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.

Background: s/Aims: Microwave ablation (MWA) is an emerging ablative therapy that surpasses previous methods by achieving higher temperatures and creating larger ablation zones within shorter periods. This study compared the therapeutic outcomes of MWA with those of liver resection in real-world clinical practice. Methods: A total of 178 patients with 259 nodules who underwent MWA or liver resection between January 2015 and July 2023 were enrolled. Local tumor progression (LTP)-free survival, overall progression (OP)-free survival, and overall survival (OS) were assessed based on the treatment modality for the index nodule. Results: Of the 178 patients, 134 with 214 nodules underwent MWA, and 44 with 45 nodules underwent liver resection. The median follow-up period was 2.0±1.5 years. The annual incidence of LTP was 3.7% for MWA and 1.4% for liver resection. Treatment modality did not significantly affect LTP-free survival (hazard ratio, 0.61; 95% confidence interval, 0.14-2.69; P=0.511). For nodules larger than 3 cm, LTP-free survival was not affected by the treatment modality. Similarly, OP-free survival and OS were not influenced by treatment modality. Conclusions MWA and liver resection demonstrated comparable treatment outcomes in terms of local tumor control, overall recurrence, and survival. MWA may be an alternative treatment option for select patients; however, further studies are necessary to generalize these findings.

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.

Purpose: Given that 40%-50% of primary central nervous system lymphoma (PCNSL) tissues exhibit aberrancy on 9p24.1, immune checkpoint inhibitors (ICI) may work for the disease. Materials and Methods: To define the role of ICIs in PCNSL, we carried out a nationwide retrospect analysis for 22 patients who had been treated with nivolumab monotherapy for relapsed or refractory PCNSL. Results: The median age at diagnosis was 66, and male: female ratio was 1:1. Patients received nivolumab after a median of 3 lines (range, 2 to 6) of therapy and at the median age of 67 years (range, 37 to 82 years). Eleven patients (50%) were refractory to the last treatment prior to nivolumab. With a median follow-up duration of 22.3 months (95% confidence interval [CI], 13.1 to 31.5), nine patients (41%) had an objective response (6 complete responses, 3 partial responses), and the median duration of response was 20.9 months (95% CI, 1.7 to 40.0). The median progression-free survival and overall survival were 2.1 months (95% CI, 0.2 to 4.0) and 18.9 months (95% CI, 5.0 to 32.8), respectively. Nivolumab was generally well-tolerated as no patients required dose reduction and only two patients required delay of treatment. Conclusion Our study suggests that nivolumab can be a reasonable option with the durable response for RR PCNSL.

The detrimental effects of hyperlipidemia on the healing of rotator cuff tears are well documented. The proposed underlying mechanisms for these effects include alterations in the extracellular matrix, inflammation, and oxidative stress, which hamper the reparative processes in the affected tendon tissues. Recent therapeutic strategies target these pathways, reflecting a growing body of research dedicated to mitigating these effects and promoting healing. This literature review aims to provide a comprehensive understanding of the pathophysiology underlying rotator cuff tears, examine the interplay between hyperlipidemia and rotator cuff tear healing, synthesize current knowledge on contributing biological mechanisms, and outline potential therapeutic interventions to optimize clinical management and treatment outcomes for patients.

Background: This study aimed to investigate changes after repeated subacromial drug injections in a rat model of normal rotator cuff. Methods: Thirty-nine male Sprague-Dawley rats were divided into groups 1 (no injection, n = 3), 2 (parecoxib, n = 18; 6 subgroups, n = 3 each; 0.5 mg/kg), and 3 (triamcinolone, n = 18; 6 subgroups, n = 3 each; 0.3 mg/kg). Groups 2 and 3 received subacromial injections 1–6 times once weekly for 6 weeks. The supraspinatus and infraspinatus tendons and muscles were used for biomechanical and histological evaluation. The subacromial bursa was used to analyze the prostaglandin E2 (PEG2) level. Results: In the biomechanical test, load-to-failure and ultimate stress decreased in groups 2 and 3 with repeated injections and the values were significantly lower in group 3 than in group 1 only at the sixth injection (p = 0.007 and p = 0.008, respectively). On the Bonar score, the cellularity, ground substance, and total score were significantly different among the 3 groups at the fifth and sixth injections (cellularity: p = 0.028 and p = 0.033, ground substance: p = 0.018 and p = 0.006, and total score: p = 0.029 and p = 0.027, respectively). The myocyte cross-sectional area of the infraspinatus muscle showed a significant difference among the 3 groups at the third and fourth injections (p = 0.031 and p = 0.020, respectively). The PEG2 level in the subacromial bursa was significantly different among the 3 groups at the third, fifth, and sixth injections (p = 0.019, p = 0.004, and p = 0.004, respectively). Conclusions In the rat model of normal rotator cuff, repeated local injections of the cyclooxygenase-2 inhibitor showed fewer negative effects on the biomechanical and histological properties of the normal tendon than triamcinolone.

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/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.