SOCS and Herpesviruses, With Emphasis on Cytomegalovirus Retinitis

Suppressor of cytokine signaling (SOCS) proteins provide selective negative feedback to prevent pathogeneses caused by overstimulation of the immune system. Of the eight known SOCS proteins, SOCS1 and SOCS3 are the best studied, and systemic deletion of either gene causes early lethality in mice. Many viruses, including herpesviruses such as herpes simplex virus and cytomegalovirus, can manipulate expression of these host proteins, with overstimulation of SOCS1 and/or SOCS3 putatively facilitating viral evasion of immune surveillance, and SOCS suppression generally exacerbating immunopathogenesis. This is particularly poignant within the eye, which contains a diverse assortment of specialized cell types working together in a tightly controlled microenvironment of immune privilege. When the immune privilege of the ocular compartment fails, inflammation causing severe immunopathogenesis and permanent, sight-threatening damage may occur, as in the case of AIDS-related human cytomegalovirus (HCMV) retinitis. Herein we review how SOCS1 and SOCS3 impact the virologic, immunologic, and/or pathologic outcomes of herpesvirus infection with particular emphasis on retinitis caused by HCMV or its mouse model experimental counterpart, murine cytomegalovirus (MCMV). The accumulated data suggests that SOCS1 and/or SOCS3 can differentially affect the severity of viral diseases in a highly cell-type-specific manner, reflecting the diversity and complexity of herpesvirus infection and the ocular compartment

Viral forensic genomics reveals the relatedness of classic herpes simplex virus strains KOS, KOS63, and KOS79

Herpes simplex virus 1 (HSV-1) is a widespread global pathogen, of which the strain KOS is one of the most extensively studied. Previous sequence studies revealed that KOS does not cluster with other strains of North American geographic origin, but instead clustered with Asian strains. We sequenced a historical isolate of the original KOS strain, called KOS63, along with a separately isolated strain attributed to the same source individual, termed KOS79. Genomic analyses revealed that KOS63 closely resembled other recently sequenced isolates of KOS and was of Asian origin, but that KOS79 was a genetically unrelated strain that clustered in genetic distance analyses with HSV-1 strains of North American/European origin. These data suggest that the human source of KOS63 and KOS79 could have been infected with two genetically unrelated strains of disparate geographic origins. A PCR RFLP test was developed for rapid identification of these strains

Gemini Near Infrared Spectrograph - Distant Quasar Survey: Prescriptions for Calibrating UV-Based Estimates of Supermassive Black Hole Masses in High-Redshift Quasars

The most reliable single-epoch supermassive black hole mass ($M_{\rm BH}$) estimates in quasars are obtained by using the velocity widths of low-ionization emission lines, typically the H$\beta$ $\lambda4861$ line. Unfortunately, this line is redshifted out of the optical band at $z\approx1$, leaving $M_{\rm BH}$ estimates to rely on proxy rest-frame ultraviolet (UV) emission lines, such as C IV $\lambda1549$ or Mg II $\lambda2800$, which contain intrinsic challenges when measuring, resulting in uncertain $M_{\rm BH}$ estimates. In this work, we aim at correcting $M_{\rm BH}$ estimates derived from the C IV and Mg II emission lines based on estimates derived from the H$\beta$ emission line. We find that employing the equivalent width of C IV in deriving $M_{\rm BH}$ estimates based on Mg II and C IV provides values that are closest to those obtained from H$\beta$. We also provide prescriptions to estimate $M_{\rm BH}$ values when only C IV, only Mg II, and both C IV and Mg II are measurable. We find that utilizing both emission lines, where available, reduces the scatter of UV-based $M_{\rm BH}$ estimates by $\sim15\%$ when compared to previous studies. Lastly, we discuss the potential of our prescriptions to provide more accurate and precise estimates of $M_{\rm BH}$ given a much larger sample of quasars at $3.20 \lesssim z \lesssim 3.50$, where both Mg II and H$\beta$ can be measured in the same near-infrared spectrum.Comment: 19 pages (AASTeX 6.3.1), 9 figures, accepted for publication in Ap

Gemini Near Infrared Spectrograph -- Distant Quasar Survey: Augmented Spectroscopic Catalog and a Prescription for Correcting UV-Based Quasar Redshifts

Quasars at $z~{\gtrsim}~1$ most often have redshifts measured from rest-frame ultraviolet emission lines. One of the most common such lines, C IV ${\lambda}1549$, shows blueshifts up to ${\approx}~5000~\rm{km~s^{-1}}$, and in rare cases even higher. This blueshifting results in highly uncertain redshifts when compared to redshift determinations from rest-frame optical emission lines, e.g., from the narrow [O III] ${\lambda}5007$ feature. We present spectroscopic measurements for 260 sources at $1.55~{\lesssim}~z~{\lesssim}~3.50$ having $-28.0~{\lesssim}~M_i~{\lesssim}~-30.0$ mag from the Gemini Near Infrared Spectrograph - Distant Quasar Survey (GNIRS-DQS) catalog, augmenting the previous iteration which contained 226 of the 260 sources whose measurements are improved upon in this work. We obtain reliable systemic redshifts based on [O III] ${\lambda}5007$ for a subset of 121 sources which we use to calibrate prescriptions for correcting UV-based redshifts. These prescriptions are based on a regression analysis involving C IV full-width-at-half-maximum intensity and equivalent width, along with the UV continuum luminosity at a rest-frame wavelength of 1350 A. Applying these corrections can improve the accuracy and the precision in the C IV-based redshift by up to ${\sim}~850~\rm{km~s^{-1}}$ and ${\sim}~150~\rm{km~s^{-1}}$, respectively, which correspond to ${\sim}~8.5$ Mpc and ${\sim}~1.5$ Mpc in comoving distance at $z~=~2.5$. Our prescriptions also improve the accuracy of the best available multi-feature redshift determination algorithm by ${\sim}~100~\rm{km~s^{-1}}$, indicating that the spectroscopic properties of the C IV emission line can provide robust redshift estimates for high-redshift quasars. We discuss the prospects of our prescriptions for cosmological and quasar studies utilizing upcoming large spectroscopic surveys.Comment: 20 pages (AASTeX 6.3.1), 8 figures, accepted for publication in Ap

Placing high-redshift quasars in perspective: A catalog of spectroscopic properties from the gemini near infrared spectrograph-distant quasar survey

We present spectroscopic measurements for 226 sources from the Gemini Near Infrared Spectrograph-Distant Quasar Survey (GNIRS-DQS). Being the largest uniform, homogeneous survey of its kind, it represents a fluxlimited sample (mi≤19.0 mag, H≤16.5 mag) of Sloan Digital Sky Survey (SDSS) quasars at 1.5 ≤ z ≤ 3.5 with a monochromatic luminosity (λLλ) at 5100 Å in the range of 1044-1046 erg s-1. A combination of the GNIRS and SDSS spectra covers principal quasar diagnostic features, chiefly the C IV λ1549, Mg II λλ2798, 2803, Hβ λ4861, and [O III] λλ4959, 5007 emission lines, in each source. The spectral inventory will be utilized primarily to develop prescriptions for obtaining more accurate and precise redshifts, black hole masses, and accretion rates for all quasars. Additionally, the measurements will facilitate an understanding of the dependence of rest-frame ultraviolet-optical spectral properties of quasars on redshift, luminosity, and Eddington ratio, and test whether the physical properties of the quasar central engine evolve over cosmic time.Fil: Matthews, Brandon M.. University of North Texas; Estados UnidosFil: Shemmer, Ohad. University of North Texas; Estados UnidosFil: Dix, Cooper. University of North Texas; Estados UnidosFil: Brotherton, Michael S.. University of Wyoming; Estados UnidosFil: Myers, Adam D.. University of Wyoming; Estados UnidosFil: Andruchow, Ileana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; ArgentinaFil: Brandt, W.N.. State University of Pennsylvania; Estados UnidosFil: Ferrero, Gabriel A.. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; ArgentinaFil: Gallagher, S.C.. The University Of Western Ontario; CanadáFil: Green, Richard. University of Arizona; Estados UnidosFil: Lira, Paulina. Universidad de Chile.; ChileFil: Plotkin, Richard M.. University of Nevada. Deparment of Physics; Estados UnidosFil: Richards, Gordon T.. Drexel University; Estados UnidosFil: Runnoe, Jessie C.. Vanderbilt University; Estados UnidosFil: Schneider, Donald P.. State University of Pennsylvania; Estados UnidosFil: Shen, Yue. University of Illinois at Urbana; Estados UnidosFil: Strauss, Michael A.. University of Princeton; Estados UnidosFil: Wills, Beverley J.. University of Texas at Austin; Estados Unido

Disconnected human resource? Proximity and the (mis)management of workplace conflict

The development of more remote sources of advice has been a notable feature of the contemporary human resource (HR) function. However, the consequences for the management of workplace conflict are largely ignored within the academic literature. This study draws on data from two qualitative studies, which examine the experiences of HR practitioners (HRPs), line managers and trade union representatives in handling and resolving conflict. It explores how different dimensions of organisational proximity shape the relationships between HRPs and other key stakeholders, and the impact of this on conflict management. The findings suggest that formal, risk averse approaches to conflict are not simply a result of geographical distance. Instead, functional specialisation has not only eroded cognitive and social proximity between HRPs, line managers and employee representatives but also within the HR function itself. This has triggered the reinforcement of bureaucratic control and embedded responses that emphasise compliance rather than resolution

On the Representability of Complete Genomes by Multiple Competing Finite-Context (Markov) Models

A finite-context (Markov) model of order yields the probability distribution of the next symbol in a sequence of symbols, given the recent past up to depth . Markov modeling has long been applied to DNA sequences, for example to find gene-coding regions. With the first studies came the discovery that DNA sequences are non-stationary: distinct regions require distinct model orders. Since then, Markov and hidden Markov models have been extensively used to describe the gene structure of prokaryotes and eukaryotes. However, to our knowledge, a comprehensive study about the potential of Markov models to describe complete genomes is still lacking. We address this gap in this paper. Our approach relies on (i) multiple competing Markov models of different orders (ii) careful programming techniques that allow orders as large as sixteen (iii) adequate inverted repeat handling (iv) probability estimates suited to the wide range of context depths used. To measure how well a model fits the data at a particular position in the sequence we use the negative logarithm of the probability estimate at that position. The measure yields information profiles of the sequence, which are of independent interest. The average over the entire sequence, which amounts to the average number of bits per base needed to describe the sequence, is used as a global performance measure. Our main conclusion is that, from the probabilistic or information theoretic point of view and according to this performance measure, multiple competing Markov models explain entire genomes almost as well or even better than state-of-the-art DNA compression methods, such as XM, which rely on very different statistical models. This is surprising, because Markov models are local (short-range), contrasting with the statistical models underlying other methods, where the extensive data repetitions in DNA sequences is explored, and therefore have a non-local character

A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model

<p>Abstract</p> <p>Background</p> <p>Bioactivity profiling using high-throughput <it>in vitro </it>assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also reduce the need for animal testing. Several public efforts are aimed at discovering patterns or classifiers in high-dimensional bioactivity space that predict tissue, organ or whole animal toxicological endpoints. Supervised machine learning is a powerful approach to discover combinatorial relationships in complex <it>in vitro/in vivo </it>datasets. We present a novel model to simulate complex chemical-toxicology data sets and use this model to evaluate the relative performance of different machine learning (ML) methods.</p> <p>Results</p> <p>The classification performance of Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Naïve Bayes (NB), Recursive Partitioning and Regression Trees (RPART), and Support Vector Machines (SVM) in the presence and absence of filter-based feature selection was analyzed using K-way cross-validation testing and independent validation on simulated <it>in vitro </it>assay data sets with varying levels of model complexity, number of irrelevant features and measurement noise. While the prediction accuracy of all ML methods decreased as non-causal (irrelevant) features were added, some ML methods performed better than others. In the limit of using a large number of features, ANN and SVM were always in the top performing set of methods while RPART and KNN (k = 5) were always in the poorest performing set. The addition of measurement noise and irrelevant features decreased the classification accuracy of all ML methods, with LDA suffering the greatest performance degradation. LDA performance is especially sensitive to the use of feature selection. Filter-based feature selection generally improved performance, most strikingly for LDA.</p> <p>Conclusion</p> <p>We have developed a novel simulation model to evaluate machine learning methods for the analysis of data sets in which in vitro bioassay data is being used to predict in vivo chemical toxicology. From our analysis, we can recommend that several ML methods, most notably SVM and ANN, are good candidates for use in real world applications in this area.</p

Cwc21p promotes the second step conformation of the spliceosome and modulates 3' splice site selection

© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. Pre-mRNA splicing involves two transesterification steps catalyzed by the spliceosome. How RNA substrates are positioned in each step and the molecular rearrangements involved, remain obscure. Here, we show that mutations in PRP16, PRP8, SNU114 and the U5 snRNA that affect this process interact genetically with CWC21, that encodes the yeast orthologue of the human SR protein, SRm300/SRRM2. Our microarray analysis shows changes in 3′ splice site selection at elevated temperature in a subset of introns in cwc21Δ cells. Considering all the available data, we propose a role for Cwc21p positioning the 3′ splice site at the transition to the second step conformation of the spliceosome, mediated through its interactions with the U5 snRNP. This suggests a mechanism whereby SRm300/SRRM2, might influence splice site selection in human cells.Wellcome Trust [087551 to J.D.Beggs, 092076 core funding grant]; Darwin Trust of Edinburgh Studentship [to A.G.]; Royal Society, Darwin Trust Research Professorship [to J.D.Beggs]; Spanish Economy Ministry [BFU2011-25697 to J.V.]. Funding for open access charge: Wellcome TrustPeer Reviewe

To formalize or not to formalize: women entrepreneurs’ sensemaking of business registration in the context of Nepal

Despite the depiction of decisions to formalize informal firms as rational and ethical, many entrepreneurs in developing countries continue to operate informally regardless of its perceived illicit status. While existing research on why entrepreneurs choose informality emphasizes the economic costs and benefits of such decisions, this often overlooks the realities of the informal economy and the constraints which marginal populations—particularly women—face. In this paper, we use institutional theory and sensemaking to understand the experiences of women in the informal economy and what formalization means to them. We use a qualitative approach to collect data from 90 women entrepreneurs in three different cities in Nepal. In our findings, we identify three groups of women with distinctive understandings of formalization—business sustainability, livelihood sufficiency and strategic alignment. Their interpretation of formalization reveals the complex, dynamic, and cyclical nature of formalization decisions. Decisions are also guided by the optimization of social and emotional logics, whereby formalization is conceived differently depending on different life stages, experiences within the informal economy and wider socio-cultural contexts. Our findings highlight the ethical implications of formalization where being a ‘good citizen’, rather than complying with formal rules and regulations, is about attuning to and fitting in with socially prescribed roles. Our research provides a nuanced view of formalization decisions, challenging idealized and ethical notions of formalization as a desired end state