Human monoclonal antibodies against <i>Staphylococcus aureus</i> surface antigens recognize <i>in vitro</i> biofilm and <i>in vivo</i> implant infections
Bibliographic record
Abstract
Abstract Implant-associated Staphylococcus aureus infections are difficult to treat because of biofilm formation. Bacteria in a biofilm are often insensitive to antibiotics and host immunity. Monoclonal antibodies (mAbs) could provide an alternative approach to improve the diagnosis and/or treatment of biofilm-related infections. Here we show that mAbs targeting common surface components of S. aureus can recognize clinically relevant biofilm types. We identify two groups of antibodies: one group that uniquely binds S. aureus in biofilm state and one that recognizes S. aureus in both biofilm and planktonic state. In a mouse model, we show that mAb 4497 (recognizing wall teichoic acid (WTA)) specifically localizes to biofilm-infected implants. In conclusion, we demonstrate the capacity of several human mAbs to detect S. aureus biofilms in vitro and in vivo . This is an important first step to develop mAbs for imaging or treating S. aureus biofilms.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".