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| http://dx.doi.org/10.1177/15330338241298854 | DOI Listing |
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A noninvasive urinary microRNA-based assay for the detection of pancreatic cancer from early to late stages: a case control study.
EClinicalMedicine
December 2024
Department of Pathology and Genetics, Laboratory of Cancer Medical Science, Hokuto Hospital, Obihiro, Hokkaido, Japan.
Background: Pancreatic cancer is highly aggressive and has a low survival rate primarily due to late-stage diagnosis and the lack of effective early detection methods. We introduce here a novel, noninvasive urinary extracellular vesicle miRNA-based assay for the detection of pancreatic cancer from early to late stages.
Methods: From September 2019 to July 2023, Urine samples were collected from patients with pancreatic cancer (n = 153) from five distinct sites (Hokuto Hospital, Kawasaki Medical School Hospital, National Cancer Center Hospital, Kagoshima University Hospital, and Kumagaya General Hospital) and non-cancer participants (n = 309) from two separate sites (Hokuto Hospital and Omiya City Clinic).
VASARI 2.0: a new updated MRI VASARI lexicon to predict grading and status in brain glioma.
Front Oncol
December 2024
NeuroRadiology Unit, Ospedale del Mare, Azienda Sanitaria Locale Napoli 1 Centro (ASL NA1 Centro), Naples, Italy.
Introduction: Precision medicine refers to managing brain tumors according to each patient's unique characteristics when it was realized that patients with the same type of tumor differ greatly in terms of survival, responsiveness to treatment, and toxicity of medication. Precision diagnostics can now be advanced through the establishment of imaging biomarkers, which necessitates quantitative image acquisition and processing. The VASARI (Visually AcceSAble Rembrandt Images) manual annotation methodology is an ideal and suitable way to determine the accurate association between genotype and imaging phenotype.
View Article and Find Full Text PDFA novel DNA damage-related gene index for predicting prognosis in gastric cancer.
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Department of Gastroenterology, Huanggang Central Hospital of Yangtze University, No.6 Qi 'an Avenue, Huangzhou District, Huanggang, 438000 Hubei China.
Gastric cancer is one of the major cancers with high cancer mortality and shows significant heterogeneity. The development of precise prognostic models is crucial for advancing treatment strategies. Recognizing the pivotal role of DNA damage in tumor progression, we conducted a consensus clustering analysis of DNA damage-related genes to categorize gastric cancer patients from the TCGA clinical cohort into distinct subtypes.
View Article and Find Full Text PDFMachine perfusion organ preservation: Highlights from the American transplant congress 2024.
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Department of Surgery, Division of Transplantation, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA.
The American Transplant Congress (ATC) 2024, held in Philadelphia, serves as a vital platform for unveiling new research and clinical experience in organ machine perfusion-a key area in organ transplantation. This year's congress gathered 4652 participants from 49 countries, including top experts, to spotlight innovations in machine perfusion across various organ types, such as the liver, kidney, heart, and lung. A total of 87 abstracts on organ machine perfusion were presented.
View Article and Find Full Text PDFTransforming precision medicine: The potential of the clinical artificial intelligent single-cell framework.
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Department of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria.
The editorial, "Clinical and translational mode of single-cell measurements: An artificial intelligent single-cell," introduces the innovative clinical artificial intelligence single-cell (caiSC) system, which merges AI with single-cell informatics to advance real-time diagnostics, disease monitoring, and treatment prediction. By combining clinical data and multimodal molecular inputs, caiSC facilitates personalized medicine, promising enhanced diagnostic precision and tailored therapeutic approaches. Despite its potential, caiSC lacks comprehensive data coverage across cell types and diseases, presenting challenges in data quality and model robustness.
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