Induction of Complement C3a Receptor Responses by Kallikrein-Related Peptidase 14
Bibliographic record
Abstract
Activation of the complement system is primarily initiated by pathogen- and damage-associated molecular patterns on cellular surfaces. However, there is increasing evidence for direct activation of individual complement components by extrinsic proteinases as part of an intricate crosstalk between physiological effector systems. We hypothesized that kallikrein-related peptidases (KLKs), previously known to regulate inflammation via proteinase-activated receptors, can also play a substantial role in innate immune responses via complement. Indeed, KLKs exemplified by KLK14 were efficiently able to cleave C3, the point of convergence of the complement cascade, indicating a potential modulation of C3-mediated functions. By using in vitro fragmentation assays, mass spectrometric analysis, and cell signaling measurements, we pinpointed the generation of the C3a fragment of C3 as a product with potential biological activity released by the proteolytic action of KLK14. Using mice with various complement deficiencies, we demonstrated that the intraplantar administration of KLK14 results in C3-associated paw edema. The edema response was dependent on the presence of the receptor for C3a but was not associated with the receptor for the downstream complement effector C5a. Our findings point to C3 as one of the potential substrates of KLKs during inflammation. Given the wide distribution of the KLKs in tissues and biological fluids where complement components may also be expressed, we suggest that via C3 processing, tissue-localized KLKs can play an extrinsic complement-related role during activation of the innate immune response.
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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 | 0.001 |
| 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 | 0.001 |
| 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".