ArticleBiophysical journal2023
Modeling and analysis of voltage gating of gap junction channels at a single-channel level.
Article in Biophysical journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Cardiac resident macrophages: the emerging role in arrhythmogenesis.Frontiers in immunology · 2026Review
- Gap Junction Channel Regulation: A Tale of Two Gates-Voltage Sensitivity of the Chemical Gate and Chemical Sensitivity of the Fast Voltage Gate.International journal of molecular sciences · 2024Review
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The advancement of single-channel-level recording via the patch-clamp technique has provided a powerful means of assessing the detailed behaviors of various types of ion channels in native and exogenously expressed cellular environments. However, such recordings of gap junction (GJ) channels are hampered by unique challenges that are related to their unusual intercellular configuration and natural clustering into densely packed plaques. Thus, the methods for reliable cross-correlation of data recorded at macroscopic and single-channel levels are lacking in studies of GJs. To address this issue, we combined our previously published four-state model (4SM) of GJ channel gating by voltage with maximum likelihood estimation (MLE)-based analyses of electrophysiological recordings of GJ channel currents. First, we consider evaluation of single-channel characteristics and the methods for efficient stochastic simulation of single GJ channels from the kinetic scheme described by 4SM using data obtained from macroscopic recordings. We then present an MLE-based methodology for extraction of information about transition rates for GJ channels and, ultimately, gating parameters defined in 4SM from recordings with visible unitary events. The validity of the proposed methodology is illustrated using stochastic simulations of single GJ channels and is extended to electrophysiological data recorded in cells expressing connexin 43 tagged with enhanced green fluorescent protein.
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