Purpose: This study elucidates the mechanism of the physiological effect of cannabidiol (CBD) by assessing its impact on lipopolysaccharide (LPS)-induced inflammation in RWPE-1 cells and prostatitis-induced by 17β-estradiol and dihydrotestosterone in a rat model, focusing on its therapeutic potential for chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS). Materials and Methods: RWPE-1 cells were stratified in vitro into three groups: (1) controls, (2) cells with LPS-induced inflammation, and (3) cells with LPS-induced inflammation and treated with CBD. Enzyme-linked immunosorbent assays and western blots were performed on cellular components and supernatants after administration of CBD. Five groups of six Sprague–Dawley male rats were assigned: (1) control, (2) CP/CPPS, (3) CP/CPPS and treated with 50 mg/kg CBD, (4) CP/CPPS and treated with 100 mg/kg CBD, and (5) CP/CPPS and treated with 150 mg/kg CBD. Prostatitis was induced through administration of 17β-estradiol and dihydrotestosterone. After four weeks of CBD treatment, a pain index was evaluated, and prostate tissue was collected for subsequent histologic examination and western blot analysis. Results: CBD demonstrated efficacy in vivo for CP/CPPS and in vitro for inflammation. It inhibited the toll-like receptor 4 (TLR4)uclear factor-kappa B (NF-κB) pathway by activating the CB2 receptor, reducing expression of interleukin-6, tumor necrosis factor-alpha, and cyclooxygenase-2 (COX2) (p<0.01). CBD exhibited analgesic effects by activating and desensitizing the TRPV1 receptor. Conclusions CBD inhibits the TLR4/NF-κB pathway by activating the CB2 receptor, desensitizes the TRPV1 receptor, and decreases the release of COX2. This results in relief of inflammation and pain in patients with CP/CPPS, indicating CBD as a potential treatment for CP/CPPS.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Purpose: This study elucidates the mechanism of the physiological effect of cannabidiol (CBD) by assessing its impact on lipopolysaccharide (LPS)-induced inflammation in RWPE-1 cells and prostatitis-induced by 17β-estradiol and dihydrotestosterone in a rat model, focusing on its therapeutic potential for chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS). Materials and Methods: RWPE-1 cells were stratified in vitro into three groups: (1) controls, (2) cells with LPS-induced inflammation, and (3) cells with LPS-induced inflammation and treated with CBD. Enzyme-linked immunosorbent assays and western blots were performed on cellular components and supernatants after administration of CBD. Five groups of six Sprague–Dawley male rats were assigned: (1) control, (2) CP/CPPS, (3) CP/CPPS and treated with 50 mg/kg CBD, (4) CP/CPPS and treated with 100 mg/kg CBD, and (5) CP/CPPS and treated with 150 mg/kg CBD. Prostatitis was induced through administration of 17β-estradiol and dihydrotestosterone. After four weeks of CBD treatment, a pain index was evaluated, and prostate tissue was collected for subsequent histologic examination and western blot analysis. Results: CBD demonstrated efficacy in vivo for CP/CPPS and in vitro for inflammation. It inhibited the toll-like receptor 4 (TLR4)uclear factor-kappa B (NF-κB) pathway by activating the CB2 receptor, reducing expression of interleukin-6, tumor necrosis factor-alpha, and cyclooxygenase-2 (COX2) (p<0.01). CBD exhibited analgesic effects by activating and desensitizing the TRPV1 receptor. Conclusions CBD inhibits the TLR4/NF-κB pathway by activating the CB2 receptor, desensitizes the TRPV1 receptor, and decreases the release of COX2. This results in relief of inflammation and pain in patients with CP/CPPS, indicating CBD as a potential treatment for CP/CPPS.

Purpose: This study elucidates the mechanism of the physiological effect of cannabidiol (CBD) by assessing its impact on lipopolysaccharide (LPS)-induced inflammation in RWPE-1 cells and prostatitis-induced by 17β-estradiol and dihydrotestosterone in a rat model, focusing on its therapeutic potential for chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS). Materials and Methods: RWPE-1 cells were stratified in vitro into three groups: (1) controls, (2) cells with LPS-induced inflammation, and (3) cells with LPS-induced inflammation and treated with CBD. Enzyme-linked immunosorbent assays and western blots were performed on cellular components and supernatants after administration of CBD. Five groups of six Sprague–Dawley male rats were assigned: (1) control, (2) CP/CPPS, (3) CP/CPPS and treated with 50 mg/kg CBD, (4) CP/CPPS and treated with 100 mg/kg CBD, and (5) CP/CPPS and treated with 150 mg/kg CBD. Prostatitis was induced through administration of 17β-estradiol and dihydrotestosterone. After four weeks of CBD treatment, a pain index was evaluated, and prostate tissue was collected for subsequent histologic examination and western blot analysis. Results: CBD demonstrated efficacy in vivo for CP/CPPS and in vitro for inflammation. It inhibited the toll-like receptor 4 (TLR4)uclear factor-kappa B (NF-κB) pathway by activating the CB2 receptor, reducing expression of interleukin-6, tumor necrosis factor-alpha, and cyclooxygenase-2 (COX2) (p<0.01). CBD exhibited analgesic effects by activating and desensitizing the TRPV1 receptor. Conclusions CBD inhibits the TLR4/NF-κB pathway by activating the CB2 receptor, desensitizes the TRPV1 receptor, and decreases the release of COX2. This results in relief of inflammation and pain in patients with CP/CPPS, indicating CBD as a potential treatment for CP/CPPS.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.