While glutamate, a key neurotransmitter in the central nervous system, is fundamental to neuronal viability and normal brain function, its excessive accumulation leads to oxidative stress, contributing to neuronal damage and neurodegenerative diseases. In this study, we investigated the effect of β-lapachone (β-Lap), a naturally occurring naphthoquinone, on glutamate-induced injury in HT22 cells and explored the underlying mechanism involved. Our results show that β-Lap significantly improved cell viability in a dose-dependent manner. Additionally, β-Lap exhibited a significant antioxidant activity, reducing intracellular reactive oxygen species levels and restoring glutathione levels. The antioxidant capacity of β-Lap was further demonstrated through 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and 2,2’-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) radical scavenging assays. Western blot analysis revealed that β-Lap upregulated brain-derived neurotrophic factor (BDNF) and promoted the phosphorylation of tropomyosin receptor kinase B (TrkB), extracellular signal-regulated kinase (ERK), and cAMP response elementbinding protein (CREB), which were downregulated by glutamate. Furthermore, β-Lap enhanced the cellular antioxidant molecules, nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1). In conclusion, β-Lap can protect HT22 cells against glutamate-induced injury by activating the BDNF/TrkB/ERK/CREB and ERK/Nrf2/HO-1 signaling pathways, suggesting its therapeutic potential for neurodegenerative diseases.

While glutamate, a key neurotransmitter in the central nervous system, is fundamental to neuronal viability and normal brain function, its excessive accumulation leads to oxidative stress, contributing to neuronal damage and neurodegenerative diseases. In this study, we investigated the effect of β-lapachone (β-Lap), a naturally occurring naphthoquinone, on glutamate-induced injury in HT22 cells and explored the underlying mechanism involved. Our results show that β-Lap significantly improved cell viability in a dose-dependent manner. Additionally, β-Lap exhibited a significant antioxidant activity, reducing intracellular reactive oxygen species levels and restoring glutathione levels. The antioxidant capacity of β-Lap was further demonstrated through 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and 2,2’-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) radical scavenging assays. Western blot analysis revealed that β-Lap upregulated brain-derived neurotrophic factor (BDNF) and promoted the phosphorylation of tropomyosin receptor kinase B (TrkB), extracellular signal-regulated kinase (ERK), and cAMP response elementbinding protein (CREB), which were downregulated by glutamate. Furthermore, β-Lap enhanced the cellular antioxidant molecules, nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1). In conclusion, β-Lap can protect HT22 cells against glutamate-induced injury by activating the BDNF/TrkB/ERK/CREB and ERK/Nrf2/HO-1 signaling pathways, suggesting its therapeutic potential for neurodegenerative diseases.

While glutamate, a key neurotransmitter in the central nervous system, is fundamental to neuronal viability and normal brain function, its excessive accumulation leads to oxidative stress, contributing to neuronal damage and neurodegenerative diseases. In this study, we investigated the effect of β-lapachone (β-Lap), a naturally occurring naphthoquinone, on glutamate-induced injury in HT22 cells and explored the underlying mechanism involved. Our results show that β-Lap significantly improved cell viability in a dose-dependent manner. Additionally, β-Lap exhibited a significant antioxidant activity, reducing intracellular reactive oxygen species levels and restoring glutathione levels. The antioxidant capacity of β-Lap was further demonstrated through 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and 2,2’-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) radical scavenging assays. Western blot analysis revealed that β-Lap upregulated brain-derived neurotrophic factor (BDNF) and promoted the phosphorylation of tropomyosin receptor kinase B (TrkB), extracellular signal-regulated kinase (ERK), and cAMP response elementbinding protein (CREB), which were downregulated by glutamate. Furthermore, β-Lap enhanced the cellular antioxidant molecules, nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1). In conclusion, β-Lap can protect HT22 cells against glutamate-induced injury by activating the BDNF/TrkB/ERK/CREB and ERK/Nrf2/HO-1 signaling pathways, suggesting its therapeutic potential for neurodegenerative diseases.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

Purpose: Improvements in surgical quality and patient safety are critical components of the healthcare system. Despite excellent cancer survival rates in Korea, there is a lack of standardized postoperative complication management systems.To address this gap, the Korean Surgical Society initiated the development of the Korean Quality Improvement Platform in Surgery (K-QIPS) program. Methods: K-QIPS was successfully launched in 87 general hospitals. This nationwide surgical quality improvement program covers 5 major surgical fields: gastric surgery, colorectal surgery, hepatectomy and liver transplantation, pancreatectomy, and kidney transplantation. Results: Common and surgery-specific complication platforms will be developed, and the program will work toward the implementation of an artificial intelligence-based complication prediction system and the provision of evidence-based feedback to participating institutions. K-QIPS represents a significant step toward improving surgical quality and patient safety in Korea. Conclusion This program aims to reduce postoperative complications, mortality, and medical costs by providing a standardized platform for complication management and prediction. The successful implementation of this nationwide project may provide a good model for other countries that are required to improve surgical outcomes and patient care.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

Purpose: Improvements in surgical quality and patient safety are critical components of the healthcare system. Despite excellent cancer survival rates in Korea, there is a lack of standardized postoperative complication management systems.To address this gap, the Korean Surgical Society initiated the development of the Korean Quality Improvement Platform in Surgery (K-QIPS) program. Methods: K-QIPS was successfully launched in 87 general hospitals. This nationwide surgical quality improvement program covers 5 major surgical fields: gastric surgery, colorectal surgery, hepatectomy and liver transplantation, pancreatectomy, and kidney transplantation. Results: Common and surgery-specific complication platforms will be developed, and the program will work toward the implementation of an artificial intelligence-based complication prediction system and the provision of evidence-based feedback to participating institutions. K-QIPS represents a significant step toward improving surgical quality and patient safety in Korea. Conclusion This program aims to reduce postoperative complications, mortality, and medical costs by providing a standardized platform for complication management and prediction. The successful implementation of this nationwide project may provide a good model for other countries that are required to improve surgical outcomes and patient care.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

Purpose: Improvements in surgical quality and patient safety are critical components of the healthcare system. Despite excellent cancer survival rates in Korea, there is a lack of standardized postoperative complication management systems.To address this gap, the Korean Surgical Society initiated the development of the Korean Quality Improvement Platform in Surgery (K-QIPS) program. Methods: K-QIPS was successfully launched in 87 general hospitals. This nationwide surgical quality improvement program covers 5 major surgical fields: gastric surgery, colorectal surgery, hepatectomy and liver transplantation, pancreatectomy, and kidney transplantation. Results: Common and surgery-specific complication platforms will be developed, and the program will work toward the implementation of an artificial intelligence-based complication prediction system and the provision of evidence-based feedback to participating institutions. K-QIPS represents a significant step toward improving surgical quality and patient safety in Korea. Conclusion This program aims to reduce postoperative complications, mortality, and medical costs by providing a standardized platform for complication management and prediction. The successful implementation of this nationwide project may provide a good model for other countries that are required to improve surgical outcomes and patient care.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.