Adhesion Forces and Coaggregation between Vaginal Staphylococci and Lactobacilli
Bibliographic record
Abstract
Urogenital infections are the most common ailments afflicting women. They are treated with dated antimicrobials whose efficacy is diminishing. The process of infection involves pathogen adhesion and displacement of indigenous Lactobacillus crispatus and Lactobacillus jensenii. An alternative therapeutic approach to antimicrobial therapy is to reestablish lactobacilli in this microbiome through probiotic administration. We hypothesized that lactobacilli displaying strong adhesion forces with pathogens would facilitate coaggregation between the two strains, ultimately explaining the elimination of pathogens seen in vivo. Using atomic force microscopy, we found that adhesion forces between lactobacilli and three virulent toxic shock syndrome toxin 1-producing Staphylococcus aureus strains, were significantly stronger (2.2-6.4 nN) than between staphylococcal pairs (2.2-3.4 nN), especially for the probiotic Lactobacillus reuteri RC-14 (4.0-6.4 nN) after 120 s of bond-strengthening. Moreover, stronger adhesion forces resulted in significantly larger coaggregates. Adhesion between the bacteria occurred instantly upon contact and matured within one to two minutes, demonstrating the potential for rapid anti-pathogen effects using a probiotic. Coaggregation is one of the recognized mechanisms through which lactobacilli can exert their probiotic effects to create a hostile micro-environment around a pathogen. With antimicrobial options fading, it therewith becomes increasingly important to identify lactobacilli that bind strongly with pathogens.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".