A preliminary study of the effects of nighttime administration of the serotonin agonist, m-CPP, on sleep architecture and behavior in healthy volunteers

The effects of m-chlorophenylpiperazine (m-CPP) (0.5 mg/kg) on sleep architecture and behavior were examined in six healthy volunteers following a single or oral dose of the drug in a randomized, double-blind, placebo-controlled study, m-CPP reduced total leep time (TST) and sleep efficiency in all subjects. Slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep were decreased and stage 1 sleep was prolonged in a majority of subjects. Prominent behavioral and psychological effects were reported in five out of six subjects following m-CPP (but not following placebo) that interfered with sleep. The sleep disruption and behavioral activation following nighttime administration of m-CPP contrasts with the sedative properties of its parent compound, trazodone, suggesting that the hypnotic effect of trazodone is not related to the agonist profile of its metabolite, m-CPP.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/29486/1/0000572.pd

Evaluating the effect of a digital health intervention to enhance physical activity in people with chronic kidney disease (Kidney BEAM): a multicentre, randomised controlled trial in the UK

BACKGROUND: Remote digital health interventions to enhance physical activity provide a potential solution to improve the sedentary behaviour, physical inactivity, and poor health-related quality of life that are typical of chronic conditions, particularly for people with chronic kidney disease. However, there is a need for high-quality evidence to support implementation in clinical practice. The Kidney BEAM trial evaluated the clinical effect of a 12-week physical activity digital health intervention on health-related quality of life. METHODS: In a single-blind, randomised controlled trial conducted at 11 centres in the UK, adult participants (aged ≥18 years) with chronic kidney disease were recruited and randomly assigned (1:1) to the Kidney BEAM physical activity digital health intervention or a waiting list control group. Randomisation was performed with a web-based system, in randomly permuted blocks of six. Outcome assessors were masked to treatment allocation. The primary outcome was the difference in the Kidney Disease Quality of Life Short Form version 1.3 Mental Component Summary (KDQoL-SF1.3 MCS) between baseline and 12 weeks. The trial was powered to detect a clinically meaningful difference of 3 arbitrary units (AU) in KDQoL-SF1.3 MCS. Outcomes were analysed by an intention-to-treat approach using an analysis of covariance model, with baseline measures and age as covariates. The trial was registered with ClinicalTrials.gov, NCT04872933. FINDINGS: Between May 6, 2021, and Oct 30, 2022, 1102 individuals were assessed for eligibility, of whom 340 participants were enrolled and randomly assigned to the Kidney BEAM intervention group (n=173) or the waiting list control group (n=167). 268 participants completed the trial (112 in the Kidney BEAM group and 156 in the waiting list control group). All 340 randomly assigned participants were included in the intention-to treat population. At 12 weeks, there was a significant improvement in KDQoL-SF.13 MCS score in the Kidney BEAM group (from mean 44·6 AU [SD 10·8] at baseline to 47·0 AU [10·6] at 12 weeks) compared with the waiting list control group (from 46·1 AU [10·5] to 45·0 AU [10·1]; between-group difference of 3·1 AU [95% CI 1·8-4·4]; p<0·0001). INTERPRETATION: The Kidney BEAM physical activity platform is an efficacious digital health intervention to improve mental health-related quality of life in patients with chronic kidney disease. These findings could facilitate the incorporation of remote digital health interventions into clinical practice and offer a potential intervention worthy of investigation in other chronic conditions. FUNDING: Kidney Research UK

Behavioral Biomarkers of Sleepiness

For those endeavoring to develop better methods of measuring/quantifying sleepiness, the “Holy Grail” is a measure that is maximally objective, completely unobtrusive, exquisitely sensitive, and absolutely specific (i.e., varies only as a function of sleepiness). By these criteria, physiological measures (e.g., based on brain activity such as EEG, fMRI, near-infrared spectroscopy, etc.) would appear to hold the most promise. However, from an operational standpoint, the utility of a sleepiness measure is derived not from its ability to sensitively reflect the brain's extant level of sleepiness per se, but from the implications that this level of sleepiness has for the individual's current and near-term ability to safely and efficiently perform operationally-relevant tasks. Thus, an ideal operationally-relevant sleepiness measure is one that is unobtrusively embedded in the actual operational task, and allows sleepiness-related performance deficits to be distinguished from performance deficits due to other causes. Toward this end, we have developed a PVT-derived metric that incorporates the entire distribution of responses within a PVT session, and reflects changes in the pattern of performance that can be used to identify and quantify “state instability”—the putative physiological state that specifically underlies sleepiness-induced performance deficits

Sleep deprivation impairs recognition of specific emotions

Emotional processing is particularly sensitive to sleep deprivation, but research on the topic has been limited and prior studies have generally evaluated only a circumscribed subset of emotion categories. Here, we evaluated the effects of one night of sleep deprivation and a night of subsequent recovery sleep on the ability to identify the six most widely agreed upon basic emotion categories (happiness, surprise, fear, sadness, disgust, anger). Healthy adults (29 males; 25 females) classified a series of 120 standard facial expressions that were computer morphed with their most highly confusable expression counterparts to create continua of expressions that differed in discriminability between emotion categories (e.g., combining 70% happiness+30% surprise; 90% surprise+10% fear). Accuracy at identifying the dominant emotion for each morph was assessed after a normal night of sleep, again following a night of total sleep deprivation, and finally after a night of recovery sleep. Sleep deprivation was associated with significantly reduced accuracy for identifying the expressions of happiness and sadness in the morphed faces. Gender differences in accuracy were not observed and none of the other emotions showed significant changes as a function of sleep loss. Accuracy returned to baseline after recovery sleep. Findings suggest that sleep deprivation adversely affects the recognition of subtle facial cues of happiness and sadness, the two emotions that are most relevant to highly evolved prosocial interpersonal interactions involving affiliation and empathy, while the recognition of other more primitive survival-oriented emotional face cues may be relatively robust against sleep loss. Keywords: Sleep deprivation, Emotion recognition, Facial expression, Perceptio