A hidden Markov model for decoding and the analysis of replay in spike trains

We present a hidden Markov model that describes variation in an animal’s position associated with varying levels of activity in action potential spike trains of individual place cell neurons. The model incorporates a coarse-graining of position, which we find to be a more parsimonious description of the system than other models. We use a sequential Monte Carlo algorithm for Bayesian inference of model parameters, including the state space dimension, and we explain how to estimate position from spike train observations (decoding). We obtain greater accuracy over other methods in the conditions of high temporal resolution and small neuronal sample size. We also present a novel, model-based approach to the study of replay: the expression of spike train activity related to behaviour during times of motionlessness or sleep, thought to be integral to the consolidation of long-term memories. We demonstrate how we can detect the time, information content and compression rate of replay events in simulated and real hippocampal data recorded from rats in two different environments, and verify the correlation between the times of detected replay events and of sharp wave/ripples in the local field potential

The diffusion of financial supervisory governance ideas

Who is watching the financial services industry? Since 1980, there have been multiple waves of thought about whether the ministry of finance, the central bank, a specialized regulator or some combination of these should have supervisory authority. These waves have been associated with the convergence of actual practices. How much and through what channels did internationally promoted ideas about supervisory 'best practice' influence institutional design choices? I use a new dataset of 83 countries and jurisdictions between the 1980s and 2007 to examine the diffusion of supervisory ideas. With this data, I employ Cox Proportional Hazard and Competing Risks Event History Analyses to evaluate the possible causal roles best practice policy ideas might have played. I find that banking crises and certain peer groups can encourage policy convergence on heavily promoted ideas

Identification of stable QTLs for vegetative and reproductive traits in the microvine (Vitis vinifera L.) using the 18 K Infinium chip

UMR AGAP - équipe DAAV - Diversité, adaptation et amélioration de la vigne[b]Background[/b] [br/]The increasing temperature associated with climate change impacts grapevine phenology and development with critical effects on grape yield and composition. Plant breeding has the potential to deliver new cultivars with stable yield and quality under warmer climate conditions, but this requires the identification of stable genetic determinants. This study tested the potentialities of the microvine to boost genetics in grapevine. A mapping population of 129 microvines derived from Picovine x Ugni Blanc flb, was genotyped with the Illumina® 18 K SNP (Single Nucleotide Polymorphism) chip. Forty-three vegetative and reproductive traits were phenotyped outdoors over four cropping cycles, and a subset of 22 traits over two cropping cycles in growth rooms with two contrasted temperatures, in order to map stable QTLs (Quantitative Trait Loci). [br/][b]Results[/b] [br/]Ten stable QTLs for berry development and quality or leaf area were identified on the parental maps. A new major QTL explaining up to 44 % of total variance of berry weight was identified on chromosome 7 in Ugni Blanc flb, and co-localized with QTLs for seed number (up to 76 % total variance), major berry acids at green lag phase (up to 35 %), and other yield components (up to 25 %). In addition, a minor QTL for leaf area was found on chromosome 4 of the same parent. In contrast, only minor QTLs for berry acidity and leaf area could be found as moderately stable in Picovine. None of the transporters recently identified as mutated in low acidity apples or Cucurbits were included in the several hundreds of candidate genes underlying the above berry QTLs, which could be reduced to a few dozen candidate genes when a priori pertinent biological functions and organ specific expression were considered. [br/][b]Conclusions[/b] [br/]This study combining the use of microvine and a high throughput genotyping technology was innovative for grapevine genetics. It allowed the identification of 10 stable QTLs, including the first berry acidity QTLs reported so far in a Vitis vinifera intra-specific cross. Robustness of a set of QTLs was assessed with respect to temperature variatio

Small-Molecule Protein-Protein Interaction Inhibitor of Oncogenic Rho Signaling

Uncontrolled activation of Rho signaling by RhoGEFs, in particular AKAP13 (Lbc) and its close homologs, is implicated in a number of human tumors with poor prognosis and resistance to therapy. Structure predictions and alanine scanning mutagenesis of Lbc identified a circumscribed hot region for RhoA recognition and activation. Virtual screening targeting that region led to the discovery of an inhibitor of Lbc-RhoA interaction inside cells. By interacting with the DH domain, the compound inhibits the catalytic activity of Lbc, halts cellular responses to activation of oncogenic Lbc pathways, and reverses a number of prostate cancer cell phenotypes such as proliferation, migration, and invasiveness. This study provides insights into the structural determinants of Lbc-RhoA recognition. This is a successful example of structure-based discovery of a small protein-protein interaction inhibitor able to halt oncogenic Rho signaling in cancer cells with therapeutic implications

High variablity of Greenland surface temperature over the past 4000 years estimated from trapped air in ice core

第2回極域科学シンポジウム　氷床コアセッション 11月16日（水） 国立極地研究所 2階大会議

DFSeer: A visual analytics approach to facilitate model selection for demand forecasting

Selecting an appropriate model to forecast product demand is critical to the manufacturing industry. However, due to the data complexity, market uncertainty and users' demanding requirements for the model, it is challenging for demand analysts to select a proper model. Although existing model selection methods can reduce the manual burden to some extent, they often fail to present model performance details on individual products and reveal the potential risk of the selected model. This paper presents DFSeer, an interactive visualization system to conduct reliable model selection for demand forecasting based on the products with similar historical demand. It supports model comparison and selection with different levels of details. Besides, it shows the difference in model performance on similar products to reveal the risk of model selection and increase users' confidence in choosing a forecasting model. Two case studies and interviews with domain experts demonstrate the effectiveness and usability of DFSeer.Comment: 10 pages, 5 figures, ACM CHI 202

Exocrine Proteins Including Trypsin(ogen) as a Key Biomarker in Type 1 Diabetes

   Objective Proteomic profiling can identify useful biomarkers. Monozygotic(MZ) twins, discordant for a condition represent an ideal test population. We aimed to investigate and validate proteomic profiling in twins with type 1 diabetes and in other well characterised cohorts. Research Design and Methods A broad, multiplex analysis of 4068 proteins in sera from MZ twins concordant (n=43) and discordant for type 1 diabetes (n=27) identified major differences which were subsequently validated by a trypsin(ogen) assay in MZ pairs concordant (n=39) and discordant (n=42) for type 1 diabetes, individuals at-risk (n=195) and with type 1 diabetes (n=990), as well as with non-insulin requiring adult-onset diabetes diagnosed as either autoimmune (n=96) or type 2 (n=291). Results Proteomic analysis identified major differences between exocrine enzyme levels in discordant MZ twin pairs despite strong correlation between twins, whether concordant or discordant for type 1 diabetes (p Conclusions Type 1 diabetes is associated with altered exocrine function, even before onset. Twin data suggest roles for genetic and non-genetically determined factors. Exocrine/endocrine interactions are important under-investigated factors in type 1 diabetes.</p