An easy-to-fabricate clearable CuS-superstructure-based multifunctional theranostic platform for efficient imaging guided chemo-photothermal therapy
Bibliographic record
Abstract
Despite drug delivery systems (DDSs) receiving ever-increasing attention, development of a simple, effective, sensitive and clearable drug delivery and multifunctional theranostic nanoplatform for cancer therapy is still highly desirable and remains a challenge. Herein, using a one-step solvothermal method, hollow acanthosphere-like CuS superstructures assembled from ∼10 nm nanoparticles (NPs) were successfully obtained and used as an efficient drug delivery and theranostic platform for photoacoustic (PA) and infrared (IR) thermal imaging-guided cancer combination therapy. The special hollow characteristic of CuS superstructures with mesoporous shells and large cavities grants them high drug loading capacity; they demonstrate near-infrared (NIR)/pH stimuli-sensitive drug release and pronounced synergetic effects of chemo-photothermal therapy both in vitro and in vivo. In particular, our as-fabricated hollow loose CuS superstructures, with easily breakable characteristic, are biodegradable and able to be cleared from the body when their therapy task is completed. This CuS-superstructure-based clearable drug delivery and "all-in-one" cancer theranostic platform might provide possibilities for improving therapeutic efficacy and minimizing adverse effects.
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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".