Peptidic sequence “HSEAETGPP” is recognized by the sera of pars planitis patients
Bibliographic record
Abstract
PURPOSE: HLA class II, p-36 protein, heat shock protein and retinal antigens have been associated with pars planitis (PP), but their participation in the development of the disease are unknown. A search for new molecules related to PP is necessary. This work focused on the identification of peptides recognized by PP patient sera using the phage display method. METHODS: Sera of PP patients were used to isolate peptides fused to M13-phage pIII protein. The response of PP and healthy sera to peptides was determined by ELISA. PCR amplification and sequencing of peptide-encoding fragments from clones with high recognition by PP sera were used to characterize displayed peptides. RESULTS: One hundred clones were randomly selected from a phage display library after three panning rounds using serum proteins from a PP patient. The immunologic response level of 100 clones selected were determined with a major number of patients, it was found that one clone was recognized stronger in PP patients sera than in healthy sera (PP vs. healthy; P < 0.05). The peptide-encoding region of this clone was sequenced and translated. The peptide sequence corresponded to HSEAETGPP. An identical amino acid sequence to HSEAETGPP is found in the human proline-rich transmembrane protein 2 which has not been related with eye diseases. CONCLUSION: These results suggest that the peptide HSEAETGPP is associated with PP.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".