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Background and Aims Drug-coated balloons (DCBs) have demonstrated favourable outcomes following endovascular therapy for femoropopliteal artery (FPA) disease. However, uncertainty remains whether the use of intravascular ultrasound (IVUS) can improve the outcomes of DCBs. Methods This prospective, multicentre, randomized trial, conducted at seven centres in South Korea, compared the outcomes of IVUS-guided vs. angiography-guided angioplasty for treating FPA disease with DCBs. Patients were assigned to receive IVUS-guided (n = 119) or angiography-guided (n = 118) angioplasty using DCBs. The primary endpoint was 12-month primary patency. Results Between May 2016 and August 2022, 237 patients were enrolled and 204 (86.0%) completed the trial (median follow-up; 363 days). The IVUS guidance group showed significantly higher primary patency [83.8% vs. 70.1%; cumulative difference 19.6% (95% confidence interval 6.8 to 32.3); P =.01] and increased freedom from clinically driven target lesion revascularization [92.4% vs. 83.0%; difference 11.6% (95% confidence interval 3.1 to 20.1); P =.02], sustained clinical improvement (89.1% vs. 76.3%, P =.01), and haemodynamic improvement (82.4% vs. 66.9%, P =.01) at 12 months compared with the angiography guidance group. The IVUS group utilized larger balloon diameters and pressures for pre-dilation, more frequent post-dilation, and higher pressures for post-dilation, resulting in a greater post-procedural minimum lumen diameter (3.90 ± 0.59 vs. 3.71 ± 0.73 mm, P =.03). Conclusions Intravascular ultrasound guidance significantly improved the outcomes of DCBs for FPA disease in terms of primary patency, freedom from clinically driven target lesion revascularization, and sustained clinical and haemodynamic improvement at 12 months. These benefits may be attributed to IVUS-guided optimization of the lesion before and after DCB treatment. [ABSTRACT FROM AUTHOR]

Endometrial cancer is the most common gynecologic malignancy. PTEN is a negative regulator of PI3K signaling and is deficient in > 50% of primary human endometrial cancer. Amplification of ERBB2 promotes tumorigenesis and pathogenesis of several human cancers. However, the effect of ERBB2 targeting has not been studied in endometrial cancer with PTEN mutations. The murine model Pgrcre/+Erbb2f/fPtenf/f (Erbb2d/d Ptend/d) was developed to evaluate the effect of ERBB2 targeted therapy in endometrial cancer with PTEN deficiency. Histopathological and molecular analysis was performed for Ptend/d and Erbb2d/dPtend/d mice. Histopathological analysis revealed that Erbb2d/dPtend/d mice significantly reduced development and progression of endometrial cancer compared to Ptend/d mice. Furthermore, percentage of proliferative cells in Erbb2d/dPtend/d mice revealed anti-tumorigenic effect of Erbb2 ablation compared to Ptend/d mice. Our results demonstrate that Erbb2 ablation reveals a significant suppression of tumorigenesis on endometrial cancer of Ptend/d mice. Our results suggest that Erbb2 functions as an oncogene in endometrial cancer of Ptend/d mice implying that Erbb2 targeting can be used as an effective therapeutic approach for treatment of endometrial cancer with PTEN deficiency to hinder cancer development. [ABSTRACT FROM AUTHOR]

Objective: Granulomatous invasive fungal sinusitis (GIFS) is a rare and life-threatening disease, whereas fungus ball (FB) is the most common form of noninvasive fungal sinusitis. Both GIFS and FB primarily develop in immunocompetent patients, with the former associated with higher mortality and morbidity. Methods: A chart review and review of the literature. Results: We present the case of a 77-year-old woman with mixed fungal sinusitis who was successfully treated with voriconazole. Conclusions: GIFS and FB can coexist in extremely rare cases, known as mixed fungal sinusitis; however, the diagnosis and subsequent treatment of mixed fungal sinusitis can be delayed because of a lack of awareness of the underlying concept. Therefore, it is crucial for clinicians to recognize the concept of mixed fungal sinusitis. [ABSTRACT FROM AUTHOR]

The evidence about the associations of leukocyte telomere length (LTL) and intermediary cardiovascular phenotypes with adverse cardiovascular outcomes is inconclusive. This study assessed these relationships with cardiovascular imaging, electrocardiography, and the risks of sudden cardiac death (SCD), coronary events, and heart failure (HF) admission. We conducted a cross-sectional analysis of UK Biobank participants enrolled between 2006 and 2010. LTL was measured using quantitative polymerase chain reactions. Electronic health records were used to determine the incidence of SCD, coronary events, and HF admission. Cardiovascular measurements were made using cardiovascular magnetic resonance imaging and machine learning. The associations of LTL with SCD, coronary events, and HF admission and cardiac magnetic resonance imaging, electrocardiogram parameters of 33,043 and 19,554 participants were evaluated by multivariate regression. The median (interquartile range) follow-up period was 11.9 (11.2–12.6) years. Data was analyzed from January to May 2023. Among the 403,382 white participants without coronary artery disease or HF, 181,637 (45.0%) were male with a mean age of 57.1 years old. LTL was independently negatively associated with a risk of SCD (LTL third quartile vs first quartile: hazard ratio [HR]: 0.81, 95% confidence interval [CI]: 0.72–0.92), coronary events (LTL third quartile vs first quartile: HR: 0.88, 95% CI: 0.84–0.92), and HF admission (LTL fourth quartile vs first quartile: HR: 0.84, 95% CI: 0.74–0.95). LTL was also independently positively associated with cardiac remodeling, specifically left ventricular mass index, left-ventricular-end systolic and diastolic volumes, mean left ventricular myocardial wall thickness, left ventricular stroke volume, and with electrocardiogram changes along the negative degree of T-axis. Cross-sectional study results showed that LTL was positively associated with heart size and cardiac function in middle age, but electrocardiography results did not show these associations, which could explain the negative association between LTL and risk of SCD, coronary events, and HF admission in UK Biobank participants. [ABSTRACT FROM AUTHOR]

Adversarial attacks have received much attention as communication network applications rise in popularity. Connected and Automated Vehicles (CAVs) must be protected against adversarial attacks to ensure passenger and vehicle safety on the road. Nevertheless, CAVs are susceptible to several types of attacks, such as those that target intra- and inter-vehicle networks. These harmful attacks not only cause user privacy and confidentiality to be lost, but they also have more grave repercussions, such as physical harm and death. It is critical to precisely and quickly identify adversarial attacks to protect CAVs. This research proposes (1) a new dataset comprising three adversarial attacks in the CAV network traffic and normal traffic, (2) a two-phased adversarial attack detection technique named TAAD-CAV, where in the first phase, an ensemble voting classifier having three machine learning classifiers and one separate deep learning classifier is trained, and the output is used in the next phase. In the second phase, a meta classifier (i.e., Decision Tree is used as a meta classifier) is trained on the combined predictions from the previous phase to detect adversarial attacks. We preprocess the dataset by cleaning data, removing missing values, and adjusting the Z-score normalization. Evaluation metrics such as accuracy, recall, precision, F1-score, and confusion matrix are employed to evaluate and compare the performance of the proposed model. Results reveal that TAAD-CAV achieves the highest accuracy with a value of 70% compared with individual ML and DL classifiers. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to determine the feasibility and limitations of deep learning–based coronary calcium scoring using positron emission tomography-computed tomography (PET-CT) in comparison with coronary calcium scoring using ECG-gated non-contrast-enhanced cardiac computed tomography (CaCT). Materials and methods: A total of 215 individuals who underwent both CaCT and PET-CT were enrolled in this retrospective study. The Agatston method was used to calculate the coronary artery calcium scores (CACS) from CaCT, PET-CT(reader), and PET-CT(AI) to analyse the effect of using different modalities and AI-based software on CACS measurement. The total CACS and CACS classified according to the CAC-DRS guidelines were compared between the three sets of CACS. The differences, correlation coefficients, intraclass coefficients (ICC), and concordance rates were analysed. Statistical significance was set at p < 0.05. Results: The correlation coefficient of the total CACS from CaCT and PET-CT(reader) was 0.837, PET-CT(reader) and PET-CT(AI) was 0.894, and CaCT and PET-CT(AI) was 0.768. The ICC of CACS from CaCT and PET-CT(reader) was 0.911, PET-CT(reader) and PET-CT(AI) was 0.958, and CaCT and PET-CT(AI) was 0.842. The concordance rate between CaCT and PET-CT(AI) was 73.8%, with a false-negative rate of 37.3% and a false-positive rate of 4.4%. Age and male sex were associated with an increased misclassification rate. Conclusions: Artificial intelligence–assisted CACS measurements in PET-CT showed comparable results to CACS in coronary calcium CT. However, the relatively high false-negative results and tendency to underestimate should be of concern. Clinical relevance statement: Application of automated calcium scoring to PET-CT studies could potentially select patients at high risk of coronary artery disease from among cancer patients known to be susceptible to coronary artery disease and undergoing routine PET-CT scans. Key Points: • Cancer patients are susceptible to coronary disease, and PET-CT could be potentially used to calculate coronary artery calcium score (CACS). • Calcium scoring using artificial intelligence in PET-CT automatically provides CACS with high ICC to CACS in coronary calcium CT. • However, underestimation and false negatives of CACS calculation in PET-CT should be considered. [ABSTRACT FROM AUTHOR]

Endometrial cancer (EC) is the most common gynecologic malignancy. While the majority of patients present with early-stage and low-grade EC and have an excellent prognosis, a subset has metastatic disease at presentation or develops distant recurrence after initial treatment of the primary. However, the lack of prognostic biomarkers for metastatic EC is a critical barrier. Arginase 1 (ARG1) regulates the last step of the urea cycle, and an increase in ARG1 has been correlated as a poor prognostic factor in a variety of cancers. In the present study, ARG1 expression was evaluated as a potential prognostic marker for metastatic EC in endometrial hyperplasia and cancer of mice with Pten mutation as well as Pten and Mig-6 double mutations. While Pten mutation in the uterus is not sufficient for distant metastasis, mice with concurrent ablation of Mig-6 and Pten develop distant metastasis. Our immunostaining and RT-qPCR analysis revealed that the expression of ARG1 in early stage of EC as well as endometrial hyperplasia from mice deficient in Mig-6 and Pten mutations significantly increased compared to Pten mutation in the uterus. The results suggest that a high level of ARG1 is associated with poor prognosis in association with EC of mouse. [ABSTRACT FROM AUTHOR]

Tuberculosis (TB) is an infectious disease caused by Mycobacterium. It primarily impacts the lungs but can also endanger other organs, such as the renal system, spine, and brain. When an infected individual sneezes, coughs, or speaks, the virus can spread through the air, which contributes to its high contagiousness. The goal is to enhance detection recognition with an X-ray image dataset. This paper proposed a novel approach, named the Tuberculosis Segmentation-Guided Diagnosis Model (TSSG-CNN) for Detecting Tuberculosis, using a combined semantic segmentation and adaptive convolutional neural network (CNN) architecture. The proposed approach is distinguished from most of the previously proposed approaches in that it uses the combination of a deep learning segmentation model with a follow-up classification model based on CNN layers to segment chest X-ray images more precisely as well as to improve the diagnosis of TB. It contrasts with other approaches like ILCM, which is optimized for sequential learning, and explainable AI approaches, which focus on explanations. Moreover, our model is beneficial for the simplified procedure of feature optimization from the perspectives of approach using the Mayfly Algorithm (MA). Other models, including simple CNN, Batch Normalized CNN (BN-CNN), and Dense CNN (DCNN), are also evaluated on this dataset to evaluate the effectiveness of the proposed approach. The performance of the TSSG-CNN model outperformed all the models with an impressive accuracy of 98.75% and an F1 score of 98.70%. The evaluation findings demonstrate how well the deep learning segmentation model works and the potential for further research. The results suggest that this is the most accurate strategy and highlight the potential of the TSSG-CNN Model as a useful technique for precise and early diagnosis of TB. [ABSTRACT FROM AUTHOR]

Background: Nasal polyps and inverted papillomas often look similar. Clinically, it is difficult to distinguish the masses by endoscopic examination. Therefore, in this study, we aimed to develop a deep learning algorithm for computer-aided diagnosis of nasal endoscopic images, which may provide a more accurate clinical diagnosis before pathologic confirmation of the nasal masses. Methods: By performing deep learning of nasal endoscope images, we evaluated our computer-aided diagnosis system's assessment ability for nasal polyps and inverted papilloma and the feasibility of their clinical application. We used curriculum learning pre-trained with patches of nasal endoscopic images and full-sized images. The proposed model's performance for classifying nasal polyps, inverted papilloma, and normal tissue was analyzed using five-fold cross-validation. Results: The normal scores for our best-performing network were 0.9520 for recall, 0.7900 for precision, 0.8648 for F1-score, 0.97 for the area under the curve, and 0.8273 for accuracy. For nasal polyps, the best performance was 0.8162, 0.8496, 0.8409, 0.89, and 0.8273, respectively, for recall, precision, F1-score, area under the curve, and accuracy. Finally, for inverted papilloma, the best performance was obtained for recall, precision, F1-score, area under the curve, and accuracy values of 0.5172, 0.8125, 0.6122, 0.83, and 0.8273, respectively. Conclusion: Although there were some misclassifications, the results of gradient-weighted class activation mapping were generally consistent with the areas under the curve determined by otolaryngologists. These results suggest that the convolutional neural network is highly reliable in resolving lesion locations in nasal endoscopic images. [ABSTRACT FROM AUTHOR]

Connected and automated vehicles (CAVs), integrated with sensors, cameras, and communication networks, are transforming the transportation industry and providing new opportunities for consumers to enjoy personalized and seamless experiences. The fast proliferation of connected vehicles on the road and the growing trend of autonomous driving create vast amounts of data that need to be analyzed in real time. Anomaly detection in CAVs refers to identifying any unusual or unforeseen behavior in the data generated by vehicles' various sensors and components. Anomaly detection aims to identify any unusual behavior that might indicate a problem or a malfunction in the vehicle. To identify and detect anomalies efficiently, a method must deal with noisy data, missing data, dynamic frequency data, and low- and high-magnitude data, and it must be accurate enough to detect anomalies in a dynamic sensor streaming environment. Therefore, this paper proposes a fast and efficient hard-voting-based technique named FT-HV, comprising three fine-tuned machine learning algorithms to detect and classify anomaly behavior in CAVs for single and mixed sensory datasets. In experiments, we evaluate our approach on the benchmark Sensor Anomaly dataset that contains data from various vehicle sensors at low and high magnitudes. Further, it contains single and mixed anomaly types that are challenging to detect and identify. The results reveal that the proposed approach outperforms existing solutions for detecting single anomaly types at low magnitudes and detecting mixed anomaly types in all settings. Furthermore, this research is envisioned to help detect and identify anomalies early and efficiently promote safer and more resilient CAVs. [ABSTRACT FROM AUTHOR]

The learning accuracy of neuromorphic computing that mimics the biological brain, is affected by the conductance‐modulation characteristics of an artificial synapse. In ferroelectric‐based devices, these characteristics are implemented using a distribution of polarization values. Therefore, the distribution in a ferroelectric thin film with various external voltage signals is investigate. As polarization switching proceeds with voltage pulse, the domains of the switched polarization become larger. In ferroelectric‐gate field effect transistors, the channel layer assumed to lie beneath the ferroelectrics experiences a local conductance change, according to the polarization distribution of the ferroelectric layer. It is found that small clusters with high conductivity become large clusters in the channel layer as the polarization switching proceeds. When the additional pulses are applied, the high conductive regions eventually connect (i.e., percolate) in the channel layer and the conductance of the layer is greatly increased. Adjusting the height of the applied voltage can slow down or speed up this phenomenon. Also, the nanosecond voltage pulses are employed and the width of the conductive pathway is adjusted. It enables to fine‐tune the conductance of the channel layer. It demonstrates that conductance modulation is optimized with an appropriate voltage pulse train pattern. [ABSTRACT FROM AUTHOR]

The hydrographic variability in the fjords of Svalbard significantly influences water mass properties, causing distinct patterns of microbial diversity and community composition between surface and subsurface layers. However, surveys on the phytoplankton-associated bacterial communities, pivotal to ecosystem functioning in Arctic fjords, are limited. This study investigated the interactions between phytoplankton and heterotrophic bacterial communities in Svalbard fjord waters through comprehensive eDNA metabarcoding with 16S and 18S rRNA genes. The 16S rRNA sequencing results revealed a homogenous community composition including a few dominant heterotrophic bacteria across fjord waters, whereas 18S rRNA results suggested a spatially diverse eukaryotic plankton distribution. The relative abundances of heterotrophic bacteria showed a depth-wise distribution. By contrast, the dominant phytoplankton populations exhibited variable distributions in surface waters. In the network model, the linkage of phytoplankton (Prasinophytae and Dinophyceae) to heterotrophic bacteria, particularly Actinobacteria, suggested the direct or indirect influence of bacterial contributions on the fate of phytoplankton-derived organic matter. Our prediction of the metabolic pathways for bacterial activity related to phytoplankton-derived organic matter suggested competitive advantages and symbiotic relationships between phytoplankton and heterotrophic bacteria. Our findings provide valuable insights into the response of phytoplankton-bacterial interactions to environmental changes in Arctic fjords. [ABSTRACT FROM AUTHOR]

Nitrogen (N) lost during beef cattle production accompanies various environmental risks and has become a rising concern among agricultural stakeholders. The objective of this study was to quantify the N footprint of producing Hanwoo beef cattle, which is a Korean indigenous breed of cattle, in Korea at the farm gate through a life cycle assessment approach. Field surveys were conducted on 106 farms across 9 provinces to identify regional distinctions in farming systems and evaluate total N losses from beef production. N losses were calculated using emission factors from the refined IPCC guidelines, which were then expressed as N footprint (g N/kg of live body weight (LBW)). Uncertainty and sensitivity analyses were deployed to evaluate the precision of the results and identify factors that contributed to the output. The N footprint averaged 132.7(± 61.8) g N/kg LBW and varied between provinces according to animal categories, manure management systems, land use and fertilizer application rates. Volatilization was the highest contributing factor, followed by leaching and denitrification, each representing 68.5, 21.4, and 10.1 percent of the N footprint, respectively. The uncertainty of the result was found to be 46.6 percent and was highly associated with emission factor uncertainties. We devised five mitigation scenarios that are cost effective and do not penalize productivity and evaluated their capacity for reducing N footprint: (i) dietary modifications to decrease animal N excretion rate; (ii) microorganism additives to reduce volatilization from housing; (iii) manure storages recycling manure within the farm to replace synthetic fertilizers; (iv) distributing biochar to the field after fertilizer application to curtail losses from crop production; (v) combination of i, ii, iii, and iv. Combining these scenarios demonstrated the potential to reduce 12.1 percent of the total N footprint. The extents of mitigation scenarios varied across provinces (ranging from 5.2 to 21.7 percent) and were shown to be contingent on feeding practices and type of crop cultivated. Overall, our study provides a national metric that can be utilized to communicate the environmental impacts of Korean beef production. The analyses indicate that more precise results could be achieved with future endeavors towards developing country-specific emission factors. The mitigation potentials of the presented scenarios propose possibilities for feasible and sustainable beef production in Korea. [ABSTRACT FROM AUTHOR]

Background: Early identification of the severity of hypoxic-ischemic brain injury (HIBI) after cardiac arrest can be used to help plan appropriate subsequent therapy. We evaluated whether conductivity of cerebral tissue measured using magnetic resonance-based conductivity imaging (MRCI), which provides contrast derived from the concentration and mobility of ions within the imaged tissue, can reflect the severity of HIBI in the early hours after cardiac arrest. Methods: Fourteen minipigs were resuscitated after 5 min or 12 min of untreated cardiac arrest. MRCI was performed at baseline and at 1 h and 3.5 h after return of spontaneous circulation (ROSC). Results: In both groups, the conductivity of cerebral tissue significantly increased at 1 h after ROSC compared with that at baseline (P = 0.031 and 0.016 in the 5-min and 12-min groups, respectively). The increase was greater in the 12-min group, resulting in significantly higher conductivity values in the 12-min group (P = 0.030). At 3.5 h after ROSC, the conductivity of cerebral tissue in the 12-min group remained increased (P = 0.022), whereas that in the 5-min group returned to its baseline level. Conclusions: The conductivity of cerebral tissue was increased in the first hours after ROSC, and the increase was more prominent and lasted longer in the 12-min group than in the 5-min group. Our findings suggest the promising potential of MRCI as a tool to estimate the severity of HIBI in the early hours after cardiac arrest. [ABSTRACT FROM AUTHOR]

Although pulmonary vein isolation (PVI) gaps and extrapulmonary vein triggers contribute to recurrence after atrial fibrillation (AF) ablation, their precise mechanisms remain unproven. Our study assessed the impact of PVI gaps on rhythm outcomes using a human AF digital twin. We included 50 patients (76.0% with persistent AF) who underwent catheter ablation with a realistic AF digital twin by integrating computed tomography and electroanatomical mapping. We evaluated the final rhythm status, including AF and atrial tachycardia (AT), across 600 AF episodes, considering factors including PVI level, PVI gap number, and pacing locations. Our findings revealed that antral PVI had a significantly lower ratio of AF at the final rhythm (28% vs. 56%, p = 0.002) than ostial PVI. Increasing PVI gap numbers correlated with an increased ratio of AF at the final rhythm (p < 0.001). Extra-PV induction yielded a higher ratio of AF at the final rhythm than internal PV induction (77.5% vs. 59.0%, p < 0.001). In conclusion, our human AF digital twin model helped assess AF maintenance mechanisms. Clinical trial registration: https://www.clinicaltrials.gov; Unique identifier: NCT02138695. [ABSTRACT FROM AUTHOR]

Open in new tab Download slide OBJECTIVES In this cohort study, we aimed to assess the 1-year clinical outcomes of using the E-vita Open NEO™ hybrid prosthesis for total arch replacement with frozen elephant trunk (FET) to repair extensive aortic pathologies. METHODS We reviewed individuals who underwent thoracic aortic surgery between April 2021 and March 2023 from the Gangnam Severance Aortic Registry. Exclusion criteria included ascending aortic replacement, 1 or 2 partial arch replacement, descending aortic replacement and total arch replacement without an FET. Finally, all consecutive patients who underwent total arch replacement and FET with E-vita Open NEO for aortic arch pathologies between April 2021 and March 2023 were included in this cohort study. The patients were divided into 3 groups based on their pathology: acute aortic dissection, chronic aortic dissection and thoracic aortic aneurysm. The primary end point was in-hospital mortality. The secondary end points during the postoperative period comprised stroke, spinal cord injury and redo sternotomy for bleeding. Additionally, the secondary end points during the follow-up period included the 1-year survival rate, 1-year freedom from all aortic procedures and 1-year freedom from unplanned aortic interventions. RESULTS The study included 167 patients in total: 92 patients (55.1%) with acute aortic dissection, 20 patients (12.0%) with chronic aortic dissection and 55 patients (32.9%) with thoracic aortic aneurysm. The in-hospital mortality was 1.8% (n  = 3). Strokes occurred in 1.8% (n  = 3) of the patients, spinal cord injury in 1.8% (n  = 3) and redo sternotomy for bleeding was performed in 3.0% (n  = 5). There were no significant differences between the pathological groups. The median follow-up period (quartile 1–quartile 3) was 198 (37–373) days, with 1-year survival rates of 95.9%. At 1 year, the freedom from all aortic procedures and unplanned aortic interventions were 90.3% and 92.0%, respectively. CONCLUSIONS The 1-year clinical outcomes of total arch replacement with FET using the E-vita Open NEO were favourable. Long-term follow-up is required to evaluate the durability of the FET. [ABSTRACT FROM AUTHOR]

Cardiac diffusion weighted-magnetic resonance imaging (DWI) has slowly developed due to its technical difficulties. However, this limitation could be overcome by advanced techniques, including a stimulated echo technique and a gradient moment nulling technique. This study aimed to develop and validate a high-order DWI sequence, using echo-planar imaging (EPI) and second-order motion-compensated (M012) diffusion gradient applied to cardiac imaging in small-sized animals with fast heart and respiratory rates, and to investigate the feasibility of cardiac DWI, diagnosing acute myocardial injury in isoproterenol-induced myocardial injury rat models. The M012 diffusion gradient sequence was designed for diffusion tensor imaging of the rat myocardium and validated in the polyvinylpyrrolidone phantom. Following sequence optimization, 23 rats with isoproterenol-induced acute myocardial injury and five healthy control rats underwent cardiac MRI, including cine imaging, T1 mapping, and DWI. Diffusion gradient was applied using a 9.4-T MRI scanner (Bruker, BioSpec 94/20, gradient amplitude = 440 mT/m, maximum slew rate = 3440 T/m/s) with double gating (electrocardiogram and respiratory gating). Troponin I was used as a serum biomarker for myocardial injury. Histopathologic examination of the heart was subsequently performed. The developed DWI sequence using EPI and M012 provided the interpretable images of rat hearts. The apparent diffusion coefficient (ADC) values were significantly higher in rats with acute myocardial injury than in the control group (1.847 ± 0.326 * 10–3 mm2/s vs. 1.578 ± 0.144 * 10–3 mm2/s, P < 0.001). Troponin I levels were increased in the blood samples of rats with acute myocardial injury (P < 0.001). Histopathologic examinations detected myocardial damage and subendocardial fibrosis in rats with acute myocardial injury. The newly developed DWI technique has the ability to detect myocardial injury in small animal models, representing high ADC values on the myocardium with isoproterenol-induced injury. [ABSTRACT FROM AUTHOR]

Background: Myocardial injury after non-cardiac surgery (MINS) has been known to be associated with mortality in various surgical patients; however, its prognostic role in abdominal aortic aneurysm (AAA) open repair remains underexplored. This study aimed to investigate the role of MINS as a predictor of mortality in patients who underwent AAA open repair. Methods: This retrospective study investigated 352 patients who underwent open repair for non-ruptured AAA. The predictors of 30-day and 1-year mortalities were investigated using logistic regression analysis. Results: MINS was diagnosed in 41% of the patients after AAA open repair in this study. MINS was an independent risk factor of 30-day mortality (odds ratio [OR]: 10.440, 95% confidence interval [CI]: 1.278–85.274, p = 0.029) and 1-year mortality (OR: 5.189, 95% CI: 1.357–19.844, p = 0.016). Kaplan–Meier survival curves demonstrated significantly lower overall survival rates in patients with MINS compared to those without MINS (p = 0.003). Conclusion: This study revealed that MINS is a common complication after AAA open repair and is an independent risk factor of 30-day and 1-year mortalities. Patients with MINS have lower overall survival rates than those without MINS. [ABSTRACT FROM AUTHOR]

This study aimed to identify and evaluate drug candidates targeting the kinase inhibitory region of suppressor of cytokine signaling (SOCS) 3 for the treatment of allergic rhinitis (AR). Utilizing an artificial intelligence (AI)-based new drug development platform, virtual screening was conducted to identify compounds inhibiting the SH2 domain binding of SOCS3. Luminescence assays assessed the ability of these compounds to restore JAK-2 activity diminished by SOCS3. Jurkat T and BEAS-2B cells were utilized to investigate changes in SOCS3 and STAT3 expression, along with STAT3 phosphorylation in response to the identified compounds. In an OVA-induced allergic rhinitis mouse model, we measured serum levels of total IgE and OVA-specific IgE, performed real-time PCR on nasal mucosa samples to quantify Th2 cytokines and IFN-γ expression, and conducted immunohistochemistry to analyze eosinophil levels. Screening identified 20 hit compounds with robust binding affinities. As the concentration of SOCS3 increased, a corresponding decrease in JAK2 activity was observed. Compounds 5 and 8 exhibited significant efficacy in restoring JAK2 activity without toxicity. Treatment with these compounds resulted in reduced SOCS3 expression and the reinstatement of STAT3 phosphorylation in Jurkat T and BEAS-2B cells. In the OVA-induced allergic rhinitis mouse model, compounds 5 and 8 effectively alleviated nasal symptoms and demonstrated lower levels of immune markers compared to the allergy group. This study underscores the promising nonclinical efficacy of compounds identified through the AI-based drug development platform. These findings introduce innovative strategies for the treatment of AR and highlight the potential therapeutic value of targeting SOCS3 in managing AR. [ABSTRACT FROM AUTHOR]

Cardiac diffusion weighted-magnetic resonance imaging (DWI) has slowly developed due to its technical difficulties. However, this limitation could be overcome by advanced techniques, including a stimulated echo technique and a gradient moment nulling technique. This study aimed to develop and validate a high-order DWI sequence, using echo-planar imaging (EPI) and second-order motion-compensated (M012) diffusion gradient applied to cardiac imaging in small-sized animals with fast heart and respiratory rates, and to investigate the feasibility of cardiac DWI, diagnosing acute myocardial injury in isoproterenol-induced myocardial injury rat models. The M012 diffusion gradient sequence was designed for diffusion tensor imaging of the rat myocardium and validated in the polyvinylpyrrolidone phantom. Following sequence optimization, 23 rats with isoproterenol-induced acute myocardial injury and five healthy control rats underwent cardiac MRI, including cine imaging, T1 mapping, and DWI. Diffusion gradient was applied using a 9.4-T MRI scanner (Bruker, BioSpec 94/20, gradient amplitude = 440 mT/m, maximum slew rate = 3440 T/m/s) with double gating (electrocardiogram and respiratory gating). Troponin I was used as a serum biomarker for myocardial injury. Histopathologic examination of the heart was subsequently performed. The developed DWI sequence using EPI and M012 provided the interpretable images of rat hearts. The apparent diffusion coefficient (ADC) values were significantly higher in rats with acute myocardial injury than in the control group (1.847 ± 0.326 * 10–3 mm2/s vs. 1.578 ± 0.144 * 10–3 mm2/s, P < 0.001). Troponin I levels were increased in the blood samples of rats with acute myocardial injury (P < 0.001). Histopathologic examinations detected myocardial damage and subendocardial fibrosis in rats with acute myocardial injury. The newly developed DWI technique has the ability to detect myocardial injury in small animal models, representing high ADC values on the myocardium with isoproterenol-induced injury. [ABSTRACT FROM AUTHOR]

The structural performance of derailment containment provision (DCP) was investigated using a grid steel frame. The DCP which was installed within the gauge of a track was capable of resisting the impact loading in the case of derailed wheels. It was also possible to control the excessive lateral movement of the derailed train. In this study, the structural performance of DCP with a post-installed anchor to a railway concrete sleeper was evaluated. For this purpose, a total of nine specimens were manufactured and static tests were conducted to investigate the structural performance. Furthermore, the shear resistance of the connecting anchor was also evaluated using grid steel frame specimens. The initial test indicated that the developed DCP for railway using grid steel frames had sufficient load-carrying capacity and performance equivalent to about 150% of the design load. The developed DCP also demonstrated sufficient load-carrying capacity up to about 140% of the designed load in combination tests that simulated conceivable boundary conditions. As analytical results, the overall DCP behavior for the specimen railway that utilized grid steel frames was appropriately tracked, and detailed information was presented. [ABSTRACT FROM AUTHOR]

A representative naturally occurring coumarin, 4-methylumbelliferone (5), was exposed to 50 kGy of gamma ray, resulting in four newly generated dihydrocoumarin products 1–4 induced by the gamma irradiation. The structures of these new products were elucidated by interpretation of spectroscopic data (NMR, MS, [α]D, and UV). The unusual bisdihydrocoumarin 4 exhibited improved tyrosinase inhibitory capacity toward mushroom tyrosinase with IC50 values of 19.8 ± 0.5 μM as compared to the original 4-methylumbelliferone (5). A kinetic analysis also exhibited that the potent metabolite 4 had non-competitive modes of action. Linkage of the hydroxymethyl group in the C-3 and C-4 positions on the lactone ring probably enhances the tyrosinase inhibitory effect of 4-methylumbelliferone (5). Thus, the novel coumarin analog 4 is an interesting new class of tyrosinase inhibitory candidates that requires further examination. [ABSTRACT FROM AUTHOR]

The treatment landscape for inflammatory bowel disease (IBD) has undergone substantial advancements with the introduction of biologics. However, a considerable number of patients either show an immediate lack of response or lose responsiveness over time, necessitating the development of innovative and effective treatment approaches. Extracellular vesicles (EVs) are small lipid bilayer-enclosed structures that facilitate cell-to-cell molecular transfer and are integral to the pathogenesis of IBD. They play pivotal roles in maintaining the integrity of the intestinal epithelial barrier and the expulsion of cellular metabolites. The potential use of EVs as drug carriers or therapeutic agents has opened up a plethora of clinical applications. This review investigates the creation and content of EVs, their role in IBD development, and advances in their isolation and analytical techniques. Furthermore, the therapeutic promise they hold for IBD is explored, along with the latest research on their roles as IBD drug delivery systems. [ABSTRACT FROM AUTHOR]

Pressure ulcers (PUs) are a prevalent skin disease affecting patients with impaired mobility and in high-risk groups. These ulcers increase patients' suffering, medical expenses, and burden on medical staff. This study introduces a clinical decision support system and verifies it for predicting real-time PU occurrences within the intensive care unit (ICU) by using MIMIC-IV and in-house ICU data. We develop various machine learning (ML) and deep learning (DL) models for predicting PU occurrences in real time using the MIMIC-IV and validate using the MIMIC-IV and Kangwon National University Hospital (KNUH) dataset. To address the challenge of missing values in time series, we propose a novel recurrent neural network model, GRU-D++. This model outperformed other experimental models by achieving the area under the receiver operating characteristic curve (AUROC) of 0.945 for the on-time prediction and AUROC of 0.912 for 48h in-advance prediction. Furthermore, in the external validation with the KNUH dataset, the fine-tuned GRU-D++ model demonstrated superior performances, achieving an AUROC of 0.898 for on-time prediction and an AUROC of 0.897 for 48h in-advance prediction. The proposed GRU-D++, designed to consider temporal information and missing values, stands out for its predictive accuracy. Our findings suggest that this model can significantly alleviate the workload of medical staff and prevent the worsening of patient conditions by enabling timely interventions for PUs in the ICU. [ABSTRACT FROM AUTHOR]

An elevated platelet count may contribute to significant thrombotic events and pose a risk for diabetic microvascular complications. Albuminuria, one of the hallmarks of diabetes, is thought to be a risk factor for endothelial dysfunction. In this study, we investigated the association between relative thrombocytosis and an increased urine albumin-to-creatinine ratio in healthy adult participants. Using multivariate analyses on data from the Korea National Health and Nutrition Examination Survey V–VI, 12,525 eligible native Koreans aged ≥ 20 were categorized into platelet count quintiles by sex. The highest platelet count quintile included younger, more obese participants with elevated white blood cell counts, poor lipid profiles, and a better estimated glomerular filtration rate. Restricted cubic spline regression analysis revealed significant associations between platelet count and fasting blood glucose, glycated hemoglobin, and urine albumin-to-creatinine ratio. Adjusted logistic regression models indicated that heightened fasting blood glucose and platelet count were linked to risk of microalbuminuria (fasting blood glucose, odds ratio = 1.026, 95%CI = 1.011–1.042; platelet count, odds ratio = 1.004, 95%CI = 1.002–1.006). Particularly, an increased platelet count was notably associated with microalbuminuria progression in subjects with impaired fasting glucose. These findings suggest that an elevated platelet count, even below diagnostic thrombocytosis levels, independently correlates with an increased risk of vascular endothelial dysfunction in patients with impaired fasting glucose. [ABSTRACT FROM AUTHOR]

Objective: To determine age-related risk factors for chronic rhinosinusitis (CRS) with asthma. Methods: Data were obtained from a national survey of non-hospitalized civilians conducted by the Korean Center for Disease Control and Prevention. CRS diagnosis was based on the guidelines of the European Position Paper on Rhinosinusitis and Nasal Polyps 2020. Asthma was judged based on whether the patient had been diagnosed with asthma in the past. Of the 45,811 survey participants, 26,335 were included in the cross-sectional study. Participants included in the study were divided into the control, CRS, and CRS with asthma groups. Age-related risk factors were analyzed in patients aged < 60 or > 60 years. Univariate logistic analyses were performed to evaluate the relationship between groups. Risk factors included age, sex, household income, residence, education level, occupation, and body mass index (BMI). Results: Education level (Odds Ratio [OR]: 0.342, P =.0003), BMI (OR: 1.09, P =.0082), and total IgE (TIgE) levels (OR: 5.582, P =.003) were significantly different between the control and the CRS with asthma group. Education level (OR: 0.478, P =.0016) and TIgE levels (OR: 4, P =.0218) were significantly different between the CRS and CRS with asthma groups under 60 years of age. BMI (OR: 1.087, P =.0443; OR: 1.104, P =.0224) showed a significant difference between all three groups with age > 60 years. Conclusion: Progression to CRS with asthma is influenced by education level, occupation, and TIgE levels in patients under 60 years of age. BMI was the only influencing factor associated with the progression to CRS with asthma in those aged > 60 years. [ABSTRACT FROM AUTHOR]

A small organic molecule (SOM), 2,2′-(3,3′′-dihexyl-[2,2′:5′,2′′-terthiophene]-5,5′′-diyl)bis(1-octyl-1H-phenanthro[9,10-d]imidazole) (1), was utilised as an additive to intercalate with reduced graphene oxides (rGOs–1) in a single walled-carbon nanotube (SWCNT) composite. The ternary composite formed by incorporating rGOs–1 into the SWCNTs exhibited improvements in thermoelectric (TE) and carrier transport properties through the strong interfacial π–π interaction between the rGOs–1 and SWCNTs. The SOM 1 hybridised with the SWCNT composite induced significant interfacial phonon scattering, resulting in a reduction in the thermal conductivity (κ) of the SWCNT composite with rGOs–1. As a result, the SWCNT composite incorporating rGOs–1 demonstrated a simultaneous improvement of the Seebeck coefficient by 15% and a reduction in κ by 32%, resulting in an enhancement in the TE figure of merit (6.8 ± 0.7 × 10−3 at 297 K), which was 2.3 times higher than that of the SWCNTs alone (2.9 ± 0.5 × 10−3). [ABSTRACT FROM AUTHOR]

Chronic rhinosinusitis (CRS) is an inflammation of the nasal and paranasal sinus mucosa, and eosinophilic CRS (eCRS) is a subtype characterized by significant eosinophil infiltration and immune response by T-helper-2 cells. The pathogenesis of eCRS is heterogeneous and involves various environmental and host factors. Proteases from external sources, such as mites, fungi, and bacteria, have been implicated in inducing type 2 inflammatory reactions. The balance between these proteases and endogenous protease inhibitors (EPIs) is considered important, and their imbalance can potentially lead to type 2 inflammatory reactions, such as eCRS. In this review, we discuss various mechanisms by which exogenous proteases influence eCRS and highlight the emerging role of endogenous protease inhibitors in eCRS pathogenesis. [ABSTRACT FROM AUTHOR]

We propose a method of manipulating the coercivity of anisotropic hydrogenation-disproportionation-desorption-recombination (HDDR) powders to fabricate high-remanence and fine-grained Nd-Fe-B magnets using only hot-pressing without a subsequent hot-deformation process. By reducing the Nd content of anisotropic HDDR precursors such that their coercivity (Hcj) is lowered, the c-axis of each HDDR particle is well-aligned parallel to the direction of the applied magnetic field during the magnetic alignment step. This is because the magnetic repulsive force between adjacent particles, determined by their remanent magnetization, decreases as a result of the low coercivity of each particle. Therefore, after hot-pressing the low-Hcj HDDR powders, a significantly higher remanence (11.2 kG) is achieved in the bulk than that achieved by hot-pressing the high-Hcj HDDR powders (8.2 kG). It is clearly confirmed by the large-scale electron backscatter diffraction (EBSD) analysis that the alignment of the c-axis of each anisotropic HDDR particle in the bulk is improved when low-Hcj HDDR powders are used to fabricate hot-pressed magnets. This coercivity manipulation of HDDR powders can be a helpful method to expand the use of HDDR powders in fabricating anisotropic Nd-Fe-B bulk magnets. [ABSTRACT FROM AUTHOR]

In this paper, a new approach is developed to numerically evaluate the structural performance of deteriorated prestressed concrete beams using the finite element analysis application RCAHEST (Reinforced Concrete Analysis in Higher Evaluation System Technology). A prestressing steel element was modified to represent the interaction between deteriorated concrete and prestressing steel. Considering the corrosion effects—as shown by the reduction of the prestressing steel section and loss of bond—a nonlinear material model was proposed for deteriorated prestressed concrete behavior. The modified damage index is intended to provide a numerical method for quantifying the structural performance of deteriorated prestressed concrete beams. The analytical procedure developed for the performance evaluation of deteriorated beams was validated by comparison with the credible test results, thereby enabling a more reliable and rational prestressed concrete beams design process. [ABSTRACT FROM AUTHOR]

Introduction: Allergic diseases are mediated by T helper cell type 2 (Th2) cells, which are differentiated by dendritic cells (DCs). Recently, it was reported that cAMP concentration in DCs is important for inducing allergic responses. However, the regulatory function of cAMP in DCs in Th2 immune responses is unclear. It was hypothesized that the regulation of G protein-coupled receptors (GPCRs) to increase cAMP levels in DCs would reduce Th2 immune responses. Methods: Human DCs from patients with allergic rhinitis (AR) and from healthy controls were subjected to next-generation sequencing (NGS) to identify potential GPCR. To investigate the functions of GPCR agonists, the in vitro co-culture experiment that THP-1 cells were differentiated into DCs and cultured with human CD4+ T-cells and an AR animal in vivo model were used. Results: Among the GPCRs, the beta-2 adrenergic receptor (ADRB2) of allergic DCs was significantly increased by NGS analysis. The expression of ADRB2 was also increased in Der p 1-treated DCs, which was reduced by treatment with the ADRB2 agonist salbutamol. Salbutamol treatment induced cAMP production in THP-1 derived DCs. In an in vitro co-culture experiment, salbutamol-treated DCs reduced the secretion of Th2 cytokine. In an in vivo AR animal experiment, salbutamol-administered mice showed reduced allergic behavior and Th2 cytokine expression in the nasal mucosa. Conclusions: The regulation of ADRB2 with salbutamol alleviated the allergic response in vitro DC-T cell co-culture and in vivo AR animal models, suggesting that ADRB2 is a therapeutic target for AR and that ADRB2 agonists may be a promising medication for AR. [ABSTRACT FROM AUTHOR]

Background: Perioperative hypoalbuminemia has a prognostic effect on mortality and morbidity in various cohorts. Patients undergoing open repair of ruptured abdominal aortic aneurysms (rAAA) are at a high risk of hypoalbuminemia due to bleeding and underlying diseases. Hence, this study aimed to investigate the predictive value of immediate postoperative hypoalbuminemia for the risk for acute kidney injury (AKI) in patients undergoing open rAAA repair. Methods: We retrospectively reviewed 143 patients who underwent open rAAA repair between January 2008 and May 2022. The patients were divided into two groups according to the presence of postoperative AKI. The perioperative serum albumin levels of the two groups were compared. The patients were further divided into two groups based on the median immediate postoperative albumin level (2.4 g/dL). The incidence of AKI was compared between the two groups. Multivariate logistic regression analysis was performed to assess the predictors of postoperative AKI. Kaplan-Meier survival curves were used to evaluate potential of AKI and albumin level as prognostic factors for mortality. Results: Immediate postoperative serum albumin was significantly lower in the AKI group than in the non-AKI group (2.11 ± 0.62 g/dL vs. 2.59 ± 0.62 g/dL, p < 0.001). The incidence of postoperative AKI was significantly higher in patients with albumin ≤ 2.4 g/dL than in patients with albumin > 2.4 g/dL (53.8% vs. 27.7%, p = 0.002). Immediate postoperative albumin level was an independent predictor of AKI (Odds ratio [OR], 0.310; 95% confidence interval [CI] 0.165–0.583, p < 0.001) and 1-year mortality (OR, 0.230; 95% CI 0.098–0.542, p = 0.001). Conclusions: Immediate postoperative hypoalbuminemia was associated with postoperative AKI and mortality in patients with rAAA. [ABSTRACT FROM AUTHOR]

The increase in maritime traffic and vessel size has strengthened the need for economical and safe maritime transportation networks. Currently, ship path planning is based on past experience and shortest route usage. However, the increasing complexity of the marine environment and the development of autonomous ships require automatic shortest path generation based on maritime traffic networks. This paper proposes an efficient shortest path planning method using Dijkstra's algorithm based on a maritime traffic network dataset created by extracting maritime traffic routes through a spatial-temporal density analysis of large-scale AIS data and Delaunay triangulation. Additionally, the depth information of all digital charts in Korea was set as a safety contour to support safe path planning. The proposed network-based shortest path planning method was compared with the path planning and sailing distance of a training ship, and compliance with maritime laws was verified. The results demonstrate the practicality and safety of the proposed method, which can enable the establishment of a safe and efficient maritime transportation network along with the development of autonomous ships. [ABSTRACT FROM AUTHOR]

Hybridizing single‐walled carbon nanotubes (SWCNTs) with π‐conjugated organic small molecules (π‐OSMs) offers a promising approach for producing high‐performance thermoelectric (TE) materials through the facile optimization of the molecular geometry and energy levels of π‐OSMs. Designing a twisted molecular structure for the π‐OSM with the highest occupied molecular orbital energy level comparable to the valence band of SWCNTs enables effective energy filtering between the two materials. The SWCNTs/twisted π‐OSM hybrid exhibits a high Seebeck coefficient of 110.4 ± 2.6 µV K−1, leading to a significantly improved power factor of 2,136 µW m−1 K−2, which is 2.6 times higher than that of SWCNTs. Moreover, a maximum figure of merit over 0.13 at room temperature is achieved via the efficient TE transport of the SWCNTs/twisted π‐OSM hybrid. The study highlights the promising potential of optimizing molecular engineering of π‐OSMs for hybridization with SWCNTs to create next‐generation, efficient TE materials. [ABSTRACT FROM AUTHOR]

Exploration of significantly active functional materials is highly valued for designing efficient electrochemical energy devices. 2D‐covalent organic frameworks (2D‐COF) have attracted significant interest in the context of important electrochemical applications due to their tunable structural and electronic properties, high thermal/chemical stability, and their carbon‐based motifs. The present review highlights the strategies and properties of modifying 2D‐COF electronically in detail and their prospects in electrochemical devices. The review clearly explains the electronic actuation methods of the COF skeletons by various synthetic and post‐synthetic strategies. The review crucially elucidates the importance of electroactive 2D‐COF as emerging functional materials in practical applications of electrochemical energy conversion devices. The review concludes by summarizing the effective strategies of 2D‐COF in improving electrocatalytic applications and suggests future research scope. The review orients the electroactive 2D‐COFs for critical analysis as advanced functional materials for a sustainable and reliable future. [ABSTRACT FROM AUTHOR]

The synergistic effect in multi‐metal electrocatalysts has gained attention as an efficient strategy for enhancing intrinsic electrocatalytic activities. In this study, a facile electrodeposition technique is used to synthesize a multi‐metal high entropy catalyst (HEC) for efficient electrocatalytic hydrogen production. To boost the synergistic effect between noble metals and transition metals, the Pt ratio is controlled in a multi‐metal electrocatalyst system. The prepared Pt‐involved HEC (Pt‐HEC) exhibits a bamboo‐like morphology with uniformly distributed elements. The 2.5 mM Pt‐HEC has outstanding electrocatalytic activity toward hydrogen evolution reaction (HER) among other Pt‐HECs, with a low overpotential of 70 mV and a Tafel slope value of 47 mV dec−1. Additionally, the Pt mass activity of the 2.5 mM Pt‐HEC is 5.6 times higher than commercial Pt/C electrocatalyst owing to the improved synergistic effect with an optimized Pt ratio. According to the electrochemical impedance spectroscopy (EIS) analysis, the proton‐coupled electron transfer (PCET) process occurs more quickly in the 2.5 mM Pt‐HEC electrocatalyst, confirming its smaller charge transfer resistance properties compared to those of the 5 and 1 mM Pt‐HEC. Therefore, HEC systems can be extensively encouraged as a platform for improving synergistic effects and enhancing electrocatalytic activities for a highly efficient HER electrocatalyst. [ABSTRACT FROM AUTHOR]

We aimed to evaluate the association between periodontitis in the upper jaw and chronic rhinosinusitis (CRS) using the nationwide Korean National Health and Nutrition Examination Survey (KNHANES) data. In this cross-sectional study, data of KNHANES participants enrolled between 2008 and 2012 were reviewed. Periodontitis of the upper teeth was diagnosed by dentists according to the community periodontal index with standardized methods. CRS was diagnosed by otorhinolaryngologists according to the European Position Paper on Rhinosinusitis and Nasal Polyps 2020 with nasal endoscopy findings. We also evaluated the association between periodontitis and CRS according to smoking and drinking status. Univariate and multivariate logistic regression analyses were performed. Overall, 28,761 participants were eligible for analysis, and 210 were diagnosed with CRS. Periodontitis was associated with CRS diagnosis (odds ratio [OR] = 1.391, 95% confidence interval [CI] = 1.013–1.912). Non-drinkers showed no significant association between periodontitis and CRS (OR = 1.142, 95% CI 0.746–1.749). However, among drinkers, periodontitis was significantly associated with CRS (OR = 1.733, 95% CI 1.091–2.753). The number of smokers with CRS was not statistically sufficient and a logistic regression model based on smoking status could not be generated. Individuals with periodontitis in the upper jaw may need to consult an otorhinolaryngologist for comorbid CRS especially according to drinking status. [ABSTRACT FROM AUTHOR]

Background: It has become important to identify and manage risk factors for subclinical atrial fibrillation (AF) with an increase in its detection rate. Thus, this research aimed to investigate whether alcohol consumption contributes to the development of subclinical AF. Methods: This prospective study enrolled 467 patients without AF from a multicenter pacemaker registry. The incidence of subclinical AF (episodes of atrial rate > 220 beats per minute without symptoms) was compared between alcohol-drinking and non-drinking groups. Results: During followup (median 18 months), the incidence and risk of long-duration atrial high-rate episodes (AHRE) ≥ 24 h were increased in the alcohol group compared to the non-alcohol group [5.47 vs. 2.10 per 100 person-years, adjusted hazard ratio (HR), 2.83; 95% confidence interval (CI), 1.14–7.04; P = 0.03]. After propensity score matching, the incidence and risk of long-duration AHRE were higher in the alcohol group (6.97 vs. 1.27 per 100 person-years, adjusted HR, 7.84; 95% CI, 1.21–50.93; P = 0.03). The mean burden of long-duration subclinical AF was higher in the alcohol group than in the non-alcohol group (0.18 vs. 1.61% during follow-up, P = 0.08). Conclusion: Alcohol consumption was associated with an increased risk of subclinical AF. Long-duration AHRE incidence and AHRE burden were higher in alcohol drinkers than in non-drinkers. [ABSTRACT FROM AUTHOR]

In this study, we applied an optimal deep learning algorithm to detect defects in OLED cells. This study aims to enhance the yield of OLEDs by reducing the number of defective products through defect detection in OLED cells. Defects in OLED cells can arise owing to various factors, but dark spots are predominantly identified and studied. Therefore, actual dark spot images were required for this study. However, obtaining real data is challenging because of security concerns in the OLED industry. Therefore, a Solver program utilizing the finite element method (FEM) was employed to generate 2000 virtual dark spot images. The generated images were categorized into two groups: initial images of dark spots and images obtained after 10,000 h. The pixel values of these dark spot images were adjusted for efficient recognition and analysis. Furthermore, CNN, ResNet-50, and VGG-16 were implemented to apply the optimal deep learning algorithms. The results showed that the VGG-16 algorithm performed the best. A defect detection model was created based on the performance metrics of the deep learning algorithms. The model was trained using 1300 dark spot images and validated using 600 dark spot images. The validation results indicated an accuracy of 0.988 and a loss value of 0.026. A defect detection model that utilizes the VGG-16 algorithm was considered suitable for distinguishing dark spot images. To test the defect detection model, 100 images of dark spots were used. The experimental results indicated an accuracy of 89%. The images were classified as acceptable or defective based on the threshold values. By applying the VGG-16 deep learning algorithm to the defect detection model, we can enhance the yield of OLED products, reduce production costs, and contribute significantly to the advancement of OLED display manufacturing technology. [ABSTRACT FROM AUTHOR]

Aortic surgery is one of the most challenging types of surgeries, which is possibly related to cognitive sequelae. We aimed to investigate the changes in resting-state functional connectivity (rsFC) associated with intraoperative circulatory arrest (CA) in aortic surgery, exploring the relationship between the altered connectivity and postoperative cognitive functions. Thirty-eight patients participated in this study (14 with CA, 24 without). Functional magnetic resonance imaging was scanned on the fifth day after surgery or after the resolution of delirium if it was developed. We assessed the differences in the development of postoperative cognitive changes and rsFC between patients with and without CA. The occurrence of postoperative delirium and postoperative cognitive dysfunction was not significantly different between the patients with and without the application of CA. However, patients with CA showed increased in posterior cingulate cortex-based connectivity with the right superior temporal gyrus, right precuneus, and right hippocampus, and medial prefrontal cortex-based connectivity with the dorsolateral prefrontal cortex. The application of moderate hypothermic CA with unilateral antegrade cerebral perfusion is unlikely to affect aspects of postoperative cognitive changes, whereas it may lead to increased rsFC of the default mode network at a subclinical level following acute brain insults. [ABSTRACT FROM AUTHOR]

Background: There is a lack of studies on utilising skeletal muscle mass via preoperative lumbar computed tomography or magnetic resonance imaging as a predictor of postoperative complications of posterior lumbar interbody fusion (PLIF) surgery in elderly patients. Methods: Patients aged >65 years who underwent PLIF were enrolled. The sum of the cross-sectional areas of the erector spinae muscles (CSABoth) was presented as the skeletal muscle mass. Postoperative complications were assessed using CSABoth, pulmonary function testing, and prognostic nutritional index (PNI). Results: Patients with postoperative complications showed significantly lower values of CSABoth (median 2266.70 (2239.73–2875.10) mm2 vs. 3060.30 (2749.25–3473.30) mm2, p < 0.001), functional vital capacity, forced expiratory volume at 1 s, and PNI. However, multiple logistic regression analysis identified American Society of Anaesthesiologists Physical Status (ASA PS) I (odds ratio 0.307 (95% confidence interval 0.110–0.852), p = 0.023), ASA PS III (4.033 (1.586–10.254), p = 0.003), CSABoth (0.999 (0.999–1.000), p < 0.001), and postoperative red blood cell (RBC) transfusion (1.603 (1.193–2.152), p = 0.002) as risk factors for postoperative complications after PLIF surgery. Conclusions: CSABoth, ASA PS III, and postoperative RBC transfusion might be used as predictors of postoperative complications after PLIF in patients aged >65 years. [ABSTRACT FROM AUTHOR]