Abnormal expression of long non-coding RNAs RMRP, CTC-487M23.5, and DGCR5 in the peripheral blood of patients with Bipolar disorder

Long non-coding RNAs (lncRNAs) have been recently considered as one of the regulatory mechanisms of the nervous system. Hence, lncRNAs may be considered diagnostic biomarkers for bipolar disorder (BD). We aimed to investigate the expression of RMRP, CTC-487M23.5, and DGCR5 lncRNAs in bipolar patients. The levels of these three lncRNAs were measured in peripheral blood mononuclear cells (PBMCs) of 50 BD patients and 50 healthy subjects by real-time PCR. Moreover, we performed a ROC curve analysis between the gene expression and some clinical features of BD patients. Significant upregulation of RMRP and CTC-487M23.5 and no significant change in levels of DGCR5 was observed in BD individuals compared with controls. Also, we found upregulation of RMRP and downregulation of CTC-487M23.5 and DGCR5 in females with BD. The areas under the ROC curve (AUC) for RMRP and CTC-487M23.5 lncRNAs were 0.80 and 0.61, respectively. There was no significant correlation between the expression of these three lncRNAs and clinical features in PBMCs of BD patients. These results suggest a role for RMRP and CTC-487M23.5 in the pathogenesis of bipolar disorder. Moreover, the peripheral expression of these two lncRNAs might be beneficial as potential biomarkers for BD.

Design and prototyping of a wristband-type wireless photoplethysmographic device for heart rate variability signal analysis

Heart Rate Variability (HRV) signal analysis provides a quantitative marker of the Autonomic Nervous System (ANS) function. A wristband-type wireless photoplethysmographic (PPG) device was custom-designed to collect and analyze the arterial pulse in the wrist. The proposed device is comprised of an optical sensor to monitor arterial pulse, a signal conditioning unit to filter and amplify the analog PPG signal, a microcontroller to digitize the analog PPG signal, and a Bluetooth module to transfer the data to a smart device. This paper proposes a novel model to represent the PPG signal as the summation of two Gaussian functions. The paper concludes with a verification procedure for HRV signal analysis during sedentary activities.

Rapid Prototyping of a Smart Device-based Wireless Reflectance Photoplethysmograph

This paper presents the design, fabrication, and testing of a wireless heart rate (HR) monitoring device based on photoplethysmography (PPG) and smart devices. PPG sensors use infrared (IR) light to obtain vital information to assess cardiac health and other physiologic conditions. The PPG data that are transferred to a computer undergo further processing to derive the Heart Rate Variability (HRV) signal, which is analyzed to generate quantitative markers of the Autonomic Nervous System (ANS). The HRV signal has numerous monitoring and diagnostic applications. To this end, wireless connectivity plays an important role in such biomedical instruments. The photoplethysmograph consists of an optical sensor to detect the changes in the light intensity reflected from the illuminated tissue, a signal conditioning unit to prepare the reflected light for further signal conditioning through amplification and filtering, a low-power microcontroller to control and digitize the analog PPG signal, and a Bluetooth module to transmit the digital data to a Bluetooth-based smart device such as a tablet. An Android app is then used to enable the smart device to acquire and digitally display the received analog PPG signal in real-time on the smart device. This article is concluded with the prototyping of the wireless PPG followed by the verification procedures of the PPG and HRV signals acquired in a laboratory environment.