5 research outputs found
A new role of AMP-activated protein kinase in regulating proliferation of mesenchymal stem cells
Purpose: Natriuretic peptides (NPs) administered during early reperfusion are protective in models of myocardial infarction. A previous study examining the endogenous components of B-type natriuretic peptide (BNP) protection of reperfused myocardium, implicated both sarcolemmal (s) KATP and mitochondrial (m) KATP channels. The indirect evidence characterising the relationship between BNP signalling and KATP was obtained using sulphonylurea receptor inhibitors in a rat isolated heart model of ischaemia-reperfusion injury. Here we seek to further examine the relationship between NPs and sKATP openings using single channel electrophysiology. Given our previous findings and the overarching consensus that cardioprotective autacoids open KATP channels, it was hypothesised that NPs elicit sKATP opening.
Methods: Cardiomyocyte isolation. Left ventricular cardiomyocytes were isolated from male Sprague-Dawley rat hearts subjected to enzymatic digestion with Liberase Blendzyme DL. Cardiomyocytes were cultured overnight in Medium 199, prior to patch clamp. Single channel patch clamp. Single channel recordings at room temperature (22°C) were made from cell attached patches bathed in Na+ Locke, pH 7.2. The recording pipette contained high KCl (140 mM), pH 7.2. Recordings (45 sec) were made over a range of patch potentials (0, -30, -60, -90, -120 mV), in the absence (control) and in the presence of bath applied BNP (10, 100 nM and 1 µM), pinacidil (200 µM) or pinacidil vehicle (DMSO, 0.25%). Recordings were also made with BNP and pinacidil applied concomitantly. Data are mean ± S.E.M.
Results: The current voltage relationship of sKATP under control conditions was linear at –ve patch potentials, the mean conductance being 52.9 ± 1.8 pS (n = 18 hearts, n = 35 cells). Pinacidil caused a four fold increase in sKATP open probability compared to control. Mean channel conductance in the presence of pinacidil was 59.9 ± 1.9 pS (n = 16 hearts, n = 44 cells). Interestingly BNP at all concentrations had negligible effects on sKATP open probability and unitary conductance. However, BNP at all concentrations and patch potentials inhibited pinacidil induced sKATP openings, restoring channel open probability to baseline.
Conclusion: These data illustrate the inhibitory effect of NP signalling on sKATP function in the cardiomyocyte under normoxia. They are concordant with the inhibitory effect of atrial NP on KATP in the pancreatic beta cell, but are in apparent conflict with the current cardioprotection paradigm. However, differential effects on sKATP and mKATP and the effects of hypoxia-reoxygenation require further exploration
Potentiation effect of the AMPK activator A-769662 on cardiac myocytes metabolism and survival
Abstract 286 van Poster session 2 Frontiers in CardioVascular Biology, London 30th March – 1st April 2012 Second Congress of the ESC Council on Basic Cardiovascular Science
Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology
Gould E, Fraser H, Parker T, et al. Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology. 2023.Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different (mostly social science) fields, and has found substantial variability among results, despite analysts having the same data and research question. We implemented an analogous study in ecology and evolutionary biology, fields in which there have been no empirical exploration of the variation in effect sizes or model predictions generated by the analytical decisions of different researchers. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment), and the project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future