3 resultados para IAS 36

em Aston University Research Archive


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Adiponectin is an abundantly circulating adipokine, orchestrating its effects through two 7-transmembrane receptors (AdipoR1 and AdipoR2). Steroidogenesis is regulated by a variety of neuropeptides and adipokines. Earlier studies have reported adipokine mediated steroid production. A key rate-limiting step in steroidogenesis is cholesterol transportation across the mitochondrial membrane by steroidogenic acute regulatory protein (StAR). Several signalling pathways regulate StAR expression. The actions of adiponectin and its role in human adrenocortical steroid biosynthesis are not fully understood. The aim of this study was to investigate the effects of adiponectin on StAR protein expression, steroidogenic genes, and cortisol production and to dissect the signalling cascades involved in the activation of StAR expression. Using qRT-PCR, Western blot analysis and ELISA, we have demonstrated that stimulation of human adrenocortical H295R cells with adiponectin results in increased cortisol secretion. This effect is accompanied by increased expression of key steroidogenic pathway genes including StAR protein expression via ERK1/2 and AMPK-dependent pathways. This has implications for our understanding of adiponectin receptor activation and peripheral steroidogenesis. Finally, our study aims to emphasise the key role of adipokines in the integration of metabolic activity and energy balance partly via the regulation of adrenal steroid production.

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In previous Statnotes, many of the statistical tests described rely on the assumption that the data are a random sample from a normal or Gaussian distribution. These include most of the tests in common usage such as the ‘t’ test ), the various types of analysis of variance (ANOVA), and Pearson’s correlation coefficient (‘r’) . In microbiology research, however, not all variables can be assumed to follow a normal distribution. Yeast populations, for example, are a notable feature of freshwater habitats, representatives of over 100 genera having been recorded . Most common are the ‘red yeasts’ such as Rhodotorula, Rhodosporidium, and Sporobolomyces and ‘black yeasts’ such as Aurobasidium pelculans, together with species of Candida. Despite the abundance of genera and species, the overall density of an individual species in freshwater is likely to be low and hence, samples taken from such a population will contain very low numbers of cells. A rare organism living in an aquatic environment may be distributed more or less at random in a volume of water and therefore, samples taken from such an environment may result in counts which are more likely to be distributed according to the Poisson than the normal distribution. The Poisson distribution was named after the French mathematician Siméon Poisson (1781-1840) and has many applications in biology, especially in describing rare or randomly distributed events, e.g., the number of mutations in a given sequence of DNA after exposure to a fixed amount of radiation or the number of cells infected by a virus given a fixed level of exposure. This Statnote describes how to fit the Poisson distribution to counts of yeast cells in samples taken from a freshwater lake.

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Introduction - Monocytes, with 3 different subsets, are implicated in the initiation and progression of the atherosclerotic plaque contributing to plaque instability and rupture. Mon1 are the “classical” monocytes with inflammatory action, whilst Mon3 are considered reparative with fibroblast deposition ability. The function of the newly described Mon2 subset is yet to be fully described. In PCI era, fewer patients have globally reduced left ventricular ejection fraction post infarction, hence the importance of studying regional wall motion abnormalities and deformation at segmental levels using longitudinal strain. Little is known of the role for the 3 monocyte subpopulations in determining global strain in ST elevation myocardial infarction patients (STEMI). Conclusion In patients with normal or mildly impaired EF post infarction, higher counts of Mon1 and Mon2 are correlated with GLS within 7 days and at 6 months of remodelling post infarction. Adverse clinical outcomes in patients with reduced convalescent GLS were predicted with Mon1 and Mon2 suggestive of an inflammatory role for the newly identified Mon2 subpopulation. These results imply an important role for monocytes in myocardial healing when assessed by subclinical ventricular function indices. Methodology - STEMI patients (n = 101, mean age 64 ± 13 years; 69% male) treated with percutaneous revascularisation were recruited within 24 h post-infarction. Peripheral blood monocyte subpopulations were enumerated and characterised using flow cytometry after staining for CD14, CD16 and CCR2. Phenotypically, monocyte subpopulations are defined as: CD14++CD16-CCR2+ (Mon1), CD14++CD16+CCR2+ (Mon2) and CD14+CD16++CCR2- (Mon3). Phagocytic activity of monocytes was measured using flow cytometry and Ecoli commercial kit. Transthoracic 2D echocardiography was performed within 7 days and at 6 months post infarct to assess global longitudinal strain (GLS) via speckle tracking. MACE was defined as recurrent acute coronary syndrome and death. Results - STEMI patients with EF ≥50% by Simpson’s biplane (n = 52) had GLS assessed. Using multivariate regression analysis higher counts of Mon1 and Mon 2 and phagocytic activity of Mon2 were significantly associated with GLS (after adjusting for age, time to hospital presentation, and peak troponin levels) (Table 1). At 6 months, the convalescent GLS remained associated with higher counts of Mon1, Mon 2. At one year follow up, using multivariate Cox regression analysis, Mon1 and Mon2 counts were an independent predictor of MACE in patients with a reduced GLS (n = 21)