RESUMO
Objective. The primary aim of our study is to advance our understanding and diagnosis of cardiac diseases. We focus on the reconstruction of myocardial transmembrane potential (TMP) from body surface potential mapping.Approach. We introduce a novel methodology for the reconstruction of the dynamic distribution of TMP. This is achieved through the integration of convolutional neural networks with conventional optimization algorithms. Specifically, we utilize the subject-specific transfer matrix to describe the dynamic changes in TMP distribution and ECG observations at the body surface. To estimate the TMP distribution, we employ LNFISTA-Net, a learnable non-local regularized iterative shrinkage-thresholding network. The coupled estimation processes are iteratively repeated until convergence.Main results. Our experiments demonstrate the capabilities and benefits of this strategy. The results highlight the effectiveness of our approach in accurately estimating the TMP distribution, thereby providing a reliable method for the diagnosis of cardiac diseases.Significance. Our approach demonstrates promising results, highlighting its potential utility for a range of applications in the medical field. By providing a more accurate and dynamic reconstruction of TMP, our methodology could significantly improve the diagnosis and treatment of cardiac diseases, thereby contributing to advancements in healthcare.
Assuntos
Cardiopatias , Coração , Humanos , Potenciais da Membrana , Coração/diagnóstico por imagem , Diagnóstico por Imagem , Miocárdio , Algoritmos , Cardiopatias/diagnóstico por imagem , Processamento de Imagem Assistida por Computador/métodosRESUMO
Earthworms can redistribute soil microbiota, and thus might affect the profile of virulence factor genes (VFGs) which are carried by pathogens in soils. Nevertheless, the knowledge of VFG profile in the earthworm guts and its interaction with earthworm gut microbiome is still lacking. Herein, we characterized earthworm gut and soil microbiome and VFG profiles in natural and agricultural ecosystems at a national scale using metagenomics. VFG profiles in the earthworm guts significantly differed from those in the surrounding soils, which was mainly driven by variations of bacterial communities. Furthermore, the total abundance of different types of VFGs in the earthworm guts was about 20-fold lower than that in the soils due to the dramatic decline (also by approximately 20-fold) of VFG-carrying bacterial pathogens in the earthworm guts. Additionally, five VFGs related to nutritional/metabolic factors and stress survival were identified as keystones merely in the microbe-VFG network in the earthworm guts, implying their pivotal roles in facilitating pathogen colonization in earthworm gut microhabitats. These findings suggest the potential roles of earthworms in reducing risks related to the presence of VFGs in soils, providing novel insights into earthworm-based bioremediation of VFG contamination in terrestrial ecosystems.