Disruption of fragmented parent bodies as the origin of asteroid families

Asteroid families are groups of small bodies that share certain orbit and spectral properties. More than 20 families have now been identified, each believed to have resulted from the collisional break-up of a large parent body in a regime where gravity controls the outcome of the collision more than the material strength of the rock. The size and velocity distributions of the family members provide important constraints for testing our understanding of the break-up process, but erosion and dynamical diffusion of the orbits over time can erase the original signature of the collision. The recently identified young Karin family provides a unique opportunity to study a collisional outcome almost unaffected by orbit evolution. Here we report numerical simulations modelling classes of collisions that reproduce the main characteristics of the Karin family. The sensitivity of the outcome of the collision to the internal structure of the parent body allows us to show that the family must have originated from the break-up of a pre-fragmented parent body, and that all large family members formed by the gravitational reaccumulation of smaller bodies. We argue that most of the identified asteroid families are likely to have had a similar history.     

Microfluidic systems: high radial acceleration in microvortices

Microfluidic systems can conveniently be used for rapid analysis of biological samples. Here we describe a single re-circulating flow, or microvortex, that can generate a maximum fluid rotational velocity of up to 12 m s(-1) and a corresponding radial acceleration in excess of 10(6)g. Such microvortices may be exploited in centrifugal microdevices to investigate the effects of high radial acceleration on biological and chemical processes.     

An epi-allelic series of p53 hypomorphs created by stable RNAi produces distinct tumor phenotypes in vivo

The application of RNA interference (RNAi) to mammalian systems has the potential to revolutionize genetics and produce novel therapies. Here we investigate whether RNAi applied to a well-characterized gene can stably suppress gene expression in hematopoietic stem cells and produce detectable phenotypes in mice. Deletion of the Trp53 tumor suppressor gene greatly accelerates Myc-induced lymphomagenesis, resulting in highly disseminated disease. To determine whether RNAi suppression of Trp53 could produce a similar phenotype, we introduced several Trp53 short hairpin RNAs (shRNAs) into hematopoietic stem cells derived from E(mu)-Myc transgenic mice, and monitored tumor onset and overall pathology in lethally irradiated recipients. Different Trp53 shRNAs produced distinct phenotypes in vivo, ranging from benign lymphoid hyperplasias to highly disseminated lymphomas that paralleled Trp53-/- lymphomagenesis in the E(mu)-Myc mouse. In all cases, the severity and type of disease correlated with the extent to which specific shRNAs inhibited p53 activity. Therefore, RNAi can stably suppress gene expression in stem cells and reconstituted organs derived from those cells. In addition, intrinsic differences between individual shRNA expression vectors targeting the same gene can be used to create an 'epi-allelic series' for dissecting gene function in vivo.     

A multiple intelligent agent system for credit risk prediction via an optimization of localized generalization error with diversity

Company bankruptcies cost billions of dollars in losses to banks each year. Thus credit risk prediction is a critical part of a bank＇s loan approval decision process. Traditional financial models for credit risk prediction are no longer adequate for describing today＇s complex relationship between the financial health and potential bankruptcy of a company. In this work, a multiple classifier system （embedded in a multiple intelligent agent system） is proposed to predict the financial health of a company. In our model, each individual agent （classifier） makes a prediction on the likelihood of credit risk based on only partial information of the company. Each of the agents is an expert, but has limited knowledge （represented by features） about the company. The decisions of all agents are combined together to form a final credit risk prediction. Experiments show that our model out-performs other existing methods using the benchmarking Compustat American Corporations dataset.     

Common variants on 1p36 and 1q42 are associated with cutaneous basal cell carcinoma but not with melanoma or pigmentation traits

To search for new sequence variants that confer risk of cutaneous basal cell carcinoma (BCC), we conducted a genome-wide SNP association study of 930 Icelanders with BCC and 33,117 controls. After analyzing 304,083 SNPs, we observed signals from loci at 1p36 and 1q42, and replicated these associations in additional sample sets from Iceland and Eastern Europe. Overall, the most significant signals were from rs7538876 on 1p36 (OR = 1.28, P = 4.4 x 10(-12)) and rs801114 on 1q42 (OR = 1.28, P = 5.9 x 10(-12)). The 1p36 locus contains the candidate genes PADI4, PADI6, RCC2 and ARHGEF10L, and the gene nearest to the 1q42 locus is the ras-homolog RHOU. Neither locus was associated with fair pigmentation traits that are known risk factors for BCC, and no risk was observed for melanoma. Approximately 1.6% of individuals of European ancestry are homozygous for both variants, and their estimated risk of BCC is 2.68 times that of noncarriers.     

Male-pattern baldness susceptibility locus at 20p11

We conducted a genome-wide association study for androgenic alopecia in 1,125 men and identified a newly associated locus at chromosome 20p11.22, confirmed in three independent cohorts (n = 1,650; OR = 1.60, P = 1.1 x 10(-14) for rs1160312). The one man in seven who harbors risk alleles at both 20p11.22 and AR (encoding the androgen receptor) has a sevenfold-increased odds of androgenic alopecia (OR = 7.12, P = 3.7 x 10(-15)).     

Genome-wide association study of leaf architecture in the maize nested association mapping population

US maize yield has increased eight-fold in the past 80 years, with half of the gain attributed to selection by breeders. During this time, changes in maize leaf angle and size have altered plant architecture, allowing more efficient light capture as planting density has increased. Through a genome-wide association study (GWAS) of the maize nested association mapping panel, we determined the genetic basis of important leaf architecture traits and identified some of the key genes. Overall, we demonstrate that the genetic architecture of the leaf traits is dominated by small effects, with little epistasis, environmental interaction or pleiotropy. In particular, GWAS results show that variations at the liguleless genes have contributed to more upright leaves. These results demonstrate that the use of GWAS with specially designed mapping populations is effective in uncovering the basis of key agronomic traits.