Biomimetic elasticity compressed assembly controls rapid intracerebral drug release to reverse microglial dysfunction
Bibliographic record
Abstract
The regulation of microglial dysfunction has become increasingly prominent in treatment of Alzheimer’s disease (AD). Herein, we develop a scalable polymer-involved biomimetic assembly that responds to intracerebral reactive oxygen species (ROS) for elastic spreading and concentration-dependent drug therapy. Structurally, a polymer of thermally sensitive deformation is selected for hydrophobic loading of curcumin (Cur) and coordinative grafting onto ultrasmall ceria (CeO 2 ) by elastic compression at transition temperature, which is further sealed by self-polymerized dopamine with apolipoprotein decoration to improve intracerebral shuttling. When triggered by ROS in the lesions, burst exposure of Cur and polymer-linked CeO 2 (PCeO 2 ) is achieved. The concentrated Cur switches amyloid-β (Aβ)–activated microglia into normal for mobilizing phagocytosis, and CeO 2 has sustainable antioxidant capacity to prevent microglial mitochondrial damage after phagocytosis of PCeO 2 -captured Aβ. After administration, our findings reveal microglia-mediated Aβ clearance, neuroprotection, and ROS elimination in AD mice. Collectively, this biomimetic assembly provides a promising approach in AD treatments.
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".