A Janus Au–Polymersome Heterostructure with Near‐Field Enhancement Effect for Implant‐Associated Infection Phototherapy
Bibliographic record
Abstract
Polymer-inorganic hybrid Janus nanoparticles (PI-JNPs) have attracted extensive attention due to their special structures and functions. However, achieving the synergistic enhancement of photochemical activity between polymer and inorganic moieties in PI-JNPs remains challenging. Herein, the construction of a novel Janus Au-porphyrin polymersome (J-AuPPS) heterostructure by a facile one-step photocatalytic synthesis is reported. The near-field enhancement (NFE) effect between porphyrin polymersome (PPS) and Au nanoparticles in J-AuPPS is achieved to enhance its near-infrared (NIR) light absorption and electric/thermal field intensity at their interface, which improves the energy transfer and energetic charge-carrier generation. Therefore, J-AuPPS shows a higher NIR-activated photothermal conversion efficiency (48.4%) and generates more singlet oxygen compared with non-Janus core-particle Au-PPS nanostructure (28.4%). As a result, J-AuPPS exhibits excellent dual-mode (photothermal/photodynamic) antibacterial and anti-biofilm performance, thereby significantly enhancing the in vivo therapeutic effect in an implant-associated-infection rat model. This work is believed to motivate the rational design of advanced hybrid JNPs with desirable NFE effect and further extend their biological applications.
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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) | 0.000 | 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 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".