The importance of Southern Ocean frontal systems for the improvement of body condition in southern elephant seals

Funding: Natural Environment Research Council, Grant/Award Numbers: NE/E018289/1, NE/L501852/1 NER/D/S/2002/00426; Scottish Funding Council, Grant/Award Number: HR09011.1. As top predators, it has been suggested that southern elephant seals serve as sentinels of ecosystem status to inform management and conservation.2. This is because southern elephant seals annually undertake two large‐scale foraging migrations for 2–3 and 7–8 months to replenish resources after fasting during breeding and moulting and often rely on dynamic macroscale latitudinal fronts to provide favourable foraging through aggregating prey.3. Yet it is largely unknown whether southern elephant seals respond to changes in frontal systems over the years, whether their foraging success is associated with specific frontal systems shifts, and how flexible southern elephant seals populations are in behaviourally adapting to changes in frontal systems.4. This study examines the relationship between frontal systems and the resource acquisition of 64 southern elephant seals during four post‐moult and three post‐breeding migrations between 2005 and 2010.5. Satellite‐relay‐data‐loggers provided in situ measurements concurrent with >27,500 dive profiles to define fronts and interfrontal zones between the Subtropical Frontal Zone and the Southern Boundary of the Antarctic Circumpolar Current. For >430,000 in situ measurements water mass properties could be identified.6. Generally, southern elephant seals associate more frequently with more southerly, higher‐latitude fronts/zones. Body condition improvements related to a given frontal system or water mass vary strongly according to year, season, month and sex.7. The variability in body condition improvements is higher in some frontal systems than in others, probably owing to shifts in the Subantarctic and Polar Front.8. During a migration, some individuals stay within ≤3 frontal systems, whilst others change between several frontal systems and primarily improve their body condition in upper ocean waters.9. Southern elephant seals do not trace particular water masses across frontal systems, and both surface and deep foraging strategies are used.10. This suggests that southern elephant seals do not target particular water masses but adjust foraging and movement strategies to exploit boundary areas at which mixing and prey aggregation is high.11. The large behavioural plasticity towards the spatio‐temporal variability in the different oceanographic regions they encounter could indicate resilience against environmental changes.PostprintPeer reviewe

Ginkgo Biloba Extract Ameliorates Oxidative Phosphorylation Performance and Rescues Aβ-Induced Failure

Energy deficiency and mitochondrial failure have been recognized as a prominent, early event in Alzheimer's disease (AD). Recently, we demonstrated that chronic exposure to amyloid-beta (Abeta) in human neuroblastoma cells over-expressing human wild-type amyloid precursor protein (APP) resulted in (i) activity changes of complexes III and IV of the oxidative phosphorylation system (OXPHOS) and in (ii) a drop of ATP levels which may finally instigate loss of synapses and neuronal cell death in AD. Therefore, the aim of the present study was to investigate whether standardized Ginkgo biloba extract LI 1370 (GBE) is able to rescue Abeta-induced defects in energy metabolism

Implementation of rapid genomic sequencing in safety-net neonatal intensive care units: protocol for the VIrtual GenOme CenteR (VIGOR) proof-of-concept study.

INTRODUCTION: Rapid genomic sequencing (rGS) in critically ill infants with suspected genetic disorders has high diagnostic and clinical utility. However, rGS has primarily been available at large referral centres with the resources and expertise to offer state-of-the-art genomic care. Critically ill infants from racial and ethnic minority and/or low-income populations disproportionately receive care in safety-net and/or community settings lacking access to state-of-the-art genomic care, contributing to unacceptable health equity gaps. VIrtual GenOme CenteR is a \u27proof-of-concept\u27 implementation science study of an innovative delivery model for genomic care in safety-net neonatal intensive care units (NICUs). METHODS AND ANALYSIS: We developed a virtual genome centre at a referral centre to remotely support safety-net NICU sites predominantly serving racial and ethnic minority and/or low-income populations and have limited to no access to rGS. Neonatal providers at each site receive basic education about genomic medicine from the study team and identify eligible infants. The study team enrols eligible infants (goal n of 250) and their parents and follows families for 12 months. Enrolled infants receive rGS, the study team creates clinical interpretive reports to guide neonatal providers on interpreting results, and neonatal providers return results to families. Data is collected via (1) medical record abstraction, (2) surveys, interviews and focus groups with neonatal providers and (3) surveys and interviews with families. We aim to examine comprehensive implementation outcomes based on the Proctor Implementation Framework using a mixed methods approach. ETHICS AND DISSEMINATION: This study is approved by the institutional review board of Boston Children\u27s Hospital (IRB-P00040496) and participating sites. Participating families are required to provide electronic written informed consent and neonatal provider consent is implied through the completion of surveys. The results will be disseminated via peer-reviewed publications and data will be made accessible per National Institutes of Health (NIH) policies. TRIAL REGISTRATION NUMBER: NCT05205356/clinicaltrials.gov

Atypical Forms of Employment in the Public Sector Are There Any?

The paper deals with various forms of atypical employment in the public sector that are widely neglected in existing research; its specific focus is on their development, scope, distribution and structural features. In the first part we break down the purely statistical category and differentiate between the disparate forms (part-time, marginal employment or minijobs, midijobs, fixed-term, agency work). In the second part we address the question if these forms are not only atypical, but also have to be classified as precarious. We distinguish various risks operative in the short, medium and long term (income, stability of employment and employability, pensions). Finally, we differentiate between employment in the private as well as the public sector and draw parallels and indicate specific differences in their development and situation. Our basic finding is that atypical forms of employment are also widespread in the public sector but are all in all less precarious than in the private sector. The distribution of individual forms shows major differences between both sectors whereas the over-all percentages are similar

Mapping Dynamic Histone Acetylation Patterns to Gene Expression in Nanog-depleted Murine Embryonic Stem Cells

Embryonic stem cells (ESC) have the potential to self-renew indefinitely and to differentiate into any of the three germ layers. The molecular mechanisms for self-renewal, maintenance of pluripotency and lineage specification are poorly understood, but recent results point to a key role for epigenetic mechanisms. In this study, we focus on quantifying the impact of histone 3 acetylation (H3K9,14ac) on gene expression in murine embryonic stem cells. We analyze genome-wide histone acetylation patterns and gene expression profiles measured over the first five days of cell differentiation triggered by silencing Nanog, a key transcription factor in ESC regulation. We explore the temporal and spatial dynamics of histone acetylation data and its correlation with gene expression using supervised and unsupervised statistical models. On a genome-wide scale, changes in acetylation are significantly correlated to changes in mRNA expression and, surprisingly, this coherence increases over time. We quantify the predictive power of histone acetylation for gene expression changes in a balanced cross-validation procedure. In an in-depth study we focus on genes central to the regulatory network of Mouse ESC, including those identified in a recent genome-wide RNAi screen and in the PluriNet, a computationally derived stem cell signature. We find that compared to the rest of the genome, ESC-specific genes show significantly more acetylation signal and a much stronger decrease in acetylation over time, which is often not reflected in an concordant expression change. These results shed light on the complexity of the relationship between histone acetylation and gene expression and are a step forward to dissect the multilayer regulatory mechanisms that determine stem cell fate.Comment: accepted at PLoS Computational Biolog

A Relative Variation-Based Method to Unraveling Gene Regulatory Networks

Gene regulatory network (GRN) reconstruction is essential in understanding the functioning and pathology of a biological system. Extensive models and algorithms have been developed to unravel a GRN. The DREAM project aims to clarify both advantages and disadvantages of these methods from an application viewpoint. An interesting yet surprising observation is that compared with complicated methods like those based on nonlinear differential equations, etc., methods based on a simple statistics, such as the so-called -score, usually perform better. A fundamental problem with the -score, however, is that direct and indirect regulations can not be easily distinguished. To overcome this drawback, a relative expression level variation (RELV) based GRN inference algorithm is suggested in this paper, which consists of three major steps. Firstly, on the basis of wild type and single gene knockout/knockdown experimental data, the magnitude of RELV of a gene is estimated. Secondly, probability for the existence of a direct regulation from a perturbed gene to a measured gene is estimated, which is further utilized to estimate whether a gene can be regulated by other genes. Finally, the normalized RELVs are modified to make genes with an estimated zero in-degree have smaller RELVs in magnitude than the other genes, which is used afterwards in queuing possibilities of the existence of direct regulations among genes and therefore leads to an estimate on the GRN topology. This method can in principle avoid the so-called cascade errors under certain situations. Computational results with the Size 100 sub-challenges of DREAM3 and DREAM4 show that, compared with the -score based method, prediction performances can be substantially improved, especially the AUPR specification. Moreover, it can even outperform the best team of both DREAM3 and DREAM4. Furthermore, the high precision of the obtained most reliable predictions shows that the suggested algorithm may be very helpful in guiding biological experiment designs

Bagging Statistical Network Inference from Large-Scale Gene Expression Data

Modern biology and medicine aim at hunting molecular and cellular causes of biological functions and diseases. Gene regulatory networks (GRN) inferred from gene expression data are considered an important aid for this research by providing a map of molecular interactions. Hence, GRNs have the potential enabling and enhancing basic as well as applied research in the life sciences. In this paper, we introduce a new method called BC3NET for inferring causal gene regulatory networks from large-scale gene expression data. BC3NET is an ensemble method that is based on bagging the C3NET algorithm, which means it corresponds to a Bayesian approach with noninformative priors. In this study we demonstrate for a variety of simulated and biological gene expression data from S. cerevisiae that BC3NET is an important enhancement over other inference methods that is capable of capturing biochemical interactions from transcription regulation and protein-protein interaction sensibly. An implementation of BC3NET is freely available as an R package from the CRAN repository

Integrative Network Biology: Graph Prototyping for Co-Expression Cancer Networks

Network-based analysis has been proven useful in biologically-oriented areas, e.g., to explore the dynamics and complexity of biological networks. Investigating a set of networks allows deriving general knowledge about the underlying topological and functional properties. The integrative analysis of networks typically combines networks from different studies that investigate the same or similar research questions. In order to perform an integrative analysis it is often necessary to compare the properties of matching edges across the data set. This identification of common edges is often burdensome and computational intensive. Here, we present an approach that is different from inferring a new network based on common features. Instead, we select one network as a graph prototype, which then represents a set of comparable network objects, as it has the least average distance to all other networks in the same set. We demonstrate the usefulness of the graph prototyping approach on a set of prostate cancer networks and a set of corresponding benign networks. We further show that the distances within the cancer group and the benign group are statistically different depending on the utilized distance measure

Amyloid precursor protein drives down-regulation of mitochondrial oxidative phosphorylation independent of amyloid beta

Amyloid precursor protein (APP) and its extracellular domain, soluble APP alpha (sAPPα) play important physiological and neuroprotective roles. However, rare forms of familial Alzheimer’s disease are associated with mutations in APP that increase toxic amyloidogenic cleavage of APP and produce amyloid beta (Aβ) at the expense of sAPPα and other non-amyloidogenic fragments. Although mitochondrial dysfunction has become an established hallmark of neurotoxicity, the link between Aβ and mitochondrial function is unclear. In this study we investigated the effects of increased levels of neuronal APP or Aβ on mitochondrial metabolism and gene expression, in human SH-SY5Y neuroblastoma cells. Increased non-amyloidogenic processing of APP, but not Aβ, profoundly decreased respiration and enhanced glycolysis, while mitochondrial DNA (mtDNA) transcripts were decreased, without detrimental effects to cell growth. These effects cannot be ascribed to Aβ toxicity, since higher levels of endogenous Aβ in our models do not cause oxidative phosphorylation (OXPHOS) perturbations. Similarly, chemical inhibition of β-secretase decreased mitochondrial respiration, suggesting that non-amyloidogenic processing of APP may be responsible for mitochondrial changes. Our results have two important implications, the need for caution in the interpretation of mitochondrial perturbations in models where APP is overexpressed, and a potential role of sAPPα or other non-amyloid APP fragments as acute modulators of mitochondrial metabolism

Hierarchical coordination of periodic genes in the cell cycle of Saccharomyces cerevisiae

<p>Abstract</p> <p>Background</p> <p>Gene networks are a representation of molecular interactions among genes or products thereof and, hence, are forming causal networks. Despite intense studies during the last years most investigations focus so far on inferential methods to reconstruct gene networks from experimental data or on their structural properties, e.g., degree distributions. Their structural analysis to gain functional insights into organizational principles of, e.g., pathways remains so far under appreciated.</p> <p>Results</p> <p>In the present paper we analyze cell cycle regulated genes in <it>S. cerevisiae</it>. Our analysis is based on the transcriptional regulatory network, representing causal interactions and not just associations or correlations between genes, and a list of known periodic genes. No further data are used. Partitioning the transcriptional regulatory network according to a graph theoretical property leads to a hierarchy in the network and, hence, in the information flow allowing to identify two groups of periodic genes. This reveals a novel conceptual interpretation of the working mechanism of the cell cycle and the genes regulated by this pathway.</p> <p>Conclusion</p> <p>Aside from the obtained results for the cell cycle of yeast our approach could be exemplary for the analysis of general pathways by exploiting the rich causal structure of inferred and/or curated gene networks including protein or signaling networks.</p