Objective Definition of Rosette Shape Variation Using a Combined Computer Vision and Data Mining Approach

Computer-vision based measurements of phenotypic variation have implications for crop improvement and food security because they are intrinsically objective. It should be possible therefore to use such approaches to select robust genotypes. However, plants are morphologically complex and identification of meaningful traits from automatically acquired image data is not straightforward. Bespoke algorithms can be designed to capture and/or quantitate specific features but this approach is inflexible and is not generally applicable to a wide range of traits. In this paper, we have used industry-standard computer vision techniques to extract a wide range of features from images of genetically diverse Arabidopsis rosettes growing under non-stimulated conditions, and then used statistical analysis to identify those features that provide good discrimination between ecotypes. This analysis indicates that almost all the observed shape variation can be described by 5 principal components. We describe an easily implemented pipeline including image segmentation, feature extraction and statistical analysis. This pipeline provides a cost-effective and inherently scalable method to parameterise and analyse variation in rosette shape. The acquisition of images does not require any specialised equipment and the computer routines for image processing and data analysis have been implemented using open source software. Source code for data analysis is written using the R package. The equations to calculate image descriptors have been also provided

Financial correlations at ultra-high frequency: theoretical models and empirical estimation

A detailed analysis of correlation between stock returns at high frequency is compared with simple models of random walks. We focus in particular on the dependence of correlations on time scales - the so-called Epps effect. This provides a characterization of stochastic models of stock price returns which is appropriate at very high frequency.Comment: 22 pages, 8 figures, 1 table, version to appear in EPJ

Peripheral mechanisms contributing to the glucocorticoid hypersensitivity in proopiomelanocortin null mice treated with corticosterone.

Proopiomelanocortin (POMC) deficiency causes severe obesity through hyperphagia of hypothalamic origin. However, low glucocorticoid levels caused by adrenal insufficiency mitigate against insulin resistance, hyperphagia and fat accretion in Pomc-/- mice. Upon exogenous glucocorticoid replacement, corticosterone-supplemented (CORT) Pomc-/- mice show exaggerated responses, including excessive fat accumulation, hyperleptinaemia and insulin resistance. To investigate the peripheral mechanisms underlying this glucocorticoid hypersensitivity, we examined the expression levels of key determinants and targets of glucocorticoid action in adipose tissue and liver. Despite lower basal expression of 11beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1), which generates active glucocorticoids within cells, CORT-mediated induction of 11beta-HSD1 mRNA levels was more pronounced in adipose tissues of Pomc-/- mice. Similarly, CORT treatment increased lipoprotein lipase mRNA levels in all fat depots in Pomc-/- mice, consistent with exaggerated fat accumulation. Glucocorticoid receptor (GR) mRNA levels were selectively elevated in liver and retroperitoneal fat of Pomc-/- mice but were corrected by CORT in the latter depot. In liver, CORT increased phosphoenolpyruvate carboxykinase mRNA levels specifically in Pomc-/- mice, consistent with their insulin-resistant phenotype. Furthermore, CORT induced hypertension in Pomc-/- mice, independently of adipose or liver renin-angiotensin system activation. These data suggest that CORT-inducible 11beta-HSD1 expression in fat contributes to the adverse cardiometabolic effects of CORT in POMC deficiency, whereas higher GR levels may be more important in liver

Meta-analysis of genes in commercially available nutrigenomic tests denotes lack of association with dietary intake and nutrient-related pathologies

Nutrigenomics is an emerging discipline that aims to investigate how individual genetic composition correlates with dietary intake, as well as how nutrition influences gene expression. Herein, the fundamental question relates to the value of nutrigenomics testing on the basis of the currently available scientific evidence. A thorough literature search has been conducted in PubMed scientific literature database for nutrigenomics research studies on 38 genes included in nutrigenomics tests provided by various private genetic testing laboratories. Data were subsequently meta-analyzed to identify possible associations between the genes of interest and dietary intake and/or nutrient-related pathologies. Data analysis occurred according to four different models due to data sparsity and inconsistency. Data from 524,592 individuals (361,153 cases and 163,439 controls) in a total of 1,170 entries were obtained. Conflicting findings indicated that there was a great incompatibility regarding the associations (or their absence) identified. No specific-and statistically significant-association was identified for any of the 38 genes of interest. In those cases, where a weak association was demonstrated, evidence was based on a limited number of studies. As solid scientific evidence is currently lacking, commercially available nutrigenomics tests cannot be presently recommended. Notwithstanding, the need for a thorough and continuous nutrigenomics research is evident as it is a highly promising tool towards precision medicine

Proteome Stability as a Key Factor of Genome Integrity

DNA damage is constantly produced by both endogenous and exogenous factors; DNA lesions then trigger the so-called DNA damaged response (DDR). This is a highly synchronized pathway that involves recognition, signaling and repair of the damage. Failure to eliminate DNA lesions is associated with genome instability, a driving force in tumorigenesis. Proteins carry out the vast majority of cellular functions and thus proteome quality control (PQC) is critical for the maintenance of cellular functionality. PQC is assured by the proteostasis network (PN), which under conditions of proteome instability address the triage decision of protein fold, hold, or degrade. Key components of the PN are the protein synthesis modules, the molecular chaperones and the two main degradation machineries, namely the autophagy-lysosome and the ubiquitin-proteasome pathways; also, part of the PN are a number of stress-responsive cellular sensors including (among others) heat shock factor 1 (Hsf1) and the nuclear factor erythroid 2-related factor 2 (Nrf2). Nevertheless, the lifestyle- and/or ageing-associated gradual accumulation of stressors results in increasingly damaged and unstable proteome due to accumulation of misfolded proteins and/or protein aggregates. This outcome may then increase genomic instability due to reduced fidelity in processes like DNA replication or repair leading to various age-related diseases including cancer. Herein, we review the role of proteostatic machineries in nuclear genome integrity and stability, as well as on DDR responses

Genetic variation at MECOM, TERT, JAK2 and HBS1L-MYB predisposes to myeloproliferative neoplasms

Clonal proliferation in myeloproliferative neoplasms (MPN) is driven by somatic mutations in JAK2, CALR or MPL, but the contribution of inherited factors is poorly characterized. Using a three-stage genome-wide association study of 3,437 MPN cases and 10,083 controls, we identify two SNPs with genome-wide significance in JAK2V617F-negative MPN: rs12339666 (JAK2; meta-analysis P=1.27 × 10−10) and rs2201862 (MECOM; meta-analysis P=1.96 × 10−9). Two additional SNPs, rs2736100 (TERT) and rs9376092 (HBS1L/MYB), achieve genome-wide significance when including JAK2V617F-positive cases. rs9376092 has a stronger effect in JAK2V617F-negative cases with CALR and/or MPL mutations (Breslow–Day P=4.5 × 10−7), whereas in JAK2V617F-positive cases rs9376092 associates with essential thrombocythemia (ET) rather than polycythemia vera (allelic χ2 P=7.3 × 10−7). Reduced MYB expression, previously linked to development of an ET-like disease in model systems, associates with rs9376092 in normal myeloid cells. These findings demonstrate that multiple germline variants predispose to MPN and link constitutional differences in MYB expression to disease phenotype

Fatty Acids Derived from Royal Jelly Are Modulators of Estrogen Receptor Functions

Royal jelly (RJ) excreted by honeybees and used as a nutritional and medicinal agent has estrogen-like effects, yet the compounds mediating these effects remain unidentified. The possible effects of three RJ fatty acids (FAs) (10-hydroxy-2-decenoic-10H2DA, 3,10-dihydroxydecanoic-3,10DDA, sebacic acid-SA) on estrogen signaling was investigated in various cellular systems. In MCF-7 cells, FAs, in absence of estradiol (E2), modulated the estrogen receptor (ER) recruitment to the pS2 promoter and pS2 mRNA levels via only ERβ but not ERα, while in presence of E2 FAs modulated both ERβ and ERα. Moreover, in presence of FAs, the E2-induced recruitment of the EAB1 co-activator peptide to ERα is masked and the E2-induced estrogen response element (ERE)-mediated transactivation is inhibited. In HeLa cells, in absence of E2, FAs inhibited the ERE-mediated transactivation by ERβ but not ERα, while in presence of E2, FAs inhibited ERE-activity by both ERβ and ERα. Molecular modeling revealed favorable binding of FAs to ERα at the co-activator-binding site, while binding assays showed that FAs did not bind to the ligand-binding pocket of ERα or ERβ. In KS483 osteoblasts, FAs, like E2, induced mineralization via an ER-dependent way. Our data propose a possible molecular mechanism for the estrogenic activities of RJ's components which, although structurally entirely different from E2, mediate estrogen signaling, at least in part, by modulating the recruitment of ERα, ERβ and co-activators to target genes