Trafficking through the blood–brain barrier is directed by core and outer surface components of layer‐by‐layer nanoparticles
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Drug-carrying nanoparticles are a promising strategy to deliver therapeutics into the brain, but their translation requires better characterization of interactions between nanomaterials and endothelial cells of the blood-brain barrier (BBB). Here, we use a library of 18 layer-by-layer electrostatically assembled nanoparticles (NPs) to independently assess the impact of NP core and surface materials on in vitro uptake, transport, and intracellular trafficking in brain endothelial cells. We demonstrate that NP core stiffness determines the magnitude of transport, while surface chemistry directs intracellular trafficking. Finally, we demonstrate that these factors similarly dictate in vivo BBB transport using intravital imaging through cranial windows in mice. We identify that hyaluronic acid surface chemistry increases transport across the BBB in vivo, and flow conditions are necessary to replicate this finding in vitro. Taken together, these findings highlight the importance of assay geometry, cell biology, and fluid flow in developing nanocarriers for delivery to the brain.
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.
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 | 0.000 | 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 it