Purpose: Patient-derived cells (PDCs) and patient-derived organoids (PDOs) are complementary preclinical models widely used in translational cancer research. However, their molecular and functional differences have not been systematically characterized. This study established and analyzed paired PDC and PDO models derived from the same gastric cancer ascites to delineate platform-dependent molecular and functional profiles. Materials and Methods: Malignant ascites or pleural fluid obtained from 6 patients with advanced gastric cancer were used to establish paired PDC and PDO models. All pairs underwent comprehensive multi-omics profiling, integrating genomic, transcriptomic, and proteomic data. Phenotypic characterization included morphological, histological, proliferative, and cell cycle analyses. Drug sensitivity assays were performed using 4 chemotherapeutic agents commonly used to treat gastric cancer. Results: The 6 paired PDC and PDO models exhibited distinct morphological characteristics.Whole-genome analyses demonstrated high concordance among primary tumors, PDCs, and PDOs, confirming tumor representation across platforms. Multi-omics profiling identified platform-dependent molecular signatures; PDOs were enriched for extracellular matrix remodeling and stemness, whereas PDCs displayed proliferation- and immune-related signatures. Clinically relevant biomarkers, including HER2 and MET alterations, were concordant with primary tumors. Notably, drug responses differed between platforms and patients, indicating platform-dependent and patient-specific chemosensitivity. Conclusions Paired PDC and PDO models derived from the same patients preserved core patient-specific tumor characteristics while exhibiting distinct molecular and functional profiles. These findings underscore the culture platform as a critical determinant of experimental outcomes and therapeutic responses. Therefore, careful selection of an appropriate preclinical model is essential to accurately address biological questions and optimize precision oncology strategies.

Background: The Korean Occupational Stress Scale (KOSS) was developed in 2004. During this time, industrial structures have evolved, and societal awareness of occupational stress has changed. This study aims to develop and validate a revised version of the Korean Occupational Stress Scale (KOSS®19), tailored for workers, reflecting these changes. Methods: The KOSS®19 was developed based on the 26-item KOSS–short form (SF) through a review by eight experts. A survey was conducted including 359 service industry workers, comprising the KOSS®19, Burnout, and Depression scales. The KOSS®19 subscales were restructured, and their reliability and validity were evaluated. Results: The KOSS®19 composed of eight subscales: hazardous physical environment (2 items), high job demand (3 items), insufficient job control (2 items), low social support (2 items), job insecurity (2 items), organizational injustice (4 items), lack of reward (2 items), and work-life imbalance (2 items). The reliability and validity of the KOSS®19 were found to be satisfactory. Conclusions The KOSS®19 is a suitable tool for assessing occupational stress, effectively replacing the original KOSS and KOSS-SF.

Background: Emotional labor refers to the management of emotions and expressions to meet the emotional requirements of a job role. This study aimed to develop a revised version of the Korean Emotional Labor Scale (KELS®11), based on the first edition (KELS-24) introduced in 2014, and to provide practical applications and guidelines for its use in the Korean workplace through a validation process. Methods: The revised version of KELS®11 was derived from the 24-item KELS, following a review process involving eight experts. To validate the scale’s reliability and validity, a self-administered survey was conducted among 359 service industry workers using KELS®11, burnout, and depression scales. KELS®11 was reclassified, and its reliability and validity were evaluated. Receiver operating characteristic curve analysis was conducted to establish sex-specific cutoff values (normal vs. high-risk groups). Results: KELS®11 was designed to account for individual, organizational, and cultural contexts. It consists of four subscales and 11 items: “emotional regulation” (2 items), “emotional dissonance” (3 items), “organizational monitoring” (2 items), and “organizational protective system for emotional labor” (4 items). KELS®11 demonstrated good validity (content validity ratio: 0.84; item convergence/discriminant validity success rates: 100%; correlation with burnout: r = 0.185–0.436, p < 0.01; correlation with depression: r = 0.128–0.339, p < 0.05) and reliability (Cronbach’s alpha: 0.597–0.795). Additionally, sex-specific reference values were established to determine risk groups based on the intensity of emotional labor exposure. Conclusions KELS®11 is a validated and reliable measurement tool designed to assess the intensity and magnitude of emotional labor in the workplace. The revised tool reflects critical considerations in the development of emotional labor measurement scales.

Background: Workplace violence refers to any act or threat of physical violence, verbal abuse, harassment, intimidation, bullying, mobbing, or other aggressive and disruptive behaviors that occur at work. This study aims to develop and validate a revision of the Korean Workplace Violence Scale (KWVS®13), based on the first edition of the Korean Workplace Violence Scale (KWVS-24), and to provide practical applications and guidelines for the Korean workplace environment. Methods: The revised KWVS®13 was developed by restructuring the 24-item KWVS through a review process involving eight experts. To validate the reliability and validity of KWVS®13, a self-administered survey comprising KWVS®13, burnout, and depression scales was conducted among 359 service industry workers. KWVS®13 was reclassified, and its reliability and validity were assessed. Receiver operating characteristic curve analysis was performed to establish sex-specific cutoff values (normal vs. risk) of the scale. Results: KWVS®13 consists of 13 items across four subscales: “psychological and sexual violence from customers” (4 items), “psychological and sexual violence from supervisors or coworkers” (4 items), “physical assault from customers, supervisors, or coworkers” (2 items), and “organizational protective system for workplace violence” (3 items). We found that KWVS®13 shows relatively good validity (content validity ratio for content validity: 0.888; success rate of item convergent and discriminant validity: 100%, and significant correlation coefficient with burnout (r = 0.115–0.83, p < 0.05) and depression (r = 0.098–0.348, p < 0.05) with the exception of Organizational Violence Protection System for Workplace Violence) and reliability (Cronbach’s alpha: 0.827–0.860). The reference values for determining risk groups according to the intensity of exposure to workplace violence are presented separately by sex. Conclusions KWVS®13 is a robust and useful measurement tool to objectively and quantitatively assess the intensity and magnitude of workplace violence. It incorporates important considerations for workplace violence assessment and provides a reliable framework for evaluating workplace violence in various professional settings.

Sepsis-associated acute kidney injury (SA-AKI) is a prominent sepsis complication, often resulting in adverse clinical outcomes. Hyperbaric oxygen therapy (HBOT), known for its anti-inflammatory characteristics, antioxidant effects, and ability to deliver high oxygen tension to hypo-perfused tissues, offers potential benefits for SA-AKI. This study investigated whether HBOT improved renal injury in sepsis and elucidated its underlying mechanisms. Methods: A lipopolysaccharide (LPS)-induced endotoxemia model was established using 8-week-old C57BL/6 mice. Thirty minutes post-LPS administration, a group of mice underwent HBOT at a 2.5 atmospheric pressure absolute with 100% oxygen for 60 minutes. After 24 hours, all mice were euthanized for measurements. Results: Our results demonstrated that HBOT effectively mitigated renal tubular cell apoptosis. Additionally, HBOT significantly reduced phosphorylated p53 proteins and cytochrome C levels, suggesting that HBOT may attenuate renal apoptosis by impeding p53 activation and cytochrome C release. Notably, HBOT preserved manganese-dependent levels of superoxide dismutase, an antioxidant enzyme, compared to the LPS group. Furthermore, transforming growth factor beta (TGF-β)/Smad4 and alpha smooth muscle actin expressions were significantly reduced in the LPS + HBOT group. Conclusion: An early single session of HBOT exhibited renoprotective effects in LPS-induced endotoxemia mice models by suppressing p53 activation and cytochrome C levels to mitigate apoptosis. The observed TGF-β decrease, downstream Smad expression reduction, and antioxidant capacity preservation following HBOT may contribute to these effects.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) as the reference standard. Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710). Conclusion QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.