Impact of Dietary Patterns on H. pylori Infection and the Modulation of Microbiota to Counteract Its Effect. A Narrative Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Helicobacter pylori (H. pylori) is a Gram-negative bacterium that colonizes the stomach and can induce gastric disease and intra-gastric lesions, including chronic gastritis, peptic ulcers, gastric adenocarcinoma, and mucosa-associated lymphoid tissue lymphoma. This bacterium is responsible for long-term complications of gastric disease. The conjunction of host genetics, immune response, bacterial virulence expression, diet, micronutrient availability, and microbiome structure influence the disease outcomes related to chronic H. pylori infection. In this regard, the consumption of unhealthy and unbalanced diets can induce microbial dysbiosis, which infection with H. pylori may contribute to. However, to date, clinical trials have reported controversial results and current knowledge in this field is inconclusive. Here, we review preclinical studies concerning the changes produced in the microbiota that may be related to H. pylori infection, as well as the involvement of diet. We summarize and discuss the last approaches based on the modulation of the microbiota to improve the negative impact of H. pylori infection and their potential translation from bench to bedside.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it