Identification of Genes Potentially Regulated by Human Polynucleotide Phosphorylase (hPNPaseold-35) Using Melanoma as a Model

Human Polynucleotide Phosphorylase (hPNPaseold-35 or PNPT1) is an evolutionarily conserved 3′→5′ exoribonuclease implicated in the regulation of numerous physiological processes including maintenance of mitochondrial homeostasis, mtRNA import and aging-associated inflammation. From an RNase perspective, little is known about the RNA or miRNA species it targets for degradation or whose expression it regulates; except for c-myc and miR-221. To further elucidate the functional implications of hPNPaseold-35 in cellular physiology, we knocked-down and overexpressed hPNPaseold-35 in human melanoma cells and performed gene expression analyses to identify differentially expressed transcripts. Ingenuity Pathway Analysis indicated that knockdown of hPNPaseold-35 resulted in significant gene expression changes associated with mitochondrial dysfunction and cholesterol biosynthesis; whereas overexpression of hPNPaseold-35 caused global changes in cell-cycle related functions. Additionally, comparative gene expression analyses between our hPNPaseold-35 knockdown and overexpression datasets allowed us to identify 77 potential “direct” and 61 potential “indirect” targets of hPNPaseold-35 which formed correlated networks enriched for cell-cycle and wound healing functional association, respectively. These results provide a comprehensive database of genes responsive to hPNPaseold-35 expression levels; along with the identification new potential candidate genes offering fresh insight into cellular pathways regulated by PNPT1 and which may be used in the future for possible therapeutic intervention in mitochondrial- or inflammation-associated disease phenotypes

Model evaluation and ensemble modelling of surface-level ozone in Europe and North America in the context of AQMEII

More than ten state-of-the-art regional air quality models have been applied as part of the Air Quality Model Evaluation International Initiative (AQMEII). These models were run by twenty independent groups in Europe and North America. Standardised modelling outputs over a full year (2006) from each group have been shared on the web-distributed ENSEMBLE system, which allows for statistical and ensemble analyses to be performed by each group. The estimated ground-level ozone mixing ratios from the models are collectively examined in an ensemble fashion and evaluated against a large set of observations from both continents. The scale of the exercise is unprecedented and offers a unique opportunity to investigate methodologies for generating skilful ensembles of regional air quality models outputs. Despite the remarkable progress of ensemble air quality modelling over the past decade, there are still outstanding questions regarding this technique. Among them, what is the best and most beneficial way to build an ensemble of members? And how should the optimum size of the ensemble be determined in order to capture data variability as well as keeping the error low? These questions are addressed here by looking at optimal ensemble size and quality of the members. The analysis carried out is based on systematic minimization of the model error and is important for performing diagnostic/probabilistic model evaluation. It is shown that the most commonly used multi-model approach, namely the average over all available members, can be outperformed by subsets of members optimally selected in terms of bias, error, and correlation. More importantly, this result does not strictly depend on the skill of the individual members, but may require the inclusion of low-ranking skill-score members. A clustering methodology is applied to discern among members and to build a skilful ensemble based on model association and data clustering, which makes no use of priori knowledge of model skill. Results show that, while the methodology needs further refinement, by optimally selecting the cluster distance and association criteria, this approach can be useful for model applications beyond those strictly related to model evaluation, such as air quality forecasting. (C) 2012 Elsevier Ltd. All rights reserved.Peer reviewe

The political import of deconstruction—Derrida’s limits?: a forum on Jacques Derrida’s specters of Marx after 25 Years, part I

Jacques Derrida delivered the basis of The Specters of Marx: The State of the Debt, the Work of Mourning, & the New International as a plenary address at the conference ‘Whither Marxism?’ hosted by the University of California, Riverside, in 1993. The longer book version was published in French the same year and appeared in English and Portuguese the following year. In the decade after the publication of Specters, Derrida’s analyses provoked a large critical literature and invited both consternation and celebration by figures such as Antonio Negri, Wendy Brown and Frederic Jameson. This forum seeks to stimulate new reflections on Derrida, deconstruction and Specters of Marx by considering how the futures past announced by the book have fared after an eventful quarter century. Maja Zehfuss, Antonio Vázquez-Arroyo and Dan Bulley and Bal Sokhi-Bulley offer sharp, occasionally exasperated, meditations on the political import of deconstruction and the limits of Derrida’s diagnoses in Specters of Marx but also identify possible paths forward for a global politics taking inspiration in Derrida’s work of the 1990s

Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data

© 2016. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. Ioannis Kioutsioukis, et al, ‘Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data’, Atmospheric Chemistry and Physics, Vol 16(24): 15629-15652, published 20 December 2016, the version of record is available at doi:10.5194/acp-16-15629-2016 Published by Copernicus Publications on behalf of the European Geosciences Union.Simulations from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as those intrinsic to the model (e.g. physical parameterization, chemical mechanism). Multi-model ensembles can improve the forecast skill, provided that certain mathematical conditions are fulfilled. In this work, four ensemble methods were applied to two different datasets, and their performance was compared for ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM10). Apart from the unconditional ensemble average, the approach behind the other three methods relies on adding optimum weights to members or constraining the ensemble to those members that meet certain conditions in time or frequency domain. The two different datasets were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). The methods are evaluated against ground level observations collected from the EMEP (European Monitoring and Evaluation Programme) and AirBase databases. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill over the single models and the ensemble mean. Verification statistics show that the deterministic models simulate better O3 than NO2 and PM10, linked to different levels of complexity in the represented processes. The unconditional ensemble mean achieves higher skill compared to each station's best deterministic model at no more than 60 % of the sites, indicating a combination of members with unbalanced skill difference and error dependence for the rest. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way. The skill improvements were higher for O3 and lower for PM10, associated with the extent of potential changes in the joint distribution of accuracy and diversity in the ensembles. The skill enhancement was superior using the weighting scheme, but the training period required to acquire representative weights was longer compared to the sub-selecting schemes. Further development of the method is discussed in the conclusion.Peer reviewedFinal Published versio

MEGAPOLI: concept of multi-scale modelling of megacity impact on air quality and climate

The EU FP7 Project MEGAPOLI: "Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation" (http://megapoli.info) brings together leading European research groups, state-of-the-art scientific tools and key players from non-European countries to investigate the interactions among megacities, air quality and climate. MEGAPOLI bridges the spatial and temporal scales that connect local emissions, air quality and weather with global atmospheric chemistry and climate. The suggested concept of multi-scale integrated modelling of megacity impact on air quality and climate and vice versa is discussed in the paper. It requires considering different spatial and temporal dimensions: time scales from seconds and hours (to understand the interaction mechanisms) up to years and decades (to consider the climate effects); spatial resolutions: with model down- and up-scaling from street- to global-scale; and two-way interactions between meteorological and chemical processes

ASSOCIATION OF BRITISH NEUROLOGISTS SUSTAINABILITY SPECIAL INTEREST GROUP (ABN SUSTAINABILITY SIG): FORMATION, OBJECTIVES AND INVITATION

We introduce the ABN Sustainability SIG. We present our aims & objectives, and practical ways of implementing sustainability strategies in Neurology.At the 2016 ABN annual meeting, a keynote speech by Dr. David Pencheon, then director of the National Health Service Sustainability Development Unit, highlighted the relevance and importance of Sustainability in Neurology. This planted the seed for our SIG’s formation. Initial interest was gathered from an ABN newsletter notice, via word-of-mouth and informal discussions at ABN annual meetings (2017, 2018). A series of teleconferences & email discussions enabled the formation of SIG byelaws and application to the ABN council.Our aims and objectivesTo be a positive force within the ABN to highlight issues surrounding global environmental sustainability.To provide a forum to consider the impact of choices made in neurology practice on global environmental sustainability. This will cover all aspects of neurology including, but not limited to, clinical practice, service provision, technological and digital developments, meetings and ABN resources and investments.To identify areas where the choice made could impact positively on global environmental sustainability and disseminate this information to the ABN membership to inform their decisions

Lysosomal and phagocytic activity is increased in astrocytes during disease progression in the SOD1 G93A mouse model of amyotrophic lateral sclerosis

Astrocytes are key players in the progression of amyotrophic lateral sclerosis (ALS). Previously, gene expression profiling of astrocytes from the pre-symptomatic stage of the SOD1G93A model of ALS has revealed reduced lactate metabolism and altered trophic support. Here, we have performed microarray analysis of symptomatic and late-stage disease astrocytes isolated by laser capture microdissection (LCM) from the lumbar spinal cord of the SOD1G93A mouse to complete the picture of astrocyte behavior throughout the disease course. Astrocytes at symptomatic and late-stage disease show a distinct up-regulation of transcripts defining a reactive phenotype, such as those involved in the lysosome and phagocytic pathways. Functional analysis of hexosaminidase B enzyme activity in the spinal cord and of astrocyte phagocytic ability has demonstrated a significant increase in lysosomal enzyme activity and phagocytic activity in SOD1G93A vs. littermate controls, validating the findings of the microarray study. In addition to the increased reactivity seen at both stages, astrocytes from late-stage disease showed decreased expression of many transcripts involved in cholesterol homeostasis. Staining for the master regulator of cholesterol synthesis, SREBP2, has revealed an increased localization to the cytoplasm of astrocytes and motor neurons in late-stage SOD1G93A spinal cord, indicating that down-regulation of transcripts may be due to an excess of cholesterol in the CNS during late-stage disease possibly due to phagocytosis of neuronal debris. Our data reveal that SOD1G93A astrocytes are characterized more by a loss of supportive function than a toxic phenotype during ALS disease progression and future studies should focus upon restorative therapies

Avoiding high ozone pollution in Delhi, India

Surface ozone is a major pollutant threatening public health, agricultural production and natural ecosystems. While measures to improve air quality in megacities such as Delhi are typically aimed at reducing levels of particulate matter (PM), ozone could become a greater threat if these measures focus on PM alone, as some air pollution mitigation steps can actually lead to an increase in surface ozone. A better understanding of the factors controlling ozone production in Delhi and the impact that PM mitigation measures have on ozone is therefore critical for improving air quality. Here, we combine in-situ observations and model analysis to investigate the impact of PM reduction on the non-linear relationship between volatile organic compounds (VOC), nitrogen oxides (NOx) and ozone. In-situ measurements of NOx, VOC, and ozone were conducted in Delhi during the APHH-India programme in summer (June) and winter (November) 2018. We observed hourly averaged ozone concentrations in the city of up to 100 ppbv in both seasons. We performed sensitivity simulations with a chemical box model to explore the impacts of PM on the non-linear VOC-NOx-ozone relationship in each season through its effect on aerosol optical depth (AOD). We find that ozone production is limited by VOC in both seasons, and is particularly sensitive to solar radiation in winter. Reducing NOx alone increases ozone, such that a 50% reduction in NOx emissions leads to 10-50% increase in surface ozone. In contrast, reducing VOC emissions can reduce ozone efficiently, such that a 50% reduction in VOC emissions leads to ~60% reduction in ozone. Reducing PM alone also increases ozone, especially in winter, by reducing its dimming effects on photolysis, such that a 50% reduction in AOD can increase ozone by 25% and it also enhances VOC-limitation. Our results highlight the importance of reducing VOC emissions alongside PM to limit ozone pollution, as well as benefitting control of PM pollution through reducing secondary organic aerosol. This will greatly benefit the health of citizens and the local ecosystem in Delhi, and could have broader application for other megacities characterized by severe PM pollution and VOC-limited ozone production

Evaluating inter-and intra-rater reliability in the bronchoscopic grading of burn inhalation injury: The iBRONCH-BII study.

The evidence that the severity of burn inhalation injury (BII) impacts clinical outcomes is inconsistent. This may be due to misclassification arising from the subjectivity in bronchoscopically grading BII using systems such as the Abbreviated Injury Score (AIS). This study aimed to evaluate inter- and intra-rater reliability in the grading of BII using the AIS. In a cohort study, specialist burns clinicians (n = 17) and novices (n = 10) graded sixteen BII bronchoscopic images using the AIS during an online meeting. Inter-rater reliability was evaluated using the Kappa statistic (k), with values < 0.60 considered clinically inadequate. The grade rating process was repeated after seven days to evaluate intra-rater reliability. Evaluation of reliability in the grading of BII bronchoscopy reports was conducted as a sensitivity analysis. Amongst all raters, inter-rater reliability was low for grading images (k = 0.30, 95 % confidence interval (CI): 0.29-0.31). Intra-rater reliability was higher than inter-rater reliability, but was still low, with median image grade rate k = 0.45 (interquartile range [IQR]:0.24-0.53). Intensivists demonstrated the highest rater reliability. Reliability in rating the grade of BII by bronchoscopic images was clinically inadequate. Strategies to improve the reliability of reporting the grade of BII are required