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This study aimed to develop and validate an effective prognostic nomogram for advanced PDAC patients. We conducted a prospective multicenter cohort study involving 1,526 advanced PDAC patients from three participating hospitals in China between January 1, 2004 and December 31, 2013. Two thirds of the patients were randomly assigned to the training set (n = 1,017), and one third were assigned to the validation set (n = 509). Multivariate cox regression analysis was performed to identify significant prognostic factors for overall survival to develop the nomogram. Internal and external validation using C-index and calibration curve were conducted in the training set and validation set respectively. As results, seven independent prognostic factors were identified: age, tumor stage, tumor size, ALT (alanine aminotransferase), ALB (albumin), CA 19-9, HBV infection status, and these factors were entered into the nomogram. The proposed nomogram showed favorable discrimination and calibration both in the training set and validation set. The C-indexes of the training set and validation set were 0.720 and 0.696 respectively, which were both significantly higher than that of the staging system (C-index = 0.613, P < 0.001). In conclusion, the proposed nomogram may be served as an effective tool for prognostic evaluation of advanced PDAC.
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http://dx.doi.org/10.1038/s41598-017-11227-8 | DOI Listing |
Interv Neuroradiol
September 2025
University Clinic for Neuroradiology, University Hospital Magdeburg, Magdeburg, Germany.
BackgroundAt present, nonvirtual neurovascular training can be performed using either an angiographic suite under fluoroscopic guidance (entailing radiation exposure) or direct optical visualization with a camera-based system. The angiographic approach offers high-fidelity visualization and catheter control but is constrained by the limited availability of such specialized facilities, whereas the camera-based approach can be implemented virtually anywhere yet lacks comparable realism in key procedural aspects. The objective of this work is to develop and evaluate a novel camera-based angiography training system (CBATS) that generates artificial angiograms and roadmaps, thereby combining the advantages of both imaging techniques while eliminating radiation exposure.
View Article and Find Full Text PDFClin Exp Immunol
September 2025
Orthopedic Center, Sunshine Union Hospital, High-tech Zone, Weifang City, Shandong Province, China.
Introduction: We attempted to perform a comprehensive bioinformatics analyses on osteoarthritis (OA) based on the NKT-related genes and explore the clinical related critical genes.
Methods: Differentially expressed genes (DEGs) and NKT-related genes from WGCNA were obtained using the dataset GSE114007, followed by intersection analysis to obtain NKT-related DEGs. Lasso regression, support vector machine and random forest were performed to screen feature genes, followed by verification with ROC curve, and nomogram model.
Clin Exp Dent Res
October 2025
Tasmanian School of Medicine, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia.
Objectives: Oral health is an important aspect of quality of life for older people, especially those with dementia. The impact of an active oral hygiene program on the oral microbiome was explored in a group of older participants (average age 84 years old) with dementia against a separate control group whose oral hygiene followed the status quo.
Materials And Methods: The oral cavity bacteriomes and mycobiomes were assessed from swabs of cheek, gum, and tongue surfaces.
J Pharm Anal
August 2025
Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
Current experimental and computational methods have limitations in accurately and efficiently classifying ion channels within vast protein spaces. Here we have developed a deep learning algorithm, GPT2 Ion Channel Classifier (GPT2-ICC), which effectively distinguishing ion channels from a test set containing approximately 239 times more non-ion-channel proteins. GPT2-ICC integrates representation learning with a large language model (LLM)-based classifier, enabling highly accurate identification of potential ion channels.
View Article and Find Full Text PDFJ Comput Soc Sci
September 2025
Chair of Research Methods in Developmental and Educational Sciences, Institute of Education, University of Zurich, Zurich, Switzerland.
School curricula guide the daily learning activities of millions of students. They embody the understanding of the education experts who designed them of how to organize the knowledge that students should acquire in a way that is optimal for learning. This can be viewed as a learning 'theory' which is, nevertheless, rarely put to the test.
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