Green Apparel Consumption: An Empirical Examination of Behavior versus Attitudes

The research reports empirical findings that contrast apparel consumers who behave in pro-environment purchasing behavior with those who do behave in pro-environmental purchasing behavior, in an effort to better understand the attitude-behavior gap commonly recognized among consumer researchers in the ethical consumption research stream. A large cross-section of U.S. Consumer data (N=1,846) provides the sample data for analyses.Demographics, product preferences, attribution behavior and intentions are contrasted between the two groups using appropriate statistical tests. Distinctly different profiles of the two consumer groups emerge, suggesting a number of directions for future research with academic and practical implications

Proteins Inform Survival-Based Differences in Patients with Glioblastoma

Background: Improving the care of patients with glioblastoma (GB) requires accurate and reliable predictors of patient prognosis. Unfortunately, while protein markers are an effective readout of cellular function, proteomics has been underutilized in GB prognostic marker discovery. Methods: For this study, GB patients were prospectively recruited and proteomics discovery using liquid chromatography-mass spectrometry analysis (LC-MS/MS) was performed for 27 patients including 13 short-term survivors (STS) (≤10 months) and 14 long-term survivors (LTS) (≥18 months). Results: Proteomics discovery identified 11 941 peptides in 2495 unique proteins, with 469 proteins exhibiting significant dysregulation when comparing STS to LTS. We verified the differential abundance of 67 out of these 469 proteins in a small previously published independent dataset. Proteins involved in axon guidance were upregulated in STS compared to LTS, while those involved in p53 signaling were upregulated in LTS. We also assessed the correlation between LS MS/MS data with RNAseq data from the same discovery patients and found a low correlation between protein abundance and mRNA expression. Finally, using LC-MS/MS on a set of 18 samples from 6 patients, we quantified the intratumoral heterogeneity of more than 2256 proteins in the multisample dataset. Conclusions: These proteomic datasets and noted protein variations present a beneficial resource for better predicting patient outcome and investigating potential therapeutic targets

Distributed micro-releases of bioterror pathogens : threat characterizations and epidemiology from uncertain patient observables.

Terrorist attacks using an aerosolized pathogen preparation have gained credibility as a national security concern since the anthrax attacks of 2001. The ability to characterize the parameters of such attacks, i.e., to estimate the number of people infected, the time of infection, the average dose received, and the rate of disease spread in contemporary American society (for contagious diseases), is important when planning a medical response. For non-contagious diseases, we address the characterization problem by formulating a Bayesian inverse problem predicated on a short time-series of diagnosed patients exhibiting symptoms. To keep the approach relevant for response planning, we limit ourselves to 3.5 days of data. In computational tests performed for anthrax, we usually find these observation windows sufficient, especially if the outbreak model employed in the inverse problem is accurate. For contagious diseases, we formulated a Bayesian inversion technique to infer both pathogenic transmissibility and the social network from outbreak observations, ensuring that the two determinants of spreading are identified separately. We tested this technique on data collected from a 1967 smallpox epidemic in Abakaliki, Nigeria. We inferred, probabilistically, different transmissibilities in the structured Abakaliki population, the social network, and the chain of transmission. Finally, we developed an individual-based epidemic model to realistically simulate the spread of a rare (or eradicated) disease in a modern society. This model incorporates the mixing patterns observed in an (American) urban setting and accepts, as model input, pathogenic transmissibilities estimated from historical outbreaks that may have occurred in socio-economic environments with little resemblance to contemporary society. Techniques were also developed to simulate disease spread on static and sampled network reductions of the dynamic social networks originally in the individual-based model, yielding faster, though approximate, network-based epidemic models. These reduced-order models are useful in scenario analysis for medical response planning, as well as in computationally intensive inverse problems

Covariation in urban birds providing cultural services or disservices and people

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.1. The spatial distributions of biodiversity and people vary across landscapes, and are critical to the delivery of ecosystem services and disservices. The high densities of people, and often of birds, in urban areas lead to frequent human-avian interactions, which can be positive or negative for people’s well-being. The identities of the bird species providing these services or disservices tend to be quite different, however it is unclear how their abundance and richness covary with human population density, and hence with potential recipients of these services and disservices. 2. We surveyed bird populations in 106 tiles (500x500 m) across the 174 km2 of an extended urban area in southern England. From the literature, we identified two groups of species: those associated with positive interactions for human well-being, and those that display behaviours that are negative for human well-being. We estimated the abundance (adjusted for detection probability) and richness of each group, and modelled how they covary with human population density. 3. Aggregation of population estimates for the 35 service and nine disservice species observed revealed 593,128 (95% confidence interval: 541,817-657,046) and 225,491 (200,134-235,066) birds, respectively. Across the surveyed tiles there were 1.09 service, and 0.42 disservice birds per person. 4. There was a peaking quadratic relationship between service abundance and human population density, but a negative linear relationship between richness and human density. Conversely, there were positive linear relationships for both abundance and richness of disservice species with human density. The ratio of service to disservice birds shifted from 3.5 to 1 at intermediate human densities to 1 to 1 in more densely populated areas. 5. Synthesis and applications. Differences in the distributions of service and disservice species, and the extremely low ratios of birds to people particularly in socioeconomically deprived areas, mean that people there have few opportunities for contact with birds, and the contact that they do have is equally likely to be negative as positive for human well-being. We recommend spatial targeting of improvements in green infrastructure, combined with the targeted provisioning of food and nesting places for service species, to promote positive interactions between birds and people.We thank M. Evans and M. Gregory for their fieldwork, and J. Harris and R. Corstanje for their advice and logistical support. All authors were supported by the Fragments, Functions, Flows and Urban Ecosystem Services project, NERC grant NE/J015237/1, funded under the NERC Biodiversity and Ecosystem Service Sustainability programme. The authors declare no conflict of interest

Body mass index, physical activity, and dietary behaviors among members of an urban community fitness center: a questionnaire survey

<p>Abstract</p> <p>Background</p> <p>Development of effective behavioral interventions to promote weight control and physical activity among diverse, underserved populations is a public health priority. Community focused wellness organizations, such as YMCAs, could provide a unique channel with which to reach such populations. This study assessed health behaviors and related characteristics of members of an urban YMCA facility.</p> <p>Methods</p> <p>We surveyed 135 randomly selected members of an urban YMCA facility in Massachusetts to examine self-reported (1) physical activity, (2) dietary behaviors, (3) body mass index, and (4) correlates of behavior change among short-term (i.e., one year or less) and long-term (i.e., more than one year) members. Chi-square tests were used to assess bivariate associations between variables, and multivariate linear regression models were fit to examine correlates of health behaviors and weight status.</p> <p>Results</p> <p>Eighty-nine percent of short-term and 94% of long-term members reported meeting current physical activity recommendations. Only 24% of short-term and 19% of long-term members met fruit and vegetable consumption recommendations, however, and more than half were overweight or obese. Length of membership was not significantly related to weight status, dietary behaviors, or physical activity. Most respondents were interested in changing health behaviors, in the preparation stage of change, and had high levels of self-efficacy to change behaviors. Short-term members had less education (p = 0.02), lower household incomes (p = 0.02), and were less likely to identify as white (p = 0.005) than long-term members. In multivariate models, females had lower BMI than males (p = 0.003) and reported less physical activity (p = 0.008). Physical activity was also inversely associated with age (p = 0.0004) and education (p = 0.02).</p> <p>Conclusion</p> <p>Rates of overweight/obesity and fruit and vegetable consumption suggested that there is a need for a weight control intervention among members of an urban community YMCA. Membership in such a community wellness facility alone might not be sufficient to help members maintain a healthy weight. The data indicate that YMCA members are interested in making changes in their dietary and physical activity behaviors. Targeting newer YMCA members might be an effective way of reaching underserved populations. These data will help inform the development of a weight control intervention tailored to this setting.</p

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment