Search

Definition: This entry paper is an attempt to explain how the discrete nature of light (energy discreteness in the form of photons) constrains the light detection process all along the evolutionary path, in the not-fully-understood photoreceptive systems of unicellular microorganisms (nonimaging systems) and in the complex and well-known visual system of higher organisms (imaging systems). All these systems are perfect examples of the interplay between physics and biology, i.e., they are the perfect topic of research for biophysicists. The paper describes how photoreceptive and visual systems achieve the goal of photon counting, which information is conveyed by a finite number of photons, and which noise factors limit light-detecting processes. [ABSTRACT FROM AUTHOR]

Josep Rizo is a Professor of Biophysics, Biochemistry and Pharmacology at the University of Texas Southwestern Medical Center, where he is Virginia Lazenby O'Hara Chair in Biochemistry. He is particularly interested in the study of the mechanisms of neurotransmitter release and intracellular membrane fusion using structural biology, a variety of biophysical techniques and reconstitution approaches. Jose has been a part of the FEBS Open Bio Editorial Board since 2021. In this interview, he shares his insights into developments in the field of neurotransmitter release, describes his move from Spain to the United States, and discusses how sometimes you need to use both logic and scientific hunches. [ABSTRACT FROM AUTHOR]

Understanding active matter has led to new perspectives on biophysics and non-equilibrium dynamics. However, the development of numerical tools for simulating active fluids capable of incorporating non-trivial boundaries or inclusions has lagged behind. Active particle-based methods, which typically excel at this, suffer from large density fluctuations that affect the dynamics of inclusions. To this end, we advance the Active-Nematic Multi-Particle Collision Dynamics algorithm, a particle-based method for simulating active nematics, by addressing the large density fluctuations that arise from activity. This paper introduces three activity formulations that mitigate the coupling between activity and local density. Local density fluctuations are decreased to a level comparable to the passive limit while retaining active nematic phenomenology and increasing the active turbulence regime four-fold in two dimensions. These developments extend the technique into a flexible tool for modeling active systems, including solutes and inclusions, with broad applications for the study of biophysical systems. Particle-based models of soft active matter are known to exhibit large density fluctuations, which may be problematic for considering homogeneous systems. Through considering the coupling of activity to local density, we reduce density fluctuations while retaining active turbulent dynamics. [ABSTRACT FROM AUTHOR]

In the past year, biophysics obtained the first impact factor of 1.5. Before starting the new work, we will review and summarize the work in 2023 and make a simple plan for the work in 2024. [ABSTRACT FROM AUTHOR]

High-quality-factor (Q) optical microcavities have attracted extensive interest due to their unique ability to confine light for resonant circulation at the micrometer scale. Particular attention has been paid to optical whispering-gallery mode (WGM) microcavities to harness their strong light–matter interactions for biological applications. Remarkably, the combination of high-Q optical WGM microcavities with microfluidic technologies can achieve a synergistic effect in the development of high-sensitivity optofluidic sensors for many emerging biological analysis applications, such as the detection of proteins, nucleic acids, viruses, and exosomes. They can also be utilized to investigate the behavior of living cells in human organisms, which may provide new technical solutions for studies in cell biology and biophysics. In this paper, we briefly review recent progress in high-Q microcavity-based optofluidic sensor technologies and their applications in biological analysis. [ABSTRACT FROM AUTHOR]

This document discusses recent advancements in molecular biophysics research in Russia. The focus has shifted from studying individual molecules to analyzing protein complexes and understanding their regulation and structure. The document also highlights the development of technology for studying the functional activity of single molecules of enzymes using nanopores. Additionally, it explores research on the SARS-CoV-2 virus, including efforts to develop a vaccine, understand the body's response to different antibody vaccines, and investigate the inflammatory response caused by the virus. The document also mentions the identification of peptides from proteins that can regulate receptor activity and be used in the treatment of autoimmune and cancer diseases. Furthermore, it provides information on the SARS-CoV-2 proteome, different variants of the virus, and the molecular basis of their differences. The document concludes by discussing the importance of reviewing existing medications and the role of protein S-acylation in virus infectivity. Overall, this document provides valuable insights into the current state of molecular biophysics research in Russia and its implications for various fields, including drug discovery and virus understanding. [Extracted from the article]

Cutting-edge X-ray sources have enabled the structural dynamics of proteins to be tracked during biochemical processes, but the findings have been questioned. Two experts discuss the implications of a study that digs into this issue.Absorption of multiple photons alters structural dynamics of proteins. [ABSTRACT FROM AUTHOR]

Genomics methods have uncovered patterns in a range of biological systems, but obscure important aspects of cell behavior: the shapes, relative locations, movement, and interactions of cells in space. Spatial technologies that collect genomic or epigenomic data while preserving spatial information have begun to overcome these limitations. These new data promise a deeper understanding of the factors that affect cellular behavior, and in particular the ability to directly test existing theories about cell state and variation in the context of morphology, location, motility, and signaling that could not be tested before. Rapid advancements in resolution, ease-of-use, and scale of spatial genomics technologies to address these questions also require an updated toolkit of statistical methods with which to interrogate these data. We present a framework to respond to this new avenue of research: four open biological questions that can now be answered using spatial genomics data paired with methods for analysis. We outline spatial data modalities for each open question that may yield specific insights, discuss how conflicting theories may be tested by comparing the data to conceptual models of biological behavior, and highlight statistical and machine learning-based tools that may prove particularly helpful to recover biological understanding. [ABSTRACT FROM AUTHOR]

Precise measurement of magnetic fields is essential for various applications, such as fundamental physics, space exploration, and biophysics. Although recent progress in quantum engineering has assisted in creating advanced quantum magnetometers, there are still ongoing challenges in improving their efficiency and noise resistance. This study focuses on using symmetric graph state resources for quantum magnetometry to enhance measurement precision by analyzing the estimation theory under time-homogeneous and time-inhomogeneous noise models. The results show a significant improvement in estimating both single and multiple Larmor frequencies. In single Larmor frequency estimation, the quantum Fisher information spans a spectrum from the standard quantum limit to the Heisenberg limit within a periodic range of the Larmor frequency, and in the case of multiple Larmor frequencies, it can exceed the standard quantum limit for both noisy cases. This study highlights the potential of graph state-based methods for improving magnetic field measurements under noisy environments. [ABSTRACT FROM AUTHOR]

Background and Objectives: Effective diagnostics of depression state using instrumental methods of biopotentials measurement is promising both as a tool for increasing the efficiency of work of a diagnostician and for application in automated hardware and software therapy complexes, including those with biofeedback, allowing to create neuroadaptive systems for correction of psychoemotional and cognitive problems of patients. The purpose of this paper is to analyze the requirements to the methodology of biophysical data collection, hardware and software for their primary processing on the basis of open datasets of psychoemotional state determination, to formulate a methodology for the formation of multimodal datasets for the study of mental states, their changes, suitable for use in machine learning algorithms, to describe a possible method of realization of these requirements in hardware and software complexes. Materials and Methods: Open datasets of depressed patients were selected to analyze the main characteristics of datasets characterizing mental states. To formulate the main requirements, publications on the features of multimodal data application for the diagnosis of depressive disorders were reviewed. Results: The result of the work are the requirements to multimodal biopotential data for the study of psychoemotional states, the methodology and functional concept of hardware-software complex for their registration, the synchronization and recording in annotated form. Conclusion: The example of depressive disorder shows the usefulness and possibility of recording multimodal, synchronized annotated data on the psycho-emotional state of the subject for research, diagnostic purposes and application as a training sample in machine learning algorithms. The proposed methodology and the concept of the hardware-software complex allow to level out the main disadvantages of multimodal systems of biopotentials registration realized in the form of separate blocks and to supplement the instrumental data with annotation by state labels and time labels.

The neurophysiological effects of spinal cord stimulation (SCS) for chronic pain are poorly understood, resulting in inefficient failure-prone programming protocols and inadequate pain relief. Nonetheless, novel stimulation patterns are regularly introduced and adopted clinically. Traditionally, paresthetic sensation is considered necessary for pain relief, although novel paradigms provide analgesia without paresthesia. However, like pain relief, the neurophysiological underpinnings of SCS-induced paresthesia are unknown. Here, we paired biophysical modeling with clinical paresthesia thresholds (of both sexes) to investigate how stimulation frequency affects the neural response to SCS relevant to paresthesia and analgesia. Specifically, we modeled the dorsal column (DC) axonal response, dorsal column nucleus (DCN) synaptic transmission, conduction failure within DC fiber collaterals, and dorsal horn network output. Importantly, we found that high-frequency stimulation reduces DC fiber activation thresholds, which in turn accurately predicts clinical paresthesia perception thresholds. Furthermore, we show that high-frequency SCS produces asynchronous DC fiber spiking and ultimately asynchronous DCN output, offering a plausible biophysical basis for why high-frequency SCS is less comfortable and produces qualitatively different sensation than low-frequency stimulation. Finally, we demonstrate that the model dorsal horn network output is sensitive to SCS-inherent variations in spike timing, which could contribute to heterogeneous pain relief across patients. Importantly, we show that model DC fiber collaterals cannot reliably follow high-frequency stimulation, strongly affecting the network output and typically producing antinociceptive effects at high frequencies. Altogether, these findings clarify how SCS affects the nervous system and provide insight into the biophysics of paresthesia generation and pain relief. [ABSTRACT FROM AUTHOR]

The study of the phenomena occurring in the plantar region is remarkably intriguing, especially when performing a normal gait cycle where the foot is under loading conditions. The effects presented in the foot while walking provide relevant indicators regarding clinical means for enhancing regular performance or rehabilitation therapies. Nevertheless, more than traditional methods are needed to biomechanically evaluate foot structural conditions, leading to an incomplete database for determining the patient's needs so that advanced methodologies provide detailed medical assessment. Therefore, it is necessary to employ technological engineering tools to optimize biomechanical plantar pressure evaluations to reach suitable personalized treatments. This research initially evaluated numerically the pressure points in the foot sole region in each one of the five stance phases in a normal gait cycle. Medical imaging techniques were utilized to construct an anatomically accurate biomodel of the soft tissues of the right foot. The Finite Element Method was employed to predict peak plantar pressure in barefoot conditions for all stance phases; results from this case study presented a close alignment with gait experimental testing implemented to analyze the feasibility and validation of all mechanical considerations for the numerical analyses. Hence, having a solid foundation in the biomechanical behavior from the first case study close estimates, a 3D-printable patient-specific insole was designed and numerically analyzed to observe the mechanical response in the plantar critical zones utilizing a personalized orthotic device. Results from the second case study notably demonstrated a crucial decrement in excessive pressure values. Employing morphological customization orthopedics modeling combined with 3D-printable materials is revolutionizing assistive device design and fabrication techniques. The fundamental contribution of this research relies on deepening the knowledge of foot biomechanics from an interdisciplinary approach by numerically analyzing pressure distribution in critical regions for all five stances phases; thus, based on the methods employed, the results obtained contribute to the advances of patient-specific foot orthopedics. [ABSTRACT FROM AUTHOR]

The vagina is an essential component of the female reproductive system and is responsible for providing female sexual satisfaction. Vaginal smooth muscle contraction plays a crucial role in various physiological processes, including sexual arousal, childbirth, and urinary continence. In pathophysiological conditions, such as pelvic floor disorders, aberrations in vaginal smooth muscle function can lead to urinary incontinence and pelvic organ prolapse. A set of cellular and sub-cellular physiological mechanisms regulates the contractile properties of the vaginal smooth muscle cells. Calcium influx is a crucial determinant of smooth muscle contraction, facilitated through voltage-dependent calcium channels and calcium release from intracellular stores. Comprehensive reviews on smooth muscle biophysics are relatively scarce within the scientific literature, likely due to the complexity and specialized nature of the topic. The objective of this review is to provide a comprehensive description of alterations in the cellular physiology of vaginal smooth muscle contraction. The benefit associated with this particular approach is that conducting a comprehensive examination of the cellular mechanisms underlying contractile activation will enable the creation of more targeted therapeutic agents to control vaginal contraction disorders. [ABSTRACT FROM AUTHOR]

High‐resolution spatio‐temporal monitoring of the cell membrane lipid order provides visual insights into the complex and sophisticated systems that control cellular physiological functions. Solvatochromic fluorescent probes are highly promising noninvasive visualization tools for identifying the ordering of the microenvironment of plasma membrane microdomains. However, conventional probes, although capable of structural analysis, lack the necessary long‐term photostability required for live imaging at the cellular level. Here, an ultra‐high‐light‐resistant solvatochromic fluorescence probe, 2‐N,N‐diethylamino‐7‐(4‐methoxycarbonylphenyl)‐9,9‐dimethylfluorene (FπCM) is reported, which enables live lipid order imaging of cell division. This probe and its derivatives exhibit sufficient fluorescence wavelengths, brightness, polarity responsiveness, low phototoxicity, and remarkable photostability under physiological conditions compared to conventional solvatochromic probes. Therefore, these probes have the potential to overcome the limitations of fluorescence microscopy, particularly those associated with photobleaching. FπCM probes can serve as valuable tools for elucidating mechanisms of cellular processes at the bio‐membrane level. [ABSTRACT FROM AUTHOR]

Metal ions can perform multiple roles ranging from regulatory to structural and are crucial for cell function. While some metal ions like Na+ are ubiquitously present at high concentrations, other ions, especially Ca2+ and transition metals, such as Zn2+ or Cu+/2+ are regulated. The concentrations above or below the physiological range cause severe changes in the behavior of biomolecules that bind them and subsequently affect the cell wellbeing. This has led to the development of specialized protocols to study metal ion binding biomolecules in bulk conditions that mimic the cell environment. Recently, there is growing evidence of influence of post-transcriptional and post-translational modifications on the affinity of the metal ion binding sites. However, such targets are difficult to obtain in amounts required for classical biophysical experiments. Single molecule techniques have revolutionized the field of biophysics, molecular and structural biology. Their biggest advantage is the ability to observe each molecule's interaction independently, without the need for synchronization. An additional benefit is its extremely low sample consumption. This feature allows characterization of designer biomolecules or targets obtained coming from natural sources. All types of biomolecules, including proteins, DNA and RNA were characterized using single molecule methods. However, one group is underrepresented in those studies. These are the metal ion binding biomolecules. Single molecule experiments often require separate optimization, due to extremely different concentrations used during the experiments. In this review we focus on single molecule methods, such as single molecule FRET, nanopores and optical tweezers that are used to study metal ion binding biomolecules. We summarize various examples of recently characterized targets and reported experimental conditions. Finally, we discuss the potential promises and pitfalls of single molecule characterization on metal ion binding biomolecules. [ABSTRACT FROM AUTHOR]

In this study, a novel, high content technique using a cylindrical acoustic transducer, stroboscopic fast imaging, and homodyne detection to recover the mechanical properties (dynamic shear modulus) of living adherent cells at low ultrasonic frequencies is presented. By analyzing the micro‐oscillations of cells, whole populations are simultaneously mechanotyped with sub‐cellular resolution. The technique can be combined with standard fluorescence imaging allowing to further cross‐correlate biological and mechanical information. The potential of the technique is demonstrated by mechanotyping co‐cultures of different cell types with significantly different mechanical properties. [ABSTRACT FROM AUTHOR]

The modeling of biological systems has recently gained much attention considering the possibility to describe the time evolution of a biological system by employing differential equations. Different frameworks have been proposed depending on the number of dynamic variables. Ordinary differential equations (ODE) are employed if time is the only dynamic variable; partial differential equations (PDE) are proposed when, in addition to the time variable, space and/or velocity variables are considered. In the context of differential equation models, new frameworks have been proposed where stochastic terms are added to classical deterministic terms. A specific model is proposed when the differential equations are coupled to initial and/or boundary conditions. This editorial article deals with the topic of this special issue, which is devoted to the new developments in the multiscale modeling of complex biological systems with special attention to the interplay between different scholars. [ABSTRACT FROM AUTHOR]

Protein dynamics form a critical bridge between protein structure and function, yet the impact of evolution on ultrafast processes inside proteins remains enigmatic. This study delves deep into nanosecond-scale protein dynamics of a structurally and functionally conserved protein across species separated by almost a billion years, investigating ten homologs in complex with their ligand. By inducing a photo-triggered destabilization of the ligand inside the binding pocket, we resolved distinct kinetic footprints for each homolog via transient infrared spectroscopy. Strikingly, we found a cascade of rearrangements within the protein complex which manifest in time points of increased dynamic activity conserved over hundreds of millions of years within a narrow window. Among these processes, one displays a subtle temporal shift correlating with evolutionary divergence, suggesting reduced selective pressure in the past. Our study not only uncovers the impact of evolution on molecular processes in a specific case, but has also the potential to initiate a field of scientific inquiry within molecular paleontology, where species are compared and classified based on the rapid pace of protein dynamic processes; a field which connects the shortest conceivable time scale in living matter (10-9 s) with the largest ones (1016 s). [ABSTRACT FROM AUTHOR]

Bioelectronic Medicine stands as an emerging field that rapidly evolves and offers distinctive clinical benefits, alongside unique challenges. It consists of the modulation of the nervous system by precise delivery of electrical current for the treatment of clinical conditions, such as post-stroke movement recovery or drug-resistant disorders. The unquestionable clinical impact of Bioelectronic Medicine is underscored by the successful translation to humans in the last decades, and the long list of preclinical studies. Given the emergency of accelerating the progress in new neuromodulation treatments (i.e., drug-resistant hypertension, autoimmune and degenerative diseases), collaboration between multiple fields is imperative. This work intends to foster multidisciplinary work and bring together different fields to provide the fundamental basis underlying Bioelectronic Medicine. In this review we will go from the biophysics of the cell membrane, which we consider the inner core of neuromodulation, to patient care. We will discuss the recently discovered mechanism of neurotransmission switching and how it will impact neuromodulation design, and we will provide an update on neuronal and glial basis in health and disease. The advances in biomedical technology have facilitated the collection of large amounts of data, thereby introducing new challenges in data analysis. We will discuss the current approaches and challenges in high throughput data analysis, encompassing big data, networks, artificial intelligence, and internet of things. Emphasis will be placed on understanding the electrochemical properties of neural interfaces, along with the integration of biocompatible and reliable materials and compliance with biomedical regulations for translational applications. Preclinical validation is foundational to the translational process, and we will discuss the critical aspects of such animal studies. Finally, we will focus on the patient point-of-care and challenges in neuromodulation as the ultimate goal of bioelectronic medicine. This review is a call to scientists from different fields to work together with a common endeavor: accelerate the decoding and modulation of the nervous system in a new era of therapeutic possibilities. [ABSTRACT FROM AUTHOR]

The biophysical characteristics of the areas that can be seen while travelling on motorways have an impact on the perception of the landscape. Highways provide diverse landscape experiences to travellers according to their natural and cultural qualities. Especially coastal ways that combine with nature and the sea have a high potential for scenic attractiveness. This study aims to analyse the scenic attractiveness of coastal ways using GIS and RS techniques. Persembe-Bolaman coastal way in the Black Sea Region of Turkey was selected as a case study. Three road features and seven viewshed features that are assumed to affect landscape attractiveness on the Persembe-Bolaman coastal road were selected. The data set of these features was categorised into three clusters by k-means clustering, one of the unsupervised learning algorithms. The most attractive cluster in terms of scenic attractiveness was selected by determining the characteristics of the clusters. In conclusion, it was found that the scenic attractiveness was the highest in Cluster-1, which corresponds to 46.3% of the selected route. [ABSTRACT FROM AUTHOR]

In the context of the 21st century and the fourth industrial revolution, the substantial proliferation of data has established it as a valuable resource, fostering enhanced computational capabilities across scientific disciplines, including physics. The integration of Machine Learning stands as a prominent solution to unravel the intricacies inherent to scientific data. While diverse machine learning algorithms find utility in various branches of physics, there exists a need for a systematic framework for the application of Machine Learning to the field. This review offers a comprehensive exploration of the fundamental principles and algorithms of Machine Learning, with a focus on their implementation within distinct domains of physics. The review delves into the contemporary trends of Machine Learning application in condensed matter physics, biophysics, astrophysics, material science, and addresses emerging challenges. The potential for Machine Learning to revolutionize the comprehension of intricate physical phenomena is underscored. Nevertheless, persisting challenges in the form of more efficient and precise algorithm development are acknowledged within this review. [ABSTRACT FROM AUTHOR]

(1) Background: Skin barrier function resides mostly in the stratum corneum, which consists of a protein component, the corneocyte (bricks), which provides a scaffold for the second component, the extracellular matrix, consisting of multilayers of lipids (mortar). These two components closely interact and this could be the basis for the differences in the biophysical properties of the skin between anatomical regions. So, the aim of this study was to compare skin microstructural properties between body sites. (2) Methods: A comparative study was conducted that included healthy individuals without previous skin diseases. Skin barrier function parameters and microtopography parameters (smoothness, roughness, desquamation, wrinkles, surface, volume, contrast, variance, homogeneity, anisotropy, total cell count, flaking index, skin surface hardness, brightness, deformability and friction) were measured on the forearm, cheek and palm. (3) Results: 44 participants were included in this study, with a mean age of 38.8 ± 15.0 years. Significant differences were found between body sites for 14 of the 15 parameters evaluated. Smoothness was higher on the forearm than on the cheek and palm (240.02 Sems vs. 348.16 vs. 408.19 Sems, p < 0.05). Hardness was higher on the palm than on the forearm and cheek (13.22 AU vs. 9.44 AU vs. 7.94 AU, p < 0.05). Moreover, we observed that sociodemographic characteristics such as age, sex, tobacco and/or alcohol use, influenced the parameters evaluated. (4) Conclusions: The differences in skin barrier function and microtopography between anatomical regions reflects the different structure of skin in each body part and could help to understand the influence of the sociodemographic characteristics on theses parameters. This information could be useful for comparison with pathological skin characteristics and for targeting new treatments. [ABSTRACT FROM AUTHOR]

Coacervation, or liquid-liquid phase separation (LLPS) of biomacromolecules, is increasingly recognized to play an important role both intracellularly and in the extracellular space. Central questions that remain to be addressed are the links between the material properties of coacervates (condensates) and both the primary and the secondary structures of their constitutive building blocks. Short LLPS-prone peptides, such as GY23 variants explored in this study, are ideal model systems to investigate these links because simple sequence modifications and the chemical environment strongly affect the viscoelastic properties of coacervates. Herein, a systematic investigation of the structure/property relationships of peptide coacervates was conducted using GY23 variants, combining biophysical characterization (plate rheology and surface force apparatus, SFA) with secondary structure investigations by infrared (IR) and circular dichroism (CD) spectroscopy. Mutating specific residues into either more hydrophobic or more hydrophilic residues strongly regulates the viscoelastic properties of GY23 coacervates. Furthermore, the ionic strength and kosmotropic characteristics (Hofmeister series) of the buffer in which LLPS is induced also significantly impact the properties of formed coacervates. Structural investigations by CD and IR indicate a direct correlation between variations in properties induced by endogenous (peptide sequence) or exogenous (ionic strength, kosmotropic characteristics, aging) factors and the β-sheet content within coacervates. These findings provide valuable insights to rationally design short peptide coacervates with programmable materials properties that are increasingly used in biomedical applications. Peptide-based coacervates display interesting properties for biomedical applications, however, the link between peptide structure and coacervate material properties remains unclear. Here, the authors report a direct correlation between the primary and secondary structures of the peptides and the viscoelastic properties of the coacervates. [ABSTRACT FROM AUTHOR]

Multifunctional light sheet imaging flow cytometry of a large population of live cells at high throughput is challenging and requires new technological advancement. Existing cytometry techniques are limited due to point-based illumination that does not allow volume interrogation and biophysical parameter estimation on the go. Here, we propose a multifunctional (multichannel, multisheet and multicolor) imaging cytometry (M3IC) system that employs vertically-aligned multi-sheet array (VAMSA) illumination for interrogating cells flowing simultaneously through multiple microfluidic channels. We studied cancer cells (volume interrogation with organelle-level resolution and high signal-to-background-ratio(SBR)) at high throughput (~2500 nl/min). M3IC system demonstrates organelle-level resolution with a SBR comparable to that of confocal, especially at low flow rates. In addition, the multicolor imaging capability of the system facilitates multi-organelle investigation, determination of critical biophysical parameters, and drug (Paclitaxel) treatment studies on cancer cells. M3IC system is expected to advance the field of fluorescence microscopy, cell biophysics, disease biology and optical physics. One main obstacle of flow cytometry techniques is the inability to image internal structure of live cells on the go, posing challenges in deciphering their biological mechanisms. To overcome this limit, the authors devise a light-sheet-based multichannel, multisheet and multicolor volume imaging cytometry for interrogating cells flowing simultaneously through microfluidic channels. [ABSTRACT FROM AUTHOR]

Background. Catheter ablation failure poses a clinical challenge for epicardial or intramural ventricular arrhythmia (VA); however, guidewire ablation within the coronary venous system (CVS) may be effective and safe for targeting VAs. Methods. The ex vivo phase included four steps. In step 1, the steam pop incidence rates during guidewire ablation at power settings of 5, 10, 15, 20, and 25 W were analyzed using 10 mm- and 20 mm-tip guidewires. In step 2, guidewire ablation was performed for application durations of 10, 20, 30, 40, 50, 60, and 90 s, and the lesion size was measured. In step 3, the effects of saline infusion (0, 1, 2, 3, and 4 mL/min) on lesion dimensions and steam pop formation were examined. In step 4, an orthogonal array was constructed to obtain the optimal guidewire ablation parameters. In the in vivo phase, guidewire ablation within the CVS was performed in three dogs, and the lesion features in 10 days after ablation were observed. Results. In step 1, the steam pop incidence rates at 5, 10, 15, 20, and 25 W were 0%, 0%, 12.5%, 62.5%, and 100% using the 10 mm-tip guidewires and 0%, 0%, 0%, 25%, and 75% using the 20 mm-tip guidewires, respectively. In step 2, we found that the lesion areas increased with an increase in the ablation duration (the maximum lesion diameters at 30, 60, and 90 s were 4.9 ± 0.4, 7.0 ± 0.8, and 9.2 ± 0.7 mm in the 10 mm group and 3.2 ± 0.5, 4.5 ± 0.4, and 5.3 ± 0.7 mm in the 20 mm-tip group, respectively). In step 3, we observed that saline infusion was negatively correlated with ablation lesions but had a lower risk of steam pop. The optimal parameters for the 20 mm-tip guidewire ablation were 15 W, 50 s, and 2 mL/min or 20 W, 70 s, and 2 mL/min. In the in vivo phase, effective ablation lesions with maximum and minimum diameters of 3.2 ± 0.3 and 2.8 ± 0.5 mm, respectively, were created by the guidewires during the 10-day observation period after ablation. Conclusion. This novel radiofrequency guidewire ablation technique can feasibly create effective lesions within the CVS, which may improve the efficacy of catheter ablation for challenging epicardial or intramural VA. [ABSTRACT FROM AUTHOR]

Cells that form tissue barriers rely on cell–cell contacts called tight junctions. These structures assemble from protein condensates that spread along the cell membrane like a water droplet spreading over glass.Step-by-step formation of tight junctions between epithelial cells. [ABSTRACT FROM AUTHOR]