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http://dx.doi.org/10.1212/WNL.0000000000001983 | DOI Listing |
Trials
January 2025
Center for Research in Neuropsychology and Cognitive and Behavioral Intervention, Faculty of Psychology and Education Sciences, University of Coimbra, Coimbra, Portugal.
Background: Breast cancer is the most diagnosed cancer in women worldwide and carries a considerable psychosocial burden. Interventions based on Acceptance and Commitment Therapy (ACT) and compassion-based approaches show promise in improving adjustment and quality of life in people with cancer. The Mind programme is an integrative ACT and compassion-based intervention tailored for women with breast cancer, which aims to prepare women for survivorship by promoting psychological flexibility and self-compassion.
View Article and Find Full Text PDFBMC Med Genomics
January 2025
Yuyao People's Hospital of Zhejiang Province, Ningbo, Zhejiang, China.
Enhancer RNA (eRNA) has emerged as a key player in cancer biology, influencing various aspects of tumor development and progression. In this study, we investigated the role of eRNAs in kidney renal clear cell carcinoma (KIRC), the most common subtype of renal cell carcinoma. Leveraging high-throughput sequencing data and bioinformatics analysis, we identified differentially expressed eRNAs in KIRC and constructed eRNA-centric regulatory networks.
View Article and Find Full Text PDFCancer Cell Int
January 2025
Department of Urology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610072, China.
Background: Tumor microenvironment (TME) plays a crucial role in tumor growth and metastasis. Exploring biomarkers that are significantly associated with TME can help guide individualized treatment of patients.
Methods: We analyzed the expression and survival of P4HB in pan-cancer through the TCGA database, and verified the protein level of P4HB by the HPA database.
Med Biol Eng Comput
January 2025
Department of Computer Science and Engineering, Shri Shankaracharya Institute of Professional Management and Technology, Raipur, (C.G.), India.
This study presents an advanced methodology for 3D heart reconstruction using a combination of deep learning models and computational techniques, addressing critical challenges in cardiac modeling and segmentation. A multi-dataset approach was employed, including data from the UK Biobank, MICCAI Multi-Modality Whole Heart Segmentation (MM-WHS) challenge, and clinical datasets of congenital heart disease. Preprocessing steps involved segmentation, intensity normalization, and mesh generation, while the reconstruction was performed using a blend of statistical shape modeling (SSM), graph convolutional networks (GCNs), and progressive GANs.
View Article and Find Full Text PDFPathology
December 2024
Department of General Surgery, Changi General Hospital, Singapore.
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