Greenhouse Effects in Global Warming based on Analogical Reasoning

Using an analogy in science and everyday life is a double-edged sword because they are accompanied by alternative ideas, in addition to scientific concepts. Schools and public education explain global warming by making a common analogy between this phenomenon and greenhouse effects (Chen in Philos Cogn Sci 105–114, 2012). Unfortunately, this analogy sometimes produces various incorrect explanatory mental models. To construct a correct understanding of global warming, it is necessary: first, to investigate the attributes of analogical reasoning; second, to understand these features by restructuring the greenhouse analogy; and third, to explore the problems and benefits of the greenhouse analogy. The characteristics of relations, rather than objects, must be mapped according to the principle of systematicity, but the public tends to preserve the attributes of the base domain, which is mapped relatively easily. In conclusion, certain facets of the prevailing greenhouse analogy cause a distorted public view of climate change. We must use the greenhouse analogy and yet simultaneously emphasize the relations and attributes highlighted and hidden in the analogy during evaluation.     

A bibliographical study of the introduction of Lavoisier's Traité élémentaire de chimie into Great Britain and America

As the most famous woman scientist of the twentieth century, there has been no shortage of books and articles on the life and career of Marie Curie (1867–1934). Her role as a director of a laboratory-based research school in the new scientific field of radioactivity, a field which embraced both chemistry and physics, however, has never been examined. In recent years, there has been a growing interest in the question of research schools, and Morrell, Ravetz, Geison, and Klosterman, amongst others, have written on this subject. Using, in part, the methodology of Morrell, this paper investigates the role of Marie Curie as a school director in the Paris Faculty in the years 1907–14, examining the work and characteristics of her school and assessing her effectiveness as a director.     

Myostatin and the skeletal muscle atrophy and hypertrophy signaling pathways

Myostatin, a member of the transforming growth factor-β superfamily, is a potent negative regulator of skeletal muscle growth and is conserved in many species, from rodents to humans. Myostatin inactivation can induce skeletal muscle hypertrophy, while its overexpression or systemic administration causes muscle atrophy. As it represents a potential target for stimulating muscle growth and/or preventing muscle wasting, myostatin regulation and functions in the control of muscle mass have been extensively studied. A wealth of data strongly suggests that alterations in skeletal muscle mass are associated with dysregulation in myostatin expression. Moreover, myostatin plays a central role in integrating/mediating anabolic and catabolic responses. Myostatin negatively regulates the activity of the Akt pathway, which promotes protein synthesis, and increases the activity of the ubiquitin–proteasome system to induce atrophy. Several new studies have brought new information on how myostatin may affect both ribosomal biogenesis and translation efficiency of specific mRNA subclasses. In addition, although myostatin has been identified as a modulator of the major catabolic pathways, including the ubiquitin–proteasome and the autophagy–lysosome systems, the underlying mechanisms are only partially understood. The goal of this review is to highlight outstanding questions about myostatin-mediated regulation of the anabolic and catabolic signaling pathways in skeletal muscle. Particular emphasis has been placed on (1) the cross-regulation between myostatin, the growth-promoting pathways and the proteolytic systems; (2) how myostatin inhibition leads to muscle hypertrophy; and (3) the regulation of translation by myostatin.     

Extremely low-coverage sequencing and imputation increases power for genome-wide association studies

Genome-wide association studies (GWAS) have proven to be a powerful method to identify common genetic variants contributing to susceptibility to common diseases. Here, we show that extremely low-coverage sequencing (0.1-0.5×) captures almost as much of the common (>5%) and low-frequency (1-5%) variation across the genome as SNP arrays. As an empirical demonstration, we show that genome-wide SNP genotypes can be inferred at a mean r(2) of 0.71 using off-target data (0.24× average coverage) in a whole-exome study of 909 samples. Using both simulated and real exome-sequencing data sets, we show that association statistics obtained using extremely low-coverage sequencing data attain similar P values at known associated variants as data from genotyping arrays, without an excess of false positives. Within the context of reductions in sample preparation and sequencing costs, funds invested in extremely low-coverage sequencing can yield several times the effective sample size of GWAS based on SNP array data and a commensurate increase in statistical power.     

Mutations in NMNAT1 cause Leber congenital amaurosis and identify a new disease pathway for retinal degeneration

Leber congenital amaurosis (LCA) is a blinding retinal disease that presents within the first year after birth. Using exome sequencing, we identified mutations in the nicotinamide adenine dinucleotide (NAD) synthase gene NMNAT1 encoding nicotinamide mononucleotide adenylyltransferase 1 in eight families with LCA, including the family in which LCA was originally linked to the LCA9 locus. Notably, all individuals with NMNAT1 mutations also have macular colobomas, which are severe degenerative entities of the central retina (fovea) devoid of tissue and photoreceptors. Functional assays of the proteins encoded by the mutant alleles identified in our study showed that the mutations reduce the enzymatic activity of NMNAT1 in NAD biosynthesis and affect protein folding. Of note, recent characterization of the slow Wallerian degeneration (Wld(s)) mouse model, in which prolonged axonal survival after injury is observed, identified NMNAT1 as a neuroprotective protein when ectopically expressed. Our findings identify a new disease mechanism underlying LCA and provide the first link between endogenous NMNAT1 dysfunction and a human nervous system disorder.     

Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits

We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.