Purpose: This study aimed to develop a comprehensive practical guide for enteral nutrition (EN) designed to enhance patient safety and reduce complications in Korea. Under the leadership of the Korean Society for Parenteral and Enteral Nutrition (KSPEN), the initiative sought to standardize EN procedures, improve decision-making, and promote effective multidisciplinary communication. Methods: The KSPEN EN committee identified key questions related to EN practices and organized them into seven sections such as prescribing, delivery route selection, formula preparation, administration, and quality management. Twenty-one experts, selected based on their expertise, conducted a thorough literature review to formulate evidence-based recommendations. Drafts underwent peer review both within and across disciplines, with final revisions completed by the KSPEN Guideline Committee. The guide, which will be published in three installments, addresses critical elements of EN therapy and safety protocols. Results: The practical guide recommends that EN orders include detailed elements and advocates the use of electronic medical records for communication. Standardized prescription forms and supplementary safety measures are outlined. Review frequency is adjusted according to patient condition—daily for critically ill or unstable patients and as dictated by institutional protocols for stable patients. Evidence indicates that adherence to these protocols reduces mortality, complications, and prescription errors. Conclusion The KSPEN practical guide offers a robust framework for the safe delivery of EN tailored to Korea’s healthcare context. It emphasizes standardized protocols and interdisciplinary collaboration to improve nutritional outcomes, patient safety, and operational efficiency. Rigorous implementation and monitoring of adherence are critical for its success.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

BACKGROUND/OBJECTIVES: Green Citrus junos (yuja) peel extract has higher naringin and hesperidin contents and antioxidant activity than yellow yuja peel extract, but its anti-obesity effects are unclear. This study examined the anti-obesity properties of green yuja peel ethanol extract (GYE) in 3T3-L1 cells and high-fat diet (HFD)-induced obese mice.MATERIALS/METHODS: The effects of GYE on adipocyte differentiation were assessed by measuring Oil red O staining, mRNA and protein expression. The beneficial effects of GYE on HFD-induced obese mice were evaluated using the body weight, body composition, visceral fat size, and biochemical analysis. RESULTS: GYE inhibited adipocyte differentiation and lipid accumulation compared to the control cells, as evidenced by Oil red O staining and the triglyceride level, respectively.GYE down-regulated the adipogenic genes CCAAT/enhancer binding protein α (C/EBPα) and peroxisome proliferator-activated receptor γ (PPARγ), and lipogenic gene diacylglycerol O-acyltransferase 2 (DGAT2). GYE at 100 μg/mL downregulated the phosphorylation levels of phosphoinositide 3-kinase (PI3K) and protein kinase B (Akt), and their downstream targets PPARγ and sterol regulatory element-binding protein-1 (SREBP-1c) compared to the control group. In obese mice, GYE (100 mg/kg/day) reduced the body weight, body weight gain, and serum lipid level compared to the control group. Analysis using dual-energy X-ray absorptiometry showed that GYE decreased the fat percentage, fat in tissue, and abdominal circumference, while it increased the lean percentage compared to control group.Furthermore, GYE significantly reduced the visceral fat weight and size compared to the control group. CONCLUSION GYE suppressed adipocyte differentiation by inhibiting the PI3K-Akt pathway in vitro and reduced the body fat mass and visceral adiposity in HFD-induced obese mice.These findings suggest that GYE is a viable natural option for combating obesity.

Hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP) are correlated with high morbidity and mortality rates. Guidelines that consider local epidemiologic data are fundamental for identifying optimal treatment strategies. However, Korea has no HAP/VAP guidelines. This study was conducted by a committee of nine experts from the Korean Academy of Tuberculosis and Respiratory Diseases Respiratory Infection Study Group using the results of Korean HAP/VAP epidemiologic studies. Eleven key questions for HAP/VAP diagnosis and treatment were addressed. The Convergence of Opinion on Suggestions and Evidence (CORE) process was used to derive suggestions, and evidence levels and recommendation grades were in accordance with the Grading of Recommendations Assessment Development and Evaluation (GRADE) methodology. Suggestions were made for the 11 key questions pertinent to diagnosis, biomarkers, antibiotics, and treatment strategies for adult patients with HAP/VAP. Using the CORE process and GRADE methodology, the committee generated a series of recommendations for HAP/VAP diagnosis and treatment in the Korean context.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

BACKGROUND/OBJECTIVES: Green Citrus junos (yuja) peel extract has higher naringin and hesperidin contents and antioxidant activity than yellow yuja peel extract, but its anti-obesity effects are unclear. This study examined the anti-obesity properties of green yuja peel ethanol extract (GYE) in 3T3-L1 cells and high-fat diet (HFD)-induced obese mice.MATERIALS/METHODS: The effects of GYE on adipocyte differentiation were assessed by measuring Oil red O staining, mRNA and protein expression. The beneficial effects of GYE on HFD-induced obese mice were evaluated using the body weight, body composition, visceral fat size, and biochemical analysis. RESULTS: GYE inhibited adipocyte differentiation and lipid accumulation compared to the control cells, as evidenced by Oil red O staining and the triglyceride level, respectively.GYE down-regulated the adipogenic genes CCAAT/enhancer binding protein α (C/EBPα) and peroxisome proliferator-activated receptor γ (PPARγ), and lipogenic gene diacylglycerol O-acyltransferase 2 (DGAT2). GYE at 100 μg/mL downregulated the phosphorylation levels of phosphoinositide 3-kinase (PI3K) and protein kinase B (Akt), and their downstream targets PPARγ and sterol regulatory element-binding protein-1 (SREBP-1c) compared to the control group. In obese mice, GYE (100 mg/kg/day) reduced the body weight, body weight gain, and serum lipid level compared to the control group. Analysis using dual-energy X-ray absorptiometry showed that GYE decreased the fat percentage, fat in tissue, and abdominal circumference, while it increased the lean percentage compared to control group.Furthermore, GYE significantly reduced the visceral fat weight and size compared to the control group. CONCLUSION GYE suppressed adipocyte differentiation by inhibiting the PI3K-Akt pathway in vitro and reduced the body fat mass and visceral adiposity in HFD-induced obese mice.These findings suggest that GYE is a viable natural option for combating obesity.

Hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP) are correlated with high morbidity and mortality rates. Guidelines that consider local epidemiologic data are fundamental for identifying optimal treatment strategies. However, Korea has no HAP/VAP guidelines. This study was conducted by a committee of nine experts from the Korean Academy of Tuberculosis and Respiratory Diseases Respiratory Infection Study Group using the results of Korean HAP/VAP epidemiologic studies. Eleven key questions for HAP/VAP diagnosis and treatment were addressed. The Convergence of Opinion on Suggestions and Evidence (CORE) process was used to derive suggestions, and evidence levels and recommendation grades were in accordance with the Grading of Recommendations Assessment Development and Evaluation (GRADE) methodology. Suggestions were made for the 11 key questions pertinent to diagnosis, biomarkers, antibiotics, and treatment strategies for adult patients with HAP/VAP. Using the CORE process and GRADE methodology, the committee generated a series of recommendations for HAP/VAP diagnosis and treatment in the Korean context.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

BACKGROUND/OBJECTIVES: Green Citrus junos (yuja) peel extract has higher naringin and hesperidin contents and antioxidant activity than yellow yuja peel extract, but its anti-obesity effects are unclear. This study examined the anti-obesity properties of green yuja peel ethanol extract (GYE) in 3T3-L1 cells and high-fat diet (HFD)-induced obese mice.MATERIALS/METHODS: The effects of GYE on adipocyte differentiation were assessed by measuring Oil red O staining, mRNA and protein expression. The beneficial effects of GYE on HFD-induced obese mice were evaluated using the body weight, body composition, visceral fat size, and biochemical analysis. RESULTS: GYE inhibited adipocyte differentiation and lipid accumulation compared to the control cells, as evidenced by Oil red O staining and the triglyceride level, respectively.GYE down-regulated the adipogenic genes CCAAT/enhancer binding protein α (C/EBPα) and peroxisome proliferator-activated receptor γ (PPARγ), and lipogenic gene diacylglycerol O-acyltransferase 2 (DGAT2). GYE at 100 μg/mL downregulated the phosphorylation levels of phosphoinositide 3-kinase (PI3K) and protein kinase B (Akt), and their downstream targets PPARγ and sterol regulatory element-binding protein-1 (SREBP-1c) compared to the control group. In obese mice, GYE (100 mg/kg/day) reduced the body weight, body weight gain, and serum lipid level compared to the control group. Analysis using dual-energy X-ray absorptiometry showed that GYE decreased the fat percentage, fat in tissue, and abdominal circumference, while it increased the lean percentage compared to control group.Furthermore, GYE significantly reduced the visceral fat weight and size compared to the control group. CONCLUSION GYE suppressed adipocyte differentiation by inhibiting the PI3K-Akt pathway in vitro and reduced the body fat mass and visceral adiposity in HFD-induced obese mice.These findings suggest that GYE is a viable natural option for combating obesity.

Hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP) are correlated with high morbidity and mortality rates. Guidelines that consider local epidemiologic data are fundamental for identifying optimal treatment strategies. However, Korea has no HAP/VAP guidelines. This study was conducted by a committee of nine experts from the Korean Academy of Tuberculosis and Respiratory Diseases Respiratory Infection Study Group using the results of Korean HAP/VAP epidemiologic studies. Eleven key questions for HAP/VAP diagnosis and treatment were addressed. The Convergence of Opinion on Suggestions and Evidence (CORE) process was used to derive suggestions, and evidence levels and recommendation grades were in accordance with the Grading of Recommendations Assessment Development and Evaluation (GRADE) methodology. Suggestions were made for the 11 key questions pertinent to diagnosis, biomarkers, antibiotics, and treatment strategies for adult patients with HAP/VAP. Using the CORE process and GRADE methodology, the committee generated a series of recommendations for HAP/VAP diagnosis and treatment in the Korean context.