Cortisol and C-Reactive Protein Vary During Sleep Loss and Recovery but Are Not Markers of Neurobehavioral Resilience

Nutraceutical blends predict enhanced health via microbiota reshaping improving cytokines and life quality: a Brazilian double-blind randomized trial

Nutraceutical interventions supporting microbiota and eliciting clinical improvements in metabolic diseases have grown significantly. Chronic stress, gut dysbiosis, and metainflammation have emerged as key factors intertwined with sleep disorders, consequently exacerbating the decline in quality of life. This study aimed to assess the effects of two nutraceutical formulations containing prebiotics (fructooligosaccharides (FOS), galactooligosaccharides (GOS), yeast β-glucans), minerals (Mg, Se, Zn), and the herbal medicine Silybum marianum L. Gaertn., Asteraceae (Milk thistle or Silymarin). These formulations, namely NSupple (without silymarin) and NSupple_Silybum (with silymarin) were tested over 180 days in overweight/obese volunteers from Brazil's southeastern region. We accessed fecal gut microbiota by partial 16S rRNA sequences; cytokines expression by CBA; anthropometrics, quality of life and sleep, as well as metabolic and hormonal parameters, at baseline (T0) and 180 days (T180) post-supplementation. Results demonstrated gut microbiota reshaping at phyla, genera, and species level post-supplementation. The Bacteroidetes phylum, Bacteroides, and Prevotella genera were positively modulated especially in the NSupple_Silybum group. Gut microbiota modulation was associated with improved sleep patterns, quality-of-life perception, cytokines expression, and anthropometric parameters post-supplementation. Our findings suggest that the nutraceutical blends positively enhance cardiometabolic and inflammatory markers. Particularly, NSupple_Silybum modulated microbiota composition, underscoring its potential significance in ameliorating metabolic dysregulation. Clinical trial registry number: NCT04810572. 23/03/2021.

The Relationship Between Mental Fatigue and Shooting Performance Over the Course of a National Collegiate Athletic Association Division I Basketball Season

ABSTRACT

Daub, BD, McLean, BD, Heishman, AD, Peak, KM, and Coutts, AJ. The relationship between mental fatigue and shooting performance over the course of a National Collegiate Athletic Association Division I basketball season. J Strength Cond Res 38(2): 334-341, 2024-The aim of this investigation was to examine the presence of mental fatigue and concurrent changes in shooting performance across various experimental weeks throughout a National Collegiate Athletic Association (NCAA) basketball season. Fifteen elite male NCAA Division I collegiate basketball players (age 20.2 ± 1.2 years, height 199.3 ± 7.1 cm, and body mass 93.1 ± 8.6 kg) volunteered for this study. Mental fatigue and basketball shooting performance was evaluated at 4 timepoints with varying seasonal demands: high game volume (GAME), high academic load (ACADEMIC), no games and no academic load (PRACTICE), and standard number of games and academic requirements (TYPICAL). Subjective mental fatigue increased significantly ( p ≤ 0.05) from Pre to Post brief psychomotor vigilance test (PVT-B) measurements at the end of the ACADEMIC week ( p = 0.002, d = 1.51) and from beginning to end of the ACADEMIC week ( p < 0.001, d = 2.21). Ratings of mental effort were significantly increased during the ACADEMIC week ( p < 0.001, d = 1.67). Recovery stress questionnaire (REST-Q) showed significant differences between week GAME and ACADEMIC with an increase in Social Stress ( p = 0.001, d = 0.84), Fatigue ( p = 0.021, d = 1.12), Disturbed Breaks ( p = 0.024, d = 0.57), and Emotional Exhaustion ( p = 0.035, d = 0.75). Lower shooting performance was observed during the ACADEMIC week from Pre to Post ( p = 0.009, d = 0.35) and higher scores Pre to Post in the TYPICAL week ( p = 0.008, d = 0.25). Basketball shooting performance was significantly reduced after increased levels of mental fatigue stemming from added academic stress. In addition, an increase in sport-specific training or games had no effect on subsequent basketball shooting performance. Special consideration should be given by coaches around examination periods because the existence of academic stressors can influence basketball shooting performance.

Sleep Quality and Evening Salivary Cortisol Levels in Association with the Psychological Resources of Parents of Children with Developmental Disorders and Type 1 Diabetes

BACKGROUND

Sleep deprivation can decrease parental well-being and degrade mental and physical health in parents of children with chronic illness. The aim of this study was to explore the associations of sleep quality, psychological stress perception, and evening salivary cortisol concentration with self-esteem, optimism and happiness in parents of children with type 1 diabetes and developmental disorders compared to parents of healthy, typically developing children.

METHODS

We studied 196 parents of children with chronic conditions, including autistic spectrum disorder (N = 33), cerebral palsy (N = 18), Down syndrome (N = 33), and diabetes mellitus type 1 (N = 40) and parents of healthy children (N = 72). We evaluated parental sleep quality, evening salivary cortisol levels, self-esteem, optimism and happiness. Multiple linear regression models were used to assess associations between variables.

RESULTS

Compared with those of the control group, the parents of children with autistic spectrum disorders had higher evening cortisol concentrations (β = 0.17; p = 0.038) and lower perceptions of happiness (β=-0.17; p = 0.017), while parents of children with type 1 diabetes had disrupted sleep quality (β = 0.25; p = 0.003). Optimism was negatively associated with the evening cortisol concentration (β=-0.18; p = 0.023) and sleep quality index (β=-0.20; p = 0.012).

CONCLUSIONS

Public health programs aimed at lifestyle habit improvement, respite care, and relaxation for parents of children with chronic conditions would be useful for improving parental sleep quality, self-esteem, optimism and happiness.

Short-term and long-term phenotypic stability of actigraphic sleep metrics involving repeated sleep loss and recovery

For the first time, we determined whether actigraphic-assessed sleep measures show inter-individual differences and intra-individual stability during baseline (BL) and recovery (REC) phases surrounding repeated total sleep deprivation (TSD). We conducted a 5-day experiment at Months 2 and 4 in two separate studies (N = 11). During each experiment, sleep measures were collected via wrist actigraphy during two BL 8 h time-in-bed (TIB) nights (B1, B2) and during two REC 8-10 h TIB nights (R1, R2). Intraclass correlation coefficients (ICCs) assessed actigraphic measure long-term stability between 2 and 4 months for (1) the pre-experimental phase before BL; and (2) the BL (B1 + B2), REC (R1 + R2), and BL and REC average (BL + REC) phases; and short-term stability at Month 2 and at Month 4; and (3) between B1 versus B2 and R1 versus R2 in each 5-day experiment. Nearly all ICCs during the pre-experimental, BL, REC, and BL + REC phases were moderate to almost perfect (0.446-0.970) between Months 2 and 4. B1 versus B2 ICCs were more stable (0.440-0.899) than almost all R1 versus R2 ICCs (-0.696 to 0.588) at Month 2 and 4. Actigraphic sleep measures show phenotypic long-term stability during BL and REC surrounding repeated TSD between 2 and 4 months. Furthermore, within each 5-day experiment at Month 2 and 4, the two BL nights before TSD were more stable than the two REC nights following TSD, likely due to increased R1 homeostatic pressure. Given the consistency of actigraphic measures across the short-term and long-term, they can serve as biomarkers to predict physiological and neurobehavioral responses to sleep loss.

Impact of bimonthly repeated total sleep deprivation and recovery sleep on cardiovascular indices

Since short sleep duration adversely affects cardiovascular (CV) health, we investigated the effects of exposures to total sleep deprivation (TSD), and baseline (BL) and recovery (REC) sleep on CV measures. We conducted a 5-day experiment at months 2 and 4 in two separate studies (N = 11 healthy adults; 5 females). During these repeated experiments, CV measures [stroke volume (SV), cardiac index (CI), systemic vascular resistance index (SVRI), left ventricular ejection time, heart rate (HR), systolic and diastolic blood pressure (SBP and DBP) and mean arterial pressure (MAP)] were collected at three assessment time points after: (1) two BL 8 h time-in-bed (TIB) sleep opportunity nights; (2) a TSD night; and (3) two REC 8-10 h TIB nights. CV measures were also collected pre-study. TSD significantly increased SV and CI, and decreased SVRI, with large effect sizes, which importantly were reversed with recovery, indicating these measures are possible novel biomarkers for assessing the adverse consequences of TSD. Pre-study SV, CI, SVRI, HR, SBP, and MAP measures also significantly associated with TSD CV responses at months 2 and 4 [Pearson's r: 0.615-0.862; r2 : 0.378-0.743], indicating they are robust correlates of future TSD CV responses. Our novel findings highlight the critical impact of sleep on CV health across time.

Sleep and memory: The impact of sleep deprivation on transcription, translational control, and protein synthesis in the brain

In countries around the world, sleep deprivation represents a widespread problem affecting school-age children, teenagers, and adults. Acute sleep deprivation and more chronic sleep restriction adversely affect individual health, impairing memory and cognitive performance as well as increasing the risk and progression of numerous diseases. In mammals, the hippocampus and hippocampus-dependent memory are vulnerable to the effects of acute sleep deprivation. Sleep deprivation induces changes in molecular signaling, gene expression and may cause changes in dendritic structure in neurons. Genome wide studies have shown that acute sleep deprivation alters gene transcription, although the pool of genes affected varies between brain regions. More recently, advances in research have drawn attention to differences in gene regulation between the level of the transcriptome compared with the pool of mRNA associated with ribosomes for protein translation following sleep deprivation. Thus, in addition to transcriptional changes, sleep deprivation also affects downstream processes to alter protein translation. In this review, we focus on the multiple levels through which acute sleep deprivation impacts gene regulation, highlighting potential post-transcriptional and translational processes that may be affected by sleep deprivation. Understanding the multiple levels of gene regulation impacted by sleep deprivation is essential for future development of therapeutics that may mitigate the effects of sleep loss.

The 3-Minute Psychomotor Vigilance Test Demonstrates Inadequate Convergent Validity Relative to the 10-Minute Psychomotor Vigilance Test Across Sleep Loss and Recovery

The Psychomotor Vigilance Test (PVT) is a widely used behavioral attention measure, with the 10-min (PVT-10) and 3-min (PVT-3) as two commonly used versions. The PVT-3 may be comparable to the PVT-10, though its convergent validity relative to the PVT-10 has not been explicitly assessed. For the first time, we utilized repeated measures correlation (rmcorr) to evaluate intra-individual associations between PVT-10 and PVT-3 versions across total sleep deprivation (TSD), chronic sleep restriction (SR) and multiple consecutive days of recovery. Eighty-three healthy adults (mean ± SD, 34.7 ± 8.9 years; 36 females) received two baseline nights (B1-B2), five SR nights (SR1-SR5), 36 h TSD, and four recovery nights (R1-R4) between sleep loss conditions. The PVT-10 and PVT-3 were completed every 2 h during wakefulness. Rmcorr compared responses on two frequently used, sensitive PVT metrics: reaction time (RT) via response speed (1/RT) and lapses (RT > 500 ms on the PVT-10 and > 355 ms on the PVT-3) by day (e.g., B2), by study phase (e.g., SR1-SR5), and by time point (1000-2000 h). PVT 1/RT correlations were generally stronger than those for lapses. The majority of correlations (48/50 [96%] for PVT lapses and 38/50 [76%] for PVT 1/RT) were values below 0.70, indicating validity issues. Overall, the PVT-3 demonstrated inadequate convergent validity with the "gold standard" PVT-10 across two different types of sleep loss and across extended recovery. Thus, the PVT-3 is not interchangeable with the PVT-10 for assessing behavioral attention performance during sleep loss based on the design of our study and the metrics we evaluated. Our results have substantial implications for design and measure selection in laboratory and applied settings, including those involving sleep deprivation.