Diagnosis of <i>Helicobacter pylori</i> infection and determination of clarithromycin resistance by fluorescence in situ hybridization from formalin-fixed, paraffin-embedded gastric biopsy specimens
Bibliographic record
Abstract
A reliable diagnostic test for Helicobacter pylori is important in clinical practice and research. The ideal diagnostic test for H. pylori should be sensitive, specific, and cost-effective. Helicobacter pylori resistance to clarithromycin is a common reason for failure of eradication therapy. The aim of this study was to evaluate the fluorescent in situ hybridization (FISH) method to detect H. pylori and determine clarithromycin resistance in formalin-fixed, paraffin-embedded gastric biopsy specimens. One hundred seventeen gastric biopsy specimens from patients with dyspepsia were examined for the presence of H. pylori by conventional culture, FISH, and histopathological methods. A set of fluorescent-labeled oligonucleotide probes binding to either H. pylori 16S rRNA or 23S rRNA sequences were used for FISH analysis. Phenotypic antibiotic susceptibilities of the isolates were tested using the Epsilometer test method (E test). Helicobacter pylori was detected in 70 of 117 biopsy specimens by histopathological examination and FISH, whereas it was detected in 47 specimens by culturing. Histopathology and FISH techniques failed to identify H. pylori in 1 biopsy sample isolated by culture. Clarithromycin resistance was found in 11 of 46 H. pylori isolates using the E test method. All of the phenotypic resistance measurements of isolates were correlated with genotypic clarithromycin resistance. Eleven clarithromycin-resistant strains were identified by FISH. The diagnosis of H. pylori infection and the determination of clarithromycin resistance in formalin-fixed, paraffin-embedded specimens using FISH is promising because it provides a rapid, reliable, and culture-independent diagnosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".