Helicobacter pylori infection in stomach leads to gastric cancer, gastric ulcer, and duodenal ulcer. More than 1 million people die each year due to these diseases, but why most H. pylori-infected individuals remain asymptomatic while a certain proportion develops such severe gastric diseases remained an enigma. Several studies indicated that gastric and intestinal microbiota may play a critical role in the development of the H. pylori-associated diseases. However, no specific microbe in the gastric or intestinal microbiota has been clearly linked to H. pylori infection and related gastric diseases. Here, we studied H. pylori infection, its virulence genes, the intestinal microbiota, and the clinical status of Trivandrum residents (N = 375) in southwestern India by standard H. pylori culture, PCR genotype, Sanger sequencing, and microbiome analyses using Illumina Miseq and Nanopore GridION. Our analyses revealed that gastric colonization by virulent H. pylori strains (vacAs1i1m1cagA+) is necessary but not sufficient for developing these diseases. Conversely, distinct microbial pools exist in the lower gut of the H. pylori-infected vs. H. pylori-non-infected individuals. Bifidobacterium (belonging to the phylum Actinobacteria) and Bacteroides (belonging to the phylum Bacteroidetes) were present in lower relative abundance for the H. pylori+ group than the H. pylori- group (p < 0.05). On the contrary, for the H. pylori+ group, genus Dialister (bacteria belonging to the phylum Firmicutes) and genus Prevotella (bacteria belonging to the phylum Bacteroidetes) were present in higher abundance compared to the H. pylori- group (p < 0.05). Notably, those who carried H. pylori in the stomach and had developed aggressive gastric diseases also had extremely low relative abundance (p < 0.05) of several Bifidobacterium species (e.g., B. adolescentis, B. longum) in the lower gut suggesting a protective role of Bifidobacterium. Our results show the link between lower gastrointestinal microbes and upper gastrointestinal diseases. Moreover, the results are important for developing effective probiotic and early prognosis of severe gastric diseases.

Background and Aims Caregivers are needed for cirrhotic patients as there is progressive decline in cognition and self‐care. We intend to study the quality of life (QOL), psychosocial burden and prevalence of mental health disorders among caregivers. Methods Cross‐sectional study where caregivers, defined as person who takes responsibility of providing care to patient, of cirrhotic patients were included. Short form 36 health survey (SF‐36) to assess QOL, Zarit Burdern Index12 (ZBI) for caregiver burden (CB). Patient Health Questionnaire (PHQ) identified depression and Generalized Anxiety Disorder (GAD‐7) questionnaires, anxiety. Results Of 132 caregivers, mean age of caregiver was 41.2 ± 10.3 years, with female preponderance. Mean MELD was 21.4 ± 7, majority belonged to CHILD C. Comparing the SF36 score of caregivers to normal population showed lower level of QOL for caregivers. Mean ZBI score – 14 ± 5.8. Mean GAD score – 8.1 ± 5.1, 54 (41%) had anxiety. Mean PHQ score – 7.8 ± 5.2, 45 (34%) had depression. Regression analysis Alcoholic cirrhosis, history of hepatic encephalopathy (HE), Anxiety, Depression and recidivism predicted CB. Treatment costs (ODDS‐1.15), alcoholic cirrhosis (ODDS –8.9), history of HE (ODDS‐7.5) and caregiver duration (ODDS‐0.25) predicted anxiety. Treatment costs (ODDS‐1.5), caregiver age (ODDS‐0.87), spouse as caregiver (ODDS‐10.9) and higher education (ODDS‐0.79) predicted depression. Conclusions Caregivers of cirrhotic patients have high prevalence of CB with low QOL and high incidence of anxiety and depression, compared with the general population. Alcoholism in patients precipitates while higher education helps cope up with these disorders.

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The data's dimensionality had already risen sharply in the last several decades. The "Dimensionality Curse" (DC) is a problem for conventional learning techniques when dealing with "Big Data (BD)" with a higher level of dimensionality. A learning model's performance degrades when there is a numerous range of features present. "Dimensionality Reduction (DR)" approaches are used to solve the DC issue, and the field of "Machine Learning (ML)" research is significant in this regard. It is a prominent procedure to use "Feature Selection (FS)" to reduce dimensions. Improved learning effectiveness such as greater classification precision, cheaper processing costs, and improved model comprehensibility are all typical outcomes of this approach that selects an optimal portion of the original features based on some relevant assessment criteria. An "Adaptive Firefly Optimization (AFO)" technique based on the "Map Reduce (MR)" platform is developed in this research. During the initial phase (mapping stage) the whole large "DataSet (DS)" is first subdivided into blocks of contexts. The AFO technique is then used to choose features from its large DS. In the final phase (reduction stage), every one of the fragmentary findings is combined into a single feature vector. Then the "Multi Kernel Support Vector Machine (MKSVM)" classifier is used as classification in this research to classify the data for appropriate class from the optimal features obtained from AFO for DR purposes. We found that the suggested algorithm AFO combined with MKSVM (AFO-MKSVM) scales very well to high-dimensional DSs which outperforms the existing approach "Linear Discriminant Analysis-Support Vector Machine (LDA-SVM)" in terms of performance. The evaluation metrics such as Information-Ratio for Dimension-Reduction, Accuracy, and Recall, indicate that the AFO-MKSVM method established a better outcome than the LDA-SVM method.

Background/Aims: This meta-analysis analyzed the effect of an indwelling biliary stent on endoscopic ultrasound (EUS)–guided tissue acquisition from pancreatic lesions.Methods: A literature search was performed to identify studies published between 2000 and July 2022 comparing the diagnostic outcomes of EUS-TA in patients with or without biliary stents. For non-strict criteria, samples reported as malignant or suspicious for malignancy were included, whereas for strict criteria, only samples reported as malignant were included in the analysis.Results: Nine studies were included in this analysis. The odds of an accurate diagnosis were significantly lower in patients with indwelling stents using both non-strict (odds ratio [OR], 0.68; 95% confidence interval [CI], 0.52–0.90) and strict criteria (OR, 0.58; 95% CI, 0.46–0.74). The pooled sensitivity with and without stents were similar (87% vs. 91%) using non-strict criteria. However, patients with stents had a lower pooled sensitivity (79% vs. 88%) when using strict criteria. The sample inadequacy rate was comparable between groups (OR, 1.12; 95% CI, 0.76–1.65). The diagnostic accuracy and sample inadequacy were comparable between plastic and metal biliary stents.Conclusions: The presence of a biliary stent may negatively affect the diagnostic outcome of EUS-TA for pancreatic lesions.