PtpA protein from Mycobacterium avium subsp. paratuberculosis as a potential marker of rheumatoid arthritis in humans
Bibliographic record
Abstract
Studies have noted the connection between Mycobacterium avium subspecies paratuberculosis (MAP) and autoimmunity. MAP is an intracellular pathogen that infects and multiplies in macrophages. To overcome the hostile environment elicited by the macrophage, MAP secretes a battery of virulence factors to neutralize the toxic effects of the macrophage. One of the virulence factors is the Protein Tyrosine Phosphatase A (PtpA), a protein secreted by MAP that interferes in the phago-lysosome fusion, rendering the pathogen unnoticed in the cytoplasm of the macrophage. This study aimed to assess the presence of PtpA antibodies in the sera of Mexican individuals with rheumatoid arthritis (RA) and investigate its possible use as a biomarker for disease activity. We compared RA patients (n = 100) to control subjects (CS) (n = 100) by assessing specific immune responses to PtpA (the antigen) by an indirect ELISA method. Results showed a significant difference in PtpA levels between RA and CS, with RA patients having a median OD of 0.4645 compared to 0.1372 in CS. Antibodies against PtpA were present in 95% of RA patients and 16% of CS (AUC = 0.9163, p = 0.0001). Male control subjects showed higher PtpA reactivity than female CS. The Disease Activity Score (DAS-28) analysis showed that individuals with moderate to high disease activity had lower levels of PtpA reactivity. The results suggest a potential connection between RA and MAP infection.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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".