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Background And Aims: Numerous studies have explored the important role of N6-methyladenosine (mA) in cancer. Nonetheless, the interaction between mA and long noncoding RNAs (lncRNAs) is poorly investigated. Herein, we systematically analyzed the role and prognostic value of mA-related lncRNAs in hepatocellular carcinoma (HCC).
Methods: The mA-related lncRNAs were identified based on the correlation coefficients with mA-related genes in HCC from The Cancer Genome Atlas. Subsequently, a novel risk score model was determined using the least absolute shrinkage and selection operator Cox regression analyses. Univariate and multivariate Cox analyses were used to identify independent prognostic factors for overall survival (OS) of HCC; thereafter, a prognostic nomogram was constructed.
Results: A total of 259 lncRNAs showed significant correlations with mA in HCC, while 29 lncRNAs had prognostic significance. Further, six critical mA-related lncRNAs (NRAV, SNHG3, KDM4A-AS1, AC074117.1, AC025176.1, and AL031985.3) were screened out to construct a novel risk score model which classified HCC patients into high- and low-risk groups. Survival analyses revealed that patients in the high-risk group exhibited worse OS, both in the training and validation groups. The risk score was also identified as an independent prognostic factor of OS, and a nomogram was established and verified with superior prediction capacity. Besides, the risk score significantly correlated with the expression of immune checkpoint genes and immune subtypes.
Conclusions: These findings indicated the significant role of mA-related lncRNAs in HCC and the potential application of the novel risk score model for prognostic prediction.
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http://dx.doi.org/10.14218/JCTH.2021.00096 | DOI Listing |
Public Health
September 2025
Department of Public Health, Erasmus MC University Medical Center, Rotterdam, the Netherlands.
Objectives: Participation rates in fecal immunochemical test (FIT)-based colorectal cancer (CRC) screening differ across socio-demographic subgroups. The largest health gains could be achieved in subgroups with low participation rates and high risk of CRC. We investigated the CRC risk within different socio-demographic subgroups with low participation in the Dutch CRC screening program.
View Article and Find Full Text PDFAm J Emerg Med
September 2025
University of Toronto, Rotman School of Management, Canada.
Study Objective: Accurately predicting which Emergency Department (ED) patients are at high risk of leaving without being seen (LWBS) could enable targeted interventions aimed at reducing LWBS rates. Machine Learning (ML) models that dynamically update these risk predictions as patients experience more time waiting were developed and validated, in order to improve the prediction accuracy and correctly identify more patients who LWBS.
Methods: The study was deemed quality improvement by the institutional review board, and collected all patient visits to the ED of a large academic medical campus over 24 months.
Turk J Pediatr
September 2025
Division of Allergy and Asthma, Department of Pediatrics, Faculty of Medicine, Hacettepe University, Ankara, Türkiye.
Animal allergens, particularly those from cats, dogs, and horses, are significant risk factors for the development of allergic diseases in childhood. Managing animal allergies requires allergen avoidance and, when this is not feasible, specific immunotherapy. Patient history remains the cornerstone of diagnosis, providing the foundation for diagnostic algorithms.
View Article and Find Full Text PDFTurk J Pediatr
September 2025
Department of Cardiorespiratory Physiotherapy and Rehabilitation, Faculty of Physical Therapy and Rehabilitation, Hacettepe University, Ankara, Türkiye.
Background: Vascular changes are observed in children with cystic fibrosis (cwCF), and gender-specific differences may impact arterial stiffness. We aimed to compare arterial stiffness and clinical parameters based on gender in cwCF and to determine the factors affecting arterial stiffness in cwCF.
Methods: Fifty-eight cwCF were included.
JMIR Res Protoc
September 2025
University of Nevada, Las Vegas, Las Vegas, NV, United States.
Background: In-hospital cardiac arrest (IHCA) remains a public health conundrum with high morbidity and mortality rates. While early identification of high-risk patients could enable preventive interventions and improve survival, evidence on the effectiveness of current prediction methods remains inconclusive. Limited research exists on patients' prearrest pathophysiological status and predictive and prognostic factors of IHCA, highlighting the need for a comprehensive synthesis of predictive methodologies.
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