Safety of multiple administrations of spermicidal LL-37 antimicrobial peptide into the mouse female reproductive tract
Bibliographic record
Abstract
We have previously demonstrated spermicidal activity of LL-37 antimicrobial peptide on mouse/human sperm and its contraceptive effects in female mice. With its microbicidal action against Neisseria gonorrhoeae, LL-37 warrants development into a multipurpose prevention technology (MPT) agent for administering into the female reproductive tract (FRT). However, it is important to verify that multiple administrations of LL-37 do not lead to damage of FRT tissues and/or irreversible loss of fecundity. Herein, we transcervically injected LL-37 (36 µM-10× spermicidal dose) into female mice in estrus in three consecutive estrous cycles. A set of mice were sacrificed for histological assessment of the vagina/cervix/uterus 24 h after the last injection, while the second set were artificially inseminated with sperm from fertile males 1 week afterwards, and then monitored for pregnancy. Mice injected with PBS in parallel were regarded as negative controls, whereas those injected with vaginal contraceptive foam (VCF, available over the counter), containing 12.5% nonoxynol-9, served as positive controls for vaginal epithelium disruption. We demonstrated that the vagina/cervix/uterus remained normal in both LL-37-injected and PBS-injected mice, which also showed 100% resumption of fecundity. In contrast, VCF-injected mice showed histological abnormalities in the vagina/cervix/uterus and only 50% of them resumed fecundity. Similarly, LL-37 multiply administered intravaginally caused no damage to FRT tissues. While our results indicate the safety of multiple treatments of LL-37 in the mouse model, similar studies have to be conducted in non-human primates and then humans. Regardless, our study provides an experimental model for studying in vivo safety of other vaginal MPT/spermicide candidates.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".