cagA gene EPIYA motif genetic characterization from Colombian Helicobacter pylori isolates: Standardization of a molecular test for rapid clinical laboratory detection
Bibliographic record
Abstract
The aim of this work was to determine current cagA gene EPIYA motifs present in Colombian Helicobacter pylori isolates using a fast and reliable molecular test. DNA from eighty-five Helicobacter pylori-cagA positive strains were analyzed. Strains were obtained from patients diagnosed with functional dyspepsia at Clínica Fundadores in Bogotá. The 3' region of the cagA gene was amplified through conventional Polymerase Chain Reaction (PCR). Obtained amplicons were sequenced using the Sanger method and analyzed with bioinformatics tools. Additionally, a significant Spearman correlation coefficient was determined between the patients' age and the number of EPIYA-C repeats; with p values < 0.05 considered significant. Estimates were obtained using a 95% CI. The 3´ variable region of the cagA gene was amplified and PCR products of the following sizes corresponded to the following EPIYA motifs: 400 bp: EPIYA AB, 500 bp: EPIYA ABC, 600 bp: EPIYA ABCC and 700 bp: ABCCC. A single PCR band was observed for 58 out of 85 Helicobacter pylori isolates, with an EPIYA distribution motif as follows: 7/85 AB (8.2%), 34/85 ABC (40%), 26/85 ABCC (30.6%) and 18/85 ABCCC (21.2%). However, in 27 out of 85 Helicobacter pylori isolates, two or more bands were observed, where the most predominant cagA genotype were ABC-ABCC (26%, 7/27) and ABCC-ABCCC (22.2%, 6/27). A direct proportionality between the number of EPIYA-C repeats and an increase in the patients' age was observed, finding a greater number of EPIYA ABCC and ABCCC repeats in the population over 50 years old. All isolates were of the Western cagA type and 51.8% of them were found to have multiple EPIYA-C repeats. These standardized molecular test allowed to identify the number of EPIYA C motifs based on band size.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".