Medicine
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Pancreatic adenocarcinoma (PAAD) results in one of the deadliest solid tumors with discouraging clinical outcomes. Growing evidence suggests that long non-coding RNAs (lncRNAs) play a crucial role in altering the growth, prognosis, migration, and invasion of pancreatic cancer cells. Cuproptosis is a novel type of cell death induced by copper (Cu) and is associated with mitochondrial respiration during the tricarboxylic acid cycle. ⋯ Higher tumor mutation burden (TMB) and lower tumor immune dysfunction and exclusion (TIDE) scores were observed in the high-risk group. Additionally, the low-risk group was hypersensitive to 3 anti-cancer medications, whereas the high-risk group was hypersensitive to one. A prognostic risk model with a good predictive ability based on cuproptosis-related lncRNAs was developed, providing a theoretical basis for personalized treatment and immunotherapeutic responses in pancreatic cancer.
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A better understanding of the network responses of cortical activities during rest and cognitive tasks is necessary. Therefore, in this study, we aimed to evaluate cerebral activities during attentional tasks by using mobile electroencephalography, identifying the types of attentional components and brain waves. ⋯ These findings contribute to the basic knowledge necessary to develop new attentional assessment methods for clinical situations.
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Carotid atherosclerosis (AS) occurs in atherosclerotic lesions of the carotid artery, which can lead to transient ischemic attack and stroke in severe cases. However, the relationship between pleckstrin (PLEK) and lymphocyte antigen 86 (LY86) and carotid AS remains unclear. The carotid AS datasets GSE43292 and GSE125771 were downloaded from the gene expression omnibus database. ⋯ Comparative toxicogenomics database analysis showed that 5 genes were associated with pneumonia, inflammation, necrosis, and drug allergy. PLEK and LY86 genes are highly expressed in carotid AS. The higher the expression of PLEK and LY86, the worse the prognosis is.
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Sentinel lymph node (SLN) status is closely related to axillary lymph node metastasis in breast cancer. However, SLN biopsy has certain limitations due to invasiveness and diagnostic efficiency. This study aimed to develop a model to predict the risk of axillary SLN metastasis in early-stage breast cancer based on mammography, a noninvasive, cost-effective, and potential complementary way. ⋯ Patients could benefit from clinical decisions guided by the present model within the threshold probabilities of 6% to 84%. The prediction model for axillary SLN metastasis showed satisfactory discrimination, calibration abilities, and wide clinical practicability. These findings suggest that our prediction model based on mammography characteristics is a reliable tool for predicting SLN metastasis in patients with early-stage breast cancer.
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There are 3 issues in bibliometrics that need to be addressed: The lack of a clear definition for author collaborations in cluster analysis that takes into account collaborations with and without self-connections; The need to develop a simple yet effective clustering algorithm for use in coword analysis, and; The inadequacy of general bibliometrics in regard to comparing research achievements and identifying articles that are worth reading and recommended for readers. The study aimed to put forth a clustering algorithm for cluster analysis (called following leader clustering [FLCA], a follower-leading clustering algorithm), examine the dissimilarities in cluster outcomes when considering collaborations with and without self-connections in cluster analysis, and demonstrate the application of the clustering algorithm in bibliometrics. ⋯ The FLCA algorithm proposed in this study offers researchers a comprehensive approach to exploring and comprehending the complex connections among authors or keywords. The study suggests that future research on ACs with cluster analysis should employ FLCA and R visualizations.