Bioinspired tissue-compliant hydrogels with multifunctions for synergistic surgery–photothermal therapy
Bibliographic record
Abstract
Operation therapy is a common treatment for many cancers, but malignant tumors likely recur and metastasize after surgery, resulting in treatment failure. In this study, we aimed at synthesizing a multifunctional hydrogel patch that features multifunctions for synergistic surgery-photothermal therapy. Our polydopamine nanoparticle (PDA NP)-crosslinked poly(acrylamide-co-N-(3-aminopropyl)methacrylamide) hydrogels undergo several dynamic interactions (e.g., hydrogen bonds, π-π interactions, and imine bonds), which confer high stretchability (∼3430%) and adhesive strength to porcine skin (∼75 kPa) that mimics soft wound tissues. Furthermore, PDA NP incorporation into the hydrogel matrix endows it with photothermal responsivity under 808 nm irradiation. As a proof of concept, our hydrogel system was used to ablate residual tumors in 4T1 tumor-bearing mice models after surgery via photothermal therapy. We find that synergistic operation-photothermal therapy effectively eradicates solid tumors and prevents cancer recurrence in mice. We envision that our work provides an effective synergistic strategy for cancer treatment and offers great potential for clinical 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) | 0.001 | 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".