Enzyme‐Inspired Controlled Release of Cucurbit[7]uril Nanovalves by Using Magnetic Mesoporous Silica
Bibliographic record
Abstract
The controlled release of drugs by biostimuli is highly desirable under physiological conditions for their potential use in advanced applications. The enzyme-inspired controlled release of cucurbituril nanovalves by using magnetic mesoporous silica nanoparticles (MSNs) in near-neutral aqueous solutions is reported for the first time. The encirclement of cucurbit[7]uril (CB[7]) onto the protonated 1,4-butanediamine stalks tethered to the external surfaces of superparamagnetic Fe(3) O(4) -embedded mesoporous silica particles leads to tight blocking of the nanopores. The supramolecular nanovalves are activated by the enzymatic decarboxylation products of lysine, cadaverine (in the protonated form), which has a high affinity for CB[7], so that the encapsulated guest molecules, calcein, in the nanopores are released into the bulk solution. The release of calcein can be controlled in small portions on command by alternating changes in enzymatic decarboxylation products and CB[7]. The amino acid derived polyamines have long been associated with cell growth and cancers. The guest molecules released from the delivery system of magnetic MSNs can act not only on sensing probes for levels of decarboxylases and polyamines, but also on efficacious drugs to specific tissues and cells for regulation of polyamine synthesis.
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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) | 0.000 | 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".