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: Sarcopenia, a multifactorial disorder involving metabolic disturbance, suggests potential for metabolite biomarkers. Carnitine (CN), essential for skeletal muscle energy metabolism, may be a candidate biomarker. We investigated whether CN metabolites are biomarkers for sarcopenia. Methods: Associations between the CN metabolites identified from an animal model of sarcopenia and muscle cells and sarcopenia status were evaluated in men from an age-matched discovery (72 cases, 72 controls) and a validation (21 cases, 47 controls) cohort. Results: An association between CN metabolites and sarcopenia showed in mouse and cell studies. In the discovery cohort, plasma C5-CN levels were lower in sarcopenic men (P=0.005). C5-CN levels in men tended to be associated with handgrip strength (HGS) (P=0.098) and were significantly associated with skeletal muscle mass (P=0.003). Each standard deviation increase in C5-CN levels reduced the odds of low muscle mass (odd ratio, 0.61; 95% confidence interval [CI], 0.42 to 0.89). The area under the receiver operating characteristic curve (AUROC) of CN score using a regression equation of C5-CN levels, for sarcopenia was 0.635 (95% CI, 0.544 to 0.726). In the discovery cohort, addition of CN score to HGS significantly improved AUROC from 0.646 (95% CI, 0.575 to 0.717; HGS only) to 0.727 (95% CI, 0.643 to 0.810; P=0.006; HGS+CN score). The improvement was confirmed in the validation cohort (AUROC=0.563; 95% CI, 0.470 to 0.656 for HGS; and AUROC=0.712; 95% CI, 0.569 to 0.855 for HGS+CN score; P=0.027). Conclusion C5-CN, indicative of low muscle mass, is a potential circulating biomarker for sarcopenia in men. Further studies are required to confirm these results and explore sarcopenia-related metabolomic changes.

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.

Human rhinovirus (HRV) causes the common cold and exacerbates chronic respiratory diseases, such as asthma and chronic obstructive pulmonary disease. Despite its significant impact on public health, there are currently no approved vaccines or antiviral treatments for HRV infection. Apoptosis is the process through which cells eliminate themselves through the systematic activation of intrinsic death pathways in response to various stimuli. It plays an important role in viral infections and serves as a key immune defense mechanism in the interactions between viruses and the host. In the present study, we investigated the antiviral effects of quercetin-3-methyl ether, a flavonoid isolated from Serratula coronata, on human rhinovirus 1B (HRV1B). Quercetin-3-methyl ether significantly inhibited HRV1B replication in HeLa cells in a concentration-dependent manner, thereby reducing cytopathic effects and viral RNA levels. Time-course and time-of-addition analyses confirmed that quercetin-3-methyl ether exhibited antiviral activity during the early stages of viral infection, potentially targeting the replication and translation phases. Gene expression analysis using microarrays revealed that pro-apoptotic genes were upregulated in quercetin-3-methyl ether-treated cells, suggesting that quercetin-3-methyl ether enhances early apoptosis to counteract HRV1B-induced immune evasion. In vivo administration of quercetin-3-methyl ether to HRV1B-infected mice significantly reduced viral RNA levels and inflammatory cytokine production in the lung tissues. Our findings demonstrated the potential of quercetin-3-methyl ether as a novel antiviral agent against HRV1B, thereby providing a promising therapeutic strategy for the management of HRV1B infections and related complications.

Acute Respiratory Distress Syndrome (ARDS) is a severe condition characterized by extensive lung inflammation and increased alveolar-capillary permeability, often triggered by infections or systemic inflammatory responses. Mesenchymal stem cells (MSCs)-based therapy holds promise for treating ARDS, as MSCs manifest immunomodulatory and regenerative properties that mitigate inflammation and enhance tissue repair. Primed MSCs, modified to augment specific functionalities, demonstrate superior therapeutic efficacy in targeted therapies compared to naive MSCs. This study explored the immunomodulatory potential of MSCs using mixed lymphocyte reaction (MLR) assays and co-culture experiments with M1/M2 macrophages. Additionally, RNA sequencing was employed to identify alterations in immune and inflammation-related factors in primed MSCs. The therapeutic effects of primed MSCs were assessed in an LPS-induced ARDS mouse model, and the underlying mechanisms were investigated through spatial transcriptomics analysis. The study revealed that MSCs primed with IFN-γ and IL-1β significantly enhanced the suppression of T cell activity compared to naive MSCs, concurrently inhibiting TNF-α while increasing IL-10 production in macrophages. Notably, combined treatment with these two cytokines resulted in a significant upregulation of immune and inflammation-regulating factors. Furthermore, our analyses elucidated the mechanisms behind the therapeutic effects of primed MSCs, including the inhibition of inflammatory cell infiltration in lung tissue, modulation of immune and inflammatory responses, and enhancement of elastin fiber formation. Signaling pathway analysis confirmed that efficacy could be enhanced by modulating NFκB and TNF-α signaling. In conclusion, in early-phase ARDS, primed MSCs displayed enhanced homing capabilities, improved lung function, and reduced inflammation.

Purpose: Lupus nephritis (LN) can be caused by the complement activation. This study aimed to investigate the differences and clinical implications of the activation pattern of the complement system for pediatric and adult LN patients. Methods: We retrospectively reviewed the medical records of 40 patients (14 pediatric and 26 adult patients) diagnosed with LN through kidney biopsy. Results: The mean ages at diagnosis of pediatric and adult patients were 11.7±2.92 and 37.3±13.5 years, respectively. At the first LN diagnosis, compared with adult patients, pediatric patients had a higher estimated glomerular filtration rate and milder proteinuria; however, there was no statistical significance. The age-adjusted mean serum complement 3 value was significantly lower in the pediatric group (33.0±11.3 mg/dL) than in the adult group (50.8±25.2 mg/dL) (P<0.01). Based on the findings of kidney biopsy, no significant differences were observed in the severity of pathologic classification and the positive rate of complements between adults and children. However, the chronicity index score of adult patients was significantly higher than that of pediatric patients and in the case of complement 4d, despite a similar positive rate, the intensity was significantly stronger for adults (2.35±0.83 vs. 1.54±0.52, (P=0.04). Conclusions The activation pattern of the complement system in LN differs clinicopathologically between pediatric and adult patients and these differences might play an important role in the age-dependent prognosis of LN.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.