Enzymatic profiling of human kallikrein 14 using phage-display substrate technology
Bibliographic record
Abstract
The human KLK14 gene is one of the newly identified serine protease genes belonging to the human kallikrein family, which contains 15 members. KLK14 , like all other members of the human kallikrein family, is predicted to encode for a secreted serine protease already found in various biological fluids. This new kallikrein is mainly expressed in prostate and endocrine tissues, but its function is still unknown. Recent studies have demonstrated that KLK14 gene expression is up-regulated in prostate and breast cancer tissues, and that higher expression levels correlate with more aggressive tumors. In this work, we used phage-display substrate technology to study the substrate specificity of hK14. A phage-displayed random pentapeptide library with exhaustive diversity was screened with purified recombinant hK14. Highly specific and sensitive substrates were selected from the library. We show that hK14 has dual activity, trypsin- and chymotrypsin-like, with a preference for cleavage after arginine residues. A SwissProt database search with selected sequences identified six potential human protein substrates for hK14. Two of them, laminin alpha-5 and collagen IV, which are major components of the extracellular matrix, have been demonstrated to be hydrolyzed efficiently by hK14.
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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) | 0.001 | 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".