A Reduction Paradigm for Multivariate Laws

A "reduction paradigm" is a theoretical framework which provides a definition of structures for multivariate laws, and allows to simplify their representation and statistical analysis. The main idea is to decompose a law as the superimposition of a "structural term" and a "noise," so that the latter can be neglected "without loss of information on the structure." When the lower structural term is supported by a lower-dimensional affine subspace, an "exhaustive dimension reduction" is achieved. We describe the reduction paradigm that results from selecting white noises, and convolution as superposition mechanism

On Multivariate Structures and Exhaustive Reductions

Simplified representations of multivariate laws, and in particular those allowing one to decrease the dimension while preserving structural information, are of paramount importance in statistical analysis. This paper concerns the "theoretical premises" of simplification. We introduce a framework that allows us to specify as "partitions" of probability laws on a Euclidian space, we show how they can be generated via "partial orders," or "binary operation" and "noise classes." Moreover, the framework allows us to identify "simplified representations" that are guaranteed to be "exhaustive" with respect to such definitions, and might live in "lower dimensions.

Modeling a Decentralized Asset Market: An Introduction the Financial "Toy Room"

In this paper, the authors describe a micro-founded simulation environment for decentralized trade in a financial asset. Within the philosophy of computer-simulated "artificial markets", this environment allows one to experiment in a modular fashion with (i) individual characterizations in terms of behaviors and learning, (ii) different architectural and institutional traits of the market, and (iii) time-embedding of events at the system and the individual level

Some Preliminary Experiments with the Financial "Toy-Room"

We describe some preliminary experiments realized with Financial "Toy-Room" (a micro-founded simulation environment for decentralized trade in a homogeneous financial asset). The experiments are aimed at testing the system, and exploring its flexibility in depicting specific contexts as sub-cases. For this purpose, we selected an issue that has been widely investigated in the literature: the existence and characterization of markets in which prices are (or are believed to be) "quality signals" passing information from informed to uninformed traders. In our out-of-equilibrium simulation analysis, we take agents to trade based on a "spread rule," and introduce "dis-synchronization" in agents' updating processes. Thus, we investigate how dis-synchronization, updating paces and spreads affect persistence of trade and the time-path of prices in extreme regimes (i.e. when all agents are informed, or all agents are uninformed)

On the compatibility of benevolence and self-interest:philanthropy and entrepreneurial orientation

This article explores the philanthropy of owner–managers of small- and medium-sized enterprises (SMEs) investigating whether and why more entrepreneurially oriented SMEs are also more likely to engage in philanthropic activities. We find support for a positive link between entrepreneurial orientation (EO) and philanthropy in a representative sample of 270 Lithuanian SMEs controlling for alternative explanations. We highlight that philanthropy is relatively common among SME owner–managers and thus complement existing research which views philanthropy as sequentially following wealth generation. In line with our theorizing, further qualitative findings point to drivers of philanthropy beyond those considered in the dominant strategic-instrumental perspective. Building on social-psychological theories of motivation, we argue and confirm that philanthropy can also be an expression of owner–managers’ altruistic values; these values can be compatible and even mutually reinforcing with entrepreneurship. Our study is set in a transition economy, Lithuania, facilitating the analysis of heterogeneity in attitudes toward philanthropy

Maternal age effect and severe germ-line bottleneck in the inheritance of human mitochondrial DNA

The manifestation of mitochondrial DNA (mtDNA) diseases depends on the frequency of heteroplasmy (the presence of several alleles in an individual), yet its transmission across generations cannot be readily predicted owing to a lack of data on the size of the mtDNA bottleneck during oogenesis. For deleterious heteroplasmies, a severe bottleneck may abruptly transform a benign (low) frequency in a mother into a disease-causing (high) frequency in her child. Here we present a high-resolution study of heteroplasmy transmission conducted on blood and buccal mtDNA of 39 healthy mother–child pairs of European ancestry (a total of 156 samples, each sequenced at ∼20,000× per site). On average, each individual carried one heteroplasmy, and one in eight individuals carried a disease-associated heteroplasmy, with minor allele frequency ≥1%. We observed frequent drastic heteroplasmy frequency shifts between generations and estimated the effective size of the germ-line mtDNA bottleneck at only ∼30–35 (interquartile range from 9 to 141). Accounting for heteroplasmies, we estimated the mtDNA germ-line mutation rate at 1.3 × 10−8 (interquartile range from 4.2 × 10−9 to 4.1 × 10−8) mutations per site per year, an order of magnitude higher than for nuclear DNA. Notably, we found a positive association between the number of heteroplasmies in a child and maternal age at fertilization, likely attributable to oocyte aging. This study also took advantage of droplet digital PCR (ddPCR) to validate heteroplasmies and confirm a de novo mutation. Our results can be used to predict the transmission of disease-causing mtDNA variants and illuminate evolutionary dynamics of the mitochondrial genome

Does gamma-aminobutyric acid (GABA) influence the development of chronic inflammation in rheumatoid arthritis?

<p>Abstract</p> <p>Background</p> <p>Recent studies have demonstrated a role for spinal p38 MAP kinase (MAPK) in the development of chronic inflammation and peripheral arthritis and a role for GABA in the inhibition of p38 MAPK mediated effects. Integrating these data suggests that GABA may play a role in downregulating mechanisms that lead to the production of proinflammatory agents such as interleukin-1, interleukin-6, and matrix metalloproteinase 3 – agents implicated in the pathogenesis of rheumatoid arthritis (RA). Genetic studies have also associated RA with members of the p38 MAPK pathway.</p> <p>Hypothesis</p> <p>We propose a hypothesis for an inefficient GABA signaling system that results in unchecked proinflammatory cytokine production via the p38 MAPK pathway. This model also supports the need for increasing research in the integration of immunology and neuroscience.</p

Gentle Masking of Low-Complexity Sequences Improves Homology Search

Detection of sequences that are homologous, i.e. descended from a common ancestor, is a fundamental task in computational biology. This task is confounded by low-complexity tracts (such as atatatatatat), which arise frequently and independently, causing strong similarities that are not homologies. There has been much research on identifying low-complexity tracts, but little research on how to treat them during homology search. We propose to find homologies by aligning sequences with “gentle” masking of low-complexity tracts. Gentle masking means that the match score involving a masked letter is , where is the unmasked score. Gentle masking slightly but noticeably improves the sensitivity of homology search (compared to “harsh” masking), without harming specificity. We show examples in three useful homology search problems: detection of NUMTs (nuclear copies of mitochondrial DNA), recruitment of metagenomic DNA reads to reference genomes, and pseudogene detection. Gentle masking is currently the best way to treat low-complexity tracts during homology search

Intergenic and Genic Sequence Lengths Have Opposite Relationships with Respect to Gene Expression

Eukaryotic genomes are mostly composed of noncoding DNA whose role is still poorly understood. Studies in several organisms have shown correlations between the length of the intergenic and genic sequences of a gene and the expression of its corresponding mRNA transcript. Some studies have found a positive relationship between intergenic sequence length and expression diversity between tissues, and concluded that genes under greater regulatory control require more regulatory information in their intergenic sequences. Other reports found a negative relationship between expression level and gene length and the interpretation was that there is selection pressure for highly expressed genes to remain small. However, a correlation between gene sequence length and expression diversity, opposite to that observed for intergenic sequences, has also been reported, and to date there is no testable explanation for this observation. To shed light on these varied and sometimes conflicting results, we performed a thorough study of the relationships between sequence length and gene expression using cell-type (tissue) specific microarray data in Arabidopsis thaliana. We measured median gene expression across tissues (expression level), expression variability between tissues (expression pattern uniformity), and expression variability between replicates (expression noise). We found that intergenic (upstream and downstream) and genic (coding and noncoding) sequences have generally opposite relationships with respect to expression, whether it is tissue variability, median, or expression noise. To explain these results we propose a model, in which the lengths of the intergenic and genic sequences have opposite effects on the ability of the transcribed region of the gene to be epigenetically regulated for differential expression. These findings could shed light on the role and influence of noncoding sequences on gene expression