A pulsed current-mode class-D low-voltage high-bandwidth power amplifier for portable NMR systems.

Low-field NMR has seen growing interest in recent years, especially for portable applications. The lower homogeneity magnets used for portable applications require short RF pulses to ensure enough transmit bandwidth to excite the sample volume and also support short echo periods. Furthermore, the preferred use of a high-Q coil to improve signal-to-noise ratio (SNR) prolongs the pulse transients.

Patient-specific deep learning model to enhance 4D-CBCT image for radiomics analysis.

4D-CBCT provides phase-resolved images valuable for radiomics analysis for outcome prediction throughout treatment courses. However, 4D-CBCT suffers from streak artifacts caused by under-sampling, which severely degrades the accuracy of radiomic features. Previously we developed group-patient-trained deep learning methods to enhance the 4D-CBCT quality for radiomics analysis, which was not optimized for individual patients.

Transcriptome analysis of collagen VI-related muscular dystrophy muscle biopsies.

Objective: To define the transcriptomic changes responsible for the histologic alterations in skeletal muscle and their progression in collagen VI-related muscular dystrophy (COL6-RD).

Methods: COL6-RD patient muscle biopsies were stratified into three groups based on the overall level of pathologic severity considering degrees of fibrosis, muscle fiber atrophy, and fatty replacement of muscle tissue. Using microarray and RNA-Seq, we then performed global gene expression profiling on the same muscle biopsies and compared their transcriptome with age- and sex-matched controls.

Analytical models of probe dynamics effects on NMR measurements.

This paper provides a detailed analysis of three common NMR probe circuits (untuned, tuned, and impedance-matched) and studies their effects on multi-pulse experiments, such as those based on the Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence. The magnitude of probe dynamics effects on broadband refocusing pulses are studied as a function of normalized RF bandwidth. Finally, the probe circuit models are integrated with spin dynamics simulations to design hardware-specific RF excitation and refocusing pulses for optimizing user-specified metrics such as signal-to-noise ratio (SNR) in grossly inhomogeneous fields.

A GIS-Based Artificial Neural Network Model for Spatial Distribution of Tuberculosis across the Continental United States.

Despite the usefulness of artificial neural networks (ANNs) in the study of various complex problems, ANNs have not been applied for modeling the geographic distribution of tuberculosis (TB) in the US. Likewise, ecological level researches on TB incidence rate at the national level are inadequate for epidemiologic inferences. We collected 278 exploratory variables including environmental and a broad range of socio-economic features for modeling the disease across the continental US.