Background/Aims: The prognostic value of serial 18F-fluorodeoxyglucose positron emission tomography/computed tomography ( 18F-FDG PET/CT) for patients with borderline resectable or locally advanced pancreatic cancer who undergo conversion surgery or continue chemotherapy without surgery has not been well-established. Methods: A retrospective analysis of patients with pancreatic ductal adenocarcinoma was conducted at Seoul National University Bundang Hospital between March 2013 and February 2022.Patients underwent PET/CT at baseline and subsequent radiologic evaluations following chemotherapy. Changes in the maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume, and total lesion glycolysis were analyzed.Based on their treatment regimens, patients were stratified into the conversion surgery group or nonconversion surgery group. Survival outcomes and various clinical factors were assessed. Results: Among 121 patients, 52 underwent conversion surgery, and 69 continued to receive chemotherapy without surgery. A significant reduction in the SUVmax was correlated with prolonged recurrence-free survival and overall survival in the conversion surgery group. Confirmation of a pathologic response indicated a significant association between reductions in the SUVmax and positive outcomes. Reductions in the metabolic tumor volume and total lesion glycolysis were associated with improved progression-free survival and overall survival in the nonconversion surgery group. Conclusions Serial PET/CT scans demonstrated prognostic value in pancreatic ductal adenocarcinoma patients, revealing distinct correlations in the conversion surgery group and nonconversion surgery group.

Natural killer (NK) cells are innate immune cells that are crucial for anticancer activity and have been developed as an immune cell therapy for leukemia. However, their limited effectiveness against solid tumors has prompted research into methods to enhance NK cell activity through combination therapies. Health supplements capable of boosting immune surveillance against tumor cells are gaining attention owing to their potential benefits. Resveratrol, a stilbenoid produced by several plants including peanuts and grapes, reportedly exerts anticancer effects and can activate immune cells. The peanut sprout extract cultivated with fermented sawdust medium (PSEFS) is rich in resveratrol, leveraging its health benefits in terms of the dry weight of herbal products, thus maximizing the utilization of resveratrol’s beneficial properties. Our study compared the efficacy of resveratrol and PSEFS and revealed that PSEFS significantly enhanced NK cell activation compared with an equivalent dose of resveratrol. We investigated the ability of PSEFS to potentiate NK cell anticancer activity, focusing on NK cell survival, tumor cell lysis, and NK cell activation in PSEFS-administered mice. Our findings suggest that PSEFS could be a potential NK cell booster for cancer immunotherapy.

Background/Aims: The prognostic value of serial 18F-fluorodeoxyglucose positron emission tomography/computed tomography ( 18F-FDG PET/CT) for patients with borderline resectable or locally advanced pancreatic cancer who undergo conversion surgery or continue chemotherapy without surgery has not been well-established. Methods: A retrospective analysis of patients with pancreatic ductal adenocarcinoma was conducted at Seoul National University Bundang Hospital between March 2013 and February 2022.Patients underwent PET/CT at baseline and subsequent radiologic evaluations following chemotherapy. Changes in the maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume, and total lesion glycolysis were analyzed.Based on their treatment regimens, patients were stratified into the conversion surgery group or nonconversion surgery group. Survival outcomes and various clinical factors were assessed. Results: Among 121 patients, 52 underwent conversion surgery, and 69 continued to receive chemotherapy without surgery. A significant reduction in the SUVmax was correlated with prolonged recurrence-free survival and overall survival in the conversion surgery group. Confirmation of a pathologic response indicated a significant association between reductions in the SUVmax and positive outcomes. Reductions in the metabolic tumor volume and total lesion glycolysis were associated with improved progression-free survival and overall survival in the nonconversion surgery group. Conclusions Serial PET/CT scans demonstrated prognostic value in pancreatic ductal adenocarcinoma patients, revealing distinct correlations in the conversion surgery group and nonconversion surgery group.

Natural killer (NK) cells are innate immune cells that are crucial for anticancer activity and have been developed as an immune cell therapy for leukemia. However, their limited effectiveness against solid tumors has prompted research into methods to enhance NK cell activity through combination therapies. Health supplements capable of boosting immune surveillance against tumor cells are gaining attention owing to their potential benefits. Resveratrol, a stilbenoid produced by several plants including peanuts and grapes, reportedly exerts anticancer effects and can activate immune cells. The peanut sprout extract cultivated with fermented sawdust medium (PSEFS) is rich in resveratrol, leveraging its health benefits in terms of the dry weight of herbal products, thus maximizing the utilization of resveratrol’s beneficial properties. Our study compared the efficacy of resveratrol and PSEFS and revealed that PSEFS significantly enhanced NK cell activation compared with an equivalent dose of resveratrol. We investigated the ability of PSEFS to potentiate NK cell anticancer activity, focusing on NK cell survival, tumor cell lysis, and NK cell activation in PSEFS-administered mice. Our findings suggest that PSEFS could be a potential NK cell booster for cancer immunotherapy.

Background/Aims: The prognostic value of serial 18F-fluorodeoxyglucose positron emission tomography/computed tomography ( 18F-FDG PET/CT) for patients with borderline resectable or locally advanced pancreatic cancer who undergo conversion surgery or continue chemotherapy without surgery has not been well-established. Methods: A retrospective analysis of patients with pancreatic ductal adenocarcinoma was conducted at Seoul National University Bundang Hospital between March 2013 and February 2022.Patients underwent PET/CT at baseline and subsequent radiologic evaluations following chemotherapy. Changes in the maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume, and total lesion glycolysis were analyzed.Based on their treatment regimens, patients were stratified into the conversion surgery group or nonconversion surgery group. Survival outcomes and various clinical factors were assessed. Results: Among 121 patients, 52 underwent conversion surgery, and 69 continued to receive chemotherapy without surgery. A significant reduction in the SUVmax was correlated with prolonged recurrence-free survival and overall survival in the conversion surgery group. Confirmation of a pathologic response indicated a significant association between reductions in the SUVmax and positive outcomes. Reductions in the metabolic tumor volume and total lesion glycolysis were associated with improved progression-free survival and overall survival in the nonconversion surgery group. Conclusions Serial PET/CT scans demonstrated prognostic value in pancreatic ductal adenocarcinoma patients, revealing distinct correlations in the conversion surgery group and nonconversion surgery group.

Natural killer (NK) cells are innate immune cells that are crucial for anticancer activity and have been developed as an immune cell therapy for leukemia. However, their limited effectiveness against solid tumors has prompted research into methods to enhance NK cell activity through combination therapies. Health supplements capable of boosting immune surveillance against tumor cells are gaining attention owing to their potential benefits. Resveratrol, a stilbenoid produced by several plants including peanuts and grapes, reportedly exerts anticancer effects and can activate immune cells. The peanut sprout extract cultivated with fermented sawdust medium (PSEFS) is rich in resveratrol, leveraging its health benefits in terms of the dry weight of herbal products, thus maximizing the utilization of resveratrol’s beneficial properties. Our study compared the efficacy of resveratrol and PSEFS and revealed that PSEFS significantly enhanced NK cell activation compared with an equivalent dose of resveratrol. We investigated the ability of PSEFS to potentiate NK cell anticancer activity, focusing on NK cell survival, tumor cell lysis, and NK cell activation in PSEFS-administered mice. Our findings suggest that PSEFS could be a potential NK cell booster for cancer immunotherapy.

Background/Aims: The prognostic value of serial 18F-fluorodeoxyglucose positron emission tomography/computed tomography ( 18F-FDG PET/CT) for patients with borderline resectable or locally advanced pancreatic cancer who undergo conversion surgery or continue chemotherapy without surgery has not been well-established. Methods: A retrospective analysis of patients with pancreatic ductal adenocarcinoma was conducted at Seoul National University Bundang Hospital between March 2013 and February 2022.Patients underwent PET/CT at baseline and subsequent radiologic evaluations following chemotherapy. Changes in the maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume, and total lesion glycolysis were analyzed.Based on their treatment regimens, patients were stratified into the conversion surgery group or nonconversion surgery group. Survival outcomes and various clinical factors were assessed. Results: Among 121 patients, 52 underwent conversion surgery, and 69 continued to receive chemotherapy without surgery. A significant reduction in the SUVmax was correlated with prolonged recurrence-free survival and overall survival in the conversion surgery group. Confirmation of a pathologic response indicated a significant association between reductions in the SUVmax and positive outcomes. Reductions in the metabolic tumor volume and total lesion glycolysis were associated with improved progression-free survival and overall survival in the nonconversion surgery group. Conclusions Serial PET/CT scans demonstrated prognostic value in pancreatic ductal adenocarcinoma patients, revealing distinct correlations in the conversion surgery group and nonconversion surgery group.

Oxidative stress is a well-established risk factor for numerous chronic diseases, emphasizing the need for efficient identification of potent antioxidants.Conventional methods for assessing antioxidant properties are often time-consuming and resource-intensive, typically relying on laborious biochemical assays. In this study, we investigated the applicability of machine learning (ML) algorithms for predicting the antioxidant activity of compounds based solely on their molecular structure. We evaluated the performance of five ML algorithms, Support Vector Machine (SVM), Logistic Regression (LR), XGBoost, Random Forest (RF), and Deep Neural Network (DNN), using a dataset of over 1,900 compounds with experimentally determined antioxidant activity. Both RF and SVM achieved the best overall performance, exhibiting high accuracy (> 0.9) and effectively distinguishing active and inactive compounds with high structural similarity. External validation using natural product data from the BATMAN database confirmed the generalizability of the RF and SVM models. Our results suggest that ML models serve as powerful tools to expedite the discovery of novel antioxidant candidates, potentially streamlining the development of future therapeutic interventions.

Oxidative stress is a well-established risk factor for numerous chronic diseases, emphasizing the need for efficient identification of potent antioxidants.Conventional methods for assessing antioxidant properties are often time-consuming and resource-intensive, typically relying on laborious biochemical assays. In this study, we investigated the applicability of machine learning (ML) algorithms for predicting the antioxidant activity of compounds based solely on their molecular structure. We evaluated the performance of five ML algorithms, Support Vector Machine (SVM), Logistic Regression (LR), XGBoost, Random Forest (RF), and Deep Neural Network (DNN), using a dataset of over 1,900 compounds with experimentally determined antioxidant activity. Both RF and SVM achieved the best overall performance, exhibiting high accuracy (> 0.9) and effectively distinguishing active and inactive compounds with high structural similarity. External validation using natural product data from the BATMAN database confirmed the generalizability of the RF and SVM models. Our results suggest that ML models serve as powerful tools to expedite the discovery of novel antioxidant candidates, potentially streamlining the development of future therapeutic interventions.

Oxidative stress is a well-established risk factor for numerous chronic diseases, emphasizing the need for efficient identification of potent antioxidants.Conventional methods for assessing antioxidant properties are often time-consuming and resource-intensive, typically relying on laborious biochemical assays. In this study, we investigated the applicability of machine learning (ML) algorithms for predicting the antioxidant activity of compounds based solely on their molecular structure. We evaluated the performance of five ML algorithms, Support Vector Machine (SVM), Logistic Regression (LR), XGBoost, Random Forest (RF), and Deep Neural Network (DNN), using a dataset of over 1,900 compounds with experimentally determined antioxidant activity. Both RF and SVM achieved the best overall performance, exhibiting high accuracy (> 0.9) and effectively distinguishing active and inactive compounds with high structural similarity. External validation using natural product data from the BATMAN database confirmed the generalizability of the RF and SVM models. Our results suggest that ML models serve as powerful tools to expedite the discovery of novel antioxidant candidates, potentially streamlining the development of future therapeutic interventions.