Influence of mouse prolactin‐inducible protein in saliva on the aggregation of oral bacteria
Bibliographic record
Abstract
INTRODUCTION: Mouse prolactin-inducible protein (mPIP) is secreted in mouse saliva and has been found to bind oral bacteria, showing the highest affinity for streptococci. Comparisons between the oral flora of mPIP knockout mice and their wild-type controls showed differences in the genera colonizing the two groups of mice. These findings suggested a role for mPIP in the colonization of the mouse oral cavity, possibly modulating the oral flora. In this in vitro study, we focused on the contribution of this protein to aggregation of oral bacteria, a process thought to promote the clearance of bacteria from the oral cavity, and one that could influence the composition of the oral bacterial community. METHODS: The aggregation of selected human and mouse oral streptococci was measured spectrophotometrically. The aggregation of oral bacteria by saliva from mPIP knockout mice, which lack mPIP, was compared with that of saliva from wild-type mice. RESULTS: Both wild-type saliva and mPIP knockout mouse saliva induced aggregation of human strain Streptococcus gordonii SK120 and mouse streptococci strains M105/6 and M106/2. Bacterial aggregation induced by the saliva of wild-type mice was significantly higher than the aggregation induced by saliva from mPIP knockout mice for all the bacterial strains. CONCLUSION: In this study it was confirmed that mPIP plays a role in the aggregation of oral bacteria. The salivary components promoting aggregation of oral bacteria are considered to be part of the oral defense mechanisms so these findings provide insight into a possible function of mPIP in host defense by promoting aggregation of oral bacteria.
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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".