Helicobacter Pylori-Induced Gastric Infections: From Pathogenesis to Novel Therapeutic Approaches Using Silver Nanoparticles

The immunopathogenesis of Helicobacter pylori-induced gastric cancer: a narrative review

Helicobacter pylori infection is a well-established risk factor for the development of gastric cancer (GC). Understanding the immunopathogenesis underlying this association is crucial for developing effective preventive and therapeutic strategies. This narrative review comprehensively explores the immunopathogenesis of H. pylori-induced GC by delving into several key aspects, emphasizing the pivotal roles played by H. pylori virulence factors, including cytotoxin-associated gene A (cagA) and vacuolating cytotoxin A (vacA), blood group antigen-binding adhesin (babA), and sialic acid binding adhesin (sabA). Moreover, the review focuses on the role of toll-like receptors (TLRs) and cytokines in the complex interplay between chronic infection and gastric carcinogenesis. Finally, the study examines the association between H. pylori evasion of the innate and adaptive immune response and development of GC. A comprehensive understanding of the immunopathogenesis of H. pylori-induced GC is essential for designing targeted interventions to prevent and manage this disease. Further research is warranted to elucidate the intricate immune responses involved and identify potential therapeutic targets to improve patient outcomes.

High-throughput screening and molecular dynamics simulations of natural products targeting LuxS/AI-2 system as a novel antibacterial strategy for antibiotic resistance in Helicobacter pylori

The main goal of treating any Helicobacter pylori (H. pylori)-related gastrointestinal disease is completely eradicating infection. Falling eradication efficiency, off-target effects, and patient noncompliance with prolonged and broad spectrums have sparked clinical interest in exploring other effective, safer therapeutic choices. As natural substances are risk-free and privileged with high levels of antibacterial activity, most of these natural chemical's specific modes of action are unknown. With the aid of in silico molecular docking-based virtual screening studies and molecular dynamic simulations, the current study is intended to gather data on numerous such natural chemicals and assess their affinity for the S-ribosyl homocysteine lyase (LuxS) protein of H. pylori. The ligand with the highest binding energy with LuxS, glucoraphanin, catechin gallate and epigallocatechin gallate were rationally selected for further computational analysis. The solution stability of the three compounds' optimal docking postures with LuxS was initially assessed using long-run molecular dynamics simulations. Using molecular dynamics simulation, the epigallocatechin gallate was found to be the most stable molecule with the highest binding free energy, indicating that it might compete with the natural ligand of the inhibitors. According to ADMET analysis, his phytochemical was a promising therapeutic candidate for an antibacterial action since it had a range of physicochemical, pharmacokinetic, and drug-like qualities and had no discernible adverse effects. Additional in vitro, in vivo, and clinical trials are needed to confirm the drug's precise efficacy during H. pylori infection.Communicated by Ramaswamy H. Sarma.

The role of bismuth nanoparticles in the inhibition of bacterial infection

Bismuth (Bi) combinations have been utilized for the treatment of bacterial infections. In addition, these metal compounds are most frequently utilized for treating gastrointestinal diseases. Usually, Bi is found as bismuthinite (Bi sulfide), bismite (Bi oxide), and bismuthite (Bi carbonate). Newly, Bi nanoparticles (BiNP) were produced for CT imaging or photothermal treatment and nanocarriers for medicine transfer. Further benefits, such as increased biocompatibility and specific surface area, are also seen in regular-size BiNPs. Low toxicity and ecologically favorable attributes have generated interest in BiNPs for biomedical approaches. Moreover, BiNPs offer an option for treating multidrug-resistant (MDR) bacteria because they communicate directly with the bacterial cell wall, induce adaptive and inherent immune reactions, generate reactive oxygen compounds, limit biofilm production, and stimulate intracellular impacts. In addition, BiNPs in amalgamation with X-ray therapy as well as have the capability to treat MDR bacteria. BiNPs as photothermal agents can realize the actual antibacterial through continuous efforts of investigators in the near future. In this article, we summarized the properties of BiNPs, and different preparation methods, also reviewed the latest advances in the BiNPs' performance and their therapeutic effects on various bacterial infections, such as Helicobacter pylori, Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli.

Endotoxemia and Gastrointestinal Cancers: Insight into the Mechanisms Underlying a Dangerous Relationship

Lipopolysaccharide (LPS), also known as endotoxin, is a component of the membrane of gram-negative bacteria and a well-recognized marker of sepsis. In case of disruption of the intestinal barrier, as occurs with unhealthy diets, alcohol consumption, or during chronic diseases, the microbiota residing in the gastrointestinal tract becomes a crucial factor in amplifying the systemic inflammatory response. Indeed, the translocation of LPS into the bloodstream and its interaction with toll-like receptors (TLRs) triggers molecular pathways involved in cytokine release and immune dysregulation. This is a critical step in the exacerbation of many diseases, including metabolic disorders and cancer. Indeed, the role of LPS in cancer development is widely recognized, and examples include gastric tumor related to Helicobacter pylori infection and hepatocellular carcinoma, both of which are preceded by a prolonged inflammatory injury; in addition, the risk of recurrence and development of metastasis appears to be associated with endotoxemia. Here, we review the mechanisms that link the promotion and progression of tumorigenesis with endotoxemia, and the possible therapeutic interventions that can be deployed to counteract these events.

A deep learning based framework for the classification of multi- class capsule gastroscope image in gastroenterologic diagnosis

Purpose: The purpose of this paper is to develop a method to automatic classify capsule gastroscope image into three categories to prevent high-risk factors for carcinogenesis, such as atrophic gastritis (AG). The purpose of this research work is to develop a deep learning framework based on transfer learning to classify capsule gastroscope image into three categories: normal gastroscopic image, chronic erosive gastritis images, and ulcer gastric image. Method: In this research work, we proposed deep learning framework based on transfer learning to classify capsule gastroscope image into three categories: normal gastroscopic image, chronic erosive gastritis images, and ulcer gastric image. We used VGG- 16, ResNet-50, and Inception V3 pre-trained models, fine-tuned them and adjust hyperparameters according to our classification problem. Results: A dataset containing 380 images was collected for each capsule gastroscope image category, and divided into training set and test set in a ratio of 70%, and 30% respectively, and then based on the dataset, three methods, including as VGG- 16, ResNet-50, and Inception v3 are used. We achieved highest accuracy of 94.80% by using VGG- 16 to diagnose and classify capsule gastroscopic images into three categories: normal gastroscopic image, chronic erosive gastritis images, and ulcer gastric image. Our proposed approach classified capsule gastroscope image with respectable specificity and accuracy. Conclusion: The primary technique and industry standard for diagnosing and treating numerous stomach problems is gastroscopy. Capsule gastroscope is a new screening tool for gastric diseases. However, a number of elements, including image quality of capsule endoscopy, the doctors' experience and fatigue, limit its effectiveness. Early identification is necessary for high-risk factors for carcinogenesis, such as atrophic gastritis (AG). Our suggested framework will help prevent incorrect diagnoses brought on by low image quality, individual experience, and inadequate gastroscopy inspection coverage, among other factors. As a result, the suggested approach will raise the standard of gastroscopy. Deep learning has great potential in gastritis image classification for assisting with achieving accurate diagnoses after endoscopic procedures.

Prevalence of Her2-neu status and its clinicopathological association in newly diagnosed gastric cancer patients

Background

This study aimed to report the prevalence of HER2-neu in newly diagnosed early or metastatic gastric cancer (GC) patients, to determine the percentage of patients achieving various IHC scores correlating with the ISH results and to establish a database for GC patients in Lebanon.

Methods

This was a national, multicenter, descriptive and cross-sectional study in patients with histologically confirmed early or metastatic GC newly diagnosed. All eligible patients underwent the IHC and ISH tests in a central laboratory. Demographics, medical history and histopathology data were collected.

Results

One hundred fifty-seven patients were included (mean age at diagnosis: 63 ± 14.1 years) during a 3.5 year period. The prevalence of HER2-neu over expression was 21% (95% CI: 15.3–27.4) using ICH and ISH. Agreement between IHC and ISH results was significantly substantial (kappa = 0.681; p-value < 0.001). Over expressed HER2-neu status was significantly associated with high ECOG performance status only.

Conclusions

The prevalence of HER2-neu over expression in newly diagnosed early or metastatic GC patients seemed to be high in Lebanon. The database generated allows to monitor trends in the epidemiology and management of GC.

Systematic Review and Meta-Analysis on the Sensitivity and Specificity of 13C/14C-Urea Breath Tests in the Diagnosis of Helicobacter pylori Infection

Helicobacter pylori (H. pylori) continues to be a major health problem worldwide, causing considerable morbidity and mortality due to peptic ulcer disease and gastric cancer. The aim of the present systematic review and meta-analysis was to determine the sensitivity and specificity of 13C/14C-urea breath tests in the diagnosis of H. pylori infection. A PRISMA systematic search appraisal and meta-analysis were conducted. A systematic literature search of PubMed, Web of Science, EMBASE, Scopus, and Google Scholar was conducted up to August 2022. Generic, methodological and statistical data were extracted from the eligible studies, which reported the sensitivity and specificity of 13C/14C-urea breath tests in the diagnosis of H. pylori infection. A random effect meta-analysis was conducted on crude sensitivity and specificity of 13C/14C-urea breath test rates. Heterogeneity was assessed by Cochran’s Q and I2 tests. The literature search yielded a total of 5267 studies. Of them, 41 articles were included in the final analysis, with a sample size ranging from 50 to 21857. The sensitivity and specificity of 13C/14C-urea breath tests in the diagnosis of H. pylori infection ranged between 64−100% and 60.5−100%, respectively. The current meta-analysis showed that the sensitivity points of estimate were 92.5% and 87.6%, according to the fixed and random models, respectively. In addition, the specificity points of estimate were 89.9% and 84.8%, according to the fixed and random models, respectively. There was high heterogeneity among the studies (I2 = 98.128 and 98.516 for the sensitivity and specificity, respectively, p-value < 0.001). The 13C/14C-urea breath tests are highly sensitive and specific for the diagnosis of H. pylori infection.