Farhad Imani

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RATIONALE Respiratory syncytial virus (RSV) is the most frequent cause of significant lower respiratory illness in infants and young children, but its pathogenesis is not fully understood. The transcription factor Nrf2 protects lungs from oxidative injury and inflammation via antioxidant response element (ARE)-mediated gene induction. OBJECTIVES The(More)
Respiratory syncytial virus (RSV) is the major cause of viral respiratory infections in children. Our previous study showed that the RSV infection induced lung epithelial cell cycle arrest, which enhanced virus replication. To address the mechanism of RSV-induced cell cycle arrest, we examined the contribution of RSV-matrix (RSV-M) protein. In this report,(More)
Ultrasound (US) radio-frequency (RF) time series is an effective tissue classification method that enables accurate cancer diagnosis, but the mechanisms underlying this method are not completely understood. This paper presents a model to describe the variations in tissue temperature and sound speed that take place during the RF time series scanning(More)
PURPOSE This paper is the first report on the monitoring of tissue ablation using ultrasound RF echo time series. METHODS We calcuate frequency and time domain features of time series of RF echoes from stationary tissue and transducer, and correlate them with ablated and non-ablated tissue properties. RESULTS We combine these features in a nonlinear(More)
During viral infections, single- and double-stranded RNA (ssRNA and dsRNA) are recognized by the host and induce innate immune responses. The cellular enzyme ADAR-1 (adenosine deaminase acting on RNA-1) activation in virally infected cells leads to presence of inosine-containing RNA (Ino-RNA). Here we report that ss-Ino-RNA is a novel viral recognition(More)
PURPOSE This paper presents the results of a large study involving fusion prostate biopsies to demonstrate that temporal ultrasound can be used to accurately classify tissue labels identified in multi-parametric magnetic resonance imaging (mp-MRI) as suspicious for cancer. METHODS We use deep learning to analyze temporal ultrasound data obtained from 255(More)
In surface-based registration for image-guided interventions, the presence of missing data can be a significant issue. This often arises with real-time imaging modalities such as ultrasound, where poor contrast can make tissue boundaries difficult to distinguish from surrounding tissue. Missing data poses two challenges: ambiguity in establishing(More)
A discrete event simulation model was developed to represent the current vehicle axle and spring assembly lines and understand their dynamics for an automotive company in need of production increase to accommodate expected demand growth. The aim of this study is to provide viable manufacturing plans to improve productivity, and we propose several(More)