Melanocortin‐1 receptor (MC1R) genotypes do not correlate with size in two cohorts of medium‐to‐giant congenital melanocytic nevi

Congenital melanocytic nevi (CMN) are cutaneous malformations whose prevalence is inversely correlated with projected adult size. CMN are caused by somatic mutations, but epidemiological studies suggest that germline genetic factors may influence CMN development. In CMN patients from the U.K., genetic variants in MC1R, such as p.V92M and loss‐of‐function variants, have been previously associated with larger CMN. We analyzed the association of MC1R variants with CMN characteristics in two distinct cohorts of medium‐to‐giant CMN patients from Spain (N = 113) and from France, Norway, Canada, and the United States (N = 53), similar at the clinical and phenotypical level except for the number of nevi per patient. We found that the p.V92M or loss‐of‐function MC1R variants either alone or in combination did not correlate with CMN size, in contrast to the U.K. CMN patients. An additional case–control analysis with 259 unaffected Spanish individuals showed a higher frequency of MC1R compound heterozygous or homozygous variant genotypes in Spanish CMN patients compared to the control population (15.9% vs. 9.3%; p = .075). Altogether, this study suggests that MC1R variants are not associated with CMN size in these non‐UK cohorts. Additional studies are required to define the potential role of MC1R as a risk factor in CMN development.     

Incorporating intraspecific variation into species distribution models improves distribution predictions,but cannot predict species traits for a wide-spread plant species

The most common approach to predicting how species ranges and ecological functions will shift with climate change is to construct correlative species distribution models (SDMs). These models use a species’ climatic distribution to determine currently suitable areas for the species and project its potential distribution under future climate scenarios. A core, rarely tested, assumption of SDMs is that all populations will respond equivalently to climate. Few studies have examined this assumption, and those that have rarely dissect the reasons for intraspecific differences. Focusing on the arctic-alpine cushion plant Silene acaulis, we compared predictive accuracy from SDMs constructed using the species’ full global distribution with composite predictions from separate SDMs constructed using subpopulations defined either by genetic or habitat differences. This is one of the first studies to compare multiple ways of constructing intraspecific-level SDMs with a species-level SDM. We also examine the contested relationship between relative probability of occurrence and species performance or ecological function, testing if SDM output can predict individual performance (plant size) and biotic interactions (facilitation). We found that both genetic- and habitat-informed SDMs are considerably more accurate than a species-level SDM, and that the genetic model substantially differs from and outperforms the habitat model. While SDMs have been used to infer population performance and possibly even biotic interactions, in our system these relationships were extremely weak. Our results indicate that individual subpopulations may respond differently to climate, although we discuss and explore several alternative explanations for the superior performance of intraspecific-level SDMs. We emphasize the need to carefully examine how to best define intraspecific-level SDMs as well as how potential genetic, environmental, or sampling variation within species ranges can critically affect SDM predictions. We urge caution in inferring population performance or biotic interactions from SDM predictions, as these often-assumed relationships are not supported in our study.     

Can S-LCA methodology support responsible sourcing of raw materials in EU policy context?

Purpose

Access, affordability and sustainability of raw material supply chains are crucial to the sustainable development of the European Union (EU) for both society and economy. The study investigates whether and how the social life cycle assessment (S-LCA) methodology can support responsible sourcing of raw materials in Europe. The potential of social indicators already available in an S-LCA database is tested for the development of new metrics to monitor social risks in raw material industries at EU policy level.

Methods

The Product Social Impact Life Cycle Assessment (PSILCA) database was identified as a data and indicators source to assess social risks in raw material industries in EU-28 and extra-EU countries. Six raw material country sectors in the scope of the European policy on raw materials were identified and aggregated among those available in PSILCA. The selection of indicators for the assessment was based on the RACER (Relevance, Acceptance, Credibility, Ease, Robustness) analysis, leading to the proposal of 9 social impact categories. An S-LCA of the selected raw material industries was, thus, performed for the EU-28 region, followed by a contribution analysis to detect direct and indirect impacts and investigate related supply chains. Finally, the social performance of raw material sectors in EU-28 was compared with that of six extra-EU countries.

Results and discussion

Considering the overall social risks in raw material industries, “Corruption”, “Fair salary”, “Health and safety” and “Freedom of association and collective bargaining” emerged as the most significant categories both in EU and extra-EU. EU-28 shows an above-average performance where the only exception is represented by the mining and quarrying sector. An investigation of the most contributing processes to social impact categories for EU-28 led to the identification of important risks originating in the supply chain and in extra-EU areas. Therefore, the S-LCA methodology confirmed the potential of a life cycle perspective to detect burdens shifting and trade-offs. However, only a limited view on the sectoral social performance could be obtained from the research due to a lack of social data.

Conclusions

The S-LCA methodology and indicators appear appropriate to perform an initial social sustainability screening, thus enabling the identification of hotspots in raw material supply chains and the prioritization of areas of action in EU policies. Further methodological developments in the S-LCA field are necessary to make the approach proposed in the paper fully adequate to support EU policies on raw materials.

     

In silico and empirical evaluation of twelve metabarcoding primer sets for insectivorous diet analyses

During the most recent decade, environmental DNA metabarcoding approaches have been both developed and improved to minimize the biological and technical biases in these protocols. However, challenges remain, notably those relating to primer design. In the current study, we comprehensively assessed the performance of ten COI and two 16S primer pairs for eDNA metabarcoding, including novel and previously published primers. We used a combined approach of in silico, in vivo‐mock community (33 arthropod taxa from 16 orders), and guano‐based analyses to identify primer sets that would maximize arthropod detection and taxonomic identification, successfully identify the predator (bat) species, and minimize the time and financial costs of the experiment. We focused on two insectivorous bat species that live together in mixed colonies: the greater horseshoe bat (Rhinolophus ferrumequinum) and Geoffroy's bat (Myotis emarginatus). We found that primer degeneracy is the main factor that influences arthropod detection in silico and mock community analyses, while amplicon length is critical for the detection of arthropods from degraded DNA samples. Our guano‐based results highlight the importance of detecting and identifying both predator and prey, as guano samples can be contaminated by other insectivorous species. Moreover, we demonstrate that amplifying bat DNA does not reduce the primers' capacity to detect arthropods. We therefore recommend the simultaneous identification of predator and prey. Finally, our results suggest that up to one‐third of prey occurrences may be unreliable and are probably not of primary interest in diet studies, which may decrease the relevance of combining several primer sets instead of using a single efficient one. In conclusion, this study provides a pragmatic framework for eDNA primer selection with respect to scientific and methodological constraints.     

First characterization of congenital myasthenic syndrome type 5 in North Africa

Molecular Biology Reports - Congenital myasthenic syndromes (CMS) are associated with defects in the structure and the function of neuromuscular junctions. These rare disorders can result from...     

Unbiased proteomic profiling of host cell extracellular vesicle composition and dynamics upon HIV‐1 infection

Cells release diverse types of extracellular vesicles (EVs), which transfer complex signals to surrounding cells. Specific markers to distinguish different EVs (e.g. exosomes, ectosomes, enveloped viruses like HIV) are still lacking. We have developed a proteomic profiling approach for characterizing EV subtype composition and applied it to human Jurkat T cells. We generated an interactive database to define groups of proteins with similar profiles, suggesting release in similar EVs. Biochemical validation confirmed the presence of preferred partners of commonly used exosome markers in EVs: CD81/ADAM10/ITGB1, and CD63/syntenin. We then compared EVs from control and HIV‐1‐infected cells. HIV infection altered EV profiles of several cellular proteins, including MOV10 and SPN, which became incorporated into HIV virions, and SERINC3, which was re‐routed to non‐viral EVs in a Nef‐dependent manner. Furthermore, we found that SERINC3 controls the surface composition of EVs. Our workflow provides an unbiased approach for identifying candidate markers and potential regulators of EV subtypes. It can be widely applied to in vitro experimental systems for investigating physiological or pathological modifications of EV release.     

Predictive markers of safety and immunogenicity of adjuvanted vaccines

Vaccination represents one of the greatest public health triumphs; in part due to the effect of adjuvants that have been included in vaccine preparations to boost the immune responses through different mechanisms. Although a variety of novel adjuvants have been under development, only a limited number have been approved by regulatory authorities for human vaccines. This report reflects the conclusions of a group of scientists from academia, regulatory agencies and industry who attended a conference on the current state of the art in the adjuvant field. Held at the U.S. Pharmacopeial Convention (USP) in Rockville, Maryland, USA, from 18 to 19 April 2013 and organized by the International Association for Biologicals (IABS), the conference focused particularly on the future development of effective adjuvants and adjuvanted vaccines and on overcoming major hurdles, such as safety and immunogenicity assessment, as well as regulatory scrutiny. More information on the conference output can be found on the IABS website, http://www.iabs.org/.     

Effect of 6-Benzoyl-benzothiazol-2-one scaffold on the pharmacological profile of α-alkoxyphenylpropionic acid derived PPAR agonists

Abstract

A series of nitrogen heterocycles containing α–ethoxyphenylpropionic acid derivatives were designed as dual PPARα/γ agonist ligands for the treatment of type 2 diabetes (T2D) and its complications. 6-Benzoyl-benzothiazol-2-one was the most tolerant of the tested heterocycles in which incorporation of O-methyl oxime ether and trifluoroethoxy group followed by enantiomeric resolution led to the (S)-stereoisomer 44?b displaying the best in vitro pharmacological profile. Compound 44?b acted as a very potent full PPARγ agonist and a weak partial agonist on the PPARα receptor subtype. Compound 44?b showed high efficacy in an ob/ob mice model with significant decreases in serum triglyceride, glucose and insulin levels but mostly with limited body-weight gain and could be considered as a selective PPARγ modulator (SPPARγM).