Detection and Identification of Active Serine Proteases in the Lower Female Reproductive Tract: A Functional Approach
Bibliographic record
Abstract
Proteases irreversibly modify proteins by hydrolyzing the bonds between amino acids and are implicated in virtually every significant biological process. Many proteases have previously been identified in cervical-vaginal fluid (CVF), the fluid covering the tissues of the lower female reproductive tract, and have been linked to a myriad of processes including the susceptibility to sexually transmitted diseases, pain sensitivity during sexual intercourse, extracellular matrix remodeling and vaginal epithelial desquamation. Interestingly, human CVF differs from other mammals in that it is uniquely acidic with levels of 4.5 or less which poses a substantial challenge for proteolytic activity in this environment. An integrated proteomic and peptidomic analysis of CVF confirmed that approximately 8% of the CVF proteome consists of proteases, predominantly serine proteases. Detailed proteomic analysis of CVF samples collected throughout the follicular and luteal phases of the menstrual cycle demonstrated that the CVF proteome remains consistent throughout the menstrual cycle. Functional proteomics using an activity-based probe (ABP) has emerged as a powerful tool to study active proteases within complex proteomes. In the current study, ABP profiling of CVF resulted in the identification of transmembrane protein serine 11D (TMPRSS11D) and kallikrein-related peptidase 13 (KLK13) as active trypsin-like serine proteases. Immunoassays showed that KLK13 is highly abundant in CVF and the expression of a panel of KLKs is not affected by the menstrual cycle phase. The finding that multiple KLKs are present at high abundance levels in CVF strengthens the hypothesis that the reproductive tissues and associated fluids are an important site for proteolytic functioning. We also observed a near complete cessation of trypsin-like proteolytic activity at physiological pH levels in CVF. Therefore, we propose a novel mechanism in which conditions characterized by an elevated pH in CVF, such as male ejaculation, postmenopausal status and bacterial infection, provide a window of opportunity for proteolytic activity in the lower female reproductive tract. Considering the fact that the proteases are involved in virtually every significant biological process, understanding the protease activity and functioning in CVF can provide important insights in their mechanism of action and ultimately lead to novel protease-targeted therapeutics.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".