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Probabilistic learning of the Purkinje network from the electrocardiogram.
Med Image Anal
January 2025
Department of Mechanical and Metallurgical Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile; Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile; Millennium Institute for Intelligent Healthcare Engineering, iHEALTH, Chile. Electronic address:
The identification of the Purkinje conduction system in the heart is a challenging task, yet essential for a correct definition of cardiac digital twins for precision cardiology. Here, we propose a probabilistic approach for identifying the Purkinje network from non-invasive clinical data such as the standard electrocardiogram (ECG). We use cardiac imaging to build an anatomically accurate model of the ventricles; we algorithmically generate a rule-based Purkinje network tailored to the anatomy; we simulate physiological electrocardiograms with a fast model; we identify the geometrical and electrical parameters of the Purkinje-ECG model with Bayesian optimization and approximate Bayesian computation.
View Article and Find Full Text PDFProfiling microRNA expression differentiates monozygotic twins in peripherical blood by droplet digital PCR.
Forensic Sci Int Genet
January 2025
School of Forensic Medicine, China Medical University, Shenyang 110000, PR China; Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, Liaoning Province 110000, PR China; China Medical University Center of Forensic Investigation, Shenyang 110000, PR China. Electronic address:
It is challenging to distinguish monozygotic (MZ) twins using traditional autosomal STR genotyping due to their nearly identical genomes. As an important kind of small non-coding RNAs, microRNAs (miRNAs) are essential regulators of gene expression and considered as excellent biomarkers due to their resistance to degradation. Moreover, droplet digital PCR (ddPCR) has emerged as a powerful technique for detecting gene mutations and pathogenic microorganisms, owing to its sensitivity and reliability.
View Article and Find Full Text PDFGenome-Wide Association Study on Imputed Genotypes of 180 Eurasian Soybean Varieties for Oil and Protein Contents in Seeds.
Plants (Basel)
January 2025
Kurchatov Genomics Center, Institute of Cytology and Genetics SB RAS, Lavrentiev Av. 10, 630090 Novosibirsk, Russia.
Soybean () is a leguminous plant with a broad range of applications, particularly in agriculture and food production, where its seed composition-especially oil and protein content-is highly valued. Improving these traits is a primary focus of soybean breeding programs. In this study, we conducted a genome-wide association study (GWAS) to identify genetic loci linked to oil and protein content in seeds, using imputed genotype data for 180 Eurasian soybean varieties and the novel "genotypic twins" approach.
View Article and Find Full Text PDFEpigenome-wide association study of Chinese monozygotic twins identifies DNA methylation loci associated with estimated glomerular filtration rate.
J Transl Med
January 2025
Department of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, 308 Ningxia Road, Qingdao, 266071, Shandong, People's Republic of China.
Background: DNA methylation (DNAm) has been shown in multiple studies to be associated with the estimated glomerular filtration rate (eGFR). However, studies focusing on Chinese populations are lacking. We conducted an epigenome-wide association study to investigate the association between DNAm and eGFR in Chinese monozygotic twins.
View Article and Find Full Text PDFChallenges and opportunities for digital twins in precision medicine from a complex systems perspective.
NPJ Digit Med
January 2025
Department of Physics and Astronomy "Galileo Galilei", University of Padua, Padova, Italy.
Digital twins (DTs) in precision medicine are increasingly viable, propelled by extensive data collection and advancements in artificial intelligence (AI), alongside traditional biomedical methodologies. We argue that including mechanistic simulations that produce behavior based on explicitly defined biological hypotheses and multiscale mechanisms is beneficial. It enables the exploration of diverse therapeutic strategies and supports dynamic clinical decision-making through insights from network science, quantitative biology, and digital medicine.
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