Acute pulmonary embolism (PE) is a common emergency with a high morbidity and mortality. Most clinical presentations are non-specific and there is a lack of suitable biomarkers for PE. For example, the traditional D-dimer tests shows a rather high sensitivity for PE, but yet a rather low positive predictive value due to its lack of specificity. Research on novel biomarkers for PE is thus of interest to improve early diagnostics and reduce the number of unnecessary computed tomography pulmonary angiogram (CTPA) scans performed. In this study we evaluate the feasibility to use label-free quantitative proteomics to discover potential biomarkers for acute PE and to monitor changes in proteins levels in PE patients over time. Blood was collected from 8 patients with CTPA verified PE and from 8 patients presenting with same symptoms but with a negative CTPA. The samples were analyzed by liquid chromatography-mass spectrometry and thirteen protein concentrations were found to be significantly changed in PE patients compared to the CTPA negative controls. This exploratory study shows that proteomic analysis can be used to identify potential biomarkers for PE as well as to monitor changes of protein levels over time.The complement proteins play a part in PE but further studies are needed to clarify their specific role in the pathophysiological process and to look for more specific proteins.
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http://dx.doi.org/10.1177/10760296221074347 | DOI Listing |
Lung Cancer
January 2025
Dept. of Medical Oncology, Princess Margaret Cancer Center, Toronto, ON, Canada.
Background: Manual extraction of real-world clinical data for research can be time-consuming and prone to error. We assessed the feasibility of using natural language processing (NLP), an AI technique, to automate data extraction for patients with advanced lung cancer (aLC). We assessed the external validity of our NLP-extracted data by comparing our findings to those reported in the literature.
View Article and Find Full Text PDFLung Cancer
January 2025
Internal Medicine III, Wakayama Medical University, Wakayama, Japan.
Objectives: The lack of definitive biomarkers presents a significant challenge for chemo-immunotherapy in extensive-stage small-cell lung cancer (ES-SCLC). We aimed to identify key genes associated with chemo-immunotherapy efficacy in ES-SCLC through comprehensive gene expression analysis using machine learning (ML).
Methods: A prospective multicenter cohort of patients with ES-SCLC who received first-line chemo-immunotherapy was analyzed.
Liver Transpl
October 2024
Department of General Surgery, Division of Transplantation, Medical University of Vienna, Vienna, Austria.
Hypothermic oxygenated machine perfusion (HOPE) preconditions liver grafts before transplantation. While beneficial effects on patient outcomes were demonstrated, biomarkers for viability assessment during HOPE are scarce and lack validation. This study aims to validate the predictive potential of perfusate flavin mononucleotide (FMN) during HOPE to enable the implementation of FMN-based assessment into clinical routine and to identify safe organ acceptance thresholds.
View Article and Find Full Text PDFNeuroradiol J
January 2025
Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Iran.
Introduction: The prevalence of neurodegenerative diseases has significantly increased, necessitating a deeper understanding of their symptoms, diagnostic processes, and prevention strategies. Frontotemporal dementia (FTD) and Alzheimer's disease (AD) are two prominent neurodegenerative conditions that present diagnostic challenges due to overlapping symptoms. To address these challenges, experts utilize a range of imaging techniques, including magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), functional MRI (fMRI), positron emission tomography (PET), and single-photon emission computed tomography (SPECT).
View Article and Find Full Text PDFAm Surg
January 2025
Division of Hepatobiliary and Pancreas Surgery, Department of Surgery, The Jikei University School of Medicine, Minato-ku, Japan.
Background/aim: The aim of this study was to investigate the prognostic impact of the inflammatory burden index (IBI), a novel inflammation-based biomarker, in patients with colorectal liver metastases (CRLM) after hepatic resection.
Patients And Methods: One hundred fifty patients with CRLM who underwent hepatectomy were retrospectively analyzed. The IBI was defined as C-reactive protein × neutrophil count/lymphocyte count.
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