Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Life Sciences
Small Molecule Modulation Of Microbiota: A Systems Pharmacology Perspective, Qiao Liu, Bohyun Lee, Lei Xie
Small Molecule Modulation Of Microbiota: A Systems Pharmacology Perspective, Qiao Liu, Bohyun Lee, Lei Xie
Publications and Research
Background
Microbes are associated with many human diseases and influence drug efficacy. Small-molecule drugs may revolutionize biomedicine by fine-tuning the microbiota on the basis of individual patient microbiome signatures. However, emerging endeavors in small-molecule microbiome drug discovery continue to follow a conventional “one-drug-one-target-one-disease” process. A systematic pharmacology approach that would suppress multiple interacting pathogenic species in the microbiome, could offer an attractive alternative solution.
Results
We construct a disease-centric signed microbe–microbe interaction network using curated microbe metabolite information and their effects on host. We develop a Signed Random Walk with Restart algorithm for the accurate prediction of effect of microbes …
Positive Rate-Dependent Action Potential Prolongation By Modulating Potassium Ion Channels, Candido Cabo
Positive Rate-Dependent Action Potential Prolongation By Modulating Potassium Ion Channels, Candido Cabo
Publications and Research
Pharmacological agents that prolong action potential duration (APD) to a larger extent at slow rates than at the fast excitation rates typical of ventricular tachycardia exhibit reverse rate dependence. Reverse rate dependence has been linked to the lack of efficacy of class III agents at preventing arrhythmias because the doses required to have an anti-arrhythmic effect at fast rates may have pro-arrhythmic effects at slow rates due to an excessive APD prolongation. In this report we show that, in computer models of the ventricular action potential, APD prolongation by accelerating phase 2 repolarization (by increasing IKs) and decelerating …
Emotion Recognition With Audio, Video, Eeg, And Emg: A Dataset And Baseline Approaches, Jin Chen, Tony Ro, Zhigang Zhu
Emotion Recognition With Audio, Video, Eeg, And Emg: A Dataset And Baseline Approaches, Jin Chen, Tony Ro, Zhigang Zhu
Publications and Research
This paper describes a new posed multimodal emotional dataset and compares human emotion classification based on four different modalities - audio, video, electromyography (EMG), and electroencephalography (EEG). The results are reported with several baseline approaches using various feature extraction techniques and machine-learning algorithms. First, we collected a dataset from 11 human subjects expressing six basic emotions and one neutral emotion. We then extracted features from each modality using principal component analysis, autoencoder, convolution network, and mel-frequency cepstral coefficient (MFCC), some unique to individual modalities. A number of baseline models have been applied to compare the classification performance in emotion recognition, …