Biodegradable Photothermal and pH Responsive Calcium Carbonate@Phospholipid@Acetalated Dextran Hybrid Platform for Advancing Biomedical Applications
Bibliographic record
Abstract
A biodegradable multifunctional carrier for combination therapy with high efficiency and low side effect is essential for effective cancer treatment and for advancing biomedical applications. Therapeutics combination could reduce multidrug resistance and minimize doses through synergism. This study develops biodegradable gold nanorods@calcium carbonate particles coated with pH‐responsive acetalated dextran and phospholipid as an advanced platform for the incorporation of versatile molecular targeted therapeutics, including hydrophilic and hydrophobic drugs, as well as the model enzyme, green fluorescent protein, or antibody. The developed calcium carbonate based hybrid particles show good biocompatibility, stability with photothermal, and pH responsiveness, which protect the payloads from premature release, and maintain the enzyme activity. The therapeutics co‐loaded CaCO 3 based hybrid particles efficiently induce cancer cell death and reduce the multidrug resistance and HER2 expression with synergism. The photothermal effects promote ultrafast therapeutics release and induce significant cytotoxicity. Importantly, Anti‐HER2 antibody or HER2 targeted therapeutic is more effective in reducing HER2 expression when combined with drug or drugs via synergism. Overall, the cheap and simply manufactured biodegradable hybrid platform has great potential for advancing biomedical applications, including targeted photothermal combination therapy by co‐delivery of different types of therapeutics, including molecular targeted drugs, antibodies, and enzymes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".