Role of tissue kallikrein-related peptidases in cervical mucus remodeling and host defense
Bibliographic record
Abstract
Human tissue kallikrein-related peptidases (KLKs) are 15 hormonally regulated genes on chromosome 19q13.4 encoding secreted serine proteases. Many KLKs are expressed throughout the female reproductive system and found in cervico-vaginal fluid (CVF). Immunohistochemistry was performed to determine KLK localization in the female reproductive system (fallopian tube, endometrium, cervix and vagina tissues). KLK levels were measured in CVF and saliva over the menstrual cycle to study whether KLKs are regulated by hormonal changes during the cycle. In vitro cleavage analysis was performed to establish whether KLKs may play a role in vaginal epithelial desquamation, mucus remodeling or processing of antimicrobial proteins. KLKs were localized in the glandular epithelium of the fallopian tubes and endometrium, the cervical mucus-secreting epithelium and vaginal stratified squamous epithelium. KLK levels peaked in CVF and saliva after ovulation. In vitro cleavage analysis confirmed KLKs 5 and 12 as capable of digesting desmoglein and desmocollin adhesion proteins and cervical mucin proteins 4 and 5B. KLK5 can digest defensin-1alpha, suggesting it may aid in cervico-vaginal host defense. We provide evidence of potential physiological roles for KLKs in cervico-vaginal physiology: in desquamation of vaginal epithelial cells, remodeling of cervical mucus and processing of antimicrobial proteins.
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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".