Neuromuscular electrical stimulation (NMES) allows activation of muscle fibers in the absence of voluntary force generation. NMES could have the potential to promote muscle homeostasis in the context of muscle disease, but the impacts of NMES on diseased muscle are not well understood. We used the zebrafish Duchenne muscular dystrophy (dmd) mutant and a longitudinal design to elucidate the consequences of NMES on muscle health. We designed four neuromuscular stimulation paradigms loosely based on weightlifting regimens. Each paradigm differentially affected neuromuscular structure, function, and survival. Only endurance neuromuscular stimulation (eNMES) improved all outcome measures. We found that eNMES improves muscle and neuromuscular junction morphology, swimming, and survival. Heme oxygenase and integrin alpha7 are required for eNMES-mediated improvement. Our data indicate that neuromuscular stimulation can be beneficial, suggesting that the right type of activity may benefit patients with muscle disease.

Introduction Sleep disorder is often the first symptom of age-related cognitive decline associated with Alzheimer’s disease (AD) observed in primary care. The relationship between sleep and early AD was examined using a patented sleep mattress designed to record respiration and high frequency movement arousals. A machine learning algorithm was developed to classify sleep features associated with early AD. Method Community-dwelling older adults (N = 95; 62–90 years) were recruited in a 3-h catchment area. Study participants were tested on the mattress device in the home bed for 2 days, wore a wrist actigraph for 7 days, and provided sleep diary and sleep disorder self-reports during the 1-week study period. Neurocognitive testing was completed in the home within 30-days of the sleep study. Participant performance on executive and memory tasks, health history and demographics were reviewed by a geriatric clinical team yielding Normal Cognition (n = 45) and amnestic MCI-Consensus (n = 33) groups. A diagnosed MCI group (n = 17) was recruited from a hospital memory clinic following diagnostic series of neuroimaging biomarker assessment and cognitive criteria for AD. Results In cohort analyses, sleep fragmentation and wake after sleep onset duration predicted poorer executive function, particularly memory performance. Group analyses showed increased sleep fragmentation and total sleep time in the diagnosed MCI group compared to the Normal Cognition group. Machine learning algorithm showed that the time latency between movement arousals and coupled respiratory upregulation could be used as a classifier of diagnosed MCI vs. Normal Cognition cases. ROC diagnostics identified MCI with 87% sensitivity; 89% specificity; and 88% positive predictive value. Discussion AD sleep phenotype was detected with a novel sleep biometric, time latency, associated with the tight gap between sleep movements and respiratory coupling, which is proposed as a corollary of sleep quality/loss that affects the autonomic regulation of respiration during sleep. Diagnosed MCI was associated with sleep fragmentation and arousal intrusion.

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Abstract-This study investigates the efficiency of a new method of powering remote sensors by the means of wireless energy transfer. The increased use of sensors for data collection comes with the inherent cost of supplying power from sources such as power cables or batteries. Wireless energy transfer technology eliminates the need for power cables or periodic battery replacement. The time and cost of setting up or expanding a sensor network will be reduced while allowing sensors to be placed in areas where running power cables or battery replacement is not feasible. This paper models wireless channels for power and data separately. Smart scheduling for the data channel is proposed to avoid transmitting data on a noisy channel where the probability of data loss is high to improve power efficiency. Analytical models have been developed and verified using simulations.

INTRODUCTION: Sleep disorder is often the first symptom of age-related cognitive decline in Mild Cognitive Impairment (MCI), or early Alzheimer’s disease. Patient or family sleep complaints in primary care do not reliably lead to screening for sleep or cognitive loss. In this study, poor sleep and arousability were examined using movement arousals, a novel biobehavioral marker of cumulative sleep loss, identified by periodic (circa 4 min) sleep movements (SM). We report that SM events trigger respiratory upregulation (RR) in healthy, but not in MCI-related, sleep. Time latency (TL) between SM-RR events is proposed as a marker of sleep loss and potentially of neurodegeneration associated with cognitive loss in MCI.METHOD. Community-dwelling older adults (N=95; 62-90 years) were tested in the home bed for two days on an “under the sheets” mattress overlay with high sensitivity for respiration and all movement, including micro-movements of SM. Wrist actigraphy (7 days) and standard sleep self-reports were collected as well. A suite of neurocognitive testing identified three groups: Normal Cognition (NC; n=45); clinic diagnosed MCI (MCI-DX; n= 17); and MCI-Consensus determined by an expert panel (MCI-CON; n=33 consensus or pre-clinical MCI) groups.RESULTS: In adjusted cohort analyses, sleep fragmentation (SF) and WASO predicted poorer memory performance selectively. Actigraphy revealed greater sleep latency (SL; p<.008), sleep duration (p<.01) and SF (p=.008) in MCI-DX compared to NC groups. Longer SL and poor sleep were associated with depression which was more prevalent in both MCI groups than NC. Neural Networks AI methods were applied to discriminate MCI and NC cases using the TL metric between SM-RR coupling events. ROC diagnostics were applied which identified MCI vs. NC cases with 87% sensitivity; 89% specificity; and 88% positive predictive value. DISCUSSION: MCI cognitive phenotype was detected with a novel sleep biomarker TL, associated with the tight gap between SM-RR coupling, which is proposed as a corollary of sleep quality/loss that affects the autonomic regulation of respiration during sleep. Movement arousals are less effective in initiating respiratory upregulation in MCI which suggests a potential mechanism for neurodegenerative changes and cognitive loss in early MCI.