Therapeutic potential of transient receptor potential (TRP) channels in psychiatric disorders.

Psychiatric disorders such as Bipolar disorder, Anxiety, Major depressive disorder, Schizophrenia, Attention-deficit/hyperactivity disorder, as well as neurological disorders such as Migraine, are linked by the evidence of altered calcium homeostasis. The disturbance of intra-cellular calcium homeostasis disrupts the activity of numerous ion channels including transient receptor potential (TRP) channels. TRP channel families comprise non-selective calcium-permeable channels that have been implicated in variety of physiological processes in the brain, as well as in the pathogenesis of psychiatric disorders. Through a comprehensive review of current research and experimentation, this investigation elucidates the role of TRP channels in psychiatric disorders. Furthermore, this review discusses about the exploration of epigenetics and TRP channels in psychiatric disorders.

Endoscopic Submucosal Dissection and Endoscopic Mucosal Resection for Barrett's Associated Neoplasia: A Systematic Review and Meta-analysis of the Published Literature.

Introduction The role of endoscopic submucosal dissection (ESD) in the treatment of Barrett's associated neoplasia (BEN) has been evolving. We examined the efficacy and safety of ESD and EMR for BEN. Methods A database search was performed for studies reporting efficacy and safety outcomes of ESD and EMR for BEN. Pooled proportional and comparative meta-analyses were performed. Results 47 studies (23 ESD, 19 EMR, and 5 comparative) were included. Mean lesion size for ESD and EMR were 22.5 mm and 15.8 mm respectively. Majority of lesions were Paris type IIa. Pooled analysis for ESD showed en-bloc resection, R0 resection, curative resection, and local recurrence rates of 98%, 78%, 65%, and 2%, respectively. Complete eradication of dysplasia (CE-D) and complete eradication of intestinal metaplasia (CE-IM) were achieved in 94% and 59% of cases. Pooled rates of perforation, intraprocedural bleeding (IPB), delayed bleeding (DB), and stricture were 1%, 1%, 2%, and 10%, respectively. Pooled analysis for EMR showed en-bloc resection, R0 resection, curative resection, and local recurrence rates of 37%, 67%, 62%, and 6%, respectively. CE-D and CE-IM were achieved in 94% and 76% of cases. Pooled rates of perforation, IPB, DB, and stricture were 0.1%, 1%, 0.4%, and 7.7%, respectively. The mean procedure time for ESD and EMR were 111.3 and 22.3 mins respectively. Comparative analysis showed higher en-bloc and R0 resection rates with ESD compared to EMR, with comparable adverse events. Conclusion ESD and EMR both can be employed to treat BEN depending on the lesion type, size, and expertise.

Mechanistic insights on TLR-4 mediated inflammatory pathway in neurodegenerative diseases.

Neurodegenerative diseases (NDDs) pose a significant issue in healthcare, needing a thorough knowledge of their complex molecular mechanisms. A diverse set of cell signaling mediators and their interactions play critical roles in neuroinflammation. The release of pro-inflammatory mediators in response to neural dysfunction is detrimental to normal cell survival. Moreover, the important role of nuclear factor-κB (NF-κB) in the central nervous system through Toll-like receptor (TLR) activation has been well established. Therefore, through a comprehensive review of current research and experimentation, this investigation elucidates the interactions between novel pharmacological agents (TLR-4/NF-κB inhibitors) and neurodegeneration encompassing Alzheimer's, Parkinson's, Huntington's disease, amyotrophic lateral sclerosis and stroke. Insights garnered from this exploration underscore the potential of TLR-4 as a therapeutic target. Through the revelation of these insights, our aim is to establish a foundation for the development of enhanced and focused therapeutic approaches in the continuous endeavor to combat neurodegeneration. This review thus serves as a roadmap, guiding future research endeavors toward innovative strategies for combatting the complex interplay between TLR-4 signaling and NDDs.

Alteration of gastric microbiota in Helicobacter pylori-infected individuals suffering from GERD, DU, and gastritis.

BACKGROUND/AIM: Helicobacter pylori (H. pylori) colonization affects the gastric microbiome, causing gastrointestinal (GI) diseases. Modern sequencing technology provides insights into GI microbe interaction with H. pylori and their metabolic pathways in causing GI diseases. We aim to compare the gastric microbiota alteration due to H. pylori infection in patients suffering from GI diseases. MATERIALS AND METHODS: Genomic DNA were isolated from gastric antrum tissue from 37 H.pylori-infected patients diagnosed with GERD, duodenal ulcers, and gastritis. We conducted the genomic library preparation and sequencing of the amplified product using 16S rRNA NGS analysis. Using microbiome analyst tool diversity analysis, random forest analysis and ANOVA were conducted to find out the comparison of microbial abundance. We have also conducted functional pathway prediction analysis using PICRUSt. RESULTS: Metagenomic analysis shows high bacterial diversity in H. pylori-positive gastritis patients. Streptococcus infantis and Neisseria subflava were significantly higher in duodenal ulcer (DU) and gastritis groups. Acinetobacter lwoffii and Helicobacter pullorum were significantly high in the gastritis group only. The functional metabolic pathway analyses revealed that gastroesophageal reflux disease (GERD) samples were significantly enriched with the energy metabolism and xenobiotic biodegradation and metabolism pathways, whereas fructose-1,6-bisphosphatase III was found less in gastritis and DU groups. CONCLUSION: There is a difference in microbiota composition in different disease outcomes. We found positive association between microbial diversity and H. pylori in gastritis group only, whereas negative association was found in DU and GERD groups. The functional metabolic pathway analysis revealed significant differences in various disease outcomes.

Computer-Aided Diagnosis for Leaving Colorectal Polyps In Situ : A Systematic Review and Meta-analysis.

BACKGROUND: Computer-aided diagnosis (CADx) allows prediction of polyp histology during colonoscopy, which may reduce unnecessary removal of nonneoplastic polyps. However, the potential benefits and harms of CADx are still unclear. PURPOSE: To quantify the benefit and harm of using CADx in colonoscopy for the optical diagnosis of small (≤5-mm) rectosigmoid polyps. DATA SOURCES: Medline, Embase, and Scopus were searched for articles published before 22 December 2023. STUDY SELECTION: Histologically verified diagnostic accuracy studies that evaluated the real-time performance of physicians in predicting neoplastic change of small rectosigmoid polyps without or with CADx assistance during colonoscopy. DATA EXTRACTION: The clinical benefit and harm were estimated on the basis of accuracy values of the endoscopist before and after CADx assistance. The certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. The outcome measure for benefit was the proportion of polyps predicted to be nonneoplastic that would avoid removal with the use of CADx. The outcome measure for harm was the proportion of neoplastic polyps that would be not resected and left in situ due to an incorrect diagnosis with the use of CADx. Histology served as the reference standard for both outcomes. DATA SYNTHESIS: Ten studies, including 3620 patients with 4103 small rectosigmoid polyps, were analyzed. The studies that assessed the performance of CADx alone (9 studies; 3237 polyps) showed a sensitivity of 87.3% (95% CI, 79.2% to 92.5%) and specificity of 88.9% (CI, 81.7% to 93.5%) in predicting neoplastic change. In the studies that compared histology prediction performance before versus after CADx assistance (4 studies; 2503 polyps), there was no difference in the proportion of polyps predicted to be nonneoplastic that would avoid removal (55.4% vs. 58.4%; risk ratio [RR], 1.06 [CI, 0.96 to 1.17]; moderate-certainty evidence) or in the proportion of neoplastic polyps that would be erroneously left in situ (8.2% vs. 7.5%; RR, 0.95 [CI, 0.69 to 1.33]; moderate-certainty evidence). LIMITATION: The application of optical diagnosis was only simulated, potentially altering the decision-making process of the operator. CONCLUSION: Computer-aided diagnosis provided no incremental benefit or harm in the management of small rectosigmoid polyps during colonoscopy. PRIMARY FUNDING SOURCE: European Commission. (PROSPERO: CRD42023402197).

Application of machine-learning model to optimize colonic adenoma detection in India.

AIMS: There is limited data on the prevalence and risk factors of colonic adenoma from the Indian sub-continent. We aimed at developing a machine-learning model to optimize colonic adenoma detection in a prospective cohort. METHODS: All consecutive adult patients undergoing diagnostic colonoscopy were enrolled between October 2020 and November 2022. Patients with a high risk of colonic adenoma were excluded. The predictive model was developed using the gradient-boosting machine (GBM)-learning method. The GBM model was optimized further by adjusting the learning rate and the number of trees and 10-fold cross-validation. RESULTS: Total 10,320 patients (mean age 45.18 ± 14.82 years; 69% men) were included in the study. In the overall population, 1152 (11.2%) patients had at least one adenoma. In patients with age > 50 years, hospital-based adenoma prevalence was 19.5% (808/4144). The area under the receiver operating curve (AUC) (SD) of the logistic regression model was 72.55% (4.91), while the AUCs for deep learning, decision tree, random forest and gradient-boosted tree model were 76.25% (4.22%), 65.95% (4.01%), 79.38% (4.91%) and 84.76% (2.86%), respectively. After model optimization and cross-validation, the AUC of the gradient-boosted tree model has increased to 92.2% (1.1%). CONCLUSIONS: Machine-learning models may predict colorectal adenoma more accurately than logistic regression. A machine-learning model may help optimize the use of colonoscopy to prevent colorectal cancers. TRIAL REGISTRATION: ClinicalTrials.gov (ID: NCT04512729).

Antibiotic susceptibility pattern of Helicobacter pylori against eight antibiotics: A study from North India.

BACKGROUND: The purpose of this analysis is to evaluate the antimicrobial susceptibility of eight drugs effective against Helicobacter pylori (H. pylori) strains and the genetic diversity of H. pylori virulence genes to foresee clinical outcomes in North India. MATERIALS AND METHODS: Fifty-eight H. pylori strains isolated from patients suffering from various gastrointestinal (GI) diseases were included in the study. MICs of various antibiotics were determined by the agar dilution method. The chi-squared test and Fisher exact test were used to determine the p-value, which was considered significant at p-value ≤ 0.05. RStudio 4.0 was used to for the data visualization. RESULTS: The prevalence of drug resistance was found to be: cefixime (CFM) (41.3%), furazolidone (FZD) (34.4%), amoxicillin (AMX) (20.7%), levofloxacin (LVFX) (70.7%), metronidazole (MTZ) (39.6%), tetracycline (TET) (20.7%), clarithromycin (CLA) (17.2%), and rifabutin (RIF) (17.2%). Out of 58 H. pylori strains, 3 were pan susceptible. There were H. pylori strains with single-drug resistance (21.8%, 12/55), dual resistance (30.9%, 17/55), triple resistance (20%, 11/55), and multidrug resistance (27.3%, 15/55). The resistance rate in MTZ, CLA and RIF were found to be significantly higher in females as compared to males (p = 0.005, p = 0.002, and p = 0.02), respectively. The resistance to TET exhibited significantly higher levels in gastritis compared to GERD, DU, and other disease groups (p = 0.04) respectively. CONCLUSION: TET, AMX, CLA, and RIF were found to be more effective antibiotics against H. pylori infections, whereas more studies are required to provide evidence on increasing resistance rate of LVFX.

Molecular characterization and phylogenetic analysis of babA gene of Helicobacter pylori isolated from Indian patients with gastrointestinal diseases.

INTRODUCTION: Outer membrane protein (OMP) of Helicobacter pylori (H. pylori) i.e., blood group antigen binding adhesin (babA) is responsible for the attachment of H. pylori in the gastric epithelium. Its adherence is causative for gastric pathology such as gastritis, peptic ulcer disease (PUD), or digestive tract disorders like erosive reflux disease (ERD) and (NERD) non-erosive reflux disease and together called Gastroesophageal reflux disease (GERD). BabA manifests rapid and varied selection via substitution of amino acid in its Leb-carbohydrate binding domain (CBD) which enables better binding preferences for distinct human populations and ABO blood group phenotypes. The positive evolutionary selection of the pathogenic factor of this genetically diverse bacterium has enabled it to adapt to the host gastric environment. Analyzing the association of virulent genes (cagA, vacA) and babA will help us better understand bacteria's pathogenicity. METHOD: 109 H. pylori strains from patients with distinct gastrointestinal diseases were genotyped using Polymerase Chain Reaction(PCR) for cagA, vacA, and babA followed by Sanger sequencing and phylogenetic analysis. RESULT: In the babA + ve genotype, a statistically significant association with p = 0.04 and < 0.0001 is seen in gastritis and ERD respectively. A significant association of genotype vacAs1m2 (p = 0.0002) was seen in gastritis, vacAs1m1 (p = 0.02) in NERD, vacAs1m1 (p < 0.0001) and vacAs1m2 (p = 0.002) in ERD. This relationship helps to detect gastritis or ERD where BabA gene can be used as an independent marker for detecting their presence. CONCLUSION: The appearance of variants within distinct disease categories is due to local genetic variation.

Consensus statements on the current landscape of artificial intelligence applications in endoscopy, addressing roadblocks, and advancing artificial intelligence in gastroenterology.

BACKGROUND AND AIMS: The American Society for Gastrointestinal Endoscopy (ASGE) AI Task Force along with experts in endoscopy, technology space, regulatory authorities, and other medical subspecialties initiated a consensus process that analyzed the current literature, highlighted potential areas, and outlined the necessary research in artificial intelligence (AI) to allow a clearer understanding of AI as it pertains to endoscopy currently. METHODS: A modified Delphi process was used to develop these consensus statements. RESULTS: Statement 1: Current advances in AI allow for the development of AI-based algorithms that can be applied to endoscopy to augment endoscopist performance in detection and characterization of endoscopic lesions. Statement 2: Computer vision-based algorithms provide opportunities to redefine quality metrics in endoscopy using AI, which can be standardized and can reduce subjectivity in reporting quality metrics. Natural language processing-based algorithms can help with the data abstraction needed for reporting current quality metrics in GI endoscopy effortlessly. Statement 3: AI technologies can support smart endoscopy suites, which may help optimize workflows in the endoscopy suite, including automated documentation. Statement 4: Using AI and machine learning helps in predictive modeling, diagnosis, and prognostication. High-quality data with multidimensionality are needed for risk prediction, prognostication of specific clinical conditions, and their outcomes when using machine learning methods. Statement 5: Big data and cloud-based tools can help advance clinical research in gastroenterology. Multimodal data are key to understanding the maximal extent of the disease state and unlocking treatment options. Statement 6: Understanding how to evaluate AI algorithms in the gastroenterology literature and clinical trials is important for gastroenterologists, trainees, and researchers, and hence education efforts by GI societies are needed. Statement 7: Several challenges regarding integrating AI solutions into the clinical practice of endoscopy exist, including understanding the role of human-AI interaction. Transparency, interpretability, and explainability of AI algorithms play a key role in their clinical adoption in GI endoscopy. Developing appropriate AI governance, data procurement, and tools needed for the AI lifecycle are critical for the successful implementation of AI into clinical practice. Statement 8: For payment of AI in endoscopy, a thorough evaluation of the potential value proposition for AI systems may help guide purchasing decisions in endoscopy. Reliable cost-effectiveness studies to guide reimbursement are needed. Statement 9: Relevant clinical outcomes and performance metrics for AI in gastroenterology are currently not well defined. To improve the quality and interpretability of research in the field, steps need to be taken to define these evidence standards. Statement 10: A balanced view of AI technologies and active collaboration between the medical technology industry, computer scientists, gastroenterologists, and researchers are critical for the meaningful advancement of AI in gastroenterology. CONCLUSIONS: The consensus process led by the ASGE AI Task Force and experts from various disciplines has shed light on the potential of AI in endoscopy and gastroenterology. AI-based algorithms have shown promise in augmenting endoscopist performance, redefining quality metrics, optimizing workflows, and aiding in predictive modeling and diagnosis. However, challenges remain in evaluating AI algorithms, ensuring transparency and interpretability, addressing governance and data procurement, determining payment models, defining relevant clinical outcomes, and fostering collaboration between stakeholders. Addressing these challenges while maintaining a balanced perspective is crucial for the meaningful advancement of AI in gastroenterology.

Micro(nano)plastics: invisible compounds with a visible impact.

The plastic related research has been an epicentre in recent times. The presence and spread of micro (nano) plastics (MNPs) are well-known in the terrestrial and aquatic environment. However, the focus on the fate and remediation of MNP in soil and groundwater is limited. The fate and bioaccumulation of ingested MNPs remain unknown within the digestive tract of animals. There is also a significant knowledge gap in understanding the ubiquitous organic environmental pollutants with MNPs in biological systems. Reducing plastic consumption, improving waste management practices, and developing environmentally friendly alternatives are some of the key steps needed to address MNP pollution. For better handling and to protect the environment from these invisible substances, policymakers and researchers urgently need to monitor and map MNP contamination in soil and groundwater.

Curative criteria for endoscopic treatment of oesophageal adenocarcinoma.

The incidence of oesophageal adenocarcinoma has been increasing rapidly in the Western world. A well-known risk factor for developing this type of tumour is reflux disease, which can cause metaplasia from the squamous cell mucosa to columnar epithelium (Barrett's Oesophagus) which can progress to dysplasia and eventually adenocarcinoma. With the rise of the incidence of oesophageal adenocarcinoma, research on the best way to manage this disease is of great importance and has changed treatment modalities over the last decades. The gold standard for superficial adenocarcinoma has shifted from surgical to endoscopic management when certain criteria are met. This review will discuss the different curative criteria for endoscopic treatment of oesophageal adenocarcinoma.

Expert endoscopist assessment of colorectal polyp size using virtual scale endoscopy, visual or snare-based estimation: a prospective video-based study.

BACKGROUND AND AIMS: Accurate polyp size estimation during colonoscopy has an impact on clinical decision-making. A laser-based virtual scale endoscope (VSE) is available to allow measuring polyp size using a virtual adaptive scale. This study evaluates video-based polyp size measurement accuracy among expert endoscopists using either VSE or visual assessment (VA) with either snare as reference size or without any reference size information. METHODS: A prospective, video-based study was conducted with 10 expert endoscopists. Video sequences from 90 polyps with known reference size (fresh specimen measured using calipers) were distributed on three different slide sets so that each slide set showed the same polyp only once with either VSE, VA or snare-based information. A slide set was randomly assigned to each endoscopist. Endoscopists were asked to provide size estimation based on video review. RESULTS: Relative accuracies for VSE, VA, and snare-based estimation were 75.1% (95% CI [71.6-78.5]), 65.0% (95% CI [59.5-70.4]) and 62.0% (95% CI [54.8-69.0]), respectively. VSE yielded significantly higher relative accuracy compared to VA (p = 0.002) and to snare (p = 0.001). A significantly lower percentage of polyps 1-5 mm were misclassified as >5 mm using VSE versus VA and snare (6.52% vs. 19.6% and 17.5%, p = 0.004) and a significantly lower percentage of polyps >5 mm were misclassified as 1-5 mm using VSE versus VA and snare (11.4% vs. 31.9% and 14.9%, p = 0.038). CONCLUSIONS: Endoscopists estimate polyp size with the highest accuracy when virtual adaptive scale information is displayed. Using a snare to assist sizing did not improve measurement accuracy compared to displaying visual information alone.

Establishment of Standards for the Referral of Large Non-Pedunculated Colorectal Polyps: An International Expert Consensus Using a Modified Delphi Process.

BACKGROUND AND AIMS: Resection of colorectal polyps has been shown to decrease the incidence and mortality of colorectal cancer. Large non-pedunculated colorectal polyps are often referred to expert centres for endoscopic resection, which requires relevant information to be conveyed to the therapeutic endoscopist to allow for triage and planning of resection technique. The primary objective of our study was to establish minimum expected standards for the referral of LNPCP for potential ER. METHODS: A Delphi methodology was employed to establish consensus on minimum expected standards for the referral of large colorectal polyps among a panel of international endoscopy experts. The expert panel was recruited through purposive sampling, and three rounds of surveys were conducted to achieve consensus, with quantitative and qualitative data analysed for each round. RESULTS: A total of 24 international experts from diverse continents participated in the Delphi study, resulting in consensus on 19 statements related to the referral of large colorectal polyps. The identified factors, including patient demographics, relevant medications, lesion factors, photodocumentation and the presence of a tattoo, were deemed important for conveying the necessary information to therapeutic endoscopists. The mean scores for the statements ranged from 7.04 to 9.29 out of 10, with high percentages of experts considering most statements as a very high priority. Subgroup analysis by continent revealed some variations in consensus rates among experts from different regions. CONCLUSION: The identified consensus statements can aid in improving the triage and planning of resection techniques for large colorectal polyps, ultimately contributing to the reduction of colorectal cancer incidence and mortality.

Physician perceptions on the current and future impact of artificial intelligence to the field of gastroenterology.

BACKGROUND AND AIMS: The use of artificial intelligence (AI) has transformative implications to the practice of gastroenterology and endoscopy. The aims of this study were to understand the perceptions of the gastroenterology community toward AI and to identify potential barriers for adoption. METHODS: A 16-question online survey exploring perceptions on the current and future implications of AI to the field of gastroenterology was developed by the American Society for Gastrointestinal Endoscopy AI Task Force and distributed to national and international society members. Participant demographic information including age, sex, experience level, and practice setting was collected. Descriptive statistics were used to summarize survey findings, and a Pearson χ2 analysis was performed to determine the association between participant demographic information and perceptions of AI. RESULTS: Of 10,162 invited gastroenterologists, 374 completed the survey. The mean age of participants was 46 years (standard deviation, 12), and 299 participants (80.0%) were men. One hundred seventy-nine participants (47.9%) had >10 years of practice experience, with nearly half working in the community setting. Only 25 participants (6.7%) reported the current use of AI in their clinical practice. Most participants (95.5%) believed that AI solutions will have a positive impact in their practice. One hundred seventy-six participants (47.1%) believed that AI will make clinical duties more technical but will also ease the burden of the electronic medical record (54.0%). The top 3 areas where AI was predicted to be most influential were endoscopic lesion detection (65.3%), endoscopic lesion characterization (65.8%), and quality metrics (32.6%). Participants voiced a desire for education on topics such as the clinical use of AI applications (64.4%), the advantages and limitations of AI applications (57.0%), and the technical methodology of AI (44.7%). Most participants (42.8%) expressed that the cost of AI implementation should be covered by their hospital. Demographic characteristics significantly associated with this perception included participants' years in practice and practice setting. CONCLUSIONS: Gastroenterologists have an overall positive perception regarding the use of AI in clinical practice but voiced concerns regarding its technical aspects and coverage of costs associated with implementation. Further education on the clinical use of AI applications with understanding of the advantages and limitations appears to be valuable in promoting adoption.

Wnt signalling pathways as mediators of neuroprotective mechanisms: therapeutic implications in stroke.

A stroke is a complicated neurological illness that occurs when there is a disruption in the blood flow to the brain. This disruption results in the damage of neurons, which then leads to functional abnormalities. The Wnt signalling pathway, which is already well-known for its important function in development and tissue homeostasis, has recently been recognised as a critical factor in the pathophysiology of stroke. Recent studies have shown the Wnt pathway's roles in stroke-related events. The complex-interactions between the Wnt pathway and stroke emphasising the pathway's contributions to neuro-protection and synaptic plasticity. The Wnt pathway's influence on neuro-genesis and synaptic plasticity underscores its potential for driving stroke recovery and rehabilitation strategies. The current review discusses about the Wnt signalling pathway in brain pathophysiology and stroke with special emphasis on the various pathways involved in the positive and negative modulation of Wnt pathway namely Phosphoinositide 3-kinase (PI3-K), Glycogen synthase kinase-3ß (GSK-3ß), Mitogen-activated protein kinase (MAPK) and nuclear factor erythroid 2-related factor 2 (Nrf2) pathway.