Shedding Light on the Galaxy Luminosity Function

From as early as the 1930s, astronomers have tried to quantify the statistical nature of the evolution and large-scale structure of galaxies by studying their luminosity distribution as a function of redshift - known as the galaxy luminosity function (LF). Accurately constructing the LF remains a popular and yet tricky pursuit in modern observational cosmology where the presence of observational selection effects due to e.g. detection thresholds in apparent magnitude, colour, surface brightness or some combination thereof can render any given galaxy survey incomplete and thus introduce bias into the LF. Over the last seventy years there have been numerous sophisticated statistical approaches devised to tackle these issues; all have advantages -- but not one is perfect. This review takes a broad historical look at the key statistical tools that have been developed over this period, discussing their relative merits and highlighting any significant extensions and modifications. In addition, the more generalised methods that have emerged within the last few years are examined. These methods propose a more rigorous statistical framework within which to determine the LF compared to some of the more traditional methods. I also look at how photometric redshift estimations are being incorporated into the LF methodology as well as considering the construction of bivariate LFs. Finally, I review the ongoing development of completeness estimators which test some of the fundamental assumptions going into LF estimators and can be powerful probes of any residual systematic effects inherent magnitude-redshift data.Comment: 95 pages, 23 figures, 3 tables. Now published in The Astronomy & Astrophysics Review. This version: bring in line with A&AR format requirements, also minor typo corrections made, additional citations and higher rez images adde

Information systems for innovation: A comparative analysis of maturity models' characteristics

Nowadays, virtually all industries are impacted by the digitalization of business enabled by information and communication technologies. Consequently, it is a major challenge to any business to increase its ability to innovate through information systems. However the effort and the investments of companies are extremely varied, they do not have the same level of maturity with respect to their innovation strategy. While some highly mature use effective approaches, others still act as novices or use inadequate practices. The question raised in this paper is how to evaluate the level of maturity of an organization with respect to information systems based innovation. Also, the question concerns the identification of the salient features of ICT centred innovation maturity models. Taking these issues into account, the paper makes the following contributions: (i) a review of sixteen innovation maturity models collected from the research and the practitioners community, gathering facts about the models and about their effectiveness; (ii) a comparative analysis of these models

Airway Secretory microRNAome Changes during Rhinovirus Infection in Early Childhood

<div><p>Background</p><p>Innate immune responses are fine-tuned by small noncoding RNA molecules termed microRNAs (miRs) that modify gene expression in response to the environment. During acute infections, miRs can be secreted in extracellular vesicles (EV) to facilitate cell-to-cell genetic communication. The purpose of this study was to characterize the baseline population of miRs secreted in EVs in the airways of young children (airway secretory microRNAome) and examine the changes during rhinovirus (RV) infection, the most common cause of asthma exacerbations and the most important early risk factor for the development of asthma beyond childhood.</p><p>Methods</p><p>Nasal airway secretions were obtained from children (≤3 yrs. old) during PCR-confirmed RV infections (n = 10) and age-matched controls (n = 10). Nasal EVs were isolated with polymer-based precipitation and global miR profiles generated using NanoString microarrays. We validated our <i>in vivo</i> airway secretory miR data in an <i>in vitro</i> airway epithelium model using apical secretions from primary human bronchial epithelial cells (HBEC) differentiated at air-liquid interface (ALI). Bioinformatics tools were used to determine the unified (nasal and bronchial) signature airway secretory miRNAome and changes during RV infection in children.</p><p>Results</p><p>Multiscale analysis identified four signature miRs comprising the baseline airway secretory miRNAome: <i>hsa-miR-630</i>, <i>hsa-miR-302d-3p</i>, <i>hsa- miR-320e</i>, <i>hsa-miR-612</i>. We identified <i>hsa-miR-155</i> as the main change in the baseline miRNAome during RV infection in young children. We investigated the potential biological relevance of the airway secretion of <i>hsa-mir-155</i> using <i>in silico</i> models derived from gene datasets of experimental <i>in vivo</i> human RV infection. These analyses confirmed that <i>hsa-miR-155</i> targetome is an overrepresented pathway in the upper airways of individuals infected with RV.</p><p>Conclusions</p><p>Comparative analysis of the airway secretory microRNAome in children indicates that RV infection is associated with airway secretion of EVs containing miR-155, which is predicted <i>in silico</i> to regulate antiviral immunity. Further characterization of the airway secretory microRNAome during health and disease may lead to completely new strategies to treat and monitor respiratory conditions in all ages.</p></div

Dysregulation of soluble epoxide hydrolase and lipidomic profiles in anorexia nervosa

Individuals with anorexia nervosa (AN) restrict eating and become emaciated. They tend to have an aversion to foods rich in fat. Because epoxide hydrolase 2 (EPHX2) was identified as a novel AN susceptibility gene, and because its protein product, soluble epoxide hydrolase (sEH), converts bioactive epoxides of polyunsaturated fatty acid (PUFA) to the corresponding diols, lipidomic and metabolomic targets of EPHX2 were assessed to evaluate the biological functions of EPHX2 and their role in AN. Epoxide substrates of sEH and associated oxylipins were measured in ill AN, recovered AN and gender- and race-matched controls. PUFA and oxylipin markers were tested as potential biomarkers for AN. Oxylipin ratios were calculated as proxy markers of in vivo sEH activity. Several free- and total PUFAs were associated with AN diagnosis and with AN recovery. AN displayed elevated n-3 PUFAs and may differ from controls in PUFA elongation and desaturation processes. Cytochrome P450 pathway oxylipins from arachidonic acid, linoleic acid, alpha-linolenic acid and docosahexaenoic acid PUFAs are associated with AN diagnosis. The diol: epoxide ratios suggest the sEH activity is higher in AN compared with controls. Multivariate analysis illustrates normalization of lipidomic profiles in recovered ANs. EPHX2 influences AN risk through in vivo interaction with dietary PUFAs. PUFA composition and concentrations as well as sEH activity may contribute to the pathogenesis and prognosis of AN. Our data support the involvement of EPHX2-associated lipidomic and oxylipin dysregulations in AN, and reveal their potential as biomarkers to assess responsiveness to future intervention or treatment