Immunofluorometric Assay of Human Kallikrein 10 and Its Identification in Biological Fluids and Tissues
Bibliographic record
Abstract
BACKGROUND: The human kallikrein 10 gene [KLK10, also known as normal epithelial cell-specific 1 gene (NES1)] is a member of the human kallikrein gene family. The KLK10 gene encodes for a secreted serine protease (hK10). We hypothesize that hK10 is secreted into various biological fluids and that its concentration changes in some disease states. The aim of this study was to develop a sensitive and specific immunoassay for hK10. METHODS: Recombinant hK10 protein was produced and purified using a Pichia pastoris yeast expression system. The protein was used as an immunogen to generate mouse and rabbit polyclonal anti-hK10 antisera. A sandwich-type immunofluorometric assay was then developed using these antibodies. RESULTS: The hK10 immunoassay has a detection limit of 0.05 microg/L. The assay is specific for hK10 and has no detectable cross-reactivity with other homologous kallikrein proteins, such as prostate-specific antigen (hK3), human glandular kallikrein 2 (hK2), and human kallikrein 6 (hK6). The assay was linear from 0 to 20 microg/L with within- and between-run CVs <10%. hK10 is expressed in many tissues, including the salivary glands, skin, and colon and is also detectable in biological fluids, including breast milk, seminal plasma, cerebrospinal fluid, amniotic fluid, and serum. CONCLUSIONS: We report development of the first immunofluorometric assay for hK10 and describe the distribution of hK10 in biological fluids and tissue extracts. This assay can be used to examine the value of hK10 as a disease biomarker.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".