Plasticity in single neuron and circuit computations

Plasticity in neural circuits can result from alterations in synaptic strength or connectivity, as well as from changes in the excitability of the neurons themselves. To better understand the role of plasticity in the brain, we need to establish how brain circuits work and the kinds of computations that different circuit structures achieve. By linking theoretical and experimental studies, we are beginning to reveal the consequences of plasticity mechanisms for network dynamics, in both simple invertebrate circuits and the complex circuits of mammalian cerebral cortex.     

Dodecahedral space topology as an explanation for weak wide-angle temperature correlations in the cosmic microwave background

The current 'standard model' of cosmology posits an infinite flat universe forever expanding under the pressure of dark energy. First-year data from the Wilkinson Microwave Anisotropy Probe (WMAP) confirm this model to spectacular precision on all but the largest scales. Temperature correlations across the microwave sky match expectations on angular scales narrower than 60 degrees but, contrary to predictions, vanish on scales wider than 60 degrees. Several explanations have been proposed. One natural approach questions the underlying geometry of space--namely, its curvature and topology. In an infinite flat space, waves from the Big Bang would fill the universe on all length scales. The observed lack of temperature correlations on scales beyond 60 degrees means that the broadest waves are missing, perhaps because space itself is not big enough to support them. Here we present a simple geometrical model of a finite space--the Poincaré dodecahedral space--which accounts for WMAP's observations with no fine-tuning required. The predicted density is Omega(0) approximately 1.013 > 1, and the model also predicts temperature correlations in matching circles on the sky.     

Notch1 functions as a tumor suppressor in mouse skin

Notch proteins are important in binary cell-fate decisions and inhibiting differentiation in many developmental systems, and aberrant Notch signaling is associated with tumorigenesis. The role of Notch signaling in mammalian skin is less well characterized and is mainly based on in vitro studies, which suggest that Notch signaling induces differentiation in mammalian skin. Conventional gene targeting is not applicable to establishing the role of Notch receptors or ligands in the skin because Notch1-/- embryos die during gestation. Therefore, we used a tissue-specific inducible gene-targeting approach to study the physiological role of the Notch1 receptor in the mouse epidermis and the corneal epithelium of adult mice. Unexpectedly, ablation of Notch1 results in epidermal and corneal hyperplasia followed by the development of skin tumors and facilitated chemical-induced skin carcinogenesis. Notch1 deficiency in skin and in primary keratinocytes results in increased and sustained expression of Gli2, causing the development of basal-cell carcinoma-like tumors. Furthermore, Notch1 inactivation in the epidermis results in derepressed beta-catenin signaling in cells that should normally undergo differentiation. Enhanced beta-catenin signaling can be reversed by re-introduction of a dominant active form of the Notch1 receptor. This leads to a reduction in the signaling-competent pool of beta-catenin, indicating that Notch1 can inhibit beta-catenin-mediated signaling. Our results indicate that Notch1 functions as a tumor-suppressor gene in mammalian skin.     

Clay minerals in surface sediments of the Pearl River drainage basin and their contribution to the South China Sea

Clay minerals have played a significant role in the study of the East Asian monsoon evolution in the South China Sea by being able to track oceanic current variations and to reveal contemporaneous paleoclimaUc changes prevailing in continental source areas. As one of the most important rivers inputting terrigenous matters to the northern South China Sea, the Pearl River was not previously paid attention to from the viewpoint of clay mineralogy. This paper presents a detailed study on clay minerals in surface sediments collected from the Pearl River drainage basin （including all three main channels, various branches, and the Lingdingyang in the estuary） by using the X-ray diffraction （XRD） method. The results indicate that the clay mineral assemblage consists dominantly of kaolinite （35%-65%）, lesser abundance of chlorite （20%-35%） and illite （12%-42%）, and very scare smectite occurrences （generally 〈5%）. Their respective distribution does not present any obvious difference throughout the Pearl River drainage basin. However, downstream the Pearl River to the northern South China Sea, the clay mineral assemblage varies significantly： kaolinite decreases gradually, smecUte and illite increase gradually. Additionally, illite chemistry index steps down and illite crystallinity steps up. These variations indicate the contribution of major kaolinite, lesser illite and chlorite, and very scarce smecUte to the northern South China Sea from the Pearl River drainage basin. The maximum contribution of clay minerals from the Pearl River is 72% to the northern margin and only 15% to the northern slope of the South China Sea. In both glacials and interglacials, kaolinite indicates that the ability of mechanical erosion occurred in the Pearl River drainage basin.     

Systematic documentation and analysis of human genetic variation in hemoglobinopathies using the microattribution approach

We developed a series of interrelated locus-specific databases to store all published and unpublished genetic variation related to hemoglobinopathies and thalassemia and implemented microattribution to encourage submission of unpublished observations of genetic variation to these public repositories. A total of 1,941 unique genetic variants in 37 genes, encoding globins and other erythroid proteins, are currently documented in these databases, with reciprocal attribution of microcitations to data contributors. Our project provides the first example of implementing microattribution to incentivise submission of all known genetic variation in a defined system. It has demonstrably increased the reporting of human variants, leading to a comprehensive online resource for systematically describing human genetic variation in the globin genes and other genes contributing to hemoglobinopathies and thalassemias. The principles established here will serve as a model for other systems and for the analysis of other common and/or complex human genetic diseases.     

Multilevel Innovation in Remote Networked Schools

Small remote rural schools in Quebec face an ongoing challenge to provide similar quality educational services than bigger schools. Since 2002, the Remote Network Schools (RNS) initiative afforded schools the opportunity to reinvent their practice by using online tools to experience collaborative learning activities with other remote schools. Teachers and students experienced quality learning and demonstrated agency by implementing the RNS in their context. Measures include: diversity of learning activities, quality of online classroom interactions, changes in teacher beliefs, and shifts in teacher and student roles. Our results show that it is a viable operating method for such schools and that other schools could contemplate implementing such innovative practices.     

Forecasting regional house price inflation: a comparison between dynamic factor models and vector autoregressive models

This paper uses the dynamic factor model framework, which accommodates a large cross‐section of macroeconomic time series, for forecasting regional house price inflation. In this study, we forecast house price inflation for five metropolitan areas of South Africa using principal components obtained from 282 quarterly macroeconomic time series in the period 1980:1 to 2006:4. The results, based on the root mean square errors of one to four quarters ahead out‐of‐sample forecasts over the period 2001:1 to 2006:4 indicate that, in the majority of the cases, the Dynamic Factor Model statistically outperforms the vector autoregressive models, using both the classical and the Bayesian treatments. We also consider spatial and non‐spatial specifications. Our results indicate that macroeconomic fundamentals in forecasting house price inflation are important. Copyright © 2010 John Wiley & Sons, Ltd.