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: 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: 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: 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.

Purpose: Papillary thyroid cancer (PTC), a common malignancy among women of reproductive age, is increasingly common during pregnancy because of routine prenatal imaging. However, the optimal timing for surgical treatment remains controversial. This study aimed to assess the safety and practicality of performing thyroid surgery during pregnancy through a comparative analysis of perioperative and pathological outcomes between pregnant and nonpregnant women. Methods: We conducted a retrospective case-control study of 100 female patients aged 20–39 years who underwent thyroid surgery for PTC between January 2019 and December 2024. Patients were grouped into pregnant (n = 14) and nonpregnant (n = 86) cohorts. Clinical, surgical, and pathological data were compared. Results: Most pregnant patients underwent surgery during the second trimester. The operative duration was significantly shorter in the pregnant group than in the nonpregnant group (71.4 ± 26.35 minutes vs. 87.2 ± 5.17 minutes, P = 0.025), and there was a trend towards a lower drain volume on postoperative day 1 (25.2 ± 15.23 mL vs. 32.7 ± 0.18 mL, P = 0.077).No significant differences were observed in terms of complication rates. Despite a higher frequency of extrathyroidal extension (P = 0.003) and advanced T stage (P = 0.038) in the pregnant group, the surgical outcomes were favorable. One neonate experienced mild intraventricular hemorrhage that resolved without sequelae. Conclusion Thyroid surgery during pregnancy, particularly in the second trimester, appears feasible in selected patients.Given the small sample and retrospective nature of this study, larger prospective studies are needed to validate these findings.

Multiple myeloma (MM), a hematological malignancy, is characterized by malignant plasma cell proliferation in the bone marrow. Recent treatment advances have significantly improved patient outcomes associated with MM.In this study, we aimed to develop comprehensive, evidence-based guidelines for the diagnosis, prognosis, and treat‑ ment of MM. We identified 12 key clinical questions essential for MM management, guiding the extensive literature review and meta-analysis of the study. Our guidelines provide evidence-based recommendations by integrating patient preferences with survey data. These recommendations include current and emerging diagnostic tools, thera‑ peutic agents, and treatment strategies. By prioritizing a patient-centered approach and rigorous data analysis, these guidelines were developed to enhance MM management, both in Korea and globally.

Objective: This study aimed to develop and validate a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to quantify gentamicin residues in milk and to establish a withdrawal period for an intramuscular gentamicin product in dairy cows. Methods: Nine Holstein cows received a gentamicin product (50 mg gentamicin sulfate/ mL) at 0.1 mL/kg twice daily at 12 h intervals via intramuscular injection. Milk samples were collected before dosing and at 12 h intervals up to 168 h after the final administration and analysed with a validated LC-MS/MS method using heptafluorobutyric acid as an ion-pairing reagent. Results: The method showed recovery rates of 86%–104%, coefficients of variation of 3%–11%, and limits of detection and quantitation of 23 and 70 ng/mL, respectively. Mean gentamicin concentrations exceeded the maximum residue limit (MRL; 0.2 mg/kg) at 12 h during treatment and 12 h after the final administration, and were < MRL in all cows from 36 h after the last dose. Based on residue depletion data and a national non-statistical guideline, a withdrawal period of 40–48 h was derived, and the regulatory withdrawal period for this product was established as 3 days. Conclusions and Relevance: The validated LC-MS/MS method enables rapid quantitation of gentamicin residues in bovine milk. A 3-day regulatory withdrawal period for this product supports milk safety, regulatory compliance, and practical use in dairy herds.

Background: Type 2 diabetes mellitus (T2DM) induces endothelial dysfunction and inflammation, which are the main factors for atherosclerosis and cardiovascular disease. The present study aimed to compare the effects of rosuvastatin monotherapy and rosuvastatin/ezetimibe combination therapy on lipid profile, insulin sensitivity, and vascular inflammatory response in patients with T2DM. Methods: A total of 101 patients with T2DM and dyslipidemia were randomized to either rosuvastatin monotherapy (5 mg/day, n=47) or rosuvastatin/ezetimibe combination therapy (5 mg/10 mg/day, n=45) and treated for 12 weeks. Serum lipids, glucose, insulin, soluble intercellular adhesion molecule-1 (sICAM-1), and peroxiredoxin 4 (PRDX4) levels were determined before and after 12 weeks of treatment. Results: The reduction in low density lipoprotein cholesterol (LDL-C) by more than 50% from baseline after treatment was more in the combination therapy group. The serum sICAM-1 levels increased significantly in both groups, but there was no difference between the two groups. The significant changes in homeostasis model assessment of insulin resistance (HOMA-IR) and PRDX4 were confirmed only in the subgroup in which LDL-C was reduced by 50% or more in the combination therapy group. However, after adjusting for diabetes mellitus duration and hypertension, the changes in HOMA-IR and PRDX4 were not significant between the two groups. Conclusion Although rosuvastatin/ezetimibe combination therapy had a greater LDL-C reduction effect than rosuvastatin monotherapy, it had no additional effects on insulin sensitivity and vascular inflammatory response. Further studies are needed on the effect of long-term treatment with ezetimibe on insulin sensitivity and vascular inflammatory response.

Mitochondrial stress and the dysregulated mitochondrial unfolded protein response (UPRmt) are linked to various diseases, including metabolic disorders, neurodegenerative diseases, and cancer. Mitokines, signaling molecules released by mitochondrial stress response and UPRmt, are crucial mediators of inter-organ communication and influence systemic metabolic and physiological processes. In this review, we provide a comprehensive overview of mitokines, including their regulation by exercise and lifestyle interventions and their implications for various diseases. The endocrine actions of mitokines related to mitochondrial stress and adaptations are highlighted, specifically the broad functions of fibroblast growth factor 21 and growth differentiation factor 15, as well as their specific actions in regulating inter-tissue communication and metabolic homeostasis. Finally, we discuss the potential of physiological and genetic interventions to reduce the hazards associated with dysregulated mitokine signaling and preserve an equilibrium in mitochondrial stress-induced responses. This review provides valuable insights into the mechanisms underlying mitochondrial regulation of health and disease by exploring mitokine interactions and their regulation, which will facilitate the development of targeted therapies and personalized interventions to improve health outcomes and quality of life.

Purpose: The objective of this study was to propose a deep-learning model for the detection of the mandibular canal on dental panoramic radiographs. Materials and Methods: A total of 2,100 panoramic radiographs (PANs) were collected from 3 different machines: RAYSCAN Alpha (n=700, PAN A), OP-100 (n=700, PAN B), and CS8100 (n=700, PAN C). Initially, an oral and maxillofacial radiologist coarsely annotated the mandibular canals. For deep learning analysis, convolutional neural networks (CNNs) utilizing U-Net architecture were employed for automated canal segmentation. Seven independent networks were trained using training sets representing all possible combinations of the 3 groups. These networks were then assessed using a hold-out test dataset. Results: Among the 7 networks evaluated, the network trained with all 3 available groups achieved an average precision of 90.6%, a recall of 87.4%, and a Dice similarity coefficient (DSC) of 88.9%. The 3 networks trained using each of the 3 possible 2-group combinations also demonstrated reliable performance for mandibular canal segmentation, as follows: 1) PAN A and B exhibited a mean DSC of 87.9%, 2) PAN A and C displayed a mean DSC of 87.8%, and 3) PAN B and C demonstrated a mean DSC of 88.4%. Conclusion This multi-device study indicated that the examined CNN-based deep learning approach can achieve excellent canal segmentation performance, with a DSC exceeding 88%. Furthermore, the study highlighted the importance of considering the characteristics of panoramic radiographs when developing a robust deep-learning network, rather than depending solely on the size of the dataset.