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Fibrinogen (FIB) plays a key role in blood coagulation and thrombosis and its concentration in blood can directly reflect health conditions, thus efficient detection of FIB would benefit the treatments of certain diseases such as liver and heart diseases. However, there is a lack of sensitive, simple, rapid and cheap FIB detection device currently, in lieu of expensive and sophisticated approaches in laboratories. Here, we propose a novel plasma separation and FIB detection platform based on a microfluidic paper-based analytical device (μPAD). It is the first time that dielectrophoretic (DEP) force is combined with capillary force on paper for plasma separation, and the separation efficiency of plasma reaches about 95%, ensuring reliable downstream FIB detection, for which we also propose a new method called the resistance-fibrinogen detection (RFD) method. It not only avoids the use of large-scale instruments for detection, but also possesses high precision and simplicity. The method is found to be reliable in FIB detection for various concentrations ranging from 127.0 to 508.0 mg dL. Moreover, the results obtained from the proposed μPAD show an excellent agreement (R = 0.9985) with those obtained from an automatic coagulation analyzer with natural human blood samples. Overall, the proposed platform provides a low-cost and reliable approach for FIB detection, especially for clinical use in resource-limited areas.
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http://dx.doi.org/10.1039/d0lc00439a | DOI Listing |
Discov Nano
September 2025
Department of Rehabilitation Medicine, Rehabilitation Medical Center, Key Laboratory of Rehabilitation Medicine in Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.
Immunoelectron Microscopy (IEM) is a technique that combines specific immunolabeling with high-resolution electron microscopic imaging to achieve precise spatial localization of biomolecules at the subcellular scale (< 10 nm) by using high-electron-density markers such as colloidal gold and quantum dots. As a core tool for analyzing the distribution of proteins, organelle interactions, and localization of disease pathology markers, it has irreplaceable value, especially in synapse research, pathogen-host interaction mechanism, and tumor microenvironment analysis. According to the differences in labeling sequence and sample processing, the IEM technology system can be divided into two categories: the first is pre-embedding labeling, which optimizes the labeling efficiency through the pre-exposure of antigenic epitopes and is especially suitable for the detection of low-abundance and sensitive antigens; the second is post-embedding labeling, which relies on the low-temperature resin embedding (e.
View Article and Find Full Text PDFScand J Gastroenterol
September 2025
Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden.
Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is associated with substantial clinical and economic burden. Fibrosis detection is key to disease management, but biopsy-defined staging is invasive, expensive, and associated with complications. We evaluated healthcare resource utilization (HCRU) and costs by disease stage using biopsy-defined staging and fibrosis-4 (FIB-4; a simple, well-validated, non-invasive tool for assessing fibrosis severity), and compared their utility for predicting long-term outcomes in MASLD.
View Article and Find Full Text PDFWorld J Gastroenterol
August 2025
Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Krung Thep Maha Nakhon, Thailand.
Background: The association between diabetes mellitus (DM) and metabolic dysfunction-associated steatotic liver disease (MASLD) is well documented, with DM increasing the risk of developing MASLD and liver fibrosis.
Aim: To evaluate the cost-effectiveness and budget impact of transient elastography (TE) for detecting significant fibrosis in Thai patients with DM.
Methods: We conducted a lifetime cost-utility analysis from a societal perspective, combining a decision tree with a Markov model.
Sci Rep
September 2025
Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel.
Liver diseases, notably cirrhosis, pose a substantial global health challenge, resulting in millions of annual deaths. Existing diagnostic methods primarily target high-risk groups, leaving a significant portion of patients undiagnosed. This study aims to develop and validate an a machine-learning prediction model, Fibro-Predict, for the early detection of advanced liver fibrosis in the general population using nationwide electronic health records (EHRs).
View Article and Find Full Text PDFSaudi J Gastroenterol
September 2025
Department of Medicine, Liver Disease Research Centre, College of Medicine, King Saud University, Riyadh, Saudi Arabia.
The reclassification of nonalcoholic fatty liver disease (NAFLD) to metabolic dysfunction-associated steatotic liver disease (MASLD) marks a significant shift in understanding liver disease, particularly in Saudi Arabia, where metabolic disorders are highly prevalent. This study aimed to develop expert consensus recommendations for early detection, specialist referral, and management of MASLD/metabolic dysfunction-associated steatohepatitis (MASH) in Saudi Arabia. A modified Delphi process was used to establish consensus among an expert panel of 15 multidisciplinary specialists, including hepatologists, endocrinologists, gastroenterologists, and primary care physicians.
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