Scientific Reports最新文献

The preferred period hypothesis posits a slowing down of motor and perceptual rhythmic preferences with age, both reflecting an increase in the common internal oscillation period. This study further investigates the preferred period hypothesis by improving the measurement of perceptual rhythmic preferences through two tasks, tempo adjustment and tempo judgment, conducted in auditory and visual modalities. The study was conducted with three groups of children (5-6, 8-9, and 11-12 years old), and a group of young adults (21 to 30 years old) during the same time of the day. Correlational analyses show that the relationship between motor and perceptual rhythmic preferences strengthens between childhood and adulthood. Multilevel analyses reveal a general slowing down of motor and perceptual rhythmic preferences, contingent on the task and modality, with distinct trajectories for males and females. Our study indicate that the range of preferred rhythms narrows with age, becoming less variable in young adulthood, at the expense of a single and consistent, default rhythm. In brief, the preferred period appears only in young adults, with no support for the idea of a slowing down of an internal oscillation that would be reflected by both motor and perceptual rhythmic preferences.

Obstructive sleep apnea (OSA) patients have varying degrees of cognitive impairment, but the specific pathogenic mechanism is still unclear. Meanwhile, poor compliance with continuous positive airway pressure (CPAP) in OSA prompts better solutions. This study aimed to identify differentially expressed genes between the non-obese OSA patients and healthy controls, and to explore potential biomarkers associated with cognitive impairment. Cohorts of healthy control (n = 20) and non-obese, treatment-naïve OSA patients (n = 20) were recruited. We collected their peripheral blood mononuclear cells and neutrophils, and their cognitive performances were evaluated by the Montreal Cognitive Assessment (MoCA). The differentially expressed genes were identified by bioinformatic analysis and confirmed by PCR. Imbalanced immune cell proportions were assessed by Cibersort. Biomarkers related to enriched cellular pathways were measured by ELISA. OSA patients showed a significant decline in overall cognitive function and were associated with higher daytime sleepiness scores. Multiple signaling pathways were enriched in the non-obese OSA cohort, including upregulation of neutrophil-degranulation. Increased monocyte proportion and decreased NK cell proportion were figured out. The relevant genes, including upregulated defensin alpha 4 (DEFA4), haptoglobin (HP), survivin (BIRC5), and suppressed interferon gamma (IFNG) expression were detected. The relative expression of DEFA4 was significantly correlated with the MoCA score and sleep parameters. Biomarkers such as myeloperoxidase (MPO), H₂O₂, and lipocalin-2, as representatives of neutrophils' activation, elevated significantly in the OSA group. The data demonstrated a positive correlation between MPO and oxygen desaturation index (ODI) and a negative correlation between MPO and lowest oxygen saturation (LSaO₂). The level of Lipocalin-2 was positively correlated with apnea-hypopnea index (AHI) and ODI and negatively correlated with LSaO₂ and MoCA score. We also observed a negative correlation between H₂O₂ and mean oxygen saturation (MSaO₂). Degranulation of neutrophils was activated in non-obese OSA patients without other complications. The process is related to OSA severity and cognitive impairment, implying its role in pathogenesis.

Programmed cell death (PCD) is a vital biological process that is essential for regulating cell progression and tumor microenvironment. This study aimed to explore the relationship between PCD-related genes expression and prognosis in thyroid cancer (THCA), especially IL20RA, as a potential prognostic marker for THCA. Data from The Cancer Genome Atlas (TCGA) database was utilized to develop a PCD-related risk prediction model based on LASSO regression along with univariate Cox regression. The correlation between PCD-related genes and immune cell infiltration was also assessed. The prognostic value of the key PCD-related gene for THCA was investigated by immunohistochemistry. The immune regulatory function and biological function of the key PCD related molecules were detected by cellular experiments. We identified four PCD-related genes (NPC2, E2F1, IL20RA, and TREM2) and constructed a risk model that exhibited excellent accuracy in predicting the prognosis of THCA. Moreover, we confirmed that high expression of IL20RA related to the poor prognosis of THCA. IL20RA promoted cell proliferation and IL20RA knockdown increased apoptosis and ferroptosis. Analysis of the immune microenvironment and detection of macrophages polarization showed that IL20RA promoted the polarization of M2 macrophages while reducing the polarization of M1. We constructed a prognostic prediction model and identified several PCD-related genes. The function of IL20RA which could potentially provide a foundation for additional investigations into diagnostic markers and treatment targets for THCA.

Internet of Things (IoT) is one of the most important emerging technologies that supports Metaverse integrating process, by enabling smooth data transfer among physical and virtual domains. Integrating sensor devices, wearables, and smart gadgets into Metaverse environment enables IoT to deepen interactions and enhance immersion, both crucial for a completely integrated, data-driven Metaverse. Nevertheless, because IoT devices are often built with minimal hardware and are connected to the Internet, they are highly susceptible to different types of cyberattacks, presenting a significant security problem for maintaining a secure infrastructure. Conventional security techniques have difficulty countering these evolving threats, highlighting the need for adaptive solutions powered by artificial intelligence (AI). This work seeks to improve trust and security in IoT edge devices integrated in to the Metaverse. This study revolves around hybrid framework that combines convolutional neural networks (CNN) and machine learning (ML) classifying models, like categorical boosting (CatBoost) and light gradient-boosting machine (LightGBM), further optimized through metaheuristics optimizers for leveraged performance. A two-leveled architecture was designed to manage intricate data, enabling the detection and classification of attacks within IoT networks. A thorough analysis utilizing a real-world IoT network attacks dataset validates the proposed architecture's efficacy in identification of the specific variants of malevolent assaults, that is a classic multi-class classification challenge. Three experiments were executed utilizing data open to public, where the top models attained a supreme accuracy of 99.83% for multi-class classification. Additionally, explainable AI methods offered valuable supplementary insights into the model's decision-making process, supporting future data collection efforts and enhancing security of these systems.

This study aimed at assessing the mechanical properties and degradation of commercial bioactive materials. The bioactive materials (Activa Bioactive Restorative, Beautifil Flow Plus F00, F03, Predicta Bulk Bioactive) and composite resin Filtek Supreme Flow were submitted to flexural and diametral tensile strength tests (FS, DTS), modulus of elasticity (ME) evaluation, and analysis of aging in 70% ethanol and saliva on their hardness and sorption. The results for DTS ranged from 33.16 MPa (Beautifil Flow Plus F03) to 47.74 MPa (Filtek Supreme Flow). The highest FS was 120.40 MPa (Predicta Bulk Bioactive), while the lowest values were 86.55 MPa (Activa Bioactive Restorative). Activa Bioactive Restorative showed the lowest ME, as well as the highest water sorption both in alcohol and artificial saliva. Moreover, aging in saliva induced a significant decrease in hardness for Activa Restorative (p < .01). Alcohol storage caused a significant decrease in hardness for all materials (p < .0001). All tested materials met the basic requirements for light-curing materials in terms of DTS and FS. However, all materials showed higher sorption in alcohol than in saliva, while hardness decreased significantly after 30 days. Predicta Bulk Bioactive presented the highest mechanical parameters, initial hardness, and the lowest sorption of alcohol and saliva.

Glaucoma poses a growing health challenge projected to escalate in the coming decades. However, current automated diagnostic approaches on Glaucoma diagnosis solely rely on black-box deep learning models, lacking explainability and trustworthiness. To address the issue, this study uses optical coherence tomography (OCT) images to develop an explainable artificial intelligence (XAI) tool for diagnosing and staging glaucoma, with a focus on its clinical applicability. A total of 334 normal and 268 glaucomatous eyes (86 early, 72 moderate, 110 advanced) were included, signal processing theory was employed, and model interpretability was rigorously evaluated. Leveraging SHapley Additive exPlanations (SHAP)-based global feature ranking and partial dependency analysis (PDA) estimated decision boundary cut-offs on machine learning (ML) models, a novel algorithm was developed to implement an XAI tool. Using the selected features, ML models produce an AUC of 0.96 (95% CI: 0.95-0.98), 0.98 (95% CI: 0.96-1.00) and 1.00 (95% CI: 1.00-1.00) respectively on differentiating early, moderate and advanced glaucoma patients. Overall, machine outperformed clinicians in the early stage and overall glaucoma diagnosis with 10.4 -11.2% higher accuracy. The developed user-friendly XAI software tool shows potential as a valuable tool for eye care practitioners, offering transparent and interpretable insights to improve decision-making.

Diffuse idiopathic skeletal hyperostosis (DISH) is a common disease in older adults that causes extensive spinal ankylosis. However, its impact on quality of life (QOL) and locomotive syndrome (LS) remains unknown. Thus, we aimed to evaluate the DISH effect on QOL and LS in community-dwelling middle-aged and older adults. Data of community volunteers who attended a health checkup in 2018-2019 were assessed. A total of 455 subjects were included. Whole spine lateral radiographs were obtained to detect DISH according to the Resnik criteria. QOL was evaluated using SF-36 and EQ5D HUSV. LS was evaluated using the stand-up and two-step tests and GLFS-25. Multivariate regression analysis was performed, adjusting for sex, age, body mass index, and knee osteoarthritis. Additionally, a sex-stratified analysis was performed. DISH was detected in 83 (18.2%) participants. Multivariate analysis demonstrated that DISH was significantly associated with low EQ5D HSUV. Multivariate analysis in men demonstrated that DISH was associated with low PCS, low EQ5D HSUV, high LS stage. Multivariate analysis in women demonstrated that DISH was not associated with any QOL or LS. DISH may be associated with a poor QOL. Additionally, DISH is more common and produces a greater clinical impact in men than in women.

Intensive care unit-acquired weakness (ICU-AW) is recognized as newly-acquired bilateral muscle weakness, which is a complication of critical illness in the ICU; however, there are no reports on the pathogenesis and early predictors of ICU-AW specifically associated with cardiogenic shock (CS). Therefore, this study aimed to investigate the clinical characteristics of ICU-AW in patients with CS requiring mechanical circulatory support (MCS). This study was a single-center, prospective, and observational study. Patients aged 16 years and older who underwent MCS for CS were included. ICU-AW was diagnosed based on Medical Research Council (MRC) score after awakening. The ICU-AW group included patients with the MRC score < 48 points, and the non-ICU-AW group included those with ≥ 48 points. Twenty-eight cases were enrolled on admission and MRC score was evaluated in 23 cases after awakening. Eleven patients were included in the non-ICU-AW group and 12 patients (52%) were in the ICU-AW group. The ICU-AW group showed a higher prevalence of extracorporeal membrane oxygenation and ventilator use. Creatine kinase, troponin T, interleukin (IL)-15 levels on admission were significantly higher, whereas hemoglobin and albumin levels were significantly lower in the ICU-AW group. A strong negative correlation was observed between the initial MRC scores and IL-15 levels. ICU-AW occurred 52% of patients with CS using MCS, indicating the significance of recognizing and managing this complication for those patients. In addition, IL-15 can be a potential biomarker for the early prediction of ICU-AW.