ObjectiveTo explore the mechanism by which Ruyan Neixiao cream （RUC） induces ferroptosis in breast precancerous lesion （BPL） cells， and to enrich the theoretical foundation for its use in the treatment of BPL. MethodsThe inhibition of cell proliferation by 1%， 2%， and 4% concentrations of Ruyanneixiao Cream transdermal solution （RUT） was assessed using cell counting kit-8 （CCK-8） and a colony formation assay. Reactive oxygen species （ROS） were measured using the DCFH-DA probe， and the levels of ferrous ions （Fe²⁺）， glutathione （GSH）， and malondialdehyde （MDA） were determined using appropriate kits. Lipid peroxidation was detected with the C11-BODIPY^581/591 fluorescent probe. The expression of nuclear factor E₂-related factor 2 （Nrf2）， solute carrier family 7 member 11 （SLC7A11）， and glutathione peroxidase 4 （GPX4） proteins was analyzed by Western blot. The BPL rat model was constructed using 2，2′-bis（hydroxymethyl）butyric acid （DMBA） combined with estrogen and progesterone， and the rats were treated with RUC for external application. After the 12^th cycle， the rats were euthanized， and histopathological changes in breast tissue were observed by hematoxylin-eosin （HE） staining. Fe²⁺ and MDA levels in breast tissue were measured using corresponding kits. The expression of Nrf2， SLC7A11， and GPX4 proteins in BPL rat breast tissue was detected by immunohistochemistry （IHC） and Western blot. ResultsCompared with the matrix group， the cell viability of MCF-10AT cells in the 1%， 2%， and 4% RUT groups was significantly reduced （P<0.05） in a concentration-dependent manner， with the 24-hour half inhibitory concentration （IC₅₀） being 2.23%. Compared with the 4% RUT group， cell viability in the RUT + Fer-1 group was significantly increased （P<0.05）. Compared with the matrix group， the colony formation rates of MCF-10AT cells in the 1%， 2%， and 4% RUT groups were significantly decreased （P<0.05）. Compared with the 4% RUT group， the cell colony formation rate of the RUT + Fer-1 group was significantly increased （P<0.05）. Compared with the matrix group， the levels of ROS and Fe²⁺ in the 1%， 2%， and 4% RUT groups were significantly increased （P<0.05）， while GSH levels were significantly decreased （P<0.05）， and MDA and lipid peroxidation levels were significantly increased （P<0.05）. Compared with the 4% RUT group， ROS and Fe²⁺ levels in the RUT + Fer-1 group were significantly reduced （P<0.05）， while GSH levels were significantly increased （P<0.05）， and MDA and lipid peroxidation levels were significantly reduced （P<0.05）. Compared with the matrix group， the protein expression levels of Nrf2， SLC7A11， and GPX4 in the 1%， 2%， and 4% RUT groups were significantly decreased （P<0.05）. Compared with the 4% RUT group， the protein expression levels of Nrf2， SLC7A11， and GPX4 in the RUT + Fer-1 group were significantly increased （P<0.05）. In the in vivo experiment， compared with the matrix group， the breast tissue histopathological status of the BPL rats in the RUC group was effectively improved， with less dilatation of the mammary ducts and more orderly duct arrangement. No pathological morphology indicative of invasive cancer was observed. Compared with the matrix group， Fe²⁺ and MDA levels in the mammary tissue of the RUC group were significantly increased （P<0.05）. Compared with the matrix group， the protein expression levels of Nrf2， SLC7A11， and GPX4 in the mammary tissue of the RUC group were significantly reduced （P<0.05）. ConclusionRUC may induce ferroptosis in BPL cells by inhibiting the Nrf2/SLC7A11/GPX4 signaling pathway， increasing Fe²⁺ accumulation， and promoting lipid peroxidation.

ObjectiveTo explore the mechanism by which Ruyan Neixiao cream （RUC） induces ferroptosis in breast precancerous lesion （BPL） cells， and to enrich the theoretical foundation for its use in the treatment of BPL. MethodsThe inhibition of cell proliferation by 1%， 2%， and 4% concentrations of Ruyanneixiao Cream transdermal solution （RUT） was assessed using cell counting kit-8 （CCK-8） and a colony formation assay. Reactive oxygen species （ROS） were measured using the DCFH-DA probe， and the levels of ferrous ions （Fe²⁺）， glutathione （GSH）， and malondialdehyde （MDA） were determined using appropriate kits. Lipid peroxidation was detected with the C11-BODIPY^581/591 fluorescent probe. The expression of nuclear factor E₂-related factor 2 （Nrf2）， solute carrier family 7 member 11 （SLC7A11）， and glutathione peroxidase 4 （GPX4） proteins was analyzed by Western blot. The BPL rat model was constructed using 2，2′-bis（hydroxymethyl）butyric acid （DMBA） combined with estrogen and progesterone， and the rats were treated with RUC for external application. After the 12^th cycle， the rats were euthanized， and histopathological changes in breast tissue were observed by hematoxylin-eosin （HE） staining. Fe²⁺ and MDA levels in breast tissue were measured using corresponding kits. The expression of Nrf2， SLC7A11， and GPX4 proteins in BPL rat breast tissue was detected by immunohistochemistry （IHC） and Western blot. ResultsCompared with the matrix group， the cell viability of MCF-10AT cells in the 1%， 2%， and 4% RUT groups was significantly reduced （P<0.05） in a concentration-dependent manner， with the 24-hour half inhibitory concentration （IC₅₀） being 2.23%. Compared with the 4% RUT group， cell viability in the RUT + Fer-1 group was significantly increased （P<0.05）. Compared with the matrix group， the colony formation rates of MCF-10AT cells in the 1%， 2%， and 4% RUT groups were significantly decreased （P<0.05）. Compared with the 4% RUT group， the cell colony formation rate of the RUT + Fer-1 group was significantly increased （P<0.05）. Compared with the matrix group， the levels of ROS and Fe²⁺ in the 1%， 2%， and 4% RUT groups were significantly increased （P<0.05）， while GSH levels were significantly decreased （P<0.05）， and MDA and lipid peroxidation levels were significantly increased （P<0.05）. Compared with the 4% RUT group， ROS and Fe²⁺ levels in the RUT + Fer-1 group were significantly reduced （P<0.05）， while GSH levels were significantly increased （P<0.05）， and MDA and lipid peroxidation levels were significantly reduced （P<0.05）. Compared with the matrix group， the protein expression levels of Nrf2， SLC7A11， and GPX4 in the 1%， 2%， and 4% RUT groups were significantly decreased （P<0.05）. Compared with the 4% RUT group， the protein expression levels of Nrf2， SLC7A11， and GPX4 in the RUT + Fer-1 group were significantly increased （P<0.05）. In the in vivo experiment， compared with the matrix group， the breast tissue histopathological status of the BPL rats in the RUC group was effectively improved， with less dilatation of the mammary ducts and more orderly duct arrangement. No pathological morphology indicative of invasive cancer was observed. Compared with the matrix group， Fe²⁺ and MDA levels in the mammary tissue of the RUC group were significantly increased （P<0.05）. Compared with the matrix group， the protein expression levels of Nrf2， SLC7A11， and GPX4 in the mammary tissue of the RUC group were significantly reduced （P<0.05）. ConclusionRUC may induce ferroptosis in BPL cells by inhibiting the Nrf2/SLC7A11/GPX4 signaling pathway， increasing Fe²⁺ accumulation， and promoting lipid peroxidation.

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/Aims: We investigated the clinical practice patterns of Korean endoscopists for the endoscopic resection of colorectal polyps. Methods: From September to November 2021, an online survey was conducted regarding the preferred resection methods for colorectal polyps, and responses were compared with the international guidelines. Results: Among 246 respondents, those with <4 years, 4–9 years, and ≥10 years of experiencein colonoscopy practices accounted for 25.6%, 34.1%, and 40.2% of endoscopists, respectively. The most preferred resection methods for non-pedunculated lesions were cold forceps polypectomy for ≤3 mm lesions (81.7%), cold snare polypectomy for 4–5 mm (61.0%) and 6–9 mm (43.5%) lesions, hot endoscopic mucosal resection (EMR) for 10–19 mm lesions (72.0%), precut EMR for 20–25 mm lesions (22.0%), and endoscopic submucosal dissection (ESD) for ≥26 mm lesions (29.3%). Hot EMR was favored for pedunculated lesions with a head size <20 mm and stalk size <10 mm (75.6%) and for those with a head size ≥20 mm or stalk size ≥10 mm (58.5%). For suspected superficial and deep submucosal lesions measuring 10–19 mm and ≥20 mm, ESD (26.0% and 38.6%) and surgery (36.6% and 46.3%) were preferred, respectively. The adherence rate to the guidelines ranged from 11.2% to 96.9%, depending on the size, shape, and histology of the lesions. Conclusions Adherence to the guidelines for endoscopic resection techniques varied depend-ing on the characteristics of colorectal polyps. Thus, an individualized approach is required to increase adherence to the guidelines.

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.

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.

Purpose: Since 1995, the Korean Gastric Cancer Association (KGCA) has been periodically conducting nationwide surveys on patients with surgically treated gastric cancer. This study details the results of the survey conducted in 2023. Materials and Methods: The survey was conducted from March to December 2024 using a standardized case report form. Data were collected on 86 items, including patient demographics, tumor characteristics, surgical procedures, and surgical outcomes. The results of the 2023 survey were compared with those of previous surveys. Results: Data from 12,751 cases were collected from 66 institutions. The mean patient age was 64.6 years, and the proportion of patients aged ≥71 years increased from 9.1% in 1995 to 31.7% in 2023. The proportion of upper-third tumors slightly decreased to 16.8% compared to 20.9% in 2019. Early gastric cancer accounted for 63.1% of cases in 2023.Regarding operative procedures, a totally laparoscopic approach was most frequently applied (63.2%) in 2023, while robotic gastrectomy steadily increased to 9.5% from 2.1% in 2014.The most common anastomotic method was the Billroth II procedure (48.8%) after distal gastrectomy and double-tract reconstruction (51.9%) after proximal gastrectomy in 2023.However, the proportion of esophago-gastrostomy with anti-reflux procedures increased to 30.9%. The rates of post-operative mortality and overall complications were 1.0% and 15.3%, respectively. Conclusions The results of the 2023 nationwide survey demonstrate the current status of gastric cancer treatment in Korea. This information will provide a basis for future gastric cancer research.

Gastric cancer is one of the most common cancers in both Korea and worldwide. Since 2004, the Korean Practice Guidelines for Gastric Cancer have been regularly updated, with the 4th edition published in 2022. The 4th edition was the result of a collaborative work by an interdisciplinary team, including experts in gastric surgery, gastroenterology, endoscopy, medical oncology, abdominal radiology, pathology, nuclear medicine, radiation oncology, and guideline development methodology. The current guideline is the 5th version, an updated version of the 4th edition. In this guideline, 6 key questions (KQs) were updated or proposed after a collaborative review by the working group, and 7 statements were developed, or revised, or discussed based on a systematic review using the MEDLINE, Embase, Cochrane Library, and KoreaMed database. Over the past 2 years, there have been significant changes in systemic treatment, leading to major updates and revisions focused on this area.Additionally, minor modifications have been made in other sections, incorporating recent research findings. The level of evidence and grading of recommendations were categorized according to the Grading of Recommendations, Assessment, Development and Evaluation system. Key factors for recommendation included the level of evidence, benefit, harm, and clinical applicability. The working group reviewed and discussed the recommendations to reach a consensus. The structure of this guideline remains similar to the 2022 version.Earlier sections cover general considerations, such as screening, diagnosis, and staging of endoscopy, pathology, radiology, and nuclear medicine. In the latter sections, statements are provided for each KQ based on clinical evidence, with flowcharts supporting these statements through meta-analysis and references. This multidisciplinary, evidence-based gastric cancer guideline aims to support clinicians in providing optimal care for gastric cancer patients.