Detection of Helicobacter pylori Microevolution and Multiple Infection from Gastric Biopsies by Housekeeping Gene Amplicon Sequencing
Bibliographic record
Abstract
Despite the great efforts devoted to research on Helicobacter pylori, the prevalence of single-strain infection or H. pylori mixed infection and its implications in the mode of transmission of this bacterium are still controversial. In this study, we explored the usefulness of housekeeping gene amplicon sequencing in the detection of H. pylori microevolution and multiple infections. DNA was extracted from five gastric biopsies from four patients infected with distinct histopathological diagnoses. PCR amplification of six H. pylori-specific housekeeping genes was then assessed on each sample. Optimal results were obtained for the cgt and luxS genes, which were selected for amplicon sequencing. A total of 11,833 cgt and 403 luxS amplicon sequences were obtained, 2042 and 112 of which were unique sequences, respectively. All cgt and luxS sequences were clustered at 97% to 9 and 13 operational taxonomic units (OTUs), respectively. For each sample from a different patient, a single OTU comprised the majority of sequences in both genes, but more than one OTU was detected in all samples. These results suggest that multiple infections with a predominant strain together with other minority strains are the main way by which H. pylori colonizes the human stomach.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".