Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Cardiovascular disease is an important risk factor for mortality among kidney transplant recipients. In this study, we aimed to investigate the association between cardiovascular risk score at kidney transplantation and long-term outcomes of patients. Methods: In this prospective, observational cohort study, we enrolled kidney transplant recipients who participated in the Korean Organ Transplantation Registry and underwent transplantation between April 2014 and December 2019. The cardiovascular risk status of kidney transplant recipients was assessed using the Framingham risk score. All-cause mortality, major adverse cardiovascular events, allograft failure, estimated glomerular filtration rates (eGFRs), and composite outcomes were evaluated after kidney transplantation. Results: Of the 4,682 kidney transplant recipients, 96 died during 30.7 ± 19.1 months of follow-up. The Kaplan-Meier survival analysis results showed that high Framingham risk scores were associated with all-cause mortality, major adverse cardiovascular events, and composite outcomes. According to the multivariable Cox analysis, high Framingham risk scores were associated with an increased risk of mortality (hazard ratio [HR], 3.20; 95% confidence interval [CI], 1.30–7.91), major adverse cardiovascular events (HR, 8.43; 95% CI, 2.41–29.52), and composite outcomes (HR, 2.05; 95% CI, 1.19–3.46). The eGFRs after transplantation were significantly higher among patients in the low Framingham risk score group (p < 0.001). However, Framingham risk scores were not associated with graft loss or rapid decline in eGFRs. Conclusion: The Framingham risk score is a useful indicator of cardiovascular events, mortality, and kidney function after kidney transplantation.

Sesquiterpene lactones, a class of natural compounds abundant in the Asteraceae family, have gained attention owing to their diverse biological activities, and particularly their anti-proliferative effects on human cancer cells. In this study, we systematically investigated the structure-activity relationship of ten sesquiterpene lactones with the aim of elucidating the structural determinants for the STAT3 inhibition governing their anti-proliferative effects. Our findings revealed a significant correlation between the STAT3 inhibitory activity and the anti-proliferative effects of sesquiterpene lactones in MDA-MB-231 breast cancer cell lines. Among the compounds tested, alantolactone and isoalantolactone emerged as the most potent STAT3 inhibitors, highlighting their potential as candidates for anticancer drug development. Through protein-ligand docking studies, we revealed the structural basis of STAT3 inhibition by sesquiterpene lactones, emphasizing the critical role of hydrogen-bonding interactions with key residues, including Arg609, Ser611, Glu612, and Ser613, in the SH2 domain of STAT3. Furthermore, our conformational analysis revealed the decisive role of the torsion angle within the geometry-optimized structures of sesquiterpene lactones in their STAT3 inhibitory activity (R=0.80, p<0.01). These findings not only provide preclinical evidence for sesquiterpene lactones as promising phytomedicines against diseases associated with abnormal STAT3 activation, but also highlight the importance of stereochemical aspects in their activity.

OBJECTIVES: Inconsistent results are available regarding the association between low estimated glomerular filtration rate (eGFR) and lung cancer risk. We aimed to explore the risk of lung cancer according to eGFR category in the Korean population. METHODS: We included 358,293 adults who underwent health checkups between 2009 and 2010, utilizing data from the National Health Insurance Service-National Sample Cohort. Participants were categorized into 3 groups based on their baseline eGFR, as determined using the Chronic Kidney Disease Epidemiology Collaboration equation: group 1 (eGFR ≥90 mL/min/1.73 m2), group 2 (eGFR ≥60 to <90 mL/min/1.73 m2), and group 3 (eGFR <60 mL/min/1.73 m2). Incidences of lung cancer were identified using the corresponding codes from the International Classification of Diseases, 10th revision. Multivariate Cox proportional hazard models were employed to calculate the adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for lung cancer incidence up to 2019. RESULTS: In multivariate analysis, group 2 exhibited a 26% higher risk of developing lung cancer than group 1 (HR, 1.26; 95% CI, 1.19 to 1.35). Furthermore, group 3 demonstrated a 72% elevated risk of lung cancer relative to group 1 (HR, 1.72; 95% CI, 1.58 to 1.89). Among participants with dipstick proteinuria of 2+ or greater, group 3 faced a significantly higher risk of lung cancer than group 1 (HR, 2.93; 95% CI, 1.37 to 6.24). CONCLUSIONS Low eGFR was significantly associated with increased lung cancer risk within the Korean population. A particularly robust association was observed in individuals with severe proteinuria, emphasizing the need for further investigation.

Polycystic ovarian syndrome (PCOS) is a common endocrine and reproductive disorder that affects 5-25% of women of reproductive age. It is characterized by hormonal imbalances, ovulatory dysfunction, and various clinical symptoms due to excess androgen. Insulin resistance, the primary cause of PCOS, can lead to weight gain and an increased risk of metabolic syndrome, if patients do not receive proper treatment and care. Subsequent complications can lead to infertility, type 2 diabetes, cardiovascular disease, endometrial cancer, and more. PCOS is known to be caused by a combination of genetic, environmental, and lifestyle factors, so early diagnosis and integrated management, including metabolic and functional medicine approaches, are important for long-term health. There are several types of PCOS, each of which requires personalized management tailored to the individual's condition. Depending on the main signs and symptoms of PCOS, treatment may include nutrition, exercise, stress management, and lifestyle modifications.

Objective: Glucagon in mammals and its homolog (adipokinetic hormone [AKH] in Drosophila melanogaster) are peptide hormones which regulate lipid metabolism by breaking down triglycerides. Although regulatory mechanisms of glucagon and Akh expression have been widely studied, post-transcriptional gene expression of glucagon has not been investigated thoroughly. In this study, we aimed to profile proteins binding with Gcg messenger RNA (mRNA) in mouse and Akh mRNA in Drosophila. Methods: Drosophila Schneider 2 (S2) and mouse 3T3-L1 cell lysates were utilized for affinity pull down of Akh and Gcg mRNA respectively using biotinylated anti-sense DNA oligoes against target mRNAs. Mass spectrometry and computational network analysis revealed mRNA-interacting proteins residing in functional proximity. Results: We observed that 1) 91 proteins interact with Akh mRNA from S2 cell lysates, 2) 34 proteins interact with Gcg mRNA from 3T3-L1 cell lysates. 3) Akh mRNA interactome revealed clusters of ribosomes and known RNA-binding proteins (RBPs). 4) Gcg mRNA interactome revealed mRNA-binding proteins including Plekha7, zinc finger protein, carboxylase, lipase, histone proteins and a cytochrome, Cyp2c44. 5) Levels of Gcg mRNA and its interacting proteins are elevated in skeletal muscles isolated from old mice compared to ones from young mice. Conclusion Akh mRNA in S2 cells are under active translation in a complex of RBPs and ribosomes. Gcg mRNA in mouse precursor adipocyte is in a condition distinct from Akh mRNA due to biochemical interactions with a subset of RBPs and histones. We anticipate that our study contributes to investigating regulatory mechanisms of Gcg and Akh mRNA decay, translation, and localization.

Purpose: We aimed to identify collaborative disaster governance through the demand and supply analysis of resources recognized by nurses during the COVID-19 pandemic. Methods: We used a descriptive study design with an online survey technique for data collection. The survey questions were developed based on focus group interviews with nurses responding to COVID-19 and expert validity testing. A 42-question online survey focusing on disaster governance was sent to nurses working in COVID-19 designated hospitals, public health offices, and schools. A total of 630 nurses participated in the survey. Demand and supply analysis was used to identify the specific components of disaster governance during a pandemic situation and analyze priority areas in disaster governance, as reported by nurses. Results: Demand and supply analysis showed that supplies procurement, cooperation, education, and environment factors clustered in the high demand and supply quadrant while labor condition, advocacy, emotional support, and workload adjustment factors clustered in the high demand but low supply quadrant, indicating a strong need in those areas of disaster governance among nurses. The nurses practicing at the public health offices and schools showed major components of disaster governance plotted in the second quadrant, indicating weak collaborative disaster governance. Conclusion These findings show that there is an unbalanced distribution among nurses, resulting in major challenges in collaborative disaster governance during COVID-19. In the future and current pandemic, collaborative disaster governance, through improved distribution, will be useful for helping nurses to access more required resources and achieve effective pandemic response.