The Editors

Luxury industry and Corporate Social Responsibility (CSR) activates are generally considered as incompatible concepts by consumers. This because luxury is generally related to hedonism, excess, and ostentation, while CSR is generally based on sobriety, moderation and ethics. However, nowadays more and more luxury companies seem highly committed toward sustainability. For example, Tiffany started certifying its diamonds as “conflict free”, Chanel incorporated “earthy materials” in its 2016 collection, and Bulgari has recently funded restoration of Rome's Spanish Steps. Therefore, it seems plausible the presence of a certain compatibility degree between luxury and CSR activities. However, this issue has received very limited empirical investigation from marketing literature. As a consequence, the present research aims to empirically test whether and under what conditions consumers react to different kinds of luxury companies’ CSR initiatives. Using the Carroll’s four dimensions model of internal vs. external CSR, we argue and demonstrated that luxury companies’ internal (versus external) CSR initiatives increase willingness to buy luxury products, but mainly for those customers who buy luxury for internal motivations and not for status ostentation, as for example individual style and personal taste

Big Data: Managing the Future\u27s Agriculture and Natural Resource Systems

Big Data: Managing the Future\u27s Agriculture and Natural Resource Systems Big data is the incredible flow of information that surrounds each of us, every day. Big data tools identify patterns and habits, not only in research, but in manufacturing, logistics–even ordering items online

How can the MHC mediate social odor via the microbiota community? A deep dive into mechanisms

Genes of the major histocompatibility complex (MHC) have long been linked to odor signaling and recently researchers’ attention has focused on MHC structuring of microbial communities and how this may in turn impact odor. However, understanding of the mechanisms through which the MHC could affect the microbiota to produce a chemical signal that is both reliable and strong enough to ensure unambiguous transmission of behaviorally important information remains poor. This is largely because empirical studies are rare, predictions are unclear, and the underlying immunological mechanisms governing MHC-microbiota interactions are often neglected. Here we review the immunological processes involving MHC class II (MHC-II) that could affect the commensal community. Focusing on immunological and medical research, we provide background knowledge for non-immunologists by describing key players within the vertebrate immune system relating to MHC-II molecules (which present extracellular-derived peptides, and thus interact with extracellular commensal microbes). We then systematically review the literature investigating MHC-odor-microbiota interactions in animals and identify areas for future research. These insights will help to design studies that are able to explore the role of MHC-II and the microbiota in the behavior of wild populations in their natural environment and consequently propel this research area forward

SmokeHaz: systematic reviews and meta-analyses of the effects of smoking on respiratory health

Background: Smoking tobacco increases the risk of respiratory disease in adults and children, but communicating the magnitude of these effects in a scientific manner that is accessible and usable by public and policymakers presents a challenge. We have therefore summarised scientific data on the impact of smoking on respiratory diseases to provide the content for a unique resource, SmokeHaz. Methods: We conducted systematic reviews and meta-analyses of longitudinal studies (published to 2013) identified from electronic databases, grey literature, and experts. Random effect meta-analyses were used to pool the findings. Results: We included 216 papers. Among adult smokers, we confirmed substantially increased risks of lung cancer (Risk Ratio (RR) 10.92, 95% CI 8.28-14.40; 34 studies), COPD (RR 4.01, 95% CI 3.18-5.05; 22 studies) and asthma (RR 1.61, 95% CI 1.07-2.42; 8 studies). Exposure to passive smoke significantly increased the risk of lung cancer in adult non-smokers; and increased the risks of asthma, wheeze, lower respiratory infections, and reduced lung function in children. Smoking significantly increased the risk of sleep apnoea, and asthma exacerbations in adult and pregnant populations; and active and passive smoking increased the risk of tuberculosis. Conclusions: These findings have been translated into easily digestible content and published on the SmokeHaz website (www.smokehaz.eu)

Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels.

Elevated serum urate levels cause gout and correlate with cardiometabolic diseases via poorly understood mechanisms. We performed a trans-ancestry genome-wide association study of serum urate in 457,690 individuals, identifying 183 loci (147 previously unknown) that improve the prediction of gout in an independent cohort of 334,880 individuals. Serum urate showed significant genetic correlations with many cardiometabolic traits, with genetic causality analyses supporting a substantial role for pleiotropy. Enrichment analysis, fine-mapping of urate-associated loci and colocalization with gene expression in 47 tissues implicated the kidney and liver as the main target organs and prioritized potentially causal genes and variants, including the transcriptional master regulators in the liver and kidney, HNF1A and HNF4A. Experimental validation showed that HNF4A transactivated the promoter of ABCG2, encoding a major urate transporter, in kidney cells, and that HNF4A p.Thr139Ile is a functional variant. Transcriptional coregulation within and across organs may be a general mechanism underlying the observed pleiotropy between urate and cardiometabolic traits.The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. Variant annotation was supported by software resources provided via the Caché Campus program of the InterSystems GmbH to Alexander Teumer