Effects of human recombinant growth hormone on exercise capacity, cardiac structure, and cardiac function in patients with adult-onset growth hormone deficiency

Objective Epidemiological studies suggest that adult-onset growth hormone deficiency (AGHD) might increase the risk of death from cardiovascular causes. Methods This was a 6-month double-blind, placebo-controlled, randomised, cross-over trial followed by a 6-month open-label phase. Seventeen patients with AGHD received either recombinant human growth hormone (rGH) (0.4 mg injection daily) or placebo for 12 weeks, underwent washout for 2 weeks, and were then crossed over to the alternative treatment for a further 12 weeks. Cardiac magnetic resonance imaging, echocardiography, and cardiopulmonary exercise testing were performed at baseline, 12 weeks, 26 weeks, and the end of the open phase (12 months). The results were compared with those of 16 age- and sex-matched control subjects. Results At baseline, patients with AGHD had a significantly higher systolic blood pressure, ejection fraction, and left ventricular mass than the control group, even when corrected for body surface area. Treatment with rGH normalised the insulin-like growth factor 1 concentration without an effect on exercise capacity, cardiac structure, or cardiac function. Conclusion Administration of rGH therapy for 6 to 9 months failed to normalise the functional and structural cardiac differences observed in patients with AGHD when compared with a control group

Phylomemetics—Evolutionary Analysis beyond the Gene

Genes are propagated by error-prone copying, and the resulting variation provides the basis for phylogenetic reconstruction of evolutionary relationships. Horizontal gene transfer may be superimposed on a tree-like evolutionary pattern, with some relationships better depicted as networks. The copying of manuscripts by scribes is very similar to the replication of genes, and phylogenetic inference programs can be used directly for reconstructing the copying history of different versions of a manuscript text. Phylogenetic methods have also been used for some time to analyse the evolution of languages and the development of physical cultural artefacts. These studies can help to answer a range of anthropological questions. We propose the adoption of the term “phylomemetics” for phylogenetic analysis of reproducing non-genetic elements

Rationale, design and methodology of APPROACH-IS II: International study of patient-reported outcomes and frailty phenotyping in adults with congenital heart disease.

In recent years, patient-reported outcomes (PROs) have received increasing prominence in cardiovascular research and clinical care. An understanding of the variability and global experience of PROs in adults with congenital heart disease (CHD), however, is still lacking. Moreover, information on epidemiological characteristics and the frailty phenotype of older adults with CHD is minimal. The APPROACH-IS II study was established to address these knowledge gaps. This paper presents the design and methodology of APPROACH-IS II. APPROACH-IS II is a cross-sectional global multicentric study that includes Part 1 (assessing PROs) and Part 2 (investigating the frailty phenotype of older adults). With 53 participating centers, located in 32 countries across six continents, the aim is to enroll 8000 patients with CHD. In Part 1, self-report surveys are used to collect data on PROs (e.g., quality of life, perceived health, depressive symptoms, autonomy support), and explanatory variables (e.g., social support, stigma, illness identity, empowerment). In Part 2, the cognitive functioning and frailty phenotype of older adults are measured using validated assessments. APPROACH-IS II will generate a rich dataset representing the international experience of individuals in adult CHD care. The results of this project will provide a global view of PROs and the frailty phenotype of adults with CHD and will thereby address important knowledge gaps. Undoubtedly, the project will contribute to the overarching aim of improving optimal living and care provision for adults with CHD

Time-resolved dual transcriptomics reveal early induced Nicotiana benthamiana root genes and conserved infection-promoting Phytophthora palmivora effectors

BACKGROUND: Plant-pathogenic oomycetes are responsible for economically important losses in crops worldwide. Phytophthora palmivora, a tropical relative of the potato late blight pathogen, causes rotting diseases in many tropical crops including papaya, cocoa, oil palm, black pepper, rubber, coconut, durian, mango, cassava and citrus. Transcriptomics have helped to identify repertoires of host-translocated microbial effector proteins which counteract defenses and reprogram the host in support of infection. As such, these studies have helped in understanding how pathogens cause diseases. Despite the importance of P. palmivora diseases, genetic resources to allow for disease resistance breeding and identification of microbial effectors are scarce. RESULTS: We employed the model plant Nicotiana benthamiana to study the P. palmivora root infections at the cellular and molecular levels. Time-resolved dual transcriptomics revealed different pathogen and host transcriptome dynamics. De novo assembly of P. palmivora transcriptome and semi-automated prediction and annotation of the secretome enabled robust identification of conserved infection-promoting effectors. We show that one of them, REX3, suppresses plant secretion processes. In a survey for early transcriptionally activated plant genes we identified a N. benthamiana gene specifically induced at infected root tips that encodes a peptide with danger-associated molecular features. CONCLUSIONS: These results constitute a major advance in our understanding of P. palmivora diseases and establish extensive resources for P. palmivora pathogenomics, effector-aided resistance breeding and the generation of induced resistance to Phytophthora root infections. Furthermore, our approach to find infection-relevant secreted genes is transferable to other pathogen-host interactions and not restricted to plants.This work was supported by the Gatsby Charitable Foundation (RG62472), by the Royal Society (RG69135) and by the European Research Council (ERC-2014-STG, H2020, 637537)

Evolution in Congenital Cardiology Education:The Rise of Digital-Learning Tools

Technology-enhanced learning is now an established part of medical education due to its ready availability and on-demand nature. This offers new opportunities but also challenges to both learners and teachers. This review outlines the current use of social media tools and online resources in medical education with a particular emphasis on congenital cardiology. It provides strategies to the reader on how to optimize learning in the digital environment and offers guidance on how such tools can be incorporated into routine educational practice. Suggestions for developing and assessing educational material online are discussed. Lastly, the concepts of digital professionalism and digital scholarship are explored to aid medical teachers and educators employ these technologies effectively into their teaching and career development

Directed partial correlation : inferring large-scale gene regulatory network through induced topology disruptions

Inferring regulatory relationships among many genes based on their temporal variation in transcript abundance has been a popular research topic. Due to the nature of microarray experiments, classical tools for time series analysis lose power since the number of variables far exceeds the number of the samples. In this paper, we describe some of the existing multivariate inference techniques that are applicable to hundreds of variables and show the potential challenges for small-sample, largescale data. We propose a directed partial correlation (DPC) method as an efficient and effective solution to regulatory network inference using these data. Specifically for genomic data, the proposed method is designed to deal with large-scale datasets. It combines the efficiency of partial correlation for setting up network topology by testing conditional independence, and the concept of Granger causality to assess topology change with induced interruptions. The idea is that when a transcription factor is induced artificially within a gene network, the disruption of the network by the induction signifies a genes role in transcriptional regulation. The benchmarking results using GeneNetWeaver, the simulator for the DREAM challenges, provide strong evidence of the outstanding performance of the proposed DPC method. When applied to real biological data, the inferred starch metabolism network in Arabidopsis reveals many biologically meaningful network modules worthy of further investigation. These results collectively suggest DPC is a versatile tool for genomics research. The R package DPC is available for download (http://code.google.com/p/dpcnet/)