A Stable Quaternized Chitosan-Black Phosphorus Nanocomposite for Synergetic Disinfection of Antibiotic-Resistant Pathogens
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Antibiotics are widely used for treatment of bacterial infections, and their overuse has contributed to microbial resistance. Currently, an alternative antibiotic-free therapy for inactivating bacteria is of great interest. Black phosphorus (BP), a biocompatible and nontoxic rising-star two-dimensional layered material, has gained remarkable interest in many bioapplications including biosensing, cancer therapy, drug delivery, and also antibacterial treatment. However, BP nanosheets suffer from instability in ambient environments due to rapid oxidation and degradation. To address this issue, BP nanosheets were modified with quaternized chitosan (QCS) by electrostatic adsorption to prepare a BP-QCS composite for photothermal/pharmaco treatment of bacterial infection. The BP-QCS has obviously enhanced solubility and chemical stability in aqueous suspensions. We have demonstrated that under near-infrared (NIR) irradiation, the BP-QCS can synergistically inactivate more than 95% methicillin-resistant Staphylococcus aureus (S. aureus) (MRSA) and Escherichia coli within 10 min with a dose of only 75 μg/mL in vitro. Meanwhile, the BP-QCS composite under NIR can synergistically inactivate 98% S. aureus in vivo. Furthermore, the BP-QCS suspensions at effective antibacterial concentrations have negligible cytotoxicity and in vivo toxicity.
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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) | 0.001 | 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 it