Binding of <i>Actinobacillus actinomycetemcomitans</i> lipopolysaccharides to <i>Peptostreptococcus micros</i> stimulates tumor necrosis factor α production by macrophage‐like cells
Bibliographic record
Abstract
Peptostreptococcus micros is a gram-positive bacterium that has been associated with periodontitis and endodontic infections. In this study, we hypothesized that P. micros binds the immunomodulating component lipopolysaccharide derived from gram-negative bacteria to increase its capacity to stimulate cytokine production by host cells. The ability of P. micros to bind Actinobacillus actinomycetemcomitans lipopolysaccharide was demonstrated by an enzyme-linked immunosorbent assay and by immunoelectron microscopy. Pretreatment of P. micros cells with A. actinomycetemcomitans lipopolysaccharide was associated with a 49-fold increase in tumor necrosis factor alpha production by human monocytic cells U937 differentiated into adherent macrophages, compared to the stimulation with untreated P. micros. This effect was suppressed by incorporating polymyxin B, a lipid A-binding substance, during treatment of macrophage-like cells with lipopolysaccharide-coated P. micros cells. This is the first study reporting a binding interaction between lipopolysaccharide and a gram-positive bacterium. This interaction represents a new mechanism that could promote the inflammatory response during periodontitis.
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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".