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Abstract Background Phospholipase C gamma 1 (PLCγ1) is an important mediator of the T cell receptor (TCR) and growth factor signaling. PLCγ1 is activated by Src family kinases (SFKs) and produces inositol 1,4,5-triphosphate (InsP3) from phosphatidylinositol 4,5-bisphosphate (PIP2). Inositol polyphosphate multikinase (IPMK) is a pleiotropic enzyme with broad substrate specificity and non-catalytic activities that mediate various functional protein-protein interactions. Therefore, IPMK plays critical functions in key biological events such as cell growth. However, the contribution of IPMK to the activation of PLCγ1 in TCR signaling remains mostly unelucidated. The current study aimed to elucidate the functions of IPMK in TCR signaling and to uncover the mode of IPMK-mediated signaling action in PLCγ1 activation. Methods Concanavalin A (ConA)-induced acute hepatitis model was established in CD4+ T cell-specific IPMK knockout mice (IPMKΔCD4). Histological analysis was performed to assess hepatic injury. Primary cultures of naïve CD4+ T cells were used to uncover the role of mechanisms of IPMK in vitro. Western blot analysis, quantitative real-time PCR, and flow cytometry were performed to analyze the TCR-stimulation-induced PLCγ1 activation and the downstream signaling pathway in naïve CD4+ T cells. Yeast two-hybrid screening and co-immunoprecipitation were conducted to identify the IPMK-binding proteins and protein complexes. Results IPMKΔCD4 mice showed alleviated ConA-induced acute hepatitis. CD4+ helper T cells in these mice showed reduced PLCγ1 Y783 phosphorylation, which subsequently dampens calcium signaling and IL-2 production. IPMK was found to contribute to PLCγ1 activation via the direct binding of IPMK to Src-associated substrate during mitosis of 68 kDa (Sam68). Mechanistically, IPMK stabilizes the interaction between Sam68 and to PLCγ1, thereby promoting PLCγ1 phosphorylation. Interfering this IPMK-Sam68 binding interaction with IPMK dominant-negative peptides impaired PLCγ1 phosphorylation. Conclusions Our results demonstrate that IPMK non-catalytically promotes PLCγ1 phosphorylation by stabilizing the PLCγ1–Sam68 complex. Targeting IPMK in CD4+ T cells may be a promising strategy for managing immune diseases caused by excessive stimulation of TCR.

Abstract Although sevoflurane is generally considered safe, reports suggest that sevoflurane may cause postoperative liver injury more frequently than previously believed. Therefore, we aimed to compare the incidence of clinically significant postoperative liver injury following non-cardiac surgery between patients who underwent sevoflurane anesthesia and propofol-based total intravenous anesthesia. We retrospectively reviewed adult surgical patients from January 2010 to September 2022 who underwent general anesthesia in our center using sevoflurane or propofol over 3 h. After 1:1 propensity score matching, the incidence of postoperative liver injury was compared between the two groups. Out of 58,300 patients reviewed, 44,345 patients were included in the analysis. After propensity score matching, 7767 patients were included in each group. The incidence of postoperative liver injury was 1.4% in the sevoflurane group, which was similar to that in the propofol group (1.6%; p = 0.432). Comparison of the severity of postoperative alanine aminotransferase elevation showed that the incidence of borderline and mild elevation was higher in the sevoflurane group, but there was no difference in the incidence of moderate and severe elevation. In conclusion, sevoflurane anesthesia over 3 h was not associated with a higher incidence of clinically significant postoperative liver injury compared to propofol anesthesia.

Background/Aims Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by fat accumulation in the liver. MASLD encompasses both steatosis and MASH. Since MASH can lead to cirrhosis and liver cancer, steatosis and MASH must be distinguished during patient treatment. Here, we investigate the genomes, epigenomes, and transcriptomes of MASLD patients to identify signature gene set for more accurate tracking of MASLD progression. Methods Biopsy-tissue and blood samples from patients with 134 MASLD, comprising 60 steatosis and 74 MASH patients were performed omics analysis. SVM learning algorithm were used to calculate most predictive features. Linear regression was applied to find signature gene set that distinguish the stage of MASLD and to validate their application into independent cohort of MASLD. Results After performing WGS, WES, WGBS, and total RNA-seq on 134 biopsy samples from confirmed MASLD patients, we provided 1,955 MASLD-associated features, out of 3,176 somatic variant callings, 58 DMRs, and 1,393 DEGs that track MASLD progression. Then, we used a SVM learning algorithm to analyze the data and select the most predictive features. Using linear regression, we identified a signature gene set capable of differentiating the various stages of MASLD and verified it in different independent cohorts of MASLD and a liver cancer cohort. Conclusions We identified a signature gene set (i.e., CAPG, HYAL3, WIPI1, TREM2, SPP1, and RNASE6) with strong potential as a panel of diagnostic genes of MASLD-associated disease.

The structure of a ship is completed by processing various steel plates and welding these plates. This butt welding of plates is defined as a seam in shipyards, and this study seeks to find a way to decrease costs by reducing the utilization of steel through effective seam arrangement. Seams were defined and classified according to purpose, and examples of “pieces” and “main plates” where seam creation had an economical saving effect were selected. For “pieces,” the change in the weight of steel utilized depending on the presence or absence of a seam was calculated, and the resulting change in cost increase was presented. In the case of the “main plate,” the quantity of seams does not change, but an example of cost variation due to the appropriate placement of seams is presented. Hence, a large difference was found in the costs of “pieces” depending on seam location. Thus, it was advantageous to create additional seams. For the “main plate,” it was found that narrow-width and wide-width materials incur more costs. This study demonstrates that creating seams is economically advantageous but may not be preferred owing to the increased workload from a production perspective.

Abstract Regulatory T cells (Treg) are CD4+ T cells with immune-suppressive function, which is defined by Foxp3 expression. However, the molecular determinants defining the suppressive population of T cells have yet to be discovered. Here we report that the cell surface protein Lrig1 is enriched in suppressive T cells and controls their suppressive behaviors. Within CD4+ T cells, Treg cells express the highest levels of Lrig1, and the expression level is further increasing with activation. The Lrig1+ subpopulation from T helper (Th) 17 cells showed higher suppressive activity than the Lrig1- subpopulation. Lrig1-deficiency impairs the suppressive function of Treg cells, while Lrig1-deficient naïve T cells normally differentiate into other T cell subsets. Adoptive transfer of CD4+Lrig1+ T cells alleviates autoimmune symptoms in colitis and lupus nephritis mouse models. A monoclonal anti-Lrig1 antibody significantly improves the symptoms of experimental autoimmune encephalomyelitis. In conclusion, Lrig1 is an important regulator of suppressive T cell function and an exploitable target for treating autoimmune conditions.

Abstract We reveal and justify, both theoretically and experimentally, the existence of a unifying criterion of the boiling crisis. This criterion emerges from an instability in the near-wall interactions of bubbles, which can be described as a percolation process driven by three fundamental boiling parameters: nucleation site density, average bubble footprint radius and product of average bubble growth time and detachment frequency. Our analysis suggests that the boiling crisis occurs on a well-defined critical surface in the multidimensional space of these parameters. Our experiments confirm the existence of this unifying criterion for a wide variety of boiling surface geometries and textures, two boiling regimes (pool and flow boiling) and two fluids (water and liquid nitrogen). This criterion constitutes a simple mechanistic rule to predict the boiling crisis, also providing a guiding principle for designing boiling surfaces that would maximize the nucleate boiling performance.

Nuclear power plants (NPPs) have technical specifications (Tech Specs) to ensure that the equipment and key operating parameters necessary for the safe operation of the power plant are maintained within limiting conditions for operation (LCO) determined by a safety analysis. The LCO of Tech Specs that identify the lowest functional capability of equipment required for safe operation for a facility must be complied for the safe operation of NPP.There have been previous studies to aid in compliance with LCO relevant to rule-based expert systems; however, there is an obvious limit to expert systems for implementing the rules for many situations related to LCO. Therefore, in this study, we present a retrieval methodology for similar LCO cases in determining whether LCO is met or not met. To reflect the natural language processing of NPP features, a domain dictionary was built, and the optimal term frequency-inverse document frequency variant was selected. The retrieval performance was improved by adding a Boolean retrieval model based on terms related to the LCO in addition to the vector space model. The developed domain dictionary and retrieval methodology are expected to be exceedingly useful in determining whether LCO is met.

Because nuclear power plants (NPPs) are safety-critical infrastructure, it is essential to increase their safety and minimize risk. To reduce human error and support decision-making by operators, several artificial-intelligence-based diagnosis methods have been proposed. However, because of the nature of data-driven methods, conventional artificial intelligence requires large amount of measurement values to train and achieve enough diagnosis resolution.We propose a graph neural network (GNN) based accident diagnosis algorithm to achieve high diagnosis resolution with limited measurements. The proposed algorithm is trained with both the knowledge about physical correlation between components and measurement values. To validate the proposed methodology has a sufficiently high diagnostic resolution with limited measurement values, the diagnosis of multiple accidents was performed with limited measurement values and also, the performance was compared with convolution neural network (CNN). In case of the experiment that requires low diagnostic resolution, both CNN and GNN showed good results. However, for the tests that requires high diagnostic resolution, GNN greatly outperformed the CNN.

According to the defense-in-depth concept, not only a preventive strategy but also an integrated cyberattack response strategy for NPPs should be established. However, there are limitations in terms of responding to penetrations, and the existing EOPs are insufficient for responding to intentional disruptions. In this study, we focus on manipulative attacks on process data. Based on an analysis of the related attack vectors and possible attack scenarios, we adopt the Kalman filter to detect process anomalies that can be caused by manipulations of process data. To compensate for these manipulations and secure MCR operators' situational awareness, we modify the Kalman filter such that it can filter out the effects of the manipulations adaptively. A case study was conducted using a hardware-in-the-loop system. The results indicated that the developed method can be used to verify whether the displayed safety-related state data are reliable and to implement the required safety response actions.

As regulatory bodies require full implementation of security controls in nuclear power plants (NPPs), security functions for critical digital assets are currently being developed. For the ultimate introduction of security controls, not alternative measures, it is important to understand the relationship between possible cyber threats to NPPs and security controls to prevent them. To address the effectiveness of the security control implementation, this study investigated the types of cyber threats that can be prevented when the security controls are implemented through the mapping of the reorganized security controls in RS-015 to cyber threats on NPPs. Through this work, the cyber threat that each security control can prevent was confirmed, and the effectiveness of several strategies for implementing the security controls were compared.This study will be a useful reference for utilities or researchers who cannot use design basis threat (DBT) directly and be helpful when introducing security controls to NPPs that do not have actual security functions.

As numerous communication devices use multiband electromagnetic waves in modern society, electromagnetic interference (EMI) shielding materials become increasingly important due to the harmful effects of electromagnetic waves. While metal-based materials have shown high shielding performance, they have many drawbacks such as high density, high processing cost, and low corrosion resistance. Conductive polymer composites (CPCs), which can overcome these shortcomings of metal-based materials, have become increasingly popular in recent years. In this study, non-oxidized graphene flakes (NOGFs) are synthesized by exfoliating the ternary graphite intercalant compound (t-GIC) and used as fillers for CPCs. The electrical conductivity and EMI shielding effiency (SE) of NOGF/polyvinylidene fluoride (PVDF), graphite/PVDF and reduced graphene oxide (rGO)/PVDF composites are investigated. NOGF/PVDF composites showed notably enhanced electrical conductivity and EMI SE than the others. This is mostly due to the non-oxidative fabrication method that does not destroy the sp2 structure of graphene sheet, thus preserving the unique electrical properties of graphene. [ABSTRACT FROM AUTHOR]

Studies have been conducted on Energy storage systems (ESS) that replaced lithium-ion batteries (LIB) by the thermal runaway of the existing LIB. Using only the supercapacitor (SC) as a direct current power source in applications such as supercapacitor-based ESSs and mobile electric vehicle charging stations (MCSs) reduces the output voltage of the SC linearly. To solve this problem, this paper combines a boost converter capable of achieving regulatable constant voltage from an input of an SC bank to an output of a rectifier and an inductor/capacitor/capacitor (LCC) resonance converter. In this paper, an electrical double-layer capacitor (EDLC) known as SC was constructed as 64.8-V 400-FEDLC for experimental analysis. This EDLC is a high-capacity EDLC bank using 120 EDLCs with 30 serial connections and 4 parallel connections. In addition, resonance compensation circuits are analyzed and designed using a first-order harmonic approximation method (FHA). The analysis shows that the LCC resonance compensation converter is more suitable for EDLC standalone systems as an energy storage system, for LCC resonance converter topologies combined with EDLC discharge characteristics, constant voltage discharge is designed under an efficient discharge strategy, i.e., variable load conditions after the first constant voltage discharge. Based on LCC compensation analysis, the system has an optimum frequency, which allows the system to operate at the maximum efficiency point. By combining constant voltage power characteristics, constant voltage power becomes the same as the optimal power point, and thus high efficiency could be maintained in the constant voltage stage. Finally, the above design is verified through experiments.

Breath volatile organic compound (VOC) analysis is a non-invasive tool for assessing health status; the compositional profile of these compounds in the breath of patients with chronic kidney disease is believed to change with decreasing renal function. We aimed to identify breath VOCs for recognizing patients with chronic kidney disease. Using thermal desorption–gas chromatography/mass spectrometry, untargeted analysis of breath markers was performed using breath samples of healthy controls (n = 18) versus non-dialysis (n = 21) and hemodialysis (n = 12) patients with chronic kidney disease in this cross-sectional study. A total of 303 VOCs alongside 12 clinical variables were used to determine the breath VOC profile. Metabolomic analysis revealed that age, systolic blood pressure, and fifty-eight breath VOCs differed significantly between the chronic kidney disease group (non-dialysis + hemodialysis) and healthy controls. Thirty-six VOCs and two clinical variables that showed significant associations with chronic kidney disease in the univariate analysis were further analyzed. Different spectra of breath volatile organic compounds between the control and chronic kidney disease groups were obtained. A multivariate model incorporating age, 2-methyl-pentane, and cyclohexanone showed high performance (accuracy, 86%) in identifying patients with chronic kidney disease with odds ratios of 0.18 (95% CI, 0.07–2.49, p = 0.013); 2.10 (0.94–2.24, p = 0.025); and 2.31 (0.88–2.64, p = 0.008), respectively. Hence, this study showed that renal dysfunction induces a characteristic profile of breath VOCs that can be used as non-invasive potential biomarkers in screening tests for CKD.

Spontaneous intracranial hypotension (SIH) is not rare, but its diagnosis remains challenging. SIH tends to be misdiagnosed as postdural puncture headache when orthostatic headache develops subsequent to spinal anesthesia because both have similar symptoms. We report the case of a 35-year-old man with orthostatic headache following spinal anesthesia, who did not respond to conventional therapy for postdural puncture headache. SIH was confirmed after epidural fluid collection was identified at the thoracic spine level on magnetic resonance myelography. Physicians must consider SIH despite a history of neuraxial block. Diagnostic work-up is necessary to identify potential cerebrospinal fluid leakage in refractory cases.

Ultrasound provides direct visualization of blood vessels and soft tissues around the sympathetic chain and potentially minimizes injury to these critical anatomic structures when performing stellate ganglion block (SGB). We report an atypical left vertebral artery course detected during an ultrasound prescan before performing a SGB. The left vertebral and inferior thyroid arteries were identified on the longus colli muscle's ventral surface at the C6 level. This report was the first to demonstrate ultrasound images of a vulnerable vertebral artery to intravascular injection. The study emphasized the importance of identifying the sonoanatomy before performing procedures involving the anterior cervical vertebrae.

The survival of motor neuron (SMN) protein is a major component of the pre-mRNA splicing machinery and is required for RNA metabolism. Although SMN has been considered a fundamental gene for the central nervous system, due to its relationship with neuromuscular diseases, such as spinal muscular atrophy, recent studies have also revealed the requirement of SMN in non-neuronal cells in the peripheral regions. Here, we report that the fibro-adipogenic progenitor subpopulation expressing Dpp4 (Dpp4+ FAPs) is required for the neuromuscular system. Furthermore, we also reveal that BRCA1-associated protein-1 (Bap1) is crucial for the stabilization of SMN in FAPs by preventing its ubiquitination-dependent degradation. Inactivation of Bap1 in FAPs decreased SMN levels and accompanied degeneration of the neuromuscular junction, leading to loss of motor neurons and muscle atrophy. Overexpression of the ubiquitination-resistant SMN variant, SMNK186R, in Bap1-null FAPs completely prevented neuromuscular degeneration. In addition, transplantation of Dpp4+ FAPs, but not Dpp4– FAPs, completely rescued neuromuscular defects. Our data reveal the crucial role of Bap1-mediated SMN stabilization in Dpp4+ FAPs for the neuromuscular system and provide the possibility of cell-based therapeutics to treat neuromuscular diseases.

Summary: Dermal fibroblasts lose stem cell potency after birth, which prevents regenerative healing. However, the underlying intracellular mechanisms are largely unknown. We uncover the postnatal maturation of papillary fibroblasts (PFs) driven by the extensive Twist2-mediated remodeling of chromatin accessibility. A loss of the regenerative ability of postnatal PFs occurs with decreased H3K27ac levels. Single-cell transcriptomics, assay for transposase-accessible chromatin sequencing (ATAC-seq), and chromatin immunoprecipitation sequencing (ChIP-seq) reveal the postnatal maturation trajectory associated with the loss of the regenerative trajectory in PFs, which is characterized by a marked decrease in chromatin accessibility and H3K27ac modifications. Histone deacetylase inhibition delays spontaneous chromatin remodeling, thus maintaining the regenerative ability of postnatal PFs. Genomic analysis identifies Twist2 as a major regulator within chromatin regions with decreased accessibility during the postnatal period. When Twist2 is genetically deleted in dermal fibroblasts, the intracellular cascade of postnatal maturation is significantly delayed. Our findings reveal the comprehensive intracellular mechanisms underlying intrinsic postnatal changes in dermal fibroblasts.

Background The purpose of this study was to compare the anatomical features of the internal mammary vessels (IMVs) at the second and third intercostal spaces (ICSs) with regard to their use as recipient vessels in deep inferior epigastric artery perforator (DIEP) flap breast reconstruction. Methods A total of 38 consecutive DIEP breast reconstructions in 36 patients were performed using IMVs as recipient vessels between March 2017 and August 2018. The intraoperative findings and postoperative complications were analyzed. Anatomical analyses were performed using intraoperative measurements and computed tomography (CT) angiographic images. Results CT angiographic analysis revealed the mean diameter of the deep inferior epigastric artery to be 2.42±0.27 mm, while that of the deep inferior epigastric vein was 2.91±0.30 mm. A larger mean vessel diameter was observed at the second than at the third ICS for both the internal mammary artery (2.26±0.32 mm vs. 1.99±0.33 mm, respectively; P=0.001) and the internal mammary vein (IMv) (2.52±0.46 mm vs. 2.05±0.42 mm, respectively; P

It is reported that about 20% of accidents at nuclear power plants in Korea and abroad are caused by human error. One of the main factors contributing to human error is fatigue, so it is necessary to prevent human errors that may occur when the task is performed in an improper state by grasping the status of the operator in advance. In this study, we propose a method of evaluating operator's fitness-for-duty (FFD) using various parameters including eye movement data, subjective fatigue ratings, and operator's performance. Parameters for evaluating FFD were selected through a literature survey. We performed experiments that test subjects who felt various levels of fatigue monitor information of indicators and diagnose a system malfunction. In order to find meaningful characteristics in measured data consisting of various parameters, hierarchical clustering analysis, an unsupervised machine-learning technique, is used. The characteristics of each cluster were analyzed; fitness-for-duty of each cluster was evaluated. The appropriateness of the number of clusters obtained through clustering analysis was evaluated using both the Elbow and Silhouette methods. Finally, it was statistically shown that the suggested methodology for evaluating FFD does not generate additional fatigue in subjects. Relevance to industry: The methodology for evaluating an operator's fitness for duty in advance is proposed, and it can prevent human errors that might be caused by inappropriate condition in nuclear industries. Keywords: Fatigue, Eye tracking, Fitness for duty (FFD), Clustering analysis

Objectives As of March 3, 2020, the Shincheonji religious group accounted for the majority of Korean cases of coronavirus disease 2019 (COVID-19). Nonetheless, the most likely cause of the broad spread of COVID-19 among members of the Shincheonji religious group remains largely unknown. Methods We obtained data of laboratory-confirmed cases related to the Shincheonji religious group from press releases by Korean public health authorities and news reports. We measured the period from the date of illness onset to the date of COVID-19 confirmation. Results We analysed data from 59 cases (median age, 30 years). The estimated median period between the date of symptom onset and the date of COVID-19 confirmation was 4 days (95% confidence interval, 1-12). Conclusions There was a delay in COVID-19 confirmation from the date of illness onset among the cases linked to the Shincheonji religious group. This delay likely contributed to the occurrence of many cases of COVID-19 in the group.

Nuclear Power Plants (NPPs) are physically isolated from external networks and have different operational environments than conventional information technology (IT) systems. Accordingly, NPPs were regarded as safe from external cyber-attacks. However, it was later determined that isolated networks are not safe from cyber-attacks. Malicious data injection attacks on Programmable Logic Controllers (PLCs) deployed in the safety system of NPPs are critical to nuclear facilities, as they were in the Stuxnet attack. It is necessary to monitor the integrity of PLC data and protect the PLCs from cyber threats such as modification of deployed logic or setpoints. To address this problem, this paper proposes a novel system for monitoring data integrity of PLCs using blockchain technologies. Considering the NPP environment, we developed a private blockchain system to monitor the data integrity of PLCs. The new concept that is Proof of Monitoring (PoM) for data integrity of PLCs was proposed to overcome the limitation for applying the private blockchain to the cybersecurity of NPPs. Additionally, we developed an integrity monitoring system for the Reactor Protection System (RPS)-a safety system in NPPs-using the developed blockchain. It can detect cyber-attacks (such as false code injection attacks on PLCs) and monitor which PLC integrity has been compromised in real-time. A validation experiment using a false data injection attack on PLCs was performed on the developed system, and the results confirmed that the developed system successfully monitored the modification of data in the PLCs.

Due to the prolonged COVID-19 pandemic, wearing masks has become essential for social interaction, disturbing emotion recognition in daily life. In the present study, a total of 39 Korean participants (female = 20, mean age = 24.2 years) inferred seven emotions (happiness, surprise, fear, sadness, disgust, anger, surprise, and neutral) from uncovered, mask-covered, sunglasses-covered faces. The recognition rates were the lowest under mask conditions, followed by the sunglasses and uncovered conditions. In identifying emotions, different emotion types were associated with different areas of the face. Specifically, the mouth was the most critical area for happiness, surprise, sadness, disgust, and anger recognition, but fear was most recognized from the eyes. By simultaneously comparing faces with different parts covered, we were able to more accurately examine the impact of different facial areas on emotion recognition. We discuss the potential cultural differences and the ways in which individuals can cope with communication in which facial expressions are paramount.

We develop an extended Kalman filter-based vehicle tracking algorithm, specifically designed for uniform planar array layouts and vehicle platoon scenarios. We first propose an antenna placement strategy to design the optimal antenna array configuration for precise vehicle tracking in vehicle-to-infrastructure networks. Furthermore, a vehicle tracking algorithm is proposed to improve the position estimation performance by specifically considering the characteristics of the state evolution model for vehicles in the platoon. The proposed algorithm enables the sharing of corrected error transition vectors among platoon vehicles, for the purpose of enhancing the tracking performance for vehicles in unfavorable positions. Lastly, we propose an array partitioning algorithm that effectively divides the entire antenna array into sub-arrays for vehicles in the platoon, aiming to maximize the average tracking performance. Numerical studies verify that the proposed tracking and array partitioning algorithms improve the position estimation performance. [ABSTRACT FROM AUTHOR]

We report a case of autologous breast reconstruction in which a thoracodorsal vessel was used as a recipient vessel after a hypoplastic internal mammary vessel was found on preoperative computed tomography (CT) angiography. A 46-year-old woman with no underlying disease was scheduled to undergo skin-sparing mastectomy and breast reconstruction using a deep inferior epigastric artery perforator flap. Preoperative CT angiography showed segmental occlusion of the right subclavian artery with severe atherosclerosis and calcification near the origin of the internal mammary artery, with distal flow maintained by collateral branches. The thoracodorsal artery was selected to be the recipient vessel because CT showed that it was of adequate size and was not affected by atherosclerosis. The patient experienced no postoperative complications, and the flap survived with no vascular complications. The breasts were symmetrical at a 6-month follow-up. This case highlights that preoperative vascular imaging modalities may help surgeons avoid using diseased vessels as recipient vessels in free flap breast reconstructions.

To assess the availability of a nuclear power plant’s dynamic systems, it is necessary to consider the impact of dynamic interactions, such as components, software, and operating processes. However, there is currently no simple, easy-to-use tool for assessing the availability of these dynamic systems. The existing method, such as Markov chains, derives an accurate solution but has difficulty in modeling the system. When using conventional fault trees, the reliability of a system with dynamic characteristics cannot be evaluated accurately because the fault trees consider reliability of a specific operating configuration of the system. The dynamic reliability graph with general gates (DRGGG) allows an intuitive modeling similar to the actual system configuration, which can reduce the human errors that can occur during modeling of the target system. However, because the current DRGGG is able to evaluate the dynamic system in terms of only reliability without repair, a new evaluation method that can calculate the availability of the dynamic system with repair is proposed through this study. The proposed method extends the DRGGG by adding the repair condition to the dynamic gates. As a result of comparing the proposed method with Markov chains regarding a simple verification model, it is confirmed that the quantified value converges to the solution. Keywords: Dynamic system availability, Reliability graph with general gates, Extended dynamic gates