Genetic Approaches to Hypothalamic-Pituitary-Adrenal Axis Regulation

The normal function of the hypothalamic-pituitary-adrenal (HPA) axis, and resultant glucocorticoid (GC) secretion, is essential for human health. Disruption of GC regulation is associated with pathologic, psychological, and physiological disease states such as depression, post-traumatic stress disorder, hypertension, diabetes, and osteopenia, among others. As such, understanding the mechanisms by which HPA output is tightly regulated in its responses to environmental stressors and circadian cues has been an active area of investigation for decades. Over the last 20 years, however, advances in gene targeting and genome modification in rodent models have allowed the detailed dissection of roles for key molecular mediators and brain regions responsible for this control in vivo to emerge. Here, we summarize work done to elucidate the function of critical neuropeptide systems, GC-signaling targets, and inflammation-associated pathways in HPA axis regulation and behavior, and highlight areas for future investigation.     

Extended Kalman smoother with differential evolution technique for denoising of ECG signal

Electrocardiogram (ECG) signal gives a lot of information on the physiology of heart. In reality, noise from various sources interfere with the ECG signal. To get the correct information on physiology of the heart, noise cancellation of the ECG signal is required. In this paper, the effectiveness of extended Kalman smoother (EKS) with the differential evolution (DE) technique for noise cancellation of the ECG signal is investigated. DE is used as an automatic parameter selection method for the selection of ten optimized components of the ECG signal, and those are used to create the ECG signal according to the real ECG signal. These parameters are used by the EKS for the development of the state equation and also for initialization of the parameters of EKS. EKS framework is used for denoising the ECG signal from the single channel. The effectiveness of proposed noise cancellation technique has been evaluated by adding white, colored Gaussian noise and real muscle artifact noise at different SNR to some visually clean ECG signals from the MIT-BIH arrhythmia database. The proposed noise cancellation technique of ECG signal shows better signal to noise ratio (SNR) improvement, lesser mean square error (MSE) and percent of distortion (PRD) compared to other well-known methods.