Exploring the Key Signaling Pathways and ncRNAs in Colorectal Cancer.

Colorectal cancer (CRC) is the third most prevalent cancer to be diagnosed, and it has a substantial mortality rate. Despite numerous studies being conducted on CRC, it remains a significant health concern. The disease-free survival rates notably decrease as CRC progresses, emphasizing the urgency for effective diagnostic and therapeutic approaches. CRC development is caused by environmental factors, which mostly lead to the disruption of signaling pathways. Among these pathways, the Wingless/Integrated (Wnt) signaling pathway, Phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) signaling pathway, Mitogen-Activated Protein Kinase (MAPK) signaling pathway, Transforming Growth Factor-ß (TGF-ß) signaling pathway, and p53 signaling pathway are considered to be important. These signaling pathways are also regulated by non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). They have emerged as crucial regulators of gene expression in CRC by changing their expression levels. The altered expression patterns of these ncRNAs have been implicated in CRC progression and development, suggesting their potential as diagnostic and therapeutic targets. This review provides an overview of the five key signaling pathways and regulation of ncRNAs involved in CRC pathogenesis that are studied to identify promising avenues for diagnosis and treatment strategies.

Exploring the Regulatory Landscape of Dementia: Insights from Non-Coding RNAs.

Dementia, a multifaceted neurological syndrome characterized by cognitive decline, poses significant challenges to daily functioning. The main causes of dementia, including Alzheimer's disease (AD), frontotemporal dementia (FTD), Lewy body dementia (LBD), and vascular dementia (VD), have different symptoms and etiologies. Genetic regulators, specifically non-coding RNAs (ncRNAs) such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), are known to play important roles in dementia pathogenesis. MiRNAs, small non-coding RNAs, regulate gene expression by binding to the 3' untranslated regions of target messenger RNAs (mRNAs), while lncRNAs and circRNAs act as molecular sponges for miRNAs, thereby regulating gene expression. The emerging concept of competing endogenous RNA (ceRNA) interactions, involving lncRNAs and circRNAs as competitors for miRNA binding, has gained attention as potential biomarkers and therapeutic targets in dementia-related disorders. This review explores the regulatory roles of ncRNAs, particularly miRNAs, and the intricate dynamics of ceRNA interactions, providing insights into dementia pathogenesis and potential therapeutic avenues.

Classification of gait variation under mental workload in big five personalities.

BACKGROUND: Human behavior patterns involve mutual interactions among psychology, physiology, and stress, which are all associated with gait at different grades. RESEARCH QUESTIONS: The study aims to reveal the interrelationship among personality, mental workload, and gait patterns by capturing gait variations using inertial sensors. It also assesses individual personality traits and simulates stress to construct a gait classification model. METHODS: Sixty participants were instructed to perform regular, low, and high mental workload walking on the corridor to simulate a natural setting walking. Meanwhile inertial measurement units (IMUs) were placed on eight body parts. Mental workload was induced using the auditory n-back task, and their Big Five personality traits were evaluated. Gait data from IMUs were categorized into nine classifications of average, low, and high Big Five Inventory scores with three levels of mental workload walking. Subsequently, the segmentation gait data were used as input features for classifications in deep learning models, employing a sliding window long short-term memory network for nine classifications for different personality dimensions. RESULTS: The results indicated average accuracies of nine classifications were 83.6 % for Openness, 84.4 % for Conscientiousness, 82.0 % for Extraversion, 85.2 % for Agreeableness, and 84.5 % for Neuroticism across all IMU placements. Remarkably, gait data from the lower back IMU achieved the highest model performance, with an average accuracy of 92.7 %, in classifying the different levels of personality and mental workload walking. In contrast, the left wrist and chest showed several misclassifications among regular, low, and high mental workload walking across personality traits. SIGNIFICANCE: Successful classification can help monitor an individual's mental state in real time and analyze personality dimensions, providing feedback and suggestions. The present study demonstrated that gait characteristics can contribute to more profound and personalized health information.

The human PTGR1 gene expression is controlled by TE-derived Z-DNA forming sequence cooperating with miR-6867-5p.

Z-DNA, a well-known non-canonical form of DNA involved in gene regulation, is often found in gene promoters. Transposable elements (TEs), which make up 45% of the human genome, can move from one location to another within the genome. TEs play various biological roles in host organisms, and like Z-DNA, can influence transcriptional regulation near promoter regions. MicroRNAs (miRNAs) are a class of small non-coding RNA molecules that play a critical role in the regulation of gene expression. Although TEs can generate Z-DNA and miRNAs can bind to Z-DNA, how these factors affect gene transcription has yet to be elucidated. Here, we identified potential Z-DNA forming sequence (ZFS), including TE-derived ZFS, in the promoter of prostaglandin reductase 1 (PTGR1) by data analysis. The transcriptional activity of these ZFS in PTGR1 was confirmed using dual-luciferase reporter assays. In addition, we discovered a novel ZFS-binding miRNA (miR-6867-5p) that suppressed PTGR1 expression by targeting to ZFS. In conclusion, these findings suggest that ZFS, including TE-derived ZFS, can regulate PTGR1 gene expression and that miR-6867-5p can suppress PTGR1 by interacting with ZFS.

Factors Related to Suicidal Ideation in Adolescents According to Types of Stress.

Background: We aimed to identify the factors associated with suicidal ideation by classifying adolescents into three groups: no stress, interpersonal stress, as well as academic and career stress. Method: Using the data from the 16th Korea Youth Risk Behavior Web-Based Survey (2020), 15,343 adolescents were included in the study, and their socio-demographic characteristics as well as physical and psychological factors were assessed. A complex sample logistic regression was performed to identify factors associated with suicide. Results: The following factors were significantly associated with suicide: fatigue recovery by sleep, body mass index, physical activity, and depression in the no stress group; current school, academic grade, drinking, depression, loneliness, and anxiety in the interpersonal stress group; and gender, current school, academic grade, father's educational level, drinking, fatigue recovery by sleep, depression, loneliness, subjective health, smartphone overdependence, as well as anxiety in the academic and career stress group (P < 0.05). Conclusion: To prevent suicide among adolescents, it is necessary to consider these factors when developing educational policies.