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There is an increasing interest in the use of dried blood spot (DBS) sampling and multiple reaction monitoring in proteomics. Although several groups have explored the utility of DBS by focusing on protein detection, the reproducibility of the approach and whether it can be used for biomarker discovery in high throughput studies is yet to be determined. We assessed the reproducibility of multiplexed targeted protein measurements in DBS compared to serum. Eighty-two medium to high abundance proteins were monitored in a number of technical and biological replicates. Importantly, as part of the data analysis, several statistical quality control approaches were evaluated to detect inaccurate transitions. After implementing statistical quality control measures, the median CV on the original scale for all detected peptides in DBS was 13.2% and in Serum 8.8%. We also found a strong correlation (r = 0.72) between relative peptide abundance measured in DBS and serum. The combination of minimally invasive sample collection with a highly specific and sensitive mass spectrometry (MS) technique allows for targeted quantification of multiple proteins in a single MS run. This approach has the potential to fundamentally change clinical proteomics and personalized medicine by facilitating large-scale studies.
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http://dx.doi.org/10.1038/srep45178 | DOI Listing |
Mol Biol Rep
September 2025
School of Pharmacy, Heilongjiang University of Chinese Medicine, NO 24 Heping Road, 150040, Harbin, P. R. China.
Lysosome-dependent cell death (LDCD) is a regulated form of cell death initiated by increased lysosomal membrane permeability, leading to the cytoplasmic release of lysosomal enzymes and subsequent cellular damage. Molecular mechanisms controlling LDCD include lysosomal membrane instability and lysosomal enzyme release, which together lead to cell damage. A more profound comprehension of these underlying mechanisms may reveal new therapeutic targets for diseases associated with lysosomal dysfunction.
View Article and Find Full Text PDFBiomed Environ Sci
August 2025
Department of Epidemiology, School of Public Health, MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou 215123, Jiangsu, China;Taixing Second People's Hospital, Suzhou Medical College of Soochow University, Taizhou 225400, Jiangsu, China.
Objective: Lipid oxidation is involved in the pathogenesis of atherosclerosis and may be contribute to the development of Ischemic stroke (IS). However, the lipid profiles associated with IS have been poorly studied. We conducted a pilot study to identify potential IS-related lipid molecules and pathways using lipidomic profiling.
View Article and Find Full Text PDFJ Proteome Res
September 2025
Department of Gastroenterology and Hepatology, West China Hospital, Sichuan University, Chengdu 610041, China.
Colorectal cancer (CRC) is a major global health challenge due to its high incidence, mortality, and low rate of early detection. Early diagnosis, targeting precancerous lesions (advanced adenomas) and early stage CRC (Tis and T1), is critical for improving patient survival. Given the limitations of current detection methods for advanced adenomas, developing high-performance early diagnostic strategies is essential for effective prevention.
View Article and Find Full Text PDFEnviron Epigenet
May 2025
Université Grenoble Alpes, INSERM U1209, CNRS UMR 5309, Institut pour l'Avancée des Biosciences (IAB), Team of Environmental Epidemiology Applied to Development and Respiratory Health, 38000 Grenoble, France.
An increasing number of epigenome-wide association studies report tobacco smoking-associated DNA methylation levels. However, comprehensive replication studies remain scarce, particularly in placenta, despite their crucial interest in such a large-scale context. Using DNA methylation data from the EPIC array of 341 new placentas (85 smokers, 219 non-smokers, and 37 former smokers) from the EDEN cohort, we used a candidate approach to replicate maternal smoking-associated CpGs and regions previously identified using the 450K array, and an exploratory approach to discover new associations within EPIC-specific CpGs.
View Article and Find Full Text PDFVet World
July 2025
Department of Veterinary Science, Faculty of Veterinary Medicine, Rajamangala University of Technology Tawan-OK, Chonburi, Thailand.
Background And Aim: Granulosa cells (GCs) are crucial mediators of follicular development and oocyte competence in goats, with their gene expression profiles serving as potential biomarkers of fertility. However, the lack of a standardized, quantifiable method to assess GC quality using transcriptomic data has limited the translation of such findings into reproductive applications. This study aimed to develop a hybrid deep learning model integrating one-dimensional convolutional neural networks (1DCNNs) and gated recurrent units (GRUs) to classify GCs as fertility-supporting (FS) or non-fertility-supporting (NFS) using single-cell RNA sequencing (scRNA-seq) data.
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