BackgroundThe diagnosis and treatment of breast cancer can provoke a series of negative emotional changes in patients, further affecting their quality of life. It has been shown that patients with higher resilience have better quality of life. Social support systems are important protective factors that are necessary for the process of resilience to occur. Hence, this study aimed to investigate the role of social support in the relationship between resilience and quality of life among Chinese patients with breast cancer.Material/MethodsA demographic-disease survey, the Chinese version of the Connor-Davidson Resilience Scale 25, Medical Outcomes Study Social Support Survey, and Functional Assessment of Cancer Therapy Breast Cancer Version 3 were used to interview 98 patients with breast cancer from a teaching hospital in Chongqing, China. Data analysis was performed by descriptive statistics, independent-sample t test, one-way ANOVA, and regression analyses.ResultsThe mean scores of resilience, social support, and quality of life were 54.68, 61.73, and 80.74 respectively, which were in the moderate range. Participants with stronger social support had higher resilience and better quality of life. Social support played a partial mediator role in the relationship between resilience and quality of life. The mediation effect ratio was 28.0%.ConclusionsSocial support is essential for the development of resilience and the improvement of quality of life in Chinese patients with breast cancer. Health professionals should provide appropriate guidelines to help patients seek effective support and enhance their resilience to improve their quality of life after breast cancer.
Hepatocellular carcinoma (HCC) is one of the fastest‐rising causes of cancer‐related death worldwide, but its deficiency of specific biomarkers and therapeutic targets in the early stages lead to severe inadequacy in the early diagnosis and treatment of HCC. Covalently closed circular RNA (circRNA), which was once considered an aberrant splicing by‐product, is now drawing new interest in cancer research because of its remarkable functionality. Beneath the surface of the dominant functional proteins events, a hidden circRNA‐centric noncoding regulatory RNAs network active in the very early stage of HCC is here revealed by a genome‐wide analysis of mRNA, circRNA, and microRNA (miRNA) expression profiles. Circ‐CDYL (chromodomain Y like) is specifically up‐regulated in the early stages of HCC and therefore contributes to the properties of epithelial cell adhesion molecule (EPCAM)‐positive liver tumor‐initiating cells. Circ‐CDYL interacts with mRNAs encoding hepatoma‐derived growth factor (HDGF) and hypoxia‐inducible factor asparagine hydroxylase (HIF1AN) by acting as the sponge of miR‐892a and miR‐328‐3p, respectively. Subsequently, activation of the phosphoinositide 3‐kinase (PI3K)‐AKT serine/threonine kinase‐mechanistic target of rapamycin kinase complex 1/β‐catenin and NOTCH2 pathways, which promote the expression of the effect proteins, baculoviral IAP repeat containing 5 (BIRC5 or SURVIVIN) and MYC proto‐oncogene, is influenced by circ‐CDYL. A treatment incorporating circ‐CDYL interference and traditional enzyme inhibitors targeting PI3K and HIF1AN demonstrated highly effective inhibition of stem‐like characteristics and tumor growth in HCC. Finally, we demonstrated that circ‐CDYL expression or which combined with HDGF and HIF1AN are both independent markers for discrimination of early stages of HCC with the odds ratios of 1.09 (95% confidence interval [CI], 1.02‐1.17) and 124.58 (95% CI, 13.26‐1170.56), respectively. Conclusion: These findings uncover a circRNA‐centric noncoding regulatory RNAs network in the early stages of HCC and thus provide a possibility for surveillance and early treatment of HCC.
The performance of an advanced research version of the Weather Research and Forecasting Model (WRF) in predicting near-surface atmospheric temperature and wind conditions under various terrain and weather regimes is examined. Verification of 2-m temperature and 10-m wind speed and direction against surface Mesonet observations is conducted. Three individual events under strong synoptic forcings (i.e., a frontal system, a low-level jet, and a persistent inversion) are first evaluated. It is found that the WRF model is able to reproduce these weather phenomena reasonably well. Forecasts of near-surface variables in flat terrain generally agree well with observations, but errors also occur, depending on the predictability of the lower-atmospheric boundary layer. In complex terrain, forecasts not only suffer from the model's inability to reproduce accurate atmospheric conditions in the lower atmosphere but also struggle with representative issues due to mismatches between the model and the actual terrain. In addition, surface forecasts at finer resolutions do not always outperform those at coarser resolutions. Increasing the vertical resolution may not help predict the near-surface variables, although it does improve the forecasts of the structure of mesoscale weather phenomena. A statistical analysis is also performed for 120 forecasts during a 1-month period to further investigate forecast error characteristics in complex terrain. Results illustrate that forecast errors in near-surface variables depend strongly on the diurnal variation in surface conditions, especially when synoptic forcing is weak. Under strong synoptic forcing, the diurnal patterns in the errors break down, while the flow-dependent errors are clearly shown.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.