The Effects of a Whole-Food Plant-Based Nutrition Education Program on Blood Pressure and Potassium in Chronic Kidney Disease: A Proof-of-Concept Study.

Background/objectives: Whole-food plant-based diets (WFPBDs) are beneficial in managing hypertension in the general population but have not been well studied in chronic kidney disease (CKD), potentially due to concerns about hyperkalemia. We hypothesized that individuals with CKD 3 or 4 attending a 15-day WFPBD education program would achieve lower blood pressure compared to those who did not, without an increased risk of hyperkalemia.

Methods: This was a pilot trial of 40 subjects with mild-to-moderate CKD and hypertension but without diabetes or proteinuria from a single academic center.

BioPoint: Enhancing Human-Computer Interaction through Single-Site, Multi-Sensor Gesture Recognition.

Advancements in human-computer interaction (HCI) and machine learning are seen as key avenues to help individuals living with upper limb disabilities in accomplishing their activities of daily living. Multi-channel myoelectric systems are a promising approach for HCI due to their intuitive and accurate capture of user intent through muscle activity. However, such systems are still bulky compared to widely accepted smartwatches-like devices and as such pose a challenge for seamless integration into daily life.

Screen Guided Training Does Not Capture Goal-Oriented Behaviours: Learning Myoelectric Control Mappings From Scratch Using Context Informed Incremental Learning.

Human-machine interfaces based on myoelectric signals typically use screen-guided training (SGT) for model calibration, but this approach fails to capture realistic user behaviors. This study evaluates a user-in-the-loop context-informed incremental learning (CIIL) framework, comparing SGT, SGT followed by CIIL adaptation (SGT-A), and a novel zero-shot adaptation (ZS-A) CIIL approach that begins adapting with no prior training. Sixteen participants completed a Fitts' Law targeting task using these control schemes, with performance measured via online throughput and offline classification accuracy.

Dorsal-Ventral Reinforcement Learning Network Connectivity and Incentive-Driven Changes in Random Exploration.

Probabilistic reinforcement learning (RL) tasks assay how individuals make decisions under uncertainty. The use of internal models (model-based) or direct learning from experiences (model-free), and the degree of choice stochasticity across alternatives (i.e.

Evaluation of Co-Developed Strategies to Support Staff of a Mental Health Community Managed Organisation Implement Preventive Care: A Pilot Controlled Trial.

Background: Mental health community managed organisations (CMOs) are well placed to provide preventive care, including behaviour change conversations to address smoking, nutrition, alcohol and physical activity (snap). This study evaluates the impact of co-developed preventive care implementation support strategies, including Healthy Conversation Skills (HCS) training on CMO staff attitudes and perceptions relating to preventive care for snap behaviours.

Methods: A non-randomised controlled pilot trial was undertaken (October 2021-May 2022) with two branches of a mental health CMO (n = 1 target; n = 1 control) in NSW, Australia.