Virtually impossible: limiting Australian children and adolescents daily screen based media use

Background: Paediatric recommendations to limit children’s and adolescents’ screen based media use (SBMU) to less than two hours per day appear to have gone unheeded. Given the associated adverse physical and mental health outcomes of SBMU it is understandable that concern is growing worldwide. However, because the majority of studies measuring SBMU have focused on TV viewing, computer use, video game playing, or a combination of these the true extent of total SBMU (including non-sedentary hand held devices) and time spent on specific screen activities remains relatively unknown. This study assesses the amount of time Australian children and adolescents spend on all types of screens and specific screen activities. Methods: We administered an online instrument specifically developed to gather data on all types of SBMU and SBMU activities to 2,620 (1373 males and 1247 females) 8 to 16 year olds from 25 Australian government and non-government primary and secondary schools. Results: We found that 45% of 8 year olds to 80% of 16 year olds exceeded the recommended < 2 hours per day for screen use. A series of hierarchical linear models demonstrated different relationships between the degree to which total SBMU and SBMU on specific activities (TV viewing, Gaming, Social Networking, and Web Use) exceeded the < 2 hours recommendation in relation to sex and age. Conclusions: Current paediatric recommendations pertaining to screen use exposure may no longer be tenable because screen based media are central in the everyday lives of children and adolescents. In any reappraisal of SBMU exposure times, researchers, educators and health professionals need to take cognizance of the extent to which screen use differs across specific screen activity, sex, and age

Spermidine Promotes Human Hair Growth and Is a Novel Modulator of Human Epithelial Stem Cell Functions

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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

A Novel Pulse-Chase SILAC Strategy Measures Changes in Protein Decay and Synthesis Rates Induced by Perturbation of Proteostasis with an Hsp90 Inhibitor.

Standard proteomics methods allow the relative quantitation of levels of thousands of proteins in two or more samples. While such methods are invaluable for defining the variations in protein concentrations which follow the perturbation of a biological system, they do not offer information on the mechanisms underlying such changes. Expanding on previous work [1], we developed a pulse-chase (pc) variant of SILAC (stable isotope labeling by amino acids in cell culture). pcSILAC can quantitate in one experiment and for two conditions the relative levels of proteins newly synthesized in a given time as well as the relative levels of remaining preexisting proteins. We validated the method studying the drug-mediated inhibition of the Hsp90 molecular chaperone, which is known to lead to increased synthesis of stress response proteins as well as the increased decay of Hsp90 "clients". We showed that pcSILAC can give information on changes in global cellular proteostasis induced by treatment with the inhibitor, which are normally not captured by standard relative quantitation techniques. Furthermore, we have developed a mathematical model and computational framework that uses pcSILAC data to determine degradation constants kd and synthesis rates Vs for proteins in both control and drug-treated cells. The results show that Hsp90 inhibition induced a generalized slowdown of protein synthesis and an increase in protein decay. Treatment with the inhibitor also resulted in widespread protein-specific changes in relative synthesis rates, together with variations in protein decay rates. The latter were more restricted to individual proteins or protein families than the variations in synthesis. Our results establish pcSILAC as a viable workflow for the mechanistic dissection of changes in the proteome which follow perturbations. Data are available via ProteomeXchange with identifier PXD000538