Associations between daily mortality in London and combined oxidant capacity, ozone and nitrogen dioxide.

Both nitrogen dioxide (NO2) and ozone (O3) are powerful oxidants in ambient air that are intimately linked through atmospheric chemistry and which continuously interchange over very short timescales. Based upon atmospheric chemistry alone, there is a strong, a priori, reason for considering O3 and NO2 together in epidemiological studies, rather than either of the two pollutants separately in single-pollutant models. This paper compares two approaches to this, using Ox, defined as O3 + NO2, as a single metric and also using O3 and NO2 together in two-pollutant models. We hypothesised that the magnitude of the association between Ox and daily mortality would be greater than for NO2 and O3 individually. Using collocated hourly measurements for O3 and NO2 in London, from 2000 to 2005, we carried out a time series analysis of daily mortality. We investigated O3, NO2 and Ox individually in single-pollutant Poisson regression models and NO2 and O3 jointly in two-pollutant models in both all-year and season-specific analyses. We observed larger associations for mean 24-h concentrations of Ox (1.30 % increase in mortality per 10 ppb) than for O3 (0.87 %) and NO2 (0 %) individually. However, when analysed jointly in two-pollutant models, associations for O3 (1.54 %) and NO2 (1.07 %) were comparable to the Ox association. Season-specific analyses broadly followed this pattern irrespective of whether the Ox concentrations were driven by O3 production (summer) or depletion (winter). This novel approach in air pollution epidemiology captures the simultaneous impact of both oxidants whilst avoiding many of the statistical issues associated with two-pollutant models and potentially simplifies health impact calculations

Riverine macroinvertebrate responses to chlorine and chlorinated sewage effluents - acute chlorine tolerances of Baetis harrisoni (Ephemeroptera) from two rivers in KwaZulu-Natal, South Africa

Chlorine is widely used in South African sewage treatment works, and despite its volatility is likely to have a considerable impact on riverine ecosystems. This paper considers the results of acute (96 h) toxicity responses to chlorine of riverine mayfly nymphs Baetis harrisoni collected from the small, relatively uncontaminated suburban Westville Stream, KwaZulu-Natal and from the more severely impacted Umbilo River, which flows through the industrial area of Pinetown, KwaZulu-Natal, South Africa. The 96 h LC5

Biophotonic Tools in Cell and Tissue Diagnostics.

In order to maintain the rapid advance of biophotonics in the U.S. and enhance our competitiveness worldwide, key measurement tools must be in place. As part of a wide-reaching effort to improve the U.S. technology base, the National Institute of Standards and Technology sponsored a workshop titled "Biophotonic tools for cell and tissue diagnostics." The workshop focused on diagnostic techniques involving the interaction between biological systems and photons. Through invited presentations by industry representatives and panel discussion, near- and far-term measurement needs were evaluated. As a result of this workshop, this document has been prepared on the measurement tools needed for biophotonic cell and tissue diagnostics. This will become a part of the larger measurement road-mapping effort to be presented to the Nation as an assessment of the U.S. Measurement System. The information will be used to highlight measurement needs to the community and to facilitate solutions

Potential impacts of emissions associated with unconventional hydrocarbon extraction on UK air quality and human health

Here we report the first results of model sensitivity simulations to assess the potential impacts of emissions related to future activities linked to unconventional hydrocarbon extraction (fracking) in the UK on air pollution and human health. These simulations were performed with the Met Office Air Quality in the Unified Model, a new air quality forecasting model, and included a wide range of extra emissions of volatile organic compounds (VOCs) and nitrogen oxides (NOx) to reflect emissions from the full life-cycle of fracking related activities and simulate the impacts of these compounds on levels of nitrogen-dioxide (NO2) and ozone (O3). These model simulations highlight that increases in NOx and VOC emissions associated with unconventional hydrocarbon extraction could lead to large local increases in the monthly means of daily 1-hourly maximum NO2 of up to +30 ppb and decreases in the maximum daily 8-hourly mean O3 up to -6 ppb in the summertime. Broadly speaking, our simulations indicate increases in both of these compounds across the UK air shed throughout the year. Changes in the 1-hourly maximum of NO2 and 8-hourly mean of O3 are particularly important for their human health impacts. These respective changes in NO2 and O3 would contribute to approximately 110 (range 50-530) extra premature-deaths a year across the UK based on the use of recently reported concentration response functions for changes in annual average NO2 and O3 exposure. As such we conclude that the release of emissions of VOCs and NOx be highly controlled to prevent deleterious health impacts

Graph Edit Distance Reward: Learning to Edit Scene Graph

Scene Graph, as a vital tool to bridge the gap between language domain and image domain, has been widely adopted in the cross-modality task like VQA. In this paper, we propose a new method to edit the scene graph according to the user instructions, which has never been explored. To be specific, in order to learn editing scene graphs as the semantics given by texts, we propose a Graph Edit Distance Reward, which is based on the Policy Gradient and Graph Matching algorithm, to optimize neural symbolic model. In the context of text-editing image retrieval, we validate the effectiveness of our method in CSS and CRIR dataset. Besides, CRIR is a new synthetic dataset generated by us, which we will publish it soon for future use.Comment: 14 pages, 6 figures, ECCV camera ready versio

Development and validation of a novel bioassay to determine glucocorticoid sensitivity

BACKGROUND: Glucocorticoids (GCs) remain the first line treatment for almost all non-infectious inflammatory diseases, ranging from acute asthma to rheumatoid arthritis. However, across all conditions, patients have a variable response to GCs with approximately 30% being non-responders. This group of GC resistant patients is typically exposed to high-dose GCs and their side-effects before more appropriate immunotherapy is instituted. Hence, there is a pressing clinical need for a predictive biomarker of GC responsiveness. The availability of such a tool would also enable patient stratification for the conduct of smart clinical trials in GC resistance. Lymphocyte GC sensitivity has been shown to be closely associated with clinical GC sensitivity in a number of inflammatory diseases. However, the method for determining in vitro GC response is not standardized and requires the use of specialist equipment, including a radioisotope to quantify cellular proliferation, making it challenging to translate into clinical practice. RESULTS: Here we describe the optimization and validation of a novel non-radioactive in vitro bioassay based on measuring cellular proliferation by incorporation of bromodeoxyuridine (BrdU), termed the BrdU incorporation in lymphocyte steroid sensitivity assay (BLISS). In comparison to the current gold standard lymphocyte GC sensitivity assay in 101 healthy control samples, BLISS has an area under receiver operating characteristic of 0.82 and a sensitivity of 83% for correctly identifying GC resistant subjects. CONCLUSIONS: The performance of the novel BLISS bioassay makes it a strong candidate biomarker for clinical application. It now requires validation in a prospective patient cohort. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40364-016-0079-y) contains supplementary material, which is available to authorized users

Development and validation of a novel bioassay to determine glucocorticoid sensitivity

Background: Glucocorticoids (GCs) remain the first line treatment for almost all non-infectious inflammatory diseases, ranging from acute asthma to rheumatoid arthritis. However, across all conditions, patients have a variable response to GCs with approximately 30% being non-responders. This group of GC resistant patients is typically exposed to high-dose GCs and their side-effects before more appropriate immunotherapy is instituted. Hence, there is a pressing clinical need for a predictive biomarker of GC responsiveness. The availability of such a tool would also enable patient stratification for the conduct of smart clinical trials in GC resistance. Lymphocyte GC sensitivity has been shown to be closely associated with clinical GC sensitivity in a number of inflammatory diseases. However, the method for determining in vitro GC response is not standardized and requires the use of specialist equipment, including a radioisotope to quantify cellular proliferation, making it challenging to translate into clinical practice. / Results: Here we describe the optimization and validation of a novel non-radioactive in vitro bioassay based on measuring cellular proliferation by incorporation of bromodeoxyuridine (BrdU), termed the BrdU incorporation in lymphocyte steroid sensitivity assay (BLISS). In comparison to the current gold standard lymphocyte GC sensitivity assay in 101 healthy control samples, BLISS has an area under receiver operating characteristic of 0.82 and a sensitivity of 83% for correctly identifying GC resistant subjects. / Conclusions: The performance of the novel BLISS bioassay makes it a strong candidate biomarker for clinical application. It now requires validation in a prospective patient cohort

Predictors of anemia in preschool children: Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) project.

Background: A lack of information on the etiology of anemia has hampered the design and monitoring of anemia-control efforts.Objective: We aimed to evaluate predictors of anemia in preschool children (PSC) (age range: 6-59 mo) by country and infection-burden category.Design: Cross-sectional data from 16 surveys (n = 29,293) from the Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) project were analyzed separately and pooled by category of infection burden. We assessed relations between anemia (hemoglobin concentration <110 g/L) and severe anemia (hemoglobin concentration <70 g/L) and individual-level (age, anthropometric measures, micronutrient deficiencies, malaria, and inflammation) and household-level predictors; we also examined the proportion of anemia with concomitant iron deficiency (defined as an inflammation-adjusted ferritin concentration <12 μg/L). Countries were grouped into 4 categories on the basis of risk and burden of infectious disease, and a pooled multivariable logistic regression analysis was conducted for each group.Results: Iron deficiency, malaria, breastfeeding, stunting, underweight, inflammation, low socioeconomic status, and poor sanitation were each associated with anemia in >50% of surveys. Associations between breastfeeding and anemia were attenuated by controlling for child age, which was negatively associated with anemia. The most consistent predictors of severe anemia were malaria, poor sanitation, and underweight. In multivariable pooled models, child age, iron deficiency, and stunting independently predicted anemia and severe anemia. Inflammation was generally associated with anemia in the high- and very high-infection groups but not in the low- and medium-infection groups. In PSC with anemia, 50%, 30%, 55%, and 58% of children had concomitant iron deficiency in low-, medium-, high-, and very high-infection categories, respectively.Conclusions: Although causal inference is limited by cross-sectional survey data, results suggest anemia-control programs should address both iron deficiency and infections. The relative importance of factors that are associated with anemia varies by setting, and thus, country-specific data are needed to guide programs