Human Kallikrein 13: Production and Purification of Recombinant Protein and Monoclonal and Polyclonal Antibodies, and Development of a Sensitive and Specific Immunofluorometric Assay
Bibliographic record
Abstract
BACKGROUND: The aims of this study were to develop immunologic reagents and a sensitive and specific immunoassay for human kallikrein 13 (hK13) and to examine the presence of hK13 in human tissues and biological fluids. METHODS: Recombinant hK13 protein was produced and purified with use of a Pichia pastoris yeast expression system. The protein was used as an immunogen to generate mouse monoclonal and rabbit polyclonal anti-hK13 antibodies. A sandwich-type immunoassay was developed with these antibodies. The assay was used to measure hK13 in various biological fluids and tissue extracts. Immunohistochemical analysis was also performed on nondiseased and cancerous prostatic sections. RESULTS: The hK13 immunoassay had a detection limit of 0.05 micro g/L and showed no cross-reactivity with homologous kallikreins. The assay was linear at 0-20 micro g/L, and within-and between-run CVs were <10% (n = 12). hK13 was detected in tissues, including esophagus, tonsil, trachea, lung, cervix, and prostate. hK13 was also found in seminal plasma, amniotic fluid, follicular fluid, ascites of ovarian cancer patients, breast milk, and cytosolic extracts of ovarian cancer tissues. hK13 was immunohistochemically localized in epithelial cells of both nondiseased and cancerous prostate. hK13 appears to be overexpressed in 50% of ovarian cancer tissues compared with healthy ovarian tissues. Recovery of active enzyme added to milk or amniotic fluid was 70-98%, but was <20% when added to serum, suggesting rapid sequestration by protease inhibitors. In fluids and tissue extracts, hK13 was found in its free (approximately 30 kDa) form. CONCLUSIONS: This immunofluorometric assay for hK13 may be used to examine the value of hK13 as a disease biomarker and to further explore the physiologic and pathobiologic role of this enzyme in human disease.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".