Causal Association Analysis of Periodontitis and Inflammatory Bowel Disease: A Bidirectional Mendelian Randomization Study.

Background: Periodontitis has been reported to be associated with inflammatory bowel disease (IBD), including ulcerative colitis (UC), and Crohn's disease (CD). However, the causality of these 2 diseases remains unclear. We conducted bidirectional Mendelian randomization (MR) to investigate the causal relationship between periodontitis and IBD.

Symptom effects and central mechanism of acupuncture in patients with functional gastrointestinal disorders: a systematic review based on fMRI studies.

Background: Functional gastrointestinal disorders (FGIDs) are closely related to disorders of brain-gut interaction. FGIDs are the dominant disease of acupuncture treatment, which can improve the symptoms and emotional state.

Aim: To evaluate the results and quality of the available clinical evidence and to summarize the central mechanism and effect of acupuncture on FGIDs.

Diagnosing and grading gastric atrophy and intestinal metaplasia using semi-supervised deep learning on pathological images: development and validation study.

Objective: Patients with gastric atrophy and intestinal metaplasia (IM) were at risk for gastric cancer, necessitating an accurate risk assessment. We aimed to establish and validate a diagnostic approach for gastric biopsy specimens using deep learning and OLGA/OLGIM for individual gastric cancer risk classification.

Methods: In this study, we prospectively enrolled 545 patients suspected of atrophic gastritis during endoscopy from 13 tertiary hospitals between December 22, 2017, to September 25, 2020, with a total of 2725 whole-slide images (WSIs).

The role of the endoscopic grading of gastric intestinal metaplasia in assessing gastric cancer risk: A systematic review and meta-analysis.

Background And Aim: Patients with gastric intestinal metaplasia (IM) are at increased risk of gastric cancer (GC). The endoscopic grading of gastric intestinal metaplasia (EGGIM) with high-definition endoscopes has shown the potential to facilitate GC risk stratification. However, a comprehensive review and meta-analysis of published articles are lacking.

Chinese Herbal Medicine for Functional Dyspepsia With Psychological Disorders: A Systematic Review and Meta-Analysis.

Background And Aims: Functional dyspepsia (FD) is closely associated with gut-brain interaction disorder (DGBI), characterized by the interaction of gastrointestinal symptoms and central nervous system dysregulation. Chinese herbal medicine (CHM) has a good concurrent effect in the treatment of FD, especially for patients with concurrent psychological disorders. A meta-analysis was designed to evaluate the efficacy and safety of CHMs in the treatment of FD.

Gastric Cancer Risk of Intestinal Metaplasia Subtypes: A Systematic Review and Meta-Analysis of Cohort Studies.

Introduction: Intestinal metaplasia (IM) is an independent risk factor for gastric cancer (GC). However, the subtypes of IM as a risk factor for GC remain controversial. We performed a systematic review and meta-analysis to evaluate the relationship between IM subtypes and GC risk.

Efficacy and safety of berberine in preventing recurrence of colorectal adenomas: A systematic review and meta-analysis.

Ethnopharmacological Relevance: Berberine(BBR) is a kind of isoquinoline alkaloids extracted from the rhizomes of Coptis chinensis Franch., which was the main active ingredient. Accumulating evidence has shown that it has potential pharmacological effects in preventing the recurrence of colorectal adenomas.

The prognostic role of a combined fibrinogen and inflammation-based index in patients with metastatic breast cancer.

Background: The activation of inflammation and coagulation cascades plays an essential role in the development of various malignancies, including metastatic breast cancer (MBC). This retrospective study aimed to investigate the prognostic role of the combination of fibrinogen and the inflammation-based index in patients with MBC.

Methods: A total of 176 patients with MBC were retrospectively reviewed.

Using neural networks to estimate the losses of ascorbic acid, total phenols, flavonoid, and antioxidant activity in asparagus during thermal treatments.

Artificial neural networks (ANNs) with back-propagation algorithm were developed to predict the percentage loss of ascorbic acid, total phenols, flavonoid, and antioxidant activity in different segments of asparagus during water blanching at temperatures ranging from 65 to 95 degrees C as a function of blanching time and temperature. In this study, the one-hidden-layer ANNs are used, and the number of neurons in the hidden layer were chosen by trial and error. Optimized ANN models were developed for predicting nutrient losses in bud, upper, middle, and butt segments of asparagus.