33 research outputs found

    Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

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    In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

    Networks for improving care in patients with acute coronary syndrome: A framework

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    In recent years, it has become evident that the level of guideline adherence in patients presenting with acute coronary syndrome (ACS) is highly correlated with patient outcomes. Unfortunately, guideline adherence is low in some geographic areas and especially in those patients at high-risk. Regional networks including ambulance systems and hospitals with catheterization laboratories are able to increase guideline adherence and patient outcomes by streamlining the critical pre- and intra-hospital processes as well as improving timely access to invasive procedures and recommended medication. Successful organization of an ACS network requires engagement of multiple stakeholders to create effective solutions for the specific local setting. There is no 'one-size-fits all' strategy to set-up and successfully run an ACS network. We present a framework for how to set up and organize an effective ACS network, delivering guideline-based care to improve patient outcomes. Copyright © 2014 Informa UK, Ltd

    The entorhinal cortex of Megachiroptera: a comparative study of Wahlberg's epauletted fruit bat and the straw-coloured fruit bat

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    This study describes the organisation of the entorhinal cortex of the Megachiroptera, Strawcoloured fruit bat and Wahlberg’s epauletted fruit bat. Using Nissl and Timm stains, parvalbumin and SMI-32 immunohistochemistry, we identified 5 fields within the medial(MEA) and lateral (LEA) entorhinal areas. MEA fields ECL and EC are characterised by a poor differentiation between layers II and III, a distinct layer IV and broad, stratified layers V and VI. LEA fields EI, ER and EL are distinguished by cell clusters in layer II, a clear differentiation between layers II and III, a wide columnar layer III, and a broad sublayer Va. Clustering in LEA layer II was more typical of the Straw-coloured fruit bat. Timm-staining was most intense in layers Ib and II across all fields, and layer III of field ER. Parvalbuminlike staining varied along a medio-lateral gradient with highest immunoreactivity in layers II and III of MEA and more lateral fields of LEA. Sparse SMI-32-like immunoreactivity was seen only in Wahlberg’s epauletted fruit bat. Of the neurons in MEA layer II, ovoid stellate cells account for ~38%, polygonal stellate cells for ~8%, pyramidal cells for ~18%, oblique pyramidal cells for ~6%, and other neurons of variable morphology for ~29%. Differences between bats and other species in cellular make-up and cytoarchitecture of layer II may relate to their 3-dimensional habitat. Cytoarchitecture of layer V in conjunction with high encephalisation and structural changes in the hippocampus suggest similarities in efferent hippocampal-entorhinal-cortical interactions between fruit bats and primates

    Biomarkers of therapeutic responses in chronic Chagas disease: state of the art and future perspectives

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    The definition of a biomarker provided by the World Health Organization is any substance, structure, or process that can be measured in the body, or its products and influence, or predict the incidence or outcome of disease. Currently, the lack of prognosis and progression markers for chronic Chagas disease has posed limitations for testing new drugs to treat this neglected disease. Several molecules and techniques to detect biomarkers in Trypanosoma cruzi-infected patients have been proposed to assess whether specific treatment with benznidazole or nifurtimox is effective. Isolated proteins or protein groups from different T. cruzi stages and parasite-derived glycoproteins and synthetic neoglycoconjugates have been demonstrated to be useful for this purpose, as have nucleic acid amplification techniques. The amplification of T. cruzi DNA using the real-time polymerase chain reaction method is the leading test for assessing responses to treatment in a short period of time. Biochemical biomarkers have been tested early after specific treatment. Cytokines and surface markers represent promising molecules for the characterisation of host cellular responses, but need to be further assessed.RICET RD12/0018/0010. RICET RD12/0018/0021. AGAUR 2014SGR26. Plan Nacional de I+D+I SAF2012-35777. Plan Nacional de I+D+I SAF2013-48527-R. NIMHD/NIH 2G12MD007592. Financial support: CRESIB and IPBLN research members were partially supported by the RICET (RD12/0018/0010, RD12/0018/0021), M-JP and JG received research funds from AGAUR (2014SGR26) and Fundación Mundo Sano, M-CT and M-CL were supported by Plan Nacional de I+D+I (MINECO-Spain) (SAF2012-35777, SAF2013-48527-R and FEDER), ICA was partially supported by NIMHD/NIH (2G12MD007592). Financial support: CRESIB and IPBLN research members were partially supported by the RICET (RD12/0018/0010, RD12/0018/0021), M-JP and JG received research funds from AGAUR (2014SGR26) and Fundación Mundo Sano, M-CT and M-CL were supported by Plan Nacional de I+D+I (MINECO-Spain) (SAF2012-35777, SAF2013-48527-R and FEDER), ICA was partially supported by NIMHD/NIH (2G12MD007592).Peer reviewe
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