Chromosomal localisation of the mouse and human peripherin genes.

Using a mouse cDNA probe encoding for the major part of peripherin, a type III intermediate filament protein, we have assigned, by in situ hybridization, the mouse and human peripherin genes, Prph, to the E-F region of chromosome 15 and to the q12-q13 region of chromosome 12, respectively. These regions are known as homologous chromosomal segments containing other intermediate filament genes (keratins) and also other genes which could be co-ordinately regulated.     

Study on the structure-function relationship of polynucleotide phosphorylase: model of a proteolytic degraded polynucleotide phosphorylase.

It is already known that modification of E. coli polynucleotide phosphorylase by endogenous proteolysis induces drastic changes in both phosphorolysis and polymerisation reactions. The structural parameters of the proteolysed polynucleotide phosphorylase are described. The phosphorolysis of polynucleotide, which is quite progressive for the native enzyme, is shown to be only partially progressive for the degraded enzyme, owing to the loss of polymer attachment sites.     

Reconstitution in vitro of human gingiva

A model of human gingiva to be used in pharmacological, basic and clinical research was performed in vitro. This model was obtained through a method of low density seeding epithelialization, from a seeding made up of dissociated human gingiva epithelial cells, of a connective tissue equivalent composed of human fibroblasts included in a collagen gel. The histological and ultrastructural data show a multilayered epithelium and the biochemical analysis (two dimensional gel electrophoresis known as NEPHGE) of the cytokeratins used as molecular markers for epithelial differentiation shows the precise differentiation state of the epithelium thus reconstituted. Even though this model has less of a differentiation than that of an in vivo gingival epithelium, it does actually reproduce exactly the structures of the human gingiva namely a multilayered epithelium lying on a connective tissue. It also offers the advantage of cellular elements which are compatible with gingival graftings.     

Lethal mutagenesis and evolutionary epidemiology

The lethal mutagenesis hypothesis states that within-host populations of pathogens can be driven to extinction when the load of deleterious mutations is artificially increased with a mutagen, and becomes too high for the population to be maintained. Although chemical mutagens have been shown to lead to important reductions in viral titres for a wide variety of RNA viruses, the theoretical underpinnings of this process are still not clearly established. A few recent models sought to describe lethal mutagenesis but they often relied on restrictive assumptions. We extend this earlier work in two novel directions. First, we derive the dynamics of the genetic load in a multivariate Gaussian fitness landscape akin to classical quantitative genetics models. This fitness landscape yields a continuous distribution of mutation effects on fitness, ranging from deleterious to beneficial (i.e. compensatory) mutations. We also include an additional class of lethal mutations. Second, we couple this evolutionary model with an epidemiological model accounting for the within-host dynamics of the pathogen. We derive the epidemiological and evolutionary equilibrium of the system. At this equilibrium, the density of the pathogen is expected to decrease linearly with the genomic mutation rate U. We also provide a simple expression for the critical mutation rate leading to extinction. Stochastic simulations show that these predictions are accurate for a broad range of parameter values. As they depend on a small set of measurable epidemiological and evolutionary parameters, we used available information on several viruses to make quantitative and testable predictions on critical mutation rates. In the light of this model, we discuss the feasibility of lethal mutagenesis as an efficient therapeutic strategy.     

A note on approximating the cumulative distribution function of the time to tumor onset in multistage models

The general multistage theory of carcinogenesis is a very special type of interconnected birth and death process in which the final state is absorbing and all states except the first one are empty at time zero. An approximation proposed by Whittemore and Keller (1978, SIAM Review 20, 1-30) is assessed. It is shown that the adequacy of this approximation depends on the number of malignant cells resulting from a single normal cell. If more than one malignant cell is likely to occur, the approximation will fail.     

Using anticipatory life cycle assessment to enable future sustainable construction

The built environment is the largest single emitter of CO₂ and an important consumer of energy. Much research has gone into the improved efficiency of building operation and construction products. Life Cycle Assessment (LCA) is commonly used to assess existing buildings or building products. Classic LCA, however, is not suited for evaluating the environmental performance of developing technologies. A new approach, anticipatory LCA (a‐LCA), promises various advantages and can be used as a design constraint during the product development stage. It helps overcome four challenges: (i) data availability, (ii) stakeholder inclusion, (iii) risk assessment, and (iv) multi‐criteria problems. This article's contribution to the line of research is twofold: first, it adapts the a‐LCA approach for construction‐specific purposes in theoretical terms for the four challenges. Second, it applies the method to an innovative prefabricated modular envelope system, the CleanTechBlock (CTB), focusing on challenge (i). Thirty‐six CTB designs are tested and compared to conventional walls. Inclusion of technology foresight is achieved through structured scenario analysis. Moreover, challenge (iv) is tackled through the analysis of different environmental impact categories, transport‐related impacts, and thickness of the wall assemblies of the CTB. The case study results show that optimized material choice and product design is needed to reach the lowest environmental impact. Methodological findings highlight the importance of context‐specific solutions and the need for benchmarking new products.     

Lifting the veil on the correction of double counting incidents in hybrid life cycle assessment

Life cycle assessment (LCA) and environmentally extended input–output analyses (EEIOA) are two techniques commonly used to assess environmental impacts of an activity/product. Their strengths and weaknesses are complementary, and they are thus regularly combined to obtain hybrid LCAs. A number of approaches in hybrid LCA exist, which leads to different results. One of the differences is the method used to ensure that mixed LCA and EEIOA data do not overlap, which is referred to as correction for double counting. This aspect of hybrid LCA is often ignored in reports of hybrid assessments and no comprehensive study has been carried out on it. This article strives to list, compare, and analyze the different existing methods for the correction of double counting. We first harmonize the definitions of the existing correction methods and express them in a common notation, before introducing a streamlined variant. We then compare their respective assumptions and limitations. We discuss the loss of specific information regarding the studied activity/product and the loss of coherent financial representation caused by some of the correction methods. This analysis clarifies which techniques are most applicable to different tasks, from hybridizing individual LCA processes to integrating complete databases. We finally conclude by giving recommendations for future hybrid analyses.     

Sampling strategy optimization to increase statistical power in landscape genomics: A simulation‐based approach

An increasing number of studies are using landscape genomics to investigate local adaptation in wild and domestic populations. Implementation of this approach requires the sampling phase to consider the complexity of environmental settings and the burden of logistical constraints. These important aspects are often underestimated in the literature dedicated to sampling strategies. In this study, we computed simulated genomic data sets to run against actual environmental data in order to trial landscape genomics experiments under distinct sampling strategies. These strategies differed by design approach (to enhance environmental and/or geographical representativeness at study sites), number of sampling locations and sample sizes. We then evaluated how these elements affected statistical performances (power and false discoveries) under two antithetical demographic scenarios. Our results highlight the importance of selecting an appropriate sample size, which should be modified based on the demographic characteristics of the studied population. For species with limited dispersal, sample sizes above 200 units are generally sufficient to detect most adaptive signals, while in random mating populations this threshold should be increased to 400 units. Furthermore, we describe a design approach that maximizes both environmental and geographical representativeness of sampling sites and show how it systematically outperforms random or regular sampling schemes. Finally, we show that although having more sampling locations (between 40 and 50 sites) increase statistical power and reduce false discovery rate, similar results can be achieved with a moderate number of sites (20 sites). Overall, this study provides valuable guidelines for optimizing sampling strategies for landscape genomics experiments.     

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.