Replacement of Hydrochlorofluorocarbon (HCFC) -225 Solvent for Cleaning and Verification Sampling of NASA Propulsion Oxygen Systems Hardware, Ground Support Equipment, and Associated Test Systems

Since the 1990's, NASA's rocket propulsion test facilities at Marshall Space Flight Center (MSFC) and Stennis Space Center (SSC) have used hydrochlorofluorocarbon-225 (HCFC-225), a Class II ozone-depleting substance, to safety clean and verify the cleanliness of large scale propulsion oxygen systems and associated test facilities. In 2012 through 2014, test laboratories at MSFC, SSC, and Johnson Space Center-White Sands Test Facility collaborated to seek out, test, and qualify an environmentally preferred replacement for HCFC-225. Candidate solvents were selected, a test plan was developed, and the products were tested for materials compatibility, oxygen compatibility, cleaning effectiveness, and suitability for use in cleanliness verification and field cleaning operations. Honewell Soltice (TradeMark) Performance Fluid (trans-1-chloro-3,3, 3-trifluoropropene) was selected to replace HCFC-225 at NASA's MSFC and SSC rocket propulsion test facilities

CEBS—Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data

CEBS (Chemical Effects in Biological Systems) is an integrated public repository for toxicogenomics data, including the study design and timeline, clinical chemistry and histopathology findings and microarray and proteomics data. CEBS contains data derived from studies of chemicals and of genetic alterations, and is compatible with clinical and environmental studies. CEBS is designed to permit the user to query the data using the study conditions, the subject responses and then, having identified an appropriate set of subjects, to move to the microarray module of CEBS to carry out gene signature and pathway analysis. Scope of CEBS: CEBS currently holds 22 studies of rats, four studies of mice and one study of Caenorhabditis elegans. CEBS can also accommodate data from studies of human subjects. Toxicogenomics studies currently in CEBS comprise over 4000 microarray hybridizations, and 75 2D gel images annotated with protein identification performed by MALDI and MS/MS. CEBS contains raw microarray data collected in accordance with MIAME guidelines and provides tools for data selection, pre-processing and analysis resulting in annotated lists of genes of interest. Additionally, clinical chemistry and histopathology findings from over 1500 animals are included in CEBS. CEBS/BID: The BID (Biomedical Investigation Database) is another component of the CEBS system. BID is a relational database used to load and curate study data prior to export to CEBS, in addition to capturing and displaying novel data types such as PCR data, or additional fields of interest, including those defined by the HESI Toxicogenomics Committee (in preparation). BID has been shared with Health Canada and the US Environmental Protection Agency. CEBS is available at http://cebs.niehs.nih.gov. BID can be accessed via the user interface from https://dir-apps.niehs.nih.gov/arc/. Requests for a copy of BID and for depositing data into CEBS or BID are available at http://www.niehs.nih.gov/cebs-df/

When algorithms shape collective action: Social media and the dynamics of cloud protesting

How does the algorithmically mediated environment of social media restructure social action? This article combines social movement studies and science and technology studies to explore the role of social media in the organization, unfolding, and diffusion of contemporary protests. In particular, it examines how activists leverage the technical properties of social media to develop a joint narrative and a collective identity. To this end, it offers the notion of cloud protesting as a theoretical approach and framework for empirical analysis. Cloud protesting indicates a specific type of mobilization that is grounded on, modeled around, and enabled by social media platforms and mobile devices and the virtual universes they identify. The notion emphasizes both the productive mediation of social and mobile media and the importance of activists’ sense-making activities. It also acknowledges that social media set in motion a process that is sociotechnical in nature rather than merely sociological or communicative, and thus can be understood only by intersecting the material and the symbolic dimensions of contemporary digitally mediated collective action. The article shows how the specific materiality of social media intervenes in the actors’ meaning work by fostering four mechanisms—namely performance, interpellation, temporality, and reproducibility—which concur to create a "politics of visibility" that alters traditional identity dynamics. In addition, it exposes the connection between organizational patterns and the role of individuals, explaining how the politics of visibility is the result of a process that originates and ends within the individual—which ultimately creates individuals-in-the-group rather than groups

Stigma and Ebola survivorship in liberia: Results from a longitudinal cohort study

Background Survivors of the 2014–2016 West Africa Ebola epidemic have been reported to suffer high levels of stigmatization after return to their communities. We sought to characterize the stigma encountered by a cohort of Ebola survivors in Liberia over time. Methods Ebola-related stigma was assessed from June 2015 to August 2017 in 299 adolescent and adult Liberian Ebola Survivor Cohort participants at three month intervals using adapted HIV stigma scales scored from 0 to 10 according to the proportion of answers indicating stigmatization. Findings The median time from Ebola Virus Disease (EVD) to study entry was 393 days (IQR 336–492). Participants (43% female) had a median age of 31 (IQR 25–40) years. Mean self-reported stigma levels were greater at baseline (6.28 ± 0.15 [IQR: 4.38–8.75]) compared to the first post-baseline visit (0.60 ± 0.10 [IQR: 0–0]; p<0.0001). During follow-up, stigma levels were stable. Baseline stigma significantly increased during enrollment and following clusters of Ebola re-emergence in Liberia. Survivors encountered primarily enacted and perceived external stigma rather than internalized stigma. Conclusions Ebola-related stigma was prevalent among Liberian survivors more than a year after EVD recovery. Self-reported stigma was greater in the period before cohort enrollment; however, some degree of stigmatization persisted years after EVD. Transient rises in stigma were observed following episodic Ebola re-emergence of EVD in Liberia. During future EVD outbreaks, enhanced public health interventions designed to prevent and mitigate Ebola-related stigma that is enacted and external should be implemented to support survivor recovery and community re-integration

Inverse gene expression patterns for macrophage activating hepatotoxicants and peroxisome proliferators in rat liver

Abstract Macrophage activation contributes to adverse effects produced by a number of hepatotoxic compounds. Transcriptional profiles elicited by two macrophage activators, LPS and zymosan A, were compared to those produced by 100 paradigm compounds (mostly hepatotoxicants) using cDNA microarrays. Several hepatotoxicants previously reported to activate liver macrophages produced transcriptional responses similar to LPS and zymosan, and these were used to construct a gene signature profile for macrophage activators in the liver. Measurement of cytokine mRNAs in the same liver samples by RT-PCR independently confirmed that these compounds are associated with macrophage activation. In addition to expected effects on acute phase proteins and metabolic pathways that are regulated by LPS and inflammation, a strong induction was observed for many endoplasmic reticulum-associated stress/chaperone proteins. Additionally, many genes in our macrophage activator signature profile were well-characterized PPARa-induced genes which were repressed by macrophage activators. A shared gene signature profile for peroxisome proliferators was determined using a training set of clofibrate, WY 14643, diethylhexylphthalate, diisononylphthalate, perfluorodecanoic acid, perfluoroheptanoic acid, and perfluorooctanoic acid. The signature profile included macrophage activator-induced genes that were repressed by peroxisome proliferators. NSAIDs comprised an interesting pharmacological class in that some compounds, notably diflunisal, co-clustered with peroxisome proliferators whereas several others co-clustered with macrophage activators, possibly due to endotoxin exposure secondary to their adverse effects on the gastrointestinal system. While much of these data confirmed findings from the literature, the transcriptional patterns detected using this toxicogenomics approach showed relationships between genes and biological pathways requiring complex analysis to be discerned.

Influence of family and friend smoking on intentions to smoke and smoking-related attitudes and refusal self-efficacy among 9-10 year old children from deprived neighbourhoods: a cross-sectional study.

BACKGROUND: Smoking often starts in early adolescence and addiction can occur rapidly. For effective smoking prevention there is a need to identify at risk groups of preadolescent children and whether gender-specific intervention components are necessary. This study aimed to examine associations between mother, father, sibling and friend smoking and cognitive vulnerability to smoking among preadolescent children living in deprived neighbourhoods. METHODS: Cross-sectional data was collected from 9-10 year old children (n =1143; 50.7% girls; 85.6% White British) from 43 primary schools in Merseyside, England. Children completed a questionnaire that assessed their smoking-related behaviour, intentions, attitudes, and refusal self-efficacy, as well as parent, sibling and friend smoking. Data for boys and girls were analysed separately using multilevel linear and logistic regression models, adjusting for individual cognitions and school and deprivation level. RESULTS: Compared to girls, boys had lower non-smoking intentions (P = 0.02), refusal self-efficacy (P = 0.04) and were less likely to agree that smoking is 'definitely' bad for health (P < 0.01). Friend smoking was negatively associated with non-smoking intentions in girls (P < 0.01) and boys (P < 0.01), and with refusal self-efficacy in girls (P < 0.01). Sibling smoking was negatively associated with non-smoking intentions in girls (P < 0.01) but a positive association was found in boys (P = 0.02). Boys who had a smoking friend were less likely to 'definitely' believe that the smoke from other people's cigarettes is harmful (OR 0.57, 95% CI: 0.35 to 0.91, P = 0.02). Further, boys with a smoking friend (OR 0.38, 95% CI: 0.21 to 0.69, P < 0.01) or a smoking sibling (OR 0.45, 95% CI: 0.21 to 0.98) were less likely to 'definitely' believe that smoking is bad for health. CONCLUSION: This study indicates that sibling and friend smoking may represent important influences on 9-10 year old children's cognitive vulnerability toward smoking. Whilst some differential findings by gender were observed, these may not be sufficient to warrant separate prevention interventions. However, further research is needed

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

Implications of Storing Urinary DNA from Different Populations for Molecular Analyses

Molecular diagnosis using urine is established for many sexually transmitted diseases and is increasingly used to diagnose tumours and other infectious diseases. Storage of urine prior to analysis, whether due to home collection or bio-banking, is increasingly advocated yet no best practice has emerged. Here, we examined the stability of DNA in stored urine in two populations over 28 days.Urine from 40 (20 male) healthy volunteers from two populations, Italy and Zambia, was stored at four different temperatures (RT, 4 degrees C, -20 degrees C & -80 degrees C) with and without EDTA preservative solution. Urines were extracted at days 0, 1, 3, 7 and 28 after storage. Human DNA content was measured using multi-copy (ALU J) and single copy (TLR2) targets by quantitative real-time PCR. Zambian and Italian samples contained comparable DNA quantity at time zero. Generally, two trends were observed during storage; no degradation, or rapid degradation from days 0 to 7 followed by little further degradation to 28 days. The biphasic degradation was always observed in Zambia regardless of storage conditions, but only twice in Italy.Site-specific differences in urine composition significantly affect the stability of DNA during storage. Assessing the quality of stored urine for molecular analysis, by using the type of strategy described here, is paramount before these samples are used for molecular prognostic monitoring, genetic analyses and disease diagnosis

Association between age at disease onset of anti-neutrophil cytoplasmic antibody-associated vasculitis and clinical presentation and short-term outcomes

Objectives: ANCA-associated vasculitis (AAV) can affect all age groups. We aimed to show that differences in disease presentation and 6 month outcome between younger- A nd older-onset patients are still incompletely understood. Methods: We included patients enrolled in the Diagnostic and Classification Criteria for Primary Systemic Vasculitis (DCVAS) study between October 2010 and January 2017 with a diagnosis of AAV. We divided the population according to age at diagnosis: &lt;65 years or ≥65 years. We adjusted associations for the type of AAV and the type of ANCA (anti-MPO, anti-PR3 or negative). Results: A total of 1338 patients with AAV were included: 66% had disease onset at &lt;65 years of age [female 50%; mean age 48.4 years (s.d. 12.6)] and 34% had disease onset at ≥65 years [female 54%; mean age 73.6 years (s.d. 6)]. ANCA (MPO) positivity was more frequent in the older group (48% vs 27%; P = 0.001). Younger patients had higher rates of musculoskeletal, cutaneous and ENT manifestations compared with older patients. Systemic, neurologic,cardiovascular involvement and worsening renal function were more frequent in the older-onset group. Damage accrual, measured with the Vasculitis Damage Index (VDI), was significantly higher in older patients, 12% of whom had a 6 month VDI ≥5, compared with 7% of younger patients (P = 0.01). Older age was an independent risk factor for early death within 6 months from diagnosis [hazard ratio 2.06 (95% CI 1.07, 3.97); P = 0.03]. Conclusion: Within 6 months of diagnosis of AAV, patients &gt;65 years of age display a different pattern of organ involvement and an increased risk of significant damage and mortality compared with younger patients