Sleep and Biological Rhythms最新文献

This study investigated the association between common mental disorders (CMD) and sleep parameters measured objectively through actigraphy, as well as using self-reported data, among female shift workers in southern Brazil. This cross-sectional study involved 450 female participants, with 278 undergoing actigraphy. CMD was assessed using a Self-Reporting Questionnaire (SRQ-20), while self-reported sleep disturbance was measured using the Pittsburgh Sleep Quality Index (PSQI) scale. Actigraphy was utilized to measure sleep quality over a consecutive 48-h period. The odds ratios (OR) and 95% confidence intervals (CI) were estimated using multinomial logistic regression. The prevalence of sleep disturbance was 9.7% (95% CI 7.2-12.9) according to the PSQI, while CMD prevalence was 47.3% (95% CI 42.6-52.1) in the entire sample. Sleep disturbance was significantly associated with positive CMD screening (OR = 20.03; 95% CI 7.22-55.54) as well as with night shift work (OR = 5.38; 95% CI 1.75-16.52). CMD did not exhibit a statistically significant association with objective sleep quality parameters measured using actigraphy. However, adjusted analysis of sleep efficiency revealed that women on the afternoon (OR = 3.09; 95% CI 1.53-6.25) or night shifts (OR = 3.43; 95% CI 1.60-7.35) had a higher prevalence of 10 or more awakenings during sleep compared to those working morning shifts. This study highlights the high prevalence of CMD among female shift workers. Furthermore, CMD demonstrated a statistically significant association with self-reported sleep disorders within this population group. However, this association was not observed when compared with objective data collected by actigraphy.

Long-term shift work significantly impacts the health of healthcare workers, with sleep disorders (SD) being a common and urgent concern. Traditional predictive models often perform poorly in identifying minority class samples-specifically healthcare workers experiencing SD-due to dataset imbalances. This study aimed to construct a risk warning model by introducing the synthetic minority over-sampling technique (SMOTE) to improve the predictive accuracy for SD among healthcare workers engaged in long-term shift work, providing a scientific basis for early intervention. A retrospective analysis was conducted on the sleep conditions of 181 healthcare workers at CR&WISCO General Hospital, Wuhan University of Science and Technology. Participants were divided into two groups based on their sleep status: 70 individuals in group A (AG) with SD, and 111 individuals in group B (BG) without SD. The application of the SMOTE-based risk warning model was analyzed for predicting SD in healthcare workers under long-term shift work, and the model's performance was validated against two other models and three verification datasets. Multivariate logistic regression analysis of SD among healthcare workers under long-term shift work revealed that gender, age, occupation, education level, professional title, authorization strength, shift duration, work hours, anxiety, and depression were identified as independent influencing factors. The SMOTE warning model achieved a sensitivity of 83.22%, specificity of 78.67%, accuracy of 85.35%, positive predictive value (PPV) of 74.60%, and negative predictive value (NPV) of 87.67%, significantly outperforming the original dataset, backpropagation (BP) model, and the random forest (RF) model (P < 0.05). ROC curve analysis showed an AUC value of 0.85 for the SMOTE-processed data, indicating superior predictive performance of the SMOTE-based warning model. The SMOTE-based risk warning model effectively enhances the prediction of SD in healthcare workers engaged in long-term shift work, demonstrating significant clinical applicability. This finding not only contributes to improving the health management of healthcare workers but also provides a reference model for similar issues in other fields.

Supplementary information: The online version contains supplementary material available at 10.1007/s41105-025-00583-y.

[This corrects the article DOI: 10.1007/s41105-024-00562-9.].

Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive decline in cognitive function and emotional disturbances. The amygdala is an important connectivity structure in the brain and is responsible for emotional responses. 5-HT is involved in various neurodevelopmental processes in the brain. In this study, correlation study of 5-HT in brain with cognitive function and anxious-like behavior was investigated in APP/PS1 transgene mice. Multiple behavioral tests were performed to examine the cognitive function and anxiety behavior of AD mice. In vivo hippocampus long-term potentiation (LTP) was recorded to reflect synaptic plasticity. 5-HT levels in hippocampus and amygdala were determined. Further, we explored the correlation between 5-HT levels in hippocampus and amygdala and long-term cognitive behaviors and anxiety behaviors in the AD mice using linear regression analysis. Our results demonstrated that there was close linear correlation between 5-HT level in brain and spatial cognition and anxiety behavior of APP/PS1 transgene mice. 5-HT influences spatial learning and memory by regulating the synaptic plasticity in hippocampus of APP/PS1 transgenic mice. These results indicate that 5-HT might be potentially beneficial in the treatment of AD.

Sleep disorders and osteoporosis frequently co-occur in the elderly, especially among those living at high altitudes. This study aimed to investigate the association between sleep disorders and osteoporosis among elderly residents of high-altitude regions in China. We conducted a cross-sectional analysis from January 2021 to January 2023, enrolling 160 elderly participants aged 60 years and older from high-altitude areas. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI), and osteoporosis was diagnosed using dual-energy X-ray absorptiometry (DEXA). Demographic data, blood parameters, and pulmonary artery pressure were collected. Statistical analyses included descriptive statistics, correlation analysis, and logistic regression to determine the independent association between sleep disorders and osteoporosis, adjusting for potential confounders. Osteoporosis was prevalent in 65% of the participants, with 75% of those also having sleep disorders. A significant negative correlation was found between sleep quality and bone density (ρ = -0.65, P < 0.001), suggesting a positive relationship between the severity of sleep disorders and the risk of osteoporosis. Multivariate logistic regression analysis revealed a significant association between sleep disorders and the presence of osteoporosis (OR = 1.67, 95% CI: 1.20-2.20, P = 0.001). Subgroup analyses showed stronger associations in females (OR = 2.20, 95% CI: 1.50-3.20, P < 0.001) and participants aged over 70 years (OR = 2.00, 95% CI: 1.30-3.10, P = 0.002). Significant correlations were also observed in participants with oxygen saturation below 85% (OR = 2.50, 95% CI: 1.60-3.90, P < 0.001) and those with elevated pulmonary artery pressure (OR = 2.80, 95% CI: 1.80-4.30, P < 0.001). Sleep disorders are significantly associated with osteoporosis in the elderly at high altitudes, with physiological variables in this environment potentially exacerbating this relationship.

Recent research has identified the mitochondrial open reading frame of the 12S rRNA-c (MOTS-c) as a crucial mitochondrial peptide that significantly influences metabolic regulation, mimics the effects of exercise, and mitigates oxidative stress. This study aims to investigate the relationship between serum MOTS-c levels and obstructive sleep apnea (OSA) to enhance our understanding of the disease's pathophysiology. By elucidating this relationship, we hope to uncover new insights into the mechanisms underlying OSA and its associated metabolic complications. Seventy-seven participants were enrolled in this study, including 53 patients with OSA and 24 controls. We measured serum MOTS-c levels and collected participants' demographic characteristics, polysomnography (PSG) data, complete blood count (CBC) data, and sleep-related questionnaires. The study included 77 participants, consisting of 8 patients with mild OSA, 16 with moderate OSA, 29 with severe OSA, and 24 controls. The cohort comprised 26 women and 51 men. Analysis revealed that serum MOTS-c levels were significantly correlated with BMI, AHI (Apnea-Hypopnea Index), and ODI (Oxygen Desaturation Index), independent of age. Additionally, the severity of OSA was inversely related to serum MOTS-c levels, with lower levels observed in patients with more severe OSA. Variations in serum MOTS-c levels were also noted across different BMI classifications. Analysis of covariance (ANCOVA), with BMI as a covariate, demonstrated that the severity of OSA was an independent factor influencing serum MOTS-c levels. Serum MOTS-c levels correlate with both severity of OSA and BMI classification, suggesting that MOTS-c may have significant therapeutic potential for treating OSA.

Circular RNAs (circRNAs) participate in diverse biological processes. However, whether circRNAs exhibit distinct expression patterns under obstructive sleep apnea (OSA)-induced chronic intermittent hypoxia (CIH) remains unexplored. We conducted RNA sequencing to compare expression profiles between CIH rats (n = 4) and normoxic controls (n = 4), identifying differentially expressed (DE) circRNAs. After filtering candidate circRNAs, we validated their expression in four OSA patients and four controls using qRT-PCR. Principal component analysis (PCA) was employed to confirm the diagnostic potential of these circRNAs. The miRanda software predicted target microRNAs (miRNAs), and the circRNA-miRNA regulatory network was visualized using Cytoscape software. In total, we identified 43 DE circRNAs, primarily enriched in functions like protein binding, cytoskeleton organization, and supramolecular complexes. We selected eight DE circRNAs associated with CIH for validation in OSA patients (n = 4) and controls (n = 4), with five displaying significant expression differences. These eight circRNAs showed distinct expression patterns between CIH and control groups, suggesting potential utility in distinguishing CIH conditions. Notably, our analysis identified mir-466b-3p as associated with DE circRNAs in the context of CIH. In conclusion, this study described circRNA expression profiles in CIH rats and identified several circRNAs with altered expression in CIH conditions. These findings suggest areas for further research into the relationship between circRNA expression and CIH.

Supplementary information: The online version contains supplementary material available at 10.1007/s41105-025-00577-w.