suggest that some reproductive factors associated with BC differ across ethnicities and time trends, perhaps due to the prevalence of reproductive factors and the baseline hazard of BC.

Background: Insulin resistance (IR) is central to metabolic disorders and significantly influenced by diet. Studies on meal frequency (MF) and metabolic indicators have shown mixed results. This study explores the link between MF and IR in middle-aged and older adults. Methods: This prospective cohort study included 4,570 adults aged 40 to 69 years from the Korean Genome and Epidemiologic Study. MF were divided into two groups based on whether they consumed three or more, or fewer than three, meals daily. IR was evaluated using the homeostasis model assessment of insulin resistance (HOMA-IR); participants were classified as IR if their HOMA-IR value was ≥2.5. Multiple Cox proportional hazard regression analyses were conducted to examine the association between MF and the incidence of IR. Results: After adjusting for all variables, individuals in the MF ≥3 group showed a reduced incidence of IR compared to those in the MF <3 group (hazard ratio, 0.880; 95% confidence interval, 0.782 to 0.990). Additionally, subgroup analyses by sex, diabetes mellitus (DM), and body mass index (BMI) showed that this association persisted only in men, individuals without DM, and those with a BMI <25. Conclusion Our findings indicate that a higher MF among middle-aged and older adults is associated with a reduced incidence of IR. However, this association was maintained only in men, individuals without DM, and those without obesity.

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: Insulin resistance (IR) is central to metabolic disorders and significantly influenced by diet. Studies on meal frequency (MF) and metabolic indicators have shown mixed results. This study explores the link between MF and IR in middle-aged and older adults. Methods: This prospective cohort study included 4,570 adults aged 40 to 69 years from the Korean Genome and Epidemiologic Study. MF were divided into two groups based on whether they consumed three or more, or fewer than three, meals daily. IR was evaluated using the homeostasis model assessment of insulin resistance (HOMA-IR); participants were classified as IR if their HOMA-IR value was ≥2.5. Multiple Cox proportional hazard regression analyses were conducted to examine the association between MF and the incidence of IR. Results: After adjusting for all variables, individuals in the MF ≥3 group showed a reduced incidence of IR compared to those in the MF <3 group (hazard ratio, 0.880; 95% confidence interval, 0.782 to 0.990). Additionally, subgroup analyses by sex, diabetes mellitus (DM), and body mass index (BMI) showed that this association persisted only in men, individuals without DM, and those with a BMI <25. Conclusion Our findings indicate that a higher MF among middle-aged and older adults is associated with a reduced incidence of IR. However, this association was maintained only in men, individuals without DM, and those without obesity.

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: Insulin resistance (IR) is central to metabolic disorders and significantly influenced by diet. Studies on meal frequency (MF) and metabolic indicators have shown mixed results. This study explores the link between MF and IR in middle-aged and older adults. Methods: This prospective cohort study included 4,570 adults aged 40 to 69 years from the Korean Genome and Epidemiologic Study. MF were divided into two groups based on whether they consumed three or more, or fewer than three, meals daily. IR was evaluated using the homeostasis model assessment of insulin resistance (HOMA-IR); participants were classified as IR if their HOMA-IR value was ≥2.5. Multiple Cox proportional hazard regression analyses were conducted to examine the association between MF and the incidence of IR. Results: After adjusting for all variables, individuals in the MF ≥3 group showed a reduced incidence of IR compared to those in the MF <3 group (hazard ratio, 0.880; 95% confidence interval, 0.782 to 0.990). Additionally, subgroup analyses by sex, diabetes mellitus (DM), and body mass index (BMI) showed that this association persisted only in men, individuals without DM, and those with a BMI <25. Conclusion Our findings indicate that a higher MF among middle-aged and older adults is associated with a reduced incidence of IR. However, this association was maintained only in men, individuals without DM, and those without obesity.

Background: Insulin resistance (IR) is central to metabolic disorders and significantly influenced by diet. Studies on meal frequency (MF) and metabolic indicators have shown mixed results. This study explores the link between MF and IR in middle-aged and older adults. Methods: This prospective cohort study included 4,570 adults aged 40 to 69 years from the Korean Genome and Epidemiologic Study. MF were divided into two groups based on whether they consumed three or more, or fewer than three, meals daily. IR was evaluated using the homeostasis model assessment of insulin resistance (HOMA-IR); participants were classified as IR if their HOMA-IR value was ≥2.5. Multiple Cox proportional hazard regression analyses were conducted to examine the association between MF and the incidence of IR. Results: After adjusting for all variables, individuals in the MF ≥3 group showed a reduced incidence of IR compared to those in the MF <3 group (hazard ratio, 0.880; 95% confidence interval, 0.782 to 0.990). Additionally, subgroup analyses by sex, diabetes mellitus (DM), and body mass index (BMI) showed that this association persisted only in men, individuals without DM, and those with a BMI <25. Conclusion Our findings indicate that a higher MF among middle-aged and older adults is associated with a reduced incidence of IR. However, this association was maintained only in men, individuals without DM, and those without obesity.

Diabetes mellitus is characterized by hyperglycemic due to impaired insulin secretion or resistance. In our search for anti-diabetic agents, we found that a 70% EtOH extract of Rubus cochinchinensis(Tratt) enhances glucose uptake in 3T3-L1 adipocytes. R. cochinchinensis is predominantly found in East Asia, particularly in Vietnam, Laos, Cambodia, and southern in China. Despite its widespread distribution, there have been few studies on its bioactivity or chemical constituents. In this study, activity-guided fractionation of 70% EtOH extract from the leaves of R. cochinchinensis resulted in the isolation of one new ursane-type glycoside, 3-O-β-acetyl-28-O-β-D-glucopyranosyl-rotundioic acid (1), along with four known compounds (2–5). The structures of these compounds were elucidated using 1D and 2D NMR and HRESIMS data. Notably, compound 4 significantly increased the uptake level of 2-deoxy-2-[(7-nitro-2,1,3-benzoxadiazol-4-yl)amino]-D-glucose (2-NBDG) in differentiated 3T3-L1 adipocytes. This study suggests the potential of R. cochinchinensis as a promising medicinal plant for treating diabetes via glucose uptake.