Sustained Release of Dexamethasone from Sulfobutyl Ether β‐cyclodextrin Modified Self‐Assembling Peptide Nanoscaffolds in a Perinatal Rat Model of Hypoxia–Ischemia
Bibliographic record
Abstract
Abstract Inflammation plays a critical role in the development of hypoxia–ischemia (HI) induced newborn brain damage. A localized, sustained delivery of dexamethasone (Dex) through an intracerebral injection could reduce the inflammatory response in the injured perinatal brain while avoiding unnecessary side effects. Herein, investigated using anionic sulfobutyl ether β‐cyclodextrin (SBE‐β‐CD) to load Dex in the (RADA) 4 nanofiber networks as a means of reducing the inflammatory response to HI injury is investigated. The ionic interaction between SBE‐β‐CD and (RADA) 4 dramatically affects nanofiber formation and the stability of the nanoscaffold is highly dependent on the SBE‐β‐CD/(RADA) 4 ratio. It is observed that the Dex release rate is affected by the concentration of SBE‐β‐CD and (RADA) 4 peptide. A higher concentration of SBE‐β‐CD or (RADA) 4 results in a higher drug encapsulation efficiency and slower release rate of Dex. This phenomenon may be related to the structure of fiber bundles. Animal studies show that nanoscaffold loaded with Dex inhibits both microglia activation and glial scar formation compared to controls (Dex alone or nanoscaffold alone) within 2 days of injury. It is thought that this is a step toward building a multifaceted nanoscaffold that can be used to treat HI events in perinates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 teacher head, 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".