Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)

Purpose: Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) can uncover hidden information and variability within time series. We aimed to develop and validate AI models to predict ARF within 72 h after emergency department admission, primarily using highresolution biosignals collected within 4 h of arrival. Materials and Methods: Our AI model, built on convolutional recurrent neural networks, combines biosignal feature extraction and sequence modeling. The model was developed and internally validated with data from 5284 admissions [1085 (20.5%) positive for ARF], and externally validated using data from 144 admissions [7 (4.9%) positive for ARF] from another institution. We defined ARF as the application of advanced respiratory support devices. Results: Our AI model performed well in predicting ARF, achieving area under the receiver operating characteristic curve (AUROC) of 0.840 and 0.743 in internal and external validations, respectively. It outperformed the Modified Early Warning Score (MEWS) and XGBoost models built only with clinical variables. High predictive ability for mortality was observed, with AUROC up to 0.809. A 10% increase in AI prediction scores was associated with 1.44-fold and 1.42-fold increases in ARF risk and mortality risk, respectively, even after adjusting for MEWS and demographic variables. Conclusion Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction.

With the increasing use of plastics worldwide, the amount of plastic waste being discarded has also risen. This plastic waste undergoes physical and chemical processes, breaking down into smaller particles known as microplastics (MPs) or nanoplastics (NPs). Advances in technology have enhanced our ability to detect these smaller particles, and it has been confirmed that plastics can be found in marine organisms as well as within the human body. However, research on the effects of MPs or NPs on living organisms has only recently been started, and our understanding remains limited. Studies on the immunological impacts are still ongoing, revealing that MPs and NPs can differentially affect various immune cells based on the material, size, and shape of the plastic particles. In this review, we aim to provide a comprehensive understanding of the effects of MPs and NPs on the immune system. We will also explore the methods for plastic removal through physicochemical, microbial, or biological means.

Natural killer (NK) cells are innate immune cells that are crucial for anticancer activity and have been developed as an immune cell therapy for leukemia. However, their limited effectiveness against solid tumors has prompted research into methods to enhance NK cell activity through combination therapies. Health supplements capable of boosting immune surveillance against tumor cells are gaining attention owing to their potential benefits. Resveratrol, a stilbenoid produced by several plants including peanuts and grapes, reportedly exerts anticancer effects and can activate immune cells. The peanut sprout extract cultivated with fermented sawdust medium (PSEFS) is rich in resveratrol, leveraging its health benefits in terms of the dry weight of herbal products, thus maximizing the utilization of resveratrol’s beneficial properties. Our study compared the efficacy of resveratrol and PSEFS and revealed that PSEFS significantly enhanced NK cell activation compared with an equivalent dose of resveratrol. We investigated the ability of PSEFS to potentiate NK cell anticancer activity, focusing on NK cell survival, tumor cell lysis, and NK cell activation in PSEFS-administered mice. Our findings suggest that PSEFS could be a potential NK cell booster for cancer immunotherapy.

Background/Aims: Chronic gastroesophageal reflux disease (GERD) requires symptom relief and treatment of associated conditions. In this study, we aimed to compare anti-reflux mucosectomy (ARMS) and Stretta radiofrequency (SRF) for treating patients with chronic GERD who are unresponsive to proton pump inhibitors (PPIs) and to identify the indications for each procedure. Methods: Data of patients who underwent ARMS or SRF between March 2021 and April 2023 were analyzed. Changes in GERD questionnaire (GERDQ) scores, endoscopic Los Angeles (LA) grade, flap valve grade (FVG) based on Hill’s type, EndoFLIP distensibility index (DI), endoscopic Barrett’s epithelium (BE) resolution rate, and PPI withdrawal rate were compared between the two groups. Results: Improvements in the GERDQ scores and PPI withdrawal rates were similar between the groups. The ARMS group showed significantly better changes in endoscopic LA grade, FVG, and EndoFLIP DI than the SRF group. The complications were more prevalent in the ARMS group than in the SRF group. Conclusions The change in endoscopic LA grade before and after the procedure was significantly higher in the ARMS group than in the SRF group. Significant improvements in endoscopic FVG, BE resolution, and EndoFLIP DI were observed only with the ARMS group.

Background: The treatment of Kümmell disease (KD) is controversial. Corpectomy and reconstruction or osteotomy with long-level fusion was traditionally performed for the advanced KD. However, these procedures can be disadvantageous for elderly patients.Several alternative surgical procedures including transpedicular intravertebral cage augmentation (TPICA) or vertebroplasty (VP) combined with short-segment fixation (SSF) have been suggested to minimize the surgical burden. This study aimed to compare the outcomes of percutaneous TPICA plus SSF with VP plus SSF for advanced thoracolumbar (T11–L2) KD and to introduce our novel percutaneous TPICA technique using specially designed cannulated cage trials. Methods: We devised specially designed cannulated cage trials to make the TPICA procedure safer and more reproducible, minimizing the risk of the pedicle medial wall violation. All consecutive patients who underwent percutaneous TPICA or VP combined with SSF for advanced thoracolumbar KD, from January 2021 to June 2022, with ≥ 1-year follow-up at a single institution, were included. Perioperative details, clinical outcomes (visual analog scale and Oswestry Disability Index), and radiological outcomes (anterior vertebral body compression percentage and vertebral kyphotic angle [VKA] of the fractured vertebra, and local Cobb angle [LCA]) were collected and compared between the groups. Results: A total of 42 patients were enrolled, with 21 patients in each group. There were no patients with pedicle medial wall fracture in the TPICA group. Both procedures provided significantly favorable radiological outcomes compared to those preoperatively. No significant differences were observed in the changes over time in all radiological parameters between the groups. Loss of correction during the follow-up period was significantly smaller in patients with TPICA than in those with VP in VKA (median [interquartile range], 2.15 [0.30–2.80] vs. 2.90 [0.90–6.53]; p = 0.030) and LCA (2.70 ± 2.90 vs. 5.17 ± 4.40, p = 0.037). Conclusions Both procedures are minimally invasive and useful options for advanced KD, especially for elderly patients with high comorbidity. Our novel percutaneous TPICA technique using cannulated cage trials, being safer and more reproducible, may allow spine surgeons to easily perform TPICA.

We evaluated the effectiveness of the predictive low-glucose suspend (PLGS) algorithm in the DIA:CONN G8. Forty people with type 1 diabetes mellitus (T1DM) who used a DIA:CONN G8 for at least 2 months with prior experience using pumps without and with PLGS were retrospectively analyzed. The objective was to assess the changes in time spent in hypoglycemia (percent of time below range [%TBR]) before and after using PLGS. The mean age, sensor glucose levels, glucose threshold for suspension, and suspension time were 31.1±22.8 years, 159.7±23.2 mg/dL, 81.1±9.1 mg/dL, and 111.9±79.8 min/day, respectively. Overnight %TBR <70 mg/dL was significantly reduced after using the algorithm (differences=0.3%, from 1.4%±1.5% to 1.1%±1.2%, P=0.045). The glycemia risk index (GRI) improved significantly by 4.2 (from 38.8±20.9 to 34.6±19.0, P=0.002). Using the PLGS did not result in a change in the hyperglycemia metric (all P>0.05). Our findings support the PLGS in DIA:CONN G8 as an effective algorithm to improve night-time hypoglycemia and GRI in people with T1DM.

Background: Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making. Methods: This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes. Conclusion This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.

Background: The positive relationship between triiodothyronine (T3) and steatotic liver disease (SLD) demonstrated only in crosssectional study. We aimed to evaluated whether total T3 (TT3) is associated with the development/resolution of SLD in longitudinal design. Methods: This retrospective, longitudinal, population-based cohort study included 1,665 South Korean euthyroid adults with ≥4 thyroid function test. We explored the impact of mean TT3 during follow-up on development/resolution of either SLD (diagnosed by ultrasound) or modified metabolic dysfunction-associated steatotic liver disease (MASLD) using Cox proportional hazards regression models. Results: During about median 5 years follow-up, 807/1,216 (66.3%) participants among participants without SLD at baseline developed SLD, and 253/318 (79.5%) participants among participants with SLD at baseline SLD resolved fatty liver. Mean TT3 rather than thyroid stimulating hormone or mean free thyroxine was significantly related with development (adjusted hazard ratio [HR], 1.01; 95% confidence interval [CI], 1.00 to 1.02; P=0.002) and resolution (adjusted HR, 0.97; 95% CI, 0.96 to 0.99; P=0.005) of SLD. Compared with low mean TT3 group, high mean TT3 group was positively associated with development of SLD (adjusted HR, 1.20; 95% CI, 1.05 to 1.38; P=0.008) and inversely associated with resolution of SLD (adjusted HR, 0.66; 95% CI, 0.51 to 0.85; P=0.001). The statistical significance remained for development (adjusted HR, 1.29; 95% CI, 1.10 to 1.51; P=0.001) and resolution (adjusted HR, 0.71; 95% CI, 0.54 to 0.94; P=0.018) of modified MASLD. Conclusion In Korean euthyroid adults, TT3 level was associated with development and resolution of either SLD or modified MASLD.

Background/Aims: Gastric neuroendocrine tumors (GNETs), once rare, have become more prevalent due to the increased use of endoscopy and increased physician awareness. The clinical characteristics and long-term outcomes of GNET management were explored in this study. Methods: The clinical data of 69 patients who treated at Seoul National University Hospital between January 2013 and October 2023 were retrospectively studied. Baseline characteristics, recurrence rates, associated factors, and overall survival rates were analyzed. Results: Of the tumors, 71.0% were grade 1, 24.6% were grade 2, 1.4% were grade 3, and 2.9% were poorly differentiated. In terms of tumor type, 69.6% were type I, 1.4% were type II, and 29.0% were type III. A significant proportion of patients with grade 1 tumors received more endoscopic treatment, whereas a significant proportion of patients with grade 2 tumors underwent surgery or chemotherapy (p=0.015). The overall 5-year survival and recurrence rates were 93.8% and 7.25% (5/69), respectively. Among five patients who experienced recurrence, three had metachronous recurrence, all of which were type I; the remaining two patients exhibited distant hepatic metastasis, encompassing types I and III. The time to recurrence was 1 to 9.8 years.Margin positivity (p=0.002) and invasion deeper than the submucosal layer (p=0.007) were associated with higher recurrence rates. However, there was no significant association between recurrence and intestinal metaplasia, atrophic gastritis, or Helicobacter pylori infection. Conclusions Most patients with GNETs in this study had grade I and type I tumors, and the overall prognosis was favorable. Patients with risk factors for recurrence warrant further investigation. Those presenting margin positivity or deep invasion after resection should be closely monitored and undergo follow-up examinations, as necessary.