Hollow Mesoporous Silica Nanocarriers with Multifunctional Capping Agents for In Vivo Cancer Imaging and Therapy
Bibliographic record
Abstract
Efficient drug loading and selectivity in drug delivery are two key features of a good drug-carrier design. Here we report on such a drug carrier formed by using hollow mesoporous silica nanoparticles (HMS NPs) as the core and specifically designed multifunctional amphiphilic agents as the encapsulating shell. These nanocarriers combine the advantages of the HMS NP core (favorable physical and structural properties) and the versatility of an organic-based shell (e.g., specificity in chemical properties and modifiability). Moreover, both the properties of the core and the shell can be independently varied. The varied core and shell could then be integrated into a single device (drug carrier) to provide efficient and specific drug delivery. In vitro and in vivo data suggests that these drug nanocarriers are biocompatible and are able to deliver hydrophobic drugs selectively to target tumor cells. After the break of the pH-labile linkages in the shell, the drug payload can be released and the tumor cells are killed.
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".