A Novel Approach for Multichannel Epileptic Seizure Classification Based on Internet of Things Framework Using Critical Spectral Verge Feature Derived from Flower Pollination Algorithm

A novel approach for multichannel epilepsy seizure classification which will help to automatically locate seizure activity present in the focal brain region was proposed. This paper suggested an Internet of Things (IoT) framework based on a smart phone by utilizing a novel feature termed multiresolution critical spectral verge (MCSV), based on frequency-derived information for epileptic seizure classification which was optimized using a flower pollination algorithm (FPA). A wireless sensor technology (WSN) was utilized to record the electroencephalography (EEG) signal of epileptic patients. Next, the EEG signal was pre-processed utilizing a multiresolution-based adaptive filtering (MRAF) method. Then, the maximal frequency point at which the power spectral density (PSD) of each EEG segment was greater than the average spectral power of the corresponding frequency band was computed. This point was further optimized to extract a point termed as critical spectral verge (CSV) to extract the exact high frequency oscillations representing the actual seizure activity present in the EEG signal. Next, a support vector machine (SVM) classifier was used for channel-wise classification of the seizure and non-seizure regions using CSV as a feature. This process of classification using the CSV feature extracted from the MRAF output is referred to as the MCSV approach. As a final step, cloud-based services were employed to analyze the EEG information from the subject’s smart phone. An exhaustive analysis was undertaken to assess the performance of the MCSV approach for two datasets. The presented approach showed an improved performance with a 93.83% average sensitivity, a 97.94% average specificity, a 97.38% average accuracy with the SVM classifier, and a 95.89% average detection rate as compared with other state-of-the-art studies such as deep learning. The methods presented in the literature were unable to precisely localize the origination of the seizure activity in the brain region and reported a low seizure detection rate. This work introduced an optimized CSV feature which was effectively used for multichannel seizure classification and localization of seizure origination. The proposed MCSV approach will help diagnose epileptic behavior from multichannel EEG signals which will be extremely useful for neuro-experts to analyze seizure details from different regions of the brain

Nanoliposomal Nitroglycerin Exerts Potent Anti-Inflammatory Effects

Nitroglycerin (NTG) markedly enhances nitric oxide (NO) bioavailability. However, its ability to mimic the anti-inflammatory properties of NO remains unknown. Here, we examined whether NTG can suppress endothelial cell (EC) activation during inflammation and developed NTG nanoformulation to simultaneously amplify its anti-inflammatory effects and ameliorate adverse effects associated with high-dose NTG administration. Our findings reveal that NTG significantly inhibits human U937 cell adhesion to NO-deficient human microvascular ECs in vitro through an increase in endothelial NO and decrease in endothelial ICAM-1 clustering, as determined by NO analyzer, microfluorimetry, and immunofluorescence staining. Nanoliposomal NTG (NTG-NL) was formulated by encapsulating NTG within unilamellar lipid vesicles (DPhPC, POPC, Cholesterol, DHPE-Texas Red at molar ratio of 6:2:2:0.2) that were ~155 nm in diameter and readily uptaken by ECs, as determined by dynamic light scattering and quantitative fluorescence microscopy, respectively. More importantly, NTG-NL produced a 70-fold increase in NTG therapeutic efficacy when compared with free NTG while preventing excessive mitochondrial superoxide production associated with high NTG doses. Thus, these findings, which are the first to reveal the superior therapeutic effects of an NTG nanoformulation, provide the rationale for their detailed investigation for potentially superior vascular normalization therapies