Generation of a Commercial-Scale Founder Population of Porcine Reproductive and Respiratory Syndrome Virus Resistant Pigs Using CRISPR-Cas.

Disease resistance genes in livestock provide health benefits to animals and opportunities for farmers to meet the growing demand for affordable, high-quality protein. Previously, researchers used gene editing to modify the porcine CD163 gene and demonstrated resistance to a harmful virus that causes porcine reproductive and respiratory syndrome (PRRS). To maximize potential benefits, this disease resistance trait needs to be present in commercially relevant breeding populations for multiplication and distribution of pigs.

Functionally Adaptive Myosite Selection Using High-Density sEMG for Upper Limb Myoelectric Prostheses.

Objective: Our study defines a novel electrode placement method called Functionally Adaptive Myosite Selection (FAMS), as a tool for rapid and effective electrode placement during prosthesis fitting. We demonstrate a method for determining electrode placement that is adaptable towards individual patient anatomy and desired functional outcomes, agnostic to the type of classification model used, and provides insight into expected classifier performance without training multiple models.

Methods: FAMS relies on a separability metric to rapidly predict classifier performance during prosthesis fitting.

Stable Responsive EMG Sequence Prediction and Adaptive Reinforcement With Temporal Convolutional Networks.

Unlabelled: Prediction of movement intentions from electromyographic (EMG) signals is typically performed with a pattern recognition approach, wherein a short dataframe of raw EMG is compressed into an instantaneous feature-encoding that is meaningful for classification. However, EMG signals are time-varying, implying that a frame-wise approach may not sufficiently incorporate temporal context into predictions, leading to erratic and unstable prediction behavior.

Objective: We demonstrate that sequential prediction models and, specifically, temporal convolutional networks are able to leverage useful temporal information from EMG to achieve superior predictive performance.

Prosthesis with neuromorphic multilayered e-dermis perceives touch and pain.

The human body is a template for many state-of-the-art prosthetic devices and sensors. Perceptions of touch and pain are fundamental components of our daily lives that convey valuable information about our environment while also providing an element of protection from damage to our bodies. Advances in prosthesis designs and control mechanisms can aid an amputee's ability to regain lost function but often lack meaningful tactile feedback or perception.