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Abstract The importance of 3D reconstruction of coronary arteries using multiple coronary angiography (CAG) images has been increasingly recognized in the field of cardiovascular disease management. This process relies on the camera matrix’s optimization, needing correspondence info for identical point positions across two images. Therefore, an automatic method for determining correspondence between two CAG images is highly desirable. Despite this need, there is a paucity of research focusing on image matching in the CAG images. Additionally, standard deep learning image matching techniques often degrade due to unique features and noise in CAG images. This study aims to fill this gap by applying a deep learning-based image matching method specifically tailored for the CAG images. We have improved the structure of our point detector and redesigned loss function to better handle sparse labeling and indistinct local features specific to CAG images. Our method include changes to training loss and introduction of a multi-head descriptor structure leading to an approximate 6% improvement. We anticipate that our work will provide valuable insights into adapting techniques from general domains to more specialized ones like medical imaging and serve as an improved benchmark for future endeavors in X-ray image-based correspondence matching.

Abstract Free radical is a marker in various inflammatory diseases. The antioxidant effect protects us from this damage, which also plays an essential role in preventing inflammation. Inflammation protects the body from biological stimuli, and pro-inflammatory mediators are negatively affected in the immune system. Inflammation caused by LPS is an endotoxin found in the outer membrane of Gram-negative bacteria, which induces immune cells to produce inflammatory cytokines such as cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase. Based on this, the antioxidant and anti-inflammatory effects of plant extracts were investigated. First, the main phenolic compounds for the five peaks obtained from Stachys affinis extract (SAE) were identified. The antioxidant effect of each phenolic compound was confirmed through HPLC analysis before and after the competitive binding reaction between DPPH and the extract. Afterward, the anti-inflammatory effect of each phenolic compound was confirmed through competitive binding between COX2 and the extract in HPLC analysis. Lastly, the anti-inflammatory effect of SAE was confirmed through in vitro experiments and also confirmed in terms of structural binding through molecular docking. This study confirmed that phenolic compounds in SAE extract have potential antioxidant and anti-inflammatory effects, and may provide information for primary screening of medicinal plants.

In an 8-year period at two medical center, 138 patients underwent uterine artery embolization, and 11 of them were diagnosed with uterine necrosis. Among them, three were successfully conceived. However, one of them developed an arteriovenous malformation after an artificial abortion, and another experienced complications, including placenta previa and placenta accreta spectrum, which resulted in early preterm delivery and recurrent postpartum hemorrhage, necessitating subtotal hysterectomy. Therefore, it is crucial to prepare for potential adverse pregnancy outcomes in subsequent pregnancies for patients with a history of uterine necrosis.

Background/Aims Since the coronavirus disease 2019 (COVID-19) outbreak, hospitals have implemented infection control measures to minimize the spread of the virus within facilities. This study aimed to investigate the impact of COVID-19 on the incidence of healthcare-associated infections (HCAIs) and common respiratory virus (cRV) infections in hematology units. Methods This retrospective study included all patients hospitalized in Catholic Hematology Hospital between 2019 and 2020. Patients infected with vancomycin-resistant Enterococci (VRE), carbapenemase-producing Enterobacterales (CPE), Clostridium difficile infection (CDI), and cRV were analyzed. The incidence rate ratio (IRR) methods and interrupted time series analyses were performed to compare the incidence rates before and after the pandemic. Results The incidence rates of CPE and VRE did not differ between the two periods. However, the incidence of CDI increased significantly (IRR: 1.41 [p = 0.002]) after the COVID-19 pandemic. The incidence of cRV infection decreased by 76% after the COVID-19 outbreak (IRR: 0.240 [p < 0.001]). The incidence of adenovirus, parainfluenza virus, and rhinovirus infection significantly decreased in the COVID-19 period (IRRs: 0.087 [p = 0.003], 0.031 [p < 0.001], and 0.149 [p < 0.001], respectively). Conclusions The implementation of COVID-19 infection control measures reduced the incidence of cRV infection. However, CDI increased significantly and incidence rates of CPE and VRE remained unchanged in hematological patients after the pandemic. Infection control measures suitable for each type of HCAI, such as stringent hand washing for CDI and enough isolation capacities, should be implemented and maintained in future pandemics, especially in immunocompromised patients.

Objectives Education in biomedical and health informatics is essential for managing complex healthcare systems, bridging the gap between healthcare and information technology, and adapting to the digital requirements of the healthcare industry. This review presents the current status of biomedical and health informatics education domestically and internationally and proposes recommendations for future development. Methods We analyzed evidence from reports and papers to explore global trends and international and domestic examples of education. The challenges and future strategies in Korea were also discussed based on the experts’ opinions. Results This review presents international recommendations for establishing education in biomedical and health informatics, as well as global examples at the undergraduate and graduate levels in medical and nursing education. It provides a thorough examination of the best practices, strategies, and competencies in informatics education. The review also assesses the current state of medical informatics and nursing informatics education in Korea. We highlight the challenges faced by academic institutions and conclude with a call to action for educators to enhance the preparation of professionals to effectively utilize technology in any healthcare setting. Conclusions To adapt to the digitalization of healthcare, systematic and continuous workforce development is essential. Future education should prioritize curriculum innovations and the establishment of integrated education programs, focusing not only on students but also on educators and all healthcare personnel in the field. Addressing these challenges requires collaboration among educational institutions, academic societies, government agencies, and international bodies dedicated to systematic and continuous workforce development.

Abstract Background Interhospital transfer (IHT) is necessary for providing ultimate care in the current emergency care system, particularly for patients with severe trauma. However, studies on IHT during the pandemic were limited. Furthermore, evidence on the effects of the coronavirus disease 2019 (COVID-19) pandemic on IHT among patients with major trauma was lacking. Method This retrospective cohort study was conducted in an urban trauma center (TC) of a tertiary academic affiliated hospital in Daegu, Korea. The COVID-19 period was defined as from February 1, 2020 to January 31, 2021, whereas the pre-COVID-19 period was defined as the same duration of preceding span. Clinical data collected in each period were compared. We hypothesized that the COVID-19 pandemic negatively impacted IHT. Results A total of 2,100 individual patients were included for analysis. During the pandemic, the total number of IHTs decreased from 1,317 to 783 (− 40.5%). Patients were younger (median age, 63 [45–77] vs. 61[44–74] years, p = 0.038), and occupational injury was significantly higher during the pandemic (11.6% vs. 15.7%, p = 0.025). The trauma team activation (TTA) ratio was higher during the pandemic both on major trauma (57.3% vs. 69.6%, p = 0.006) and the total patient cohort (22.2% vs. 30.5%, p

As a technique in artificial intelligence, a convolution neural network model has been utilized to extract average surface roughness from the geometric characteristics of a membrane image featuring micro- and nanostructures. For surface roughness measurement, e.g. atomic force microscopy and optical profiler, the previous methods have been performed to analyze a porous membrane surface on an interest of region with a few micrometers of the restricted area according to the depth resolution. However, an image from the scanning electron microscope, combined with the feature extraction process, provides clarity on surface roughness for multiple areas with various depth resolutions. Through image preprocessing, the geometric pattern is elucidated by amplifying the disparity in pixel intensity values between the bright and dark regions of the image. The geometric pattern of the binary image and magnitude spectrum confirmed the classification of the surface roughness of images in a categorical scatter plot. A group of cropped images from an original image is used to predict the logarithmic average surface roughness values. The model predicted 4.80 % MAPE for the test dataset. The method of extracting geometric patterns through a feature map-based CNN, combined with a statistical approach, suggests an indirect surface measurement. The process is achieved through a bundle of predicted output data, which helps reduce the randomness error of the structural characteristics. A novel feature extraction approach of CNN with statistical analysis is a valuable method for revealing hidden physical characteristics in surface geometries from irregular pixel patterns in an array of images.

IntroductionTo analyse the perspectives of healthcare professionals (HCPs) regarding the acceptance of digital health solutions for growth hormone (GH) deficiency care. This study identified factors impacting HCPs’ intent to use and recommend digital solutions supporting recombinant-human growth hormone (r-hGH) therapy in Italy and Korea with a use case of connected drug delivery system (Aluetta® with Smartdot™) integrated in a platform for GH treatment support (the Growzen™ digital health ecosystem).MethodsParticipatory workshops were conducted in Rome, Italy, and Seoul, Korea, to collect the perspectives of 22 HCPs on various predefined topics. HCPs were divided into two teams, each moderated by a facilitator. The workshops progressed in five phases: introduction of the project and experts, capturing views on the current context of digitalisation, perceived usefulness and ease of use of Aluetta® with Smartdot™, exploration of the perception of health technology evolution, and combined team recommendations. Data shared by HCPs on technology acceptance were independently analysed using thematic analysis, and relevant findings were shared and validated with experts.ResultsHCPs from both Italy and Korea perceived Aluetta® with Smartdot™ and the Growzen™ based digital health ecosystem as user-friendly, intuitive, and easy-to-use solutions. These solutions can result in increased adherence, a cost-effective healthcare system, and medication self-management. Although technology adoption and readiness may vary across countries, it was agreed that using digital solutions tailored to the needs of users may help in data-driven clinical decisions and strengthen HCP–patient relationships.ConclusionHCPs’ perspectives on the digitalisation in paediatric GH therapies suggested that digital solutions enable automatic, real-time injection data transmission to support adherence monitoring and evidence-based therapy, strengthen HCP–patient relationships, and empower patients throughout the GH treatment process.

BackgroundLiver transplantation (LT) is one of the main curative treatments for hepatocellular carcinoma (HCC). Milan criteria has long been applied to candidate LT patients with HCC. However, the application of Milan criteria failed to precisely predict patients at risk of recurrence. As a result, we aimed to establish and validate a deep learning model comparing with Milan criteria and better guide post-LT treatment.MethodsA total of 356 HCC patients who received LT with complete follow-up data were evaluated. The entire cohort was randomly divided into training set (n = 286) and validation set (n = 70). Multi-layer-perceptron model provided by pycox library was first used to construct the recurrence prediction model. Then tabular neural network (TabNet) that combines elements of deep learning and tabular data processing techniques was utilized to compare with Milan criteria and verify the performance of the model we proposed.ResultsPatients with larger tumor size over 7 cm, poorer differentiation of tumor grade and multiple tumor numbers were first classified as high risk of recurrence. We trained a classification model with TabNet and our proposed model performed better than the Milan criteria in terms of accuracy (0.95 vs. 0.86, p < 0.05). In addition, our model showed better performance results with improved AUC, NRI and hazard ratio, proving the robustness of the model.ConclusionA prognostic model had been proposed based on the use of TabNet on various parameters from HCC patients. The model performed well in post-LT recurrence prediction and the identification of high-risk subgroups.

Purpose Nonambulatory pediatric patients may have low bone mineral density (BMD) and increased risk of pathologic fractures. Though bisphosphonate therapy is the mainstream medical intervention in these children, clinical data regarding this treatment are limited. Therefore, this study aimed to evaluate the effectiveness and safety of bisphosphonate therapy in such children. Methods We conducted a retrospective study of 21 nonambulatory children (Gross Motor Function Classification System level V) with BMD z-score ≤ -2.0 who were treated with intravenous pamidronate for at least 1 year. These patients received pamidronate every 4 months at a dose of 1.0 to 3.0 mg/kg for each cycle and had regular follow-ups for at least 1 year. The main outcome measures were changes in BMD, risk rate of fracture, biochemical data, and adverse events. Results The average duration of pamidronate treatment was 2.0±0.9 years, and the mean cumulative dose of pamidronate according to body weight was 7.7±2.5 mg/kg/yr. After treatment, the mean lumbar spine bone mineral content, BMD, and height-for-age-z-score-adjusted BMD z-score (BMDhazZ) significantly improved. The relative risk of fracture after treatment was 0.21 (p=0.0032), suggesting that pamidronate treatment reduced fracture incidence significantly. The increase in the average dose per body weight in each cycle significantly increased the changes in BMDhazZ. Conclusions Pamidronate treatment improved the bone health of nonambulatory children with low bone density without any significant adverse events. Independent of cumulative dosage and duration of treatment, the effectiveness of pamidronate increased significantly with an increase in the average dose per body weight in subsequent cycles.

Abstract Excess oxidative stress generated in the body causes various types of cellular damage, including DNA damage. Certain trace minerals act as antioxidants by functioning as cofactors for antioxidant enzymes. This study was conducted to evaluate the serum and hair concentrations of major antioxidant trace minerals (zinc, manganese, selenium, and chromium) and to determine the association between the oxidative stress marker urinary 8-hydroxy-2′-deoxyguanosine (8-OHdG) and serum or hair antioxidant trace mineral concentrations, according to the general characteristics of healthy adults. Study participants were selected after screening, and 108 participants aged 19–69 years were finally included. Serum and hair trace mineral concentrations were analyzed using inductively coupled plasma mass spectrometry, and urine 8-OHdG levels were quantified using an ELISA kit. Results showed that urinary 8-OHdG levels were significantly higher in exercisers than in those who did not exercise. Correlation analysis revealed that urinary 8-OHdG was negatively correlated with hair zinc in participants over 60 years of age and with poor health status, and positively correlated with hair chromium in participants with irregular dietary habits. In conclusion, these results suggest that urinary 8-OHdG is particularly correlated with hair zinc and chromium levels. Additional large-scale epidemiological studies are needed to generally confirm these findings.

Abstract Synaptic transistors (STs) with a gate/electrolyte/channel stack, where mobile ions are electrically driven across the solid electrolyte, have been considered as analog weight elements for neuromorphic computing. The current (ID) between the source and drain in the ST is analogously updated by gate voltage (VG) pulses, enabling high pattern recognition accuracy in neuromorphic systems; however, the governing physical mechanisms of the ST are not fully understood yet. Our previous physics-based simulation study showed that ion movement in the electrolyte, rather than the electrochemical reactions that occur in the channel, plays an important role in switching. In this study, we experimentally explore the properties of the HfOx electrolyte and show that by tuning the density of oxygen vacancies, it can assume the dual role of electrolyte and channel. We demonstrate analog synaptic behavior using a novel ST with a two-layer stack of CuOx/HfOx, where the CuOx is the gate and Cu ion reservoir, and the HfOx is the electrolyte and channel. To improve state retention and linearity, we introduce a Cu ion transport barrier in the form of a dense and stoichiometric Al2O3 layer. The CuOx/Al2O3/HfOx exhibits excellent state retention and improved potentiation and depression response. Energy dispersive spectroscopy mapping following potentiation confirms the role of the Al2O3 layer in confining the Cu ions in the HfOx layer. We also show that a two-step programming scheme can further enhance synaptic response and demonstrate high recognition accuracy on the Fashion-MNIST dataset in simulation.

Abstract Background Cardiovascular disease (CVD) is a significant contributor to morbidity and mortality worldwide, with CVD and post-acute COVID-19 associated CVD increasing. It remains unknown whether COVID-19 patients with weight gain are at a high risk for CVD events. Therefore, the primary objective of this study is to investigate the association between weight control and the risk of CVD following COVID-19. Methods The study included 2,024,728 adults who participated in two rounds of health screening between 2017 and 2020. The final cohort, which included 70,996 participants in the COVID-19 group and 212,869 participants in the control group. The adjusted hazard ratio of BMI change to CVD risk was calculated using Cox proportional hazards regression. Results We identified a total of 2869 cases of CVD (861 events for COVID-19 group and 2,008 events for the control group). Compared to individuals with a stable BMI, COVID-19 patients without obesity had an increased risk of CVD (adjusted hazard ratio [aHR] = 2.28; 95% confidence interval [CI], 1.15–4.53; p-value = 0.018). Additionally, non-COVID-19 patients with obesity also exhibited a higher risk of CVD (aHR = 1.58; 95% CI, 1.01–2.47; p-value = 0.046). Conclusion In conclusion, people who gained weight during the pandemic, regardless of their weight category, had a significantly higher risk of CVD associated with COVID-19 compared to those who maintained their weight before the pandemic.

Objective Beef of Jeju black cattle (JBC) is considered as a healthy meat type due to its significantly higher unsaturated fatty acids (UFA). Lipid (e.g., UFA) is highly susceptible to oxidizing agents, which results in the quality deterioration and economic value loss of meat products. Therefore, development and application of novel preservative techniques is necessary to improve the shelf-life stability of high-UFA beef. The objective of this study was to assess the applicability of chitosan-based coatings in preservation of JBC beef. Methods Different coating solutions: 2% chitosan alone, and 2% chitosan containing 0.1% or 0.3% gallic acid were prepared to investigate their applicability in preservation of fresh beef during storage. Jeju black cattle beef (2-cm thick steaks) were non-coated (control) or coated with the above coating solutions, placed on trays, over-wrapped with plastic film and stored at 4°C. The microbiological indices, color, total volatile basic nitrogen (TVBN) and lipid oxidation of the beef were investigated after 1, 10, and 21 days of storage. Results Coating with 2% chitosan alone reduced the spoilage bacteria count, TVBN and thiobarbituric acid reactive substances levels in the beef compared with control during storage (p

Nonalcoholic fatty liver disease (NAFLD), a spectrum of liver diseases characterized by excessive fat accumulation, is the leading cause of chronic liver disease. The global prevalence of NAFLD is increasing in both adults and children. In Korea, the prevalence of pediatric NAFLD increased from 8.2% in 2009 to 12.1% in 2018 according to a national surveillance study. For early screening of pediatric NAFLD, laboratory tests including aspartate aminotransferase and alanine aminotransferase; biomarkers including hepatic steatosis index, triglyceride glucose index, and fibrosis-4 index; and imaging studies including ultrasonography and magnetic resonance imaging are required. Insulin resistance plays a major role in the pathogenesis of NAFLD, which promotes insulin resistance. Thus, the association between NAFLD and insulin resistance, diabetes mellitus, and metabolic syndrome has been reported in many studies. This review addresses issues related to the epidemiology and investigation of NAFLD as well as the association between NAFLD and insulin resistance and metabolic syndrome with focus on pediatric NAFLD.

Purpose Patients with Turner syndrome (TS) have distinct neurocognitive and psychosocial characteristics. However, few clinical studies have reported neuropsychological findings in Korean patients. This study investigated the neurocognitive and psychosocial profiles of Korean children with TS. Methods This retrospective cross-sectional study analyzed 20 pediatric patients (

Abstract The multilevel current states of synaptic devices in artificial neural networks enable next-generation computing to perform cognitive functions in an energy-efficient manner. Moreover, considering large-scale synaptic arrays, multiple states programmed in a low-current regime may be required to achieve low energy consumption, as demonstrated by simple numerical calculations. Thus, we propose a three-terminal Cu-ion-actuated CuOx/HfOx/WO3 synaptic transistor array that exhibits analogously modulated channel current states in the range of tens of nanoamperes, enabled by WO3 channel engineering. The introduction of an amorphous stoichiometric WO3 channel formed by reactive sputtering with O gas significantly lowered the channel current but left it almost unchanged with respect to consecutive gate voltage pulses. An additional annealing process at 450 °C crystallized the WO3, allowing analog switching in the range of tens of nanoamperes. The incorporation of N gas during annealing induced a highly conductive channel, making the channel current modulation negligible as a function of the gate pulse. Using this optimized gate stack, Poole–Frenkel conduction was identified as a major transport characteristic in a temperature-dependent study. In addition, we found that the channel current modulation is a function of the gate current response, which is related to the degree of progressive movement of the Cu ions. Finally, the synaptic characteristics were updated using fully parallel programming and demonstrated in a 7 × 7 array. Using the CuOx/HfOx/WO3 synaptic transistors as weight elements in multilayer neural networks, we achieved a 90% recognition accuracy on the Fashion-MNIST dataset.

Background: Obesity is a risk factor for COVID-19. However, it is unknown whether weight changes can alter this risk. We investigated the association of weight changes with SARS-CoV-2 infection and acute severe COVID-19 outcomes occurring within two months of the infection. Methods: We used 6.3 million nationwide cohort. The body weight was classified as follows: (1) underweight, body mass index (BMI)

IntroductionMetabolic dysfunction-associated steatotic liver disease (MASLD) presents a growing health concern in pediatric populations due to its association with obesity and metabolic syndrome. Bioelectrical impedance analysis (BIA) offers a non-invasive and potentially effective alternative for identifying MASLD risk in youth with overweight or obesity. Therefore, this study aimed to assess the utility of BIA for screening for MASLD in the youth.MethodThis retrospective, cross-sectional study included 206 children and adolescents aged