Tunable stellate mesoporous silica nanoparticles for intracellular drug delivery
Bibliographic record
Abstract
Stellate mesoporous silica nanoparticles with special radial pore morphology were easily synthesized using triethanolamine as the base catalyst in a wide range of synthesis conditions. By adjusting the surfactant composition, reaction temperature and time, and reagent ratio, the particle size of the material could be tailored continuously ranging from 50 to 140 nm and the pore size from 2 to 20 nm. By analyzing the effects of different synthesis parameters, it is concluded that the particles are formed following a nucleation-growth mechanism and the reaction kinetics play an important role in determining the particle size and pore structure. These stellate MSNs can be conveniently functionalized with a nontoxic low molecular weight poly(ethylene imine) (PEI, 800 Da) by a delayed condensation method. The resulting nanocomposites not only possess auto-fluorescence for suitable particle tracking but also demonstrate good potential for intracellular delivery of the anticancer doxorubicin drug.
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) | 0.000 | 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".