Prediction of Epitopes in the Proteome of Helicobacter pylori
Bibliographic record
Abstract
Helicobacter pylori (H. pylori) is classified by the World Health Organization (WHO) as a group I carcinogen and is one of the most efficient human pathogens with over half of the world's population colonized by this gram-negative spiral bacterium. H. pylori can cause a chronic infection in the stomach during early childhood that persists throughout life due to diverse mechanisms of immune response evasion. H. pylori has several factors strongly associated with increased risk of disease such as toxins, adhesins, and chemoattractants, some of which are highly polymorphic, phase variable, and have different functions. Conventional treatments involve the use of antibiotics. However, treatment frequently fails due to the resistance H. pylori has progressively developed to antibiotics. This creates the need for different treatments made possible by identifying new therapeutic targets in the pathogen’s genome.The purpose of this study was an in silico prediction of T- and B- epitopes in H. pylori proteins. Twenty-two external membrane proteins from H. pylori Strain 26695 (accession number NC_000915) were identified using the web tool Vaxign (http://www.violinet.org/vaxign/). A total of one-hundred epitopes (60 class I epitopes and 40 class II epitopes) that could be used to develop novel non-antibiotics drugs for an H. pylori infection were predicted.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
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".