Chasing Cardiac Physiology And Pathology Down The Camkii Cascade.

Calcium dynamics is central in cardiac physiology, as the key event leading to the excitation-contraction coupling (ECC) and relaxation processes. The primary function of Ca(2+) in the heart is the control of mechanical activity developed by the myofibril contractile apparatus. This key role of Ca(2+) signaling explains the subtle and critical control of important events of ECC and relaxation, such Ca(2+) influx and SR Ca(2+) release and uptake. The multifunctional Ca(2+)-calmodulin-dependent protein kinase II (CaMKII) is a signaling molecule that regulates a diverse array of proteins involved not only in ECC and relaxation, but also in cell death, transcriptional activation of hypertrophy, inflammation and arrhythmias. CaMKII activity is triggered by an increase in intracellular Ca(2+) levels. This activity can be sustained, creating molecular memory after the decline in Ca(2+) concentration, by autophosphorylation of the enzyme, as well as by oxidation, glycosylation and nitrosylation at different sites of the regulatory domain of the kinase. CaMKII activity is enhanced in several cardiac diseases, altering the signaling pathways by which CaMKII regulates the different fundamental proteins involved in functional and transcriptional cardiac processes. Dysregulation of these pathways constitutes a central mechanism of various cardiac disease phenomena, like apoptosis and necrosis during ischemia/reperfusion injury, digitalis exposure, post-acidosis and heart failure arrhythmias, or cardiac hypertrophy. Here we summarize significant aspects of the molecular physiology of CaMKII and provide a conceptual framework for understanding the role of the CaMKII cascade on Ca(2+) regulation and dysregulation in cardiac health and disease.

Saturated Fatty Acids Modulate Autophagy's Proteins In The Hypothalamus.

Autophagy is an important process that regulates cellular homeostasis by degrading dysfunctional proteins, organelles and lipids. In this study, the hypothesis that obesity could lead to impairment in hypothalamic autophagy in mice was evaluated by examining the hypothalamic distribution and content of autophagic proteins in animal with obesity induced by 8 or 16 weeks high fat diet to induce obesity and in response to intracerebroventricular injections of palmitic acid. The results showed that chronic exposure to a high fat diet leads to an increased expression of inflammatory markers and downregulation of autophagic proteins. In obese mice, autophagic induction leads to the downregulation of proteins, such as JNK and Bax, which are involved in the stress pathways. In neuron cell- line, palmitate has a direct effect on autophagy even without inflammatory activity. Understanding the cellular and molecular bases of overnutrition is essential for identifying new diagnostic and therapeutic targets for obesity.

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

Controle autonomico da frequencia cardiaca de adolescentes em treinamento

Universidade Estadual de Campinas . Faculdade de Educação Física