host Stars

Accretion of planetary material onto host stars may occur throughout a star's life. Especially prone to accretion, extrasolar planets in short-period orbits, while relatively rare, constitute a significant fraction of the known population, and these planets are subject to dynamical and atmospheric influences that can drive significant mass loss. Theoretical models frame expectations regarding the rates and extent of this planetary accretion. For instance, tidal interactions between planets and stars may drive complete orbital decay during the main sequence. Many planets that survive their stars' main sequence lifetime will still be engulfed when the host stars become red giant stars. There is some observational evidence supporting these predictions, such as a dearth of close-in planets around fast stellar rotators, which is consistent with tidal spin-up and planet accretion. There remains no clear chemical evidence for pollution of the atmospheres of main sequence or red giant stars by planetary materials, but a wealth of evidence points to active accretion by white dwarfs. In this article, we review the current understanding of accretion of planetary material, from the pre- to the post-main sequence and beyond. The review begins with the astrophysical framework for that process and then considers accretion during various phases of a host star's life, during which the details of accretion vary, and the observational evidence for accretion during these phases.Comment: 18 pages, 5 figures (with some redacted), invited revie

Probability distributed time delays: integrating spatial effects into temporal models

Background: In order to provide insights into the complex biochemical processes inside a cell, modelling approaches must find a balance between achieving an adequate representation of the physical phenomena and keeping the associated computational cost within reasonable limits. This issue is particularly stressed when spatial inhomogeneities have a significant effect on system's behaviour. In such cases, a spatially-resolved stochastic method can better portray the biological reality, but the corresponding computer simulations can in turn be prohibitively expensive.Results: We present a method that incorporates spatial information by means of tailored, probability distributed time-delays. These distributions can be directly obtained by single in silico or a suitable set of in vitro experiments and are subsequently fed into a delay stochastic simulation algorithm (DSSA), achieving a good compromise between computational costs and a much more accurate representation of spatial processes such as molecular diffusion and translocation between cell compartments. Additionally, we present a novel alternative approach based on delay differential equations (DDE) that can be used in scenarios of high molecular concentrations and low noise propagation.Conclusions: Our proposed methodologies accurately capture and incorporate certain spatial processes into temporal stochastic and deterministic simulations, increasing their accuracy at low computational costs. This is of particular importance given that time spans of cellular processes are generally larger (possibly by several orders of magnitude) than those achievable by current spatially-resolved stochastic simulators. Hence, our methodology allows users to explore cellular scenarios under the effects of diffusion and stochasticity in time spans that were, until now, simply unfeasible. Our methodologies are supported by theoretical considerations on the different modelling regimes, i.e. spatial vs. delay-temporal, as indicated by the corresponding Master Equations and presented elsewhere

Measurement of the Z/gamma* + b-jet cross section in pp collisions at 7 TeV

The production of b jets in association with a Z/gamma* boson is studied using proton-proton collisions delivered by the LHC at a centre-of-mass energy of 7 TeV and recorded by the CMS detector. The inclusive cross section for Z/gamma* + b-jet production is measured in a sample corresponding to an integrated luminosity of 2.2 inverse femtobarns. The Z/gamma* + b-jet cross section with Z/gamma* to ll (where ll = ee or mu mu) for events with the invariant mass 60 < M(ll) < 120 GeV, at least one b jet at the hadron level with pT > 25 GeV and abs(eta) < 2.1, and a separation between the leptons and the jets of Delta R > 0.5 is found to be 5.84 +/- 0.08 (stat.) +/- 0.72 (syst.) +(0.25)/-(0.55) (theory) pb. The kinematic properties of the events are also studied and found to be in agreement with the predictions made by the MadGraph event generator with the parton shower and the hadronisation performed by PYTHIA.Comment: Submitted to the Journal of High Energy Physic