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Catheter ablation to prevent ventricular tachycardia (VT) that emerges late after a myocardial infarction aims to interrupt the re-entry substrate. Interruption of potential channels and regions of slow conduction that can be identified during stable sinus or paced rhythm is often effective and a number of substrate markers for guiding this approach have been described. While there is substantial agreement with different markers in some patients, the different markers select different regions for ablation in others. Mapping during VT to identify critical re-entry circuit isthmuses is likely more specific, and most useful when VT is incessant or frequent during the procedure or when sinus rhythm substrate ablation fails. Both approaches are often combined. These methods for identifying and characterizing post-infarct-related arrhythmia substrate and the re-entry circuits are reviewed.
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http://dx.doi.org/10.1016/j.jacep.2024.09.016 | DOI Listing |
Adv Healthc Mater
September 2025
Department of Biomedical Engineering, University of Delaware, Newark, DE, 19716, USA.
Organ-on-chip (OOC) technologies, also called microphysiological systems (MPS), offer dynamic microenvironments that improve upon static culture systems, yet widespread adoption has been hindered by fabrication complexity, reliance on polydimethylsiloxane (PDMS), and limited modularity. Here, a modular MPS platform is presented, designed for ease of use, reproducibility, and broad applicability. The system comprises layered elastomeric inserts for dual monolayer cell culture, which is clamped within a reusable acrylic cassette for perfusion studies.
View Article and Find Full Text PDFNat Methods
September 2025
Electron Microscopy Science Technology Platform, The Francis Crick Institute, London, UK.
Volume correlative light and electron microscopy (vCLEM) is a powerful imaging technique that enables the visualization of fluorescently labeled proteins within their ultrastructural context. Currently, vCLEM alignment relies on time-consuming and subjective manual methods. This paper presents CLEM-Reg, an algorithm that automates the three-dimensional alignment of vCLEM datasets by leveraging probabilistic point cloud registration techniques.
View Article and Find Full Text PDFNat Biotechnol
September 2025
European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK.
The size of microbial sequence databases continues to grow beyond the abilities of existing alignment tools. We introduce LexicMap, a nucleotide sequence alignment tool for efficiently querying moderate-length sequences (>250 bp) such as a gene, plasmid or long read against up to millions of prokaryotic genomes. We construct a small set of probe k-mers, which are selected to efficiently sample the entire database to be indexed such that every 250-bp window of each database genome contains multiple seed k-mers, each with a shared prefix with one of the probes.
View Article and Find Full Text PDFJ Invest Dermatol
September 2025
Department of Dermatology and Allergology, Philipps University Marburg, Marburg, Germany. Electronic address:
Pemphigus vulgaris (PV) is an autoimmune blistering disorder, which is caused by the loss of desmosomal cell-cell adhesion, initiated by the binding of IgG antibodies against the desmosomal components desmoglein (Dsg)1 and Dsg3. Dsg3-reactive CD4 T helper (Th) cells, in particular follicular Th (Tfh) cells, play a central role in autoantibody production by Dsg3-specific B cells. In this study, we challenged the concept that distinct Dsg3-reactive CD4 T cell subsets are critical in PV pathogenesis utilizing phenotypical and functional state-of-the-art ex vivo assays.
View Article and Find Full Text PDFMethods
September 2025
School of Computer and Information Engineering, Henan University, Kaifeng, Henan, China; Henan Key Laboratory of Big Data Analysis and Processing, Henan University, Kaifeng, Henan, China. Electronic address:
Genomic selection (GS) is a breeding technique that utilizes genomic markers to predict the genetic potential of crops and animals. This approach holds significant promise for accelerating the improvement of agronomic traits and addressing food security challenges. While traditional breeding methods based on statistical or machine learning techniques have been useful in predicting traits for some crops, they often fail to capture the complex interactions between genotypes and phenotypes.
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