A new enzyme-linked immunosorbent assay (ELISA) for human free and bound kallikrein 9
Bibliographic record
Abstract
BACKGROUND: Kallikrein 9 (KLK9) is a member of the human kallikrein-related peptidases family, whose physiological role and implications in disease processes remain unclear. The active form of the enzyme is predicted to have chymotryptic activity. In the present study, we produced for the first time the active recombinant protein and monoclonal antibodies, and developed novel immunoassays for the quantification of free and bound KLK9 in biological samples. METHODS: The coding sequence of mature KLK9 isoform (mat-KLK9) was expressed in an Expi293F mammalian system and the synthesized polypeptide was purified through a two-step protocol. The purified protein was used as an immunogen for production of monoclonal antibodies in mice. Hybridomas were further expanded and antibodies were purified. Newly-produced monoclonal antibodies were screened for reaction with the KLK9 recombinant protein by a state-of-the-art immunocapture/parallel reaction monitoring mass spectrometry-based methodology. RESULTS: Anti-KLK9 antibodies were combined in pairs, resulting in the development of a highly sensitive (limit of detection: 15 pg/mL) and specific (no cross-reactivity with other KLKs) sandwich-type ELISA. Highest KLK9 protein levels were found in tonsil and sweat and lower levels in the heart, kidney and liver. Hybrid immunoassays using an anti-KLK9 antibody for antigen capture and various anti-serine protease inhibitor polyclonal antibodies, revealed the presence of an a1-antichymotrypsin-bound KLK9 isoform in biological samples. CONCLUSIONS: The ELISAs for free and bound forms of KLK9 may be highly useful for the detection of KLK9 in a broad range of biological samples, thus enabling the clarification of KLK9 function and use as a potential 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".