Low-penetrance susceptibility to breast cancer due to CHEK2(*)1100delC in noncarriers of BRCA1 or BRCA2 mutations

Mutations in BRCA1 and BRCA2 confer a high risk of breast and ovarian cancer, but account for only a small fraction of breast cancer susceptibility. To find additional genes conferring susceptibility to breast cancer, we analyzed CHEK2 (also known as CHK2), which encodes a cell-cycle checkpoint kinase that is implicated in DNA repair processes involving BRCA1 and p53 (refs 3,4,5). We show that CHEK2(*)1100delC, a truncating variant that abrogates the kinase activity, has a frequency of 1.1% in healthy individuals. However, this variant is present in 5.1% of individuals with breast cancer from 718 families that do not carry mutations in BRCA1 or BRCA2 (P = 0.00000003), including 13.5% of individuals from families with male breast cancer (P = 0.00015). We estimate that the CHEK2(*)1100delC variant results in an approximately twofold increase of breast cancer risk in women and a tenfold increase of risk in men. By contrast, the variant confers no increased cancer risk in carriers of BRCA1 or BRCA2 mutations. This suggests that the biological mechanisms underlying the elevated risk of breast cancer in CHEK2 mutation carriers are already subverted in carriers of BRCA1 or BRCA2 mutations, which is consistent with participation of the encoded proteins in the same pathway.     

Environmentally mediated synergy between perception and behaviour in mobile robots

The notion that behaviour influences perception seems self-evident, but the mechanism of their interaction is not known. Perception and behaviour are usually considered to be separate processes. In this view, perceptual learning constructs compact representations of sensory events, reflecting their statistical properties, independently of behavioural relevance. Behavioural learning, however, forms associations between perception and action, organized by reinforcement, without regard for the construction of perception. It is generally assumed that the interaction between these two processes is internal to the agent, and can be explained solely in terms of the neuronal substrate. Here we show, instead, that perception and behaviour can interact synergistically via the environment. Using simulated and real mobile robots, we demonstrate that perceptual learning directly supports behavioural learning and so promotes a progressive structuring of behaviour. This structuring leads to a systematic bias in input sampling, which directly affects the organization of the perceptual system. This external, environmentally mediated feedback matches the perceptual system to the emerging behavioural structure, so that the behaviour is stabilized.     

Somatosensory basis of speech production

The hypothesis that speech goals are defined acoustically and maintained by auditory feedback is a central idea in speech production research. An alternative proposal is that speech production is organized in terms of control signals that subserve movements and associated vocal-tract configurations. Indeed, the capacity for intelligible speech by deaf speakers suggests that somatosensory inputs related to movement play a role in speech production-but studies that might have documented a somatosensory component have been equivocal. For example, mechanical perturbations that have altered somatosensory feedback have simultaneously altered acoustics. Hence, any adaptation observed under these conditions may have been a consequence of acoustic change. Here we show that somatosensory information on its own is fundamental to the achievement of speech movements. This demonstration involves a dissociation of somatosensory and auditory feedback during speech production. Over time, subjects correct for the effects of a complex mechanical load that alters jaw movements (and hence somatosensory feedback), but which has no measurable or perceptible effect on acoustic output. The findings indicate that the positions of speech articulators and associated somatosensory inputs constitute a goal of speech movements that is wholly separate from the sounds produced.     

Initializing K-means Batch Clustering: A Critical Evaluation of Several Techniques

K-means clustering is arguably the most popular technique for partitioning data. Unfortunately, K-means suffers from the well-known problem of locally optimal solutions. Furthermore, the final partition is dependent upon the initial configuration, making the choice of starting partitions all the more important. This paper evaluates 12 procedures proposed in the literature and provides recommendations for best practices.     

The Ter mutation in the dead end gene causes germ cell loss and testicular germ cell tumours

In mice, the Ter mutation causes primordial germ cell (PGC) loss in all genetic backgrounds. Ter is also a potent modifier of spontaneous testicular germ cell tumour (TGCT) susceptibility in the 129 family of inbred strains, and markedly increases TGCT incidence in 129-Ter/Ter males. In 129-Ter/Ter mice, some of the remaining PGCs transform into undifferentiated pluripotent embryonal carcinoma cells, and after birth differentiate into various cells and tissues that compose TGCTs. Here, we report the positional cloning of Ter, revealing a point mutation that introduces a termination codon in the mouse orthologue (Dnd1) of the zebrafish dead end (dnd) gene. PGC deficiency is corrected both with bacterial artificial chromosomes that contain Dnd1 and with a Dnd1-encoding transgene. Dnd1 is expressed in fetal gonads during the critical period when TGCTs originate. DND1 has an RNA recognition motif and is most similar to the apobec complementation factor, a component of the cytidine to uridine RNA-editing complex. These results suggest that Ter may adversely affect essential aspects of RNA biology during PGC development. DND1 is the first protein known to have an RNA recognition motif directly implicated as a heritable cause of spontaneous tumorigenesis. TGCT development in the 129-Ter mouse strain models paediatric TGCT in humans. This work will have important implications for our understanding of the genetic control of TGCT pathogenesis and PGC biology.     

A Binary Integer Program to Maximize the Agreement Between Partitions

This research note focuses on a problem where the cluster sizes for two partitions of the same object set are assumed known; however, the actual assignments of objects to clusters are unknown for one or both partitions. The objective is to find a contingency table that produces maximum possible agreement between the two partitions, subject to constraints that the row and column marginal frequencies for the table correspond exactly to the cluster sizes for the partitions. This problem was described by H. Messatfa (Journal of Classification, 1992, pp. 5–15), who provided a heuristic procedure based on the linear transportation problem. We present an exact solution procedure using binary integer programming. We demonstrate that our proposed method efficiently obtains optimal solutions for problems of practical size. We would like to thank the Editor, Willem Heiser, and an anonymous reviewer for helpful comments that resulted in improvements of this article.     

Fitting an extended INDSCAL model to three-way proximity data

The INDSCAL individual differences scaling model is extended by assuming dimensions specific to each stimulus or other object, as well as dimensions common to all stimuli or objects. An alternating maximum likelihood procedure is used to seek maximum likelihood estimates of all parameters of this EXSCAL (Extended INDSCAL) model, including parameters of monotone splines assumed in a quasi-nonmetric approach. The rationale for and numerical details of this approach are described and discussed, and the resulting EXSCAL method is illustrated on some data on perception of musical timbres.     

Polygenic susceptibility to breast cancer and implications for prevention

The knowledge of human genetic variation that will come from the human genome sequence makes feasible a polygenic approach to disease prevention, in which it will be possible to identify individuals as susceptible by their genotype profile and to prevent disease by targeting interventions to those at risk. There is doubt, however, regarding the magnitude of these genetic effects and thus the potential to apply them to either individuals or populations. We have therefore examined the potential for prediction of risk based on common genetic variation using data from a population-based series of individuals with breast cancer. The data are compatible with a log-normal distribution of genetic risk in the population that is sufficiently wide to provide useful discrimination of high- and low-risk groups. Assuming all of the susceptibility genes could be identified, the half of the population at highest risk would account for 88% of all affected individuals. By contrast, if currently identified risk factors for breast cancer were used to stratify the population, the half of the population at highest risk would account for only 62% of all cases. These results suggest that the construction and use of genetic-risk profiles may provide significant improvements in the efficacy of population-based programs of intervention for cancers and other diseases.     

Condition models for wintering Northern Pintails in the Southern High Plains

Three condition models for wintering Northern Pintails ( Anas acuta ) were tested for their ability to predict fat mass, logarithm of fat mass, or a condition index (CI) incorporating fat mass. Equations generated to predict fat mass and the logarithm of fat mass accounted for more than 69% of the variation in these dependent variables. Log transformations of body mass, wing length, and total length explained at least 60% of the variation in CI. All models performed better on an independent data set. Mean prediction error was minimal (≤8% of measured variables) and negative for all models. Regression models apply to live and dead pintails and thus represent tools that have utility in a wide variety of studies on pintail condition.