Epigenetic memory in induced pluripotent stem cells.

Somatic cell nuclear transfer and transcription-factor-based reprogramming revert adult cells to an embryonic state, and yield pluripotent stem cells that can generate all tissues. Through different mechanisms and kinetics, these two reprogramming methods reset genomic methylation, an epigenetic modification of DNA that influences gene expression, leading us to hypothesize that the resulting pluripotent stem cells might have different properties. Here we observe that low-passage induced pluripotent stem cells (iPSCs) derived by factor-based reprogramming of adult murine tissues harbour residual DNA methylation signatures characteristic of their somatic tissue of origin, which favours their differentiation along lineages related to the donor cell, while restricting alternative cell fates. Such an 'epigenetic memory' of the donor tissue could be reset by differentiation and serial reprogramming, or by treatment of iPSCs with chromatin-modifying drugs. In contrast, the differentiation and methylation of nuclear-transfer-derived pluripotent stem cells were more similar to classical embryonic stem cells than were iPSCs. Our data indicate that nuclear transfer is more effective at establishing the ground state of pluripotency than factor-based reprogramming, which can leave an epigenetic memory of the tissue of origin that may influence efforts at directed differentiation for applications in disease modelling or treatment

UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

Background: Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Results: Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. Conclusions: The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.The National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0310-1004)

International Veterinary Epilepsy Task Force consensus proposal: Medical treatment of canine epilepsy in Europe

In Europe, the number of antiepileptic drugs (AEDs) licensed for dogs has grown considerably over the last years. Nevertheless, the same questions remain, which include, 1) when to start treatment, 2) which drug is best used initially, 3) which adjunctive AED can be advised if treatment with the initial drug is unsatisfactory, and 4) when treatment changes should be considered. In this consensus proposal, an overview is given on the aim of AED treatment, when to start long-term treatment in canine epilepsy and which veterinary AEDs are currently in use for dogs. The consensus proposal for drug treatment protocols, 1) is based on current published evidence-based literature, 2) considers the current legal framework of the cascade regulation for the prescription of veterinary drugs in Europe, and 3) reflects the authors’ experience. With this paper it is aimed to provide a consensus for the management of canine idiopathic epilepsy. Furthermore, for the management of structural epilepsy AEDs are inevitable in addition to treating the underlying cause, if possible

Epigenetic memory in induced pluripotent stem cells

Somatic cell nuclear transfer and transcription-factor-based reprogramming revert adult cells to an embryonic state, and yield pluripotent stem cells that can generate all tissues. Through different mechanisms and kinetics, these two reprogramming methods reset genomic methylation, an epigenetic modification of DNA that influences gene expression, leading us to hypothesize that the resulting pluripotent stem cells might have different properties. Here we observe that low-passage induced pluripotent stem cells (iPSCs) derived by factor-based reprogramming of adult murine tissues harbour residual DNA methylation signatures characteristic of their somatic tissue of origin, which favours their differentiation along lineages related to the donor cell, while restricting alternative cell fates. Such an ‘epigenetic memory’ of the donor tissue could be reset by differentiation and serial reprogramming, or by treatment of iPSCs with chromatin-modifying drugs. In contrast, the differentiation and methylation of nuclear-transfer-derived pluripotent stem cells were more similar to classical embryonic stem cells than were iPSCs. Our data indicate that nuclear transfer is more effective at establishing the ground state of pluripotency than factor-based reprogramming, which can leave an epigenetic memory of the tissue of origin that may influence efforts at directed differentiation for applications in disease modelling or treatment.National Institutes of Health (U.S.) (NIH grant RO1-DK70055)National Institutes of Health (U.S.) (NIH Grant RO1-DK59279)National Institutes of Health (U.S.) (American Recovery and Reinvestment Act (RC2-HL102815))National Institutes of Health (U.S.) (NIH (K99HL093212-01))Cooley’s Anemia FoundationNational Institutes of Health (U.S.) (NIH LLS (3567-07))National Institutes of Health (U.S.) (NIH grant R37CA054358)National Institutes of Health (U.S.) (NIH grant P50HG003233)National Institutes of Health (U.S.) (NIH grant R01AI047457)National Institutes of Health (U.S.) (NIH Grant R01AI047458)National Institutes of Health (U.S.) (CA86065)National Institutes of Health (U.S.) (HL099999)Thomas and Stacey Siebel FoundationCalifornia Institute for Regenerative Medicine (Fellowship T1-00001

Interactions between obstructive sleep apnea syndrome and insulin resistance

Previous studies have shown Obstructive Sleep Apnea (OSA) as a risk factor for development of cardiovascular and cerebrovascular disease. However, controversies remain as to whether these changes are consequences of the associated obesity or OSA itself results in endocrine and metabolic changes, including impairment of insulin sensitivity, growth hormone, secretion inflammatory cytokines alterations, activation of peripheral sympathetic activity, and hipothalamic-pituitary-adrenal (HPA) axis, that may predispose to vascular disease. Furthermore many cardiovascular risk factors, such as hypertension, obesity, insulin resistance and type 2 diabetes, are strongly associated with OSA. In this article, we will review the evidence and discuss possible mechanisms underlying these links and the pathophysiology of OSA morbidities.Estudos anteriores mostraram que pacientes com Apnéia Obstrutiva do Sono (AOS) apresentam maior risco para doenças cardiovasculares. Entretanto, permanece controverso se essa associação depende da obesidade ou se ocorre devido a alterações fisiológicas decorrentes da desordem do sono, como ativação do sistema nervoso simpático, da inflamação e desordens do eixo corticotrófico e somatotrófico, que predispõem a danos vasculares. Além disso, muitos fatores de risco para doenças cardiovasculares (DCV) estão fortemente associados ao distúrbio respiratório, entre eles hipertensão, obesidade, resistência à insulina e diabetes tipo 2 (DM2). Neste artigo, vamos discutir a interação entre resistência à insulina e AOS e os possíveis mecanismos fisiopatológicos que contribuem para suas co-morbidades.Universidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Departamento de Clínica MédicaUniversidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Departamento de PsicobiologiaUNIFESP, EPM, Depto. de Clínica MédicaUNIFESP, EPM, Depto. de PsicobiologiaSciEL

State pension funds and corporate social responsibility: do beneficiaries’ political values influence funds’ investment decisions?

This study explores the underlying drivers of US public pension funds’ tendency to tilt their portfolios towards companies with stronger corporate social responsibility (CSR). Studying the equity holdings of large, internally-managed US state pension funds, we find evidence that the political leaning of their beneficiaries and political pressures by state politicians affect funds’ investment decisions. State pension funds from states with Democratic-leaning beneficiaries tilt their portfolios more strongly towards companies that perform well on CSR issues, and this tendency is intensified when the state government is dominated by Democratic state politicians. Moreover, we find that funds which tilt their portfolios towards companies with superior CSR scores generate a slightly higher return compared with their counterparts. Overall, our findings indicate that funds align their investment choices with the financial and non-financial interests of their beneficiaries when deciding whether to incorporate CSR into their equity allocations

Novel evolutionary algorithm identifies interactions driving infestation of triatoma dimidiata, a chagas disease vector

Chagas disease is a lethal, neglected tropical disease. Unfortunately, aggressive insecticide-spraying campaigns have not been able to eliminate domestic infestation of Triatoma dimidiata, the native vector in Guatemala. To target interventions toward houses most at risk of infestation, comprehensive socioeconomic and entomologic surveys were conducted in two towns in Jutiapa, Guatemala. Given the exhaustively large search space associated with combinations of risk factors, traditional statistics are limited in their ability to discover risk factor interactions. Two recently developed statistical evolutionary algorithms, specifically designed to accommodate risk factor interactions and heterogeneity, were applied to this large combinatorial search space and used in tandem to identify sets of risk factor combinations associated with infestation. The optimal model includes 10 risk factors in what is known as a third-order disjunctive normal form (i.e., infested households have chicken coops AND deteriorated bedroom walls OR an accumulation of objects AND dirt floors AND total number of occupants 3 5 AND years of electricity 3 5 OR poor hygienic condition ratings AND adobe walls AND deteriorated walls AND dogs). Houses with dirt floors and deteriorated walls have been reported previously as risk factors and align well with factors currently targeted by Ecohealth interventions to minimize infestation. However, the tandem evolutionary algorithms also identified two new socioeconomic risk factors (i.e., households having many occupants and years of electricity 3 5). Identifying key risk factors may help with the development of new Ecohealth interventions and/or reduce the survey time needed to identify houses most at risk

Computational Stem Cell Biology: Open Questions and Guiding Principles

Computational biology is enabling an explosive growth in our understanding of stem cells and our ability to use them for disease modeling, regenerative medicine, and drug discovery. We discuss four topics that exemplify applications of computation to stem cell biology: cell typing, lineage tracing, trajectory inference, and regulatory networks. We use these examples to articulate principles that have guided computational biology broadly and call for renewed attention to these principles as computation becomes increasingly important in stem cell biology. We also discuss important challenges for this field with the hope that it will inspire more to join this exciting area