Mutations in myosin heavy chain 11 cause a syndrome associating thoracic aortic aneurysm/aortic dissection and patent ductus arteriosus

We have recently described two kindreds presenting thoracic aortic aneurysm and/or aortic dissection (TAAD) and patent ductus arteriosus (PDA) and mapped the disease locus to 16p12.2-p13.13 (ref. 3). We now demonstrate that the disease is caused by mutations in the MYH11 gene affecting the C-terminal coiled-coil region of the smooth muscle myosin heavy chain, a specific contractile protein of smooth muscle cells (SMC). All individuals bearing the heterozygous mutations, even if asymptomatic, showed marked aortic stiffness. Examination of pathological aortas showed large areas of medial degeneration with very low SMC content. Abnormal immunological recognition of SM-MHC and the colocalization of wild-type and mutant rod proteins in SMC, in conjunction with differences in their coimmunoprecipitation capacities, strongly suggest a dominant-negative effect. Human MYH11 gene mutations provide the first example of a direct change in a specific SMC protein leading to an inherited arterial disease.     

Heritable germline epimutation of MSH2 in a family with hereditary nonpolyposis colorectal cancer

Epimutations in the germline, such as methylation of the MLH1 gene, may contribute to hereditary cancer syndrome in human, but their transmission to offspring has never been documented. Here we report a family with inheritance, in three successive generations, of germline allele-specific and mosaic hypermethylation of the MSH2 gene, without evidence of DNA mismatch repair gene mutation. Three siblings carrying the germline methylation developed early-onset colorectal or endometrial cancers, all with microsatellite instability and MSH2 protein loss. Clonal bisulfite sequencing and pyrosequencing showed different methylation levels in different somatic tissues, with the highest level recorded in rectal mucosa and colon cancer tissue, and the lowest in blood leukocytes. This mosaic state of germline methylation with different tissue distribution could act as the first hit and provide a mechanism for genetic disease inheritance that may deviate from the mendelian pattern and be overlooked in conventional leukocyte-based genetic diagnosis strategy.     

Inorganic-Organic Composite Materials for Lithium Batteries

1 Results In order to develop high capacity anode materials for enhancing the performance of lithium-ion batteries,silicon (Si) and a variety of metals that alloy with lithium,such as Sn,Sb,and Al,were studied and found to be promising candidates as anode materials[1-4].Among them,Si appears to be the most attractive candidate due to its large theoretical lithium insertion capacity of 4 200 mAh g-1[1].Unfortunately,there is one severe problem with the application of Si anode,i.e., the large volume chang...     

Genetic studies of diseases

The biological system is a complex physicochemical system consisting of numerous dynamic networks of biochemical reactions and signaling interactions between cellular components. This complexity makes it virtually unanalyzable by traditional methods. Hence, biological networks have been developed as a platform for integrating information from high- to low-throughput experiments for analysis of biological systems. The network analysis approach is vital for successful quantitative modeling of biological systems. The numerous online pathway databases vary widely in coverage and representation of biological processes. An integrated network-based information system for querying, visualization and analysis promised successful integration of data on a large scale. Such integrated systems will greatly facilitate the understanding of biological interactions and experimental verification.     

Forecast comparisons of four models of U.S. interest rates

In this paper we compare the out of sample forecasts from four alternative interest rate models based on expanding information sets. The random walk model is the most restrictive. The univariate time series model allows for a richer dynamic pattern and more conditioning information on own rates. The multivariate time series model permits a flexible dynamic pattern with own- and cross-series information. Finally, the forecasts from the MPS econometric model depend on the full model structure and information set. In theory, more information is preferred to less. In practice, complicated misspecified models can perform much worse than simple (also probably misspecified) models. For forecasts evaluated over the volatile 1970s the multivariate time series model forecasts are considerably better than those from simpler models which use less conditioning information, as well as forecasts from the MPS model which uses substantially more conditioning information but also imposes ‘structural’ economic restrictions.     

An extant cichlid fish radiation emerged in an extinct Pleistocene lake

The haplochromine cichlid fish of the East African Great Lakes represent some of the fastest and most species-rich adaptive radiations known, but rivers in most of Africa accommodate only a few morphologically similar species of haplochromine cichlid fish. This has been explained by the wealth of ecological opportunity in large lakes compared with rivers. It is therefore surprising that the rivers of southern Africa harbour many, ecologically diverse haplochromines. Here we present genetic, morphological and biogeographical evidence suggesting that these riverine cichlids are products of a recent adaptive radiation in a large lake that dried up in the Holocene. Haplochromine species richness peaks steeply in an area for which geological data reveal the historical existence of Lake palaeo-Makgadikgadi. The centre of this extinct lake is now a saltpan north of the Kalahari Desert, but it once hosted a rapidly evolving fish species radiation, comparable in morphological diversity to that in the extant African Great Lakes. Importantly, this lake seeded all major river systems of southern Africa with ecologically diverse cichlids. This discovery reveals how local evolutionary processes operating during a short window of ecological opportunity can have a major and lasting effect on biodiversity on a continental scale.     

Biochemistry: a cadmium enzyme from a marine diatom

The ocean biota contains a vast reservoir of genomic diversity. Here we present the sequence and preliminary characterization of a protein that is a cadmium-containing carbonic anhydrase from the marine diatom Thalassiosira weissflogii. The existence of a cadmium enzyme in marine phytoplankton may indicate that there is a unique selection pressure for metalloenzymes in the marine environment, and our discovery provides a long-awaited explanation for the nutrient-like behaviour of cadmium in the oceans.     

Imaging the Indian subcontinent beneath the Himalaya

The rocks of the Indian subcontinent are last seen south of the Ganges before they plunge beneath the Himalaya and the Tibetan plateau. They are next glimpsed in seismic reflection profiles deep beneath southern Tibet, yet the surface seen there has been modified by processes within the Himalaya that have consumed parts of the upper Indian crust and converted them into Himalayan rocks. The geometry of the partly dismantled Indian plate as it passes through the Himalayan process zone has hitherto eluded imaging. Here we report seismic images both of the decollement at the base of the Himalaya and of the Moho (the boundary between crust and mantle) at the base of the Indian crust. A significant finding is that strong seismic anisotropy develops above the decollement in response to shear processes that are taken up as slip in great earthquakes at shallower depths. North of the Himalaya, the lower Indian crust is characterized by a high-velocity region consistent with the formation of eclogite, a high-density material whose presence affects the dynamics of the Tibetan plateau.     

Functional cartography of complex metabolic networks

High-throughput techniques are leading to an explosive growth in the size of biological databases and creating the opportunity to revolutionize our understanding of life and disease. Interpretation of these data remains, however, a major scientific challenge. Here, we propose a methodology that enables us to extract and display information contained in complex networks. Specifically, we demonstrate that we can find functional modules in complex networks, and classify nodes into universal roles according to their pattern of intra- and inter-module connections. The method thus yields a 'cartographic representation' of complex networks. Metabolic networks are among the most challenging biological networks and, arguably, the ones with most potential for immediate applicability. We use our method to analyse the metabolic networks of twelve organisms from three different superkingdoms. We find that, typically, 80% of the nodes are only connected to other nodes within their respective modules, and that nodes with different roles are affected by different evolutionary constraints and pressures. Remarkably, we find that metabolites that participate in only a few reactions but that connect different modules are more conserved than hubs whose links are mostly within a single module.