An Antibacterial Nanorobotic Approach for the Specific Targeting and Removal of Multiple Drug‐Resistant <i>Staphylococcus aureus</i>
Bibliographic record
Abstract
Methicillin-resistant Staphylococcus aureus (MRSA) causes diseases ranging from skin infections to lethal sepsis and has become a serious threat to human health due to multiple-drug resistance (MDR). Therefore, a resistance-free antibacterial therapy is necessary to overcome MDR MRSA infections. In this study, an antibacterial nanorobot (Ab-nanobot) is developed wherein a cell wall-binding domain (CBD)-endolysin, acting as a sensor, is covalently conjugated with an actuator consisting of an iron oxide/silica core-shell. The CBD-endolysin sensor shows an excellent specificity to detect, bind, and accumulate on the S. aureus USA300 cell surface even in a bacterial consortium, and in host cell infections. Ab-nanobot specifically captures and kills MRSA in response to medically approved radiofrequency (RF) electromagnetic stimulation (EMS) signal. When Ab-nanobot receives the RF-EMS signal on the cell surface, actuator induces cell death in MRSA with 99.999% removal within 20 min by cell-wall damage via generation of localized heat and reactive oxygen species. The in vivo efficacy of Ab-nanobot is proven using a mice subcutaneous skin infection model. Collectively, this study offers a nanomedical resistance-free strategy to overcome MDR MRSA infections by providing a highly specific nanorobot for S. aureus.
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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".