The Effects of Ketone Supplementation on Recovery in Collegiate Male Soccer Players: Pilot Trial

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Measures of happiness: Which to choose?

Happiness is defined as the subjective enjoyment of one’s life as a whole, also called ‘life-satisfaction.’ Two components of happiness are distinguished; an affective component (how well one feels most of the time) and a cognitive component (the degree to which one perceived to get what one wants from life). In this chapter, I present an overview of valid measures of these concepts, drawing on the ‘Collection of Happiness Measures’ of the ‘World Database of Happiness’. To date (2016), this collection includes more than twothousand measures of happiness, mostly single direct questions. Links in this text lead to detail about these measures and the studies in this chapter, I describe the differences and discuss their strengths and weaknesse

Vascular disrupting agents in clinical development

Growth of human tumours depends on the supply of oxygen and nutrients via the surrounding vasculature. Therefore tumour vasculature is an attractive target for anticancer therapy. Apart from angiogenesis inhibitors that compromise the formation of new blood vessels, a second class of specific anticancer drugs has been developed. These so-called vascular disrupting agents (VDAs) target the established tumour vasculature and cause an acute and pronounced shutdown of blood vessels resulting in an almost complete stop of blood flow, ultimately leading to selective tumour necrosis. As a number of VDAs are now being tested in clinical studies, we will discuss their mechanism of action and the results obtained in preclinical studies. Also data from clinical studies will be reviewed and some considerations with regard to the future development are given

Internet of Things in Agricultural Innovation and Security

The agricultural Internet of Things (Ag-IoT) paradigm has tremendous potential in transparent integration of underground soil sensing, farm machinery, and sensor-guided irrigation systems with the complex social network of growers, agronomists, crop consultants, and advisors. The aim of the IoT in agricultural innovation and security chapter is to present agricultural IoT research and paradigm to promote sustainable production of safe, healthy, and profitable crop and animal agricultural products. This chapter covers the IoT platform to test optimized management strategies, engage farmer and industry groups, and investigate new and traditional technology drivers that will enhance resilience of the farmers to the socio-environmental changes. A review of state-of-the-art communication architectures and underlying sensing technologies and communication mechanisms is presented with coverage of recent advances in the theory and applications of wireless underground communications. Major challenges in Ag-IoT design and implementation are also discussed

Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked FilesOver the past decade genome-wide association studies (GWAS) have been applied to aid in the understanding of the biology of traits. The success of this approach is governed by the underlying effect sizes carried by the true risk variants and the corresponding statistical power to observe such effects given the study design and sample size under investigation. Previous ASD GWAS have identified genome-wide significant (GWS) risk loci; however, these studies were of only of low statistical power to identify GWS loci at the lower effect sizes (odds ratio (OR) <1.15).We conducted a large-scale coordinated international collaboration to combine independent genotyping data to improve the statistical power and aid in robust discovery of GWS loci. This study uses genome-wide genotyping data from a discovery sample (7387 ASD cases and 8567 controls) followed by meta-analysis of summary statistics from two replication sets (7783 ASD cases and 11359 controls; and 1369 ASD cases and 137308 controls).We observe a GWS locus at 10q24.32 that overlaps several genes including PITX3, which encodes a transcription factor identified as playing a role in neuronal differentiation and CUEDC2 previously reported to be associated with social skills in an independent population cohort. We also observe overlap with regions previously implicated in schizophrenia which was further supported by a strong genetic correlation between these disorders (Rg = 0.23; P = 9 × 10(-6)). We further combined these Psychiatric Genomics Consortium (PGC) ASD GWAS data with the recent PGC schizophrenia GWAS to identify additional regions which may be important in a common neurodevelopmental phenotype and identified 12 novel GWS loci. These include loci previously implicated in ASD such as FOXP1 at 3p13, ATP2B2 at 3p25.3, and a 'neurodevelopmental hub' on chromosome 8p11.23.This study is an important step in the ongoing endeavour to identify the loci which underpin the common variant signal in ASD. In addition to novel GWS loci, we have identified a significant genetic correlation with schizophrenia and association of ASD with several neurodevelopmental-related genes such as EXT1, ASTN2, MACROD2, and HDAC4.National Institutes of Mental Health (NIMH, USA) ACE Network Autism Genetic Resource Exchange (AGRE) is a program of Autism Speaks (USA) The Autism Genome Project (AGP) from Autism Speaks (USA) Canadian Institutes of Health Research (CIHR), Genome Canada Health Research Board (Ireland) Hilibrand Foundation (USA) Medical Research Council (UK) National Institutes of Health (USA) Ontario Genomics Institute University of Toronto McLaughlin Centre Simons Foundation Johns Hopkins Autism Consortium of Boston NLM Family foundation National Institute of Health grants National Health Medical Research Council Scottish Rite Spunk Fund, Inc. Rebecca and Solomon Baker Fund APEX Foundation National Alliance for Research in Schizophrenia and Affective Disorders (NARSAD) endowment fund of the Nancy Pritzker Laboratory (Stanford) Autism Society of America Janet M. Grace Pervasive Developmental Disorders Fund The Lundbeck Foundation universities and university hospitals of Aarhus and Copenhagen Stanley Foundation Centers for Disease Control and Prevention (CDC) Netherlands Scientific Organization Dutch Brain Foundation VU University Amsterdam Trinity Centre for High Performance Computing through Science Foundation Ireland Autism Genome Project (AGP) from Autism Speak

A systematic review of the reporting of Data Monitoring Committees' roles, interim analysis and early termination in pediatric clinical trials

<p>Abstract</p> <p>Background</p> <p>Decisions about interim analysis and early stopping of clinical trials, as based on recommendations of Data Monitoring Committees (DMCs), have far reaching consequences for the scientific validity and clinical impact of a trial. Our aim was to evaluate the frequency and quality of the reporting on DMC composition and roles, interim analysis and early termination in pediatric trials.</p> <p>Methods</p> <p>We conducted a systematic review of randomized controlled clinical trials published from 2005 to 2007 in a sample of four general and four pediatric journals. We used full-text databases to identify trials which reported on DMCs, interim analysis or early termination, and included children or adolescents. Information was extracted on general trial characteristics, risk of bias, and a set of parameters regarding DMC composition and roles, interim analysis and early termination.</p> <p>Results</p> <p>110 of the 648 pediatric trials in this sample (17%) reported on DMC or interim analysis or early stopping, and were included; 68 from general and 42 from pediatric journals. The presence of DMCs was reported in 89 of the 110 included trials (81%); 62 papers, including 46 of the 89 that reported on DMCs (52%), also presented information about interim analysis. No paper adequately reported all DMC parameters, and nine (15%) reported all interim analysis details. Of 32 trials which terminated early, 22 (69%) did not report predefined stopping guidelines and 15 (47%) did not provide information on statistical monitoring methods.</p> <p>Conclusions</p> <p>Reporting on DMC composition and roles, on interim analysis results and on early termination of pediatric trials is incomplete and heterogeneous. We propose a minimal set of reporting parameters that will allow the reader to assess the validity of trial results.</p