Multiresponsive Supramolecular Theranostic Nanoplatform Based on Pillar[5]arene and Diphenylboronic Acid Derivatives for Integrated Glucose Sensing and Insulin Delivery
Bibliographic record
Abstract
Abstract A closed‐loop “smart” insulin delivery system with the capability to mimic pancreatic cells will be highly desirable for diabetes treatment. This study reports a multiple stimuli‐responsive insulin delivery platform based on an explicit supramolecular strategy. Self‐assembled from a well‐designed amphiphilic host–guest complex formed by pillar[5]arene and a diphenylboronic acid derivative and loaded with insulin and glucose oxidase, the obtained insulin‐GOx‐loaded supramolecular vesicles can selectively recognize glucose, accompanied by the structure disruption and efficient release of the entrapped insulin triggered by the high glucose concentration as well as the in situ generated H2O2 and acid microenvironment during the GOx‐promoted specific oxidation of glucose into gluconic acid. Moreover, such a “smart” supramolecular theranostic nanoplatform is able to function as both a glucose sensor and a controlled insulin delivery actuator. In vivo experiments further demonstrate that this smart supramolecular nanocarrier shows fast response to hyperglycemic circumstances and can effectively regulate the glucose levels in a mouse model of type I diabetes.
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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".