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BACKGROUND/AIMS: While DNA methylation and gastric microbiome are each associated with gastric cancer (GC), their combined role in predicting GC remains unclear. This study investigated the potential of a combined DNA methylation and gastric microbiome signature to predict Helicobacter pylori-negative GC. METHODS: In this case-control study, we conducted quantitative methylation-specific polymerase chain reaction to measure the methylation levels of DKK3, SFRP1, EMX1, NKX6-1, MIR124-3, and TWIST1 in the gastric mucosa from 75 H. pylori-negative patients, including chronic gastritis (CG), intestinal metaplasia (IM), and GC. A combined analysis of DNA methylation and gastric microbiome, using 16S rRNA gene sequencing, was performed in 30 of 75 patients. RESULTS: The methylation levels of DKK3, SFRP1, EMX1, MIR124-3, and TWIST1 were significantly higher in patients with GC than in controls (all q

The role of the gastric mucosal microbiome in Helicobacter pylori-negative gastric cancer (GC) remains unclear. Therefore, we aimed to characterize the microbial alterations and host inflammatory cytokine responses in H. pylori-negative GC. Gastric mucosal samples were obtained from 137 H. pylori-negative patients with GC (n = 45) and controls (chronic gastritis or intestinal metaplasia, n = 92). We performed 16S rRNA gene sequencing (n = 67), a quantitative reverse transcription-polymerase chain reaction to determine the relative mRNA expression levels of TNF (tumor necrosis factor), IL1B (interleukin 1 beta), IL6 (interleukin 6), CXCL8 (C-X-C motif chemokine ligand 8), IL10 (interleukin 10), IL17A (interleukin 17A), TGFB1 (transforming growth factor beta 1) (n = 113), and the correlation analysis between sequencing and expression data (n = 47). Gastric mucosal microbiota in patients with GC showed reduced diversity and a significantly different composition compared to that of the controls. Lacticaseibacillus was significantly enriched, while Haemophilus and Campylobacter were depleted in the cancer group compared to the control group. These taxa could distinguish the two groups in a random forest algorithm. Moreover, the combined relative abundance of these taxa, a GC microbiome index, significantly correlated with gastric mucosal IL1B expression, which was elevated in the cancer group. Overall, altered gastric mucosal microbiota was found to be associated with increased mucosal IL1B expression in H. pylori-negative GC.

BACKGROUND/AIMS: Risk prediction models using a deep neural network (DNN) have not been reported to predict the risk of advanced colorectal neoplasia (ACRN). The aim of this study was to compare DNN models with simple clinical score models to predict the risk of ACRN in colorectal cancer screening. METHODS: Databases of screening colonoscopy from Kangbuk Samsung Hospital (n=121,794) and Kyung Hee University Hospital at Gangdong (n=3,728) were used to develop DNN-based prediction models. Two DNN models, the Asian-Pacific Colorectal Screening (APCS) model and the Korean Colorectal Screening (KCS) model, were developed and compared with two simple score models using logistic regression methods to predict the risk of ACRN. The areas under the receiver operating characteristic curves (AUCs) of the models were compared in internal and external validation databases. RESULTS: In the internal validation set, the AUCs of DNN model 1 and the APCS score model were 0.713 and 0.662 (p0.1). CONCLUSIONS: Simple score models for the risk prediction of ACRN are as useful as DNN-based models when input variables are limited. However, further studies on this issue are warranted to predict the risk of ACRN in colorectal cancer screening because DNN-based models are currently under improvement.

PURPOSE: Quality indicators of the National Endoscopy Quality Improvement Program (NEQIP) and outcome measures of endoscopy in the National Cancer Screening Program (NCSP) in Korea are not clear. We evaluated the quality indicators of the revised NEQIP and outcome measures of endoscopy at different types of healthcare facilities participating in the NCSP. MATERIALS AND METHODS: This study was conducted between March and August 2018 in primary, secondary, and tertiary healthcare facilities that perform endoscopy as a part of the NCSP. Representative endoscopists completed a questionnaire for quality indicators of the NEQIP and provided data on outcome measures for endoscopy. RESULTS: Quality indicators of the NEQIP were mostly acceptable. However, the quality indicators for annual volume of esophagogastroduodenoscopy (EGD) and colonoscopy, training for endoscopy quality improvement by endoscopy nursing staff, colonoscopy reports, documentation of pathologic lesions, quality of endoscopy reprocessing areas, and completion of endoscopy reprocessing education programs were suboptimal. For outcome measures of EGD, the number of photo-documentations and total procedure time were higher at tertiary healthcare facilities than at other facilities (p

In the normal physiological state, intestinal epithelial cells act as a defensive frontline of host mucosal immunity to tolerate constant exposure to external stimuli. In this study, we investigated the potential anti-inflammatory and gut permeability protective effects of Laminaria japonica (LJ) water extract (LJE) and three types of fermented Laminaria japonica water extracts (LJE-F1, LJE-F2, and LJE-F3) in lipopolysaccharide (LPS)-stimulated Caco-2, human intestinal epithelial cells. All four extracts significantly decreased the production of nitric oxide and interleukin-6 induced by LPS stimulus. In addition, LJE and the three types of LJE-Fs also inhibited LPS-induced loss of monolayer permeability, as assessed by changes in transepithelial electrical resistance. All four LJ extracts significantly prevented the inhibition of the protein levels of occludin, whereas LJE, LJE-F1, and LJE-F3 significantly attenuated the reduction in phosphorylation of adenosine monophosphate-activated protein kinase compared with the LPS-treated group in Caco-2 cells. In conclusion, LJE and its fermented water extracts appear to have potential gut health-promoting effects by reducing inflammation and partially regulating the tight junction-related proteins in human intestinal epithelial cells. Thus, additional studies are warranted to evaluate Laminaria japonica as a therapeutic agent for inflammatory bowel diseases.

This paper compares four time series forecasting algorithms—ARIMA, SARIMA, LSTM, and SVM—suitable for short-term load forecasting using Advanced Metering Infrastructure (AMI) data. The primary focus is on evaluating the applicability and performance of these forecasting models in predicting electricity consumption patterns, which is a critical component for implementing effective demand response (DR) strategies. The study provides a comprehensive analysis of the predictive accuracy, computational efficiency, and scalability of each algorithm using a dataset of real-time electricity consumption collected from AMI systems over a designated period. Through extensive experiments, we demonstrate that each algorithm has distinct strengths and weaknesses depending on the characteristics of the dataset. Specifically, SVM exhibited superior performance in handling nonlinear patterns and high volatility, while SARIMA effectively captured seasonal trends. LSTM showed potential in modeling complex temporal dependencies but was sensitive to hyperparameter settings and required a substantial amount of training data. This research offers practical guidelines for selecting the optimal forecasting model based on data characteristics and application needs, contributing to the development of more efficient and dynamic energy management strategies. The findings highlight the importance of integrating advanced forecasting techniques into smart grid systems to enhance the reliability and responsiveness of DR programs. This study lays a solid foundation for future research on integrating these forecasting models into real-world AMI applications to support effective demand response and grid stability. [ABSTRACT FROM AUTHOR]

Food adulteration involving the illegal addition of dyes to foodstuffs has become an alarming issue in recent years. This study developed and validated a high‐performance liquid chromatography (HPLC)–DAD (diode array detector) method for the simultaneous determination of nine azo dyes (Butter Yellow, Sudan Orange G, Para Red, Sudan I, Sudan II, Sudan III, Sudan IV, Sudan Red 7B, and Scarlet 808). Moreover, a qualitative analysis method using liquid chromatography–tandem mass spectrometry was developed to more accurately identify peaks detected in HPLC–DAD. The calibration curve represented good linearity (r2 ≥ 0.9998) over the measured concentration range of 0.5–25 mg/kg. limit of detection and limit of quantification were 0.01–0.04 and 0.04–0.12 mg/kg, respectively. Accuracy and precision were 96.0–102.6 and 0.16–2.01 (relative standard deviation%), respectively. Additionally, the measurement uncertainty and HorRat value were estimated. Several Curcuma longa L. distributed in Korea were collected and monitored for azo dye contaminants. Practical Application: The proposed HPLC–DAD method represents a significant advancement in the field, offering a reliable means of quantifying azo dyes and identifying their presence even at trace levels in adulterated turmeric. This not only contributes to ensuring the safety and integrity of turmeric products but also establishes precedent for robust analytical techniques in addressing food safety challenges. [ABSTRACT FROM AUTHOR]

Purpose An endoscopic bite block is a device to ensure that the patient's mouth remains wide open during endoscopic procedures. Wide opening of the mouth may facilitate the efficiency of one-handed mask ventilation. We evaluated the effect of an endoscopic bite block on mask ventilation among three ventilation techniques: one-handed ventilation, one-handed ventilation with an endoscopic bite block, and two-handed ventilation. Methods Fifty-nine anesthetized and paralyzed patients were included. After induction of anesthesia, one-handed ventilation, one-handed ventilation with an endoscopic bite block and two-handed ventilation were performed in a cross-over, randomized order. The primary outcome was the expiratory tidal volume (mL/kg of predicted body weight). Secondary outcomes included minute ventilation (L/min) and the incidence of inadequate mask ventilation or dead space ventilation. Results The expiratory tidal volume of one-handed ventilation with an endoscopic bite block was significantly improved when compared with that of one-handed ventilation (8.2 [6.8-10.2] mL/kg vs. 7.1 [4.5-9.0] mL/kg, respectively, difference = 1.1 mL/kg; 95% CI 0.8-2.4; P < 0.001), and was comparable to that of two-handed ventilation (8.9 [6.3-11.5] mL/kg; difference = 0.7 mL/kg; 95% CI - 0.7 to 1.5; P = 0.432). Minute ventilation was also significantly improved in one-handed ventilation with an endoscopic bite block compared with that in one-handed ventilation (7.4 [6.3-8.6] L/min vs. 6.7 [4.2-7.9] L/min, respectively, difference = 0.7 L/min; 95% CI 0.6-2.0; P < 0.001), and was comparable to that of two-handed ventilation (7.7 [6.5-9.5] L/min; difference = 0.3 L/min; 95% CI - 0.5 to 1.4; P = 0.390). The incidence of inadequate ventilation or dead space ventilation was not different among the ventilation techniques (P = 0.080). Conclusion The use of an endoscopic bite block improved one-handed mask ventilation, showing comparable efficacy with two-handed mask ventilation., Author(s): Hyerim Kim [sup.1], Jee-Eun Chang [sup.1], Jung-Man Lee [sup.1], Dongwook Won [sup.1], Hyo Jun Yang [sup.1], Jin-Young Hwang [sup.1] [sup.2] Author Affiliations: (1) grid.412479.d, Department of Anesthesiology and Pain [...]