Impact of Drug Size on Brain Tumor and Brain Parenchyma Delivery after a Blood–Brain Barrier Disruption
Bibliographic record
Abstract
Drug delivery to the brain is influenced by the blood-brain barrier (BBB) and blood-tumor barrier (BTB) to an extent that is still debated in neuro-oncology. In this paper, we studied the delivery across the BTB and the BBB of compounds with different molecular sizes in normal and glioma-bearing rats. Studies were performed at baseline as well as after an osmotic BBB disruption (BBBD) using dynamic contrast-enhanced magnetic resonance imaging and two T₁ contrast agents (CAs), Magnevist (743 Da) and Gadomer (17,000 Da). More specifically, we determined the time window for the BBB permeability, the distribution and we calculated the brain exposure to the CAs. A different pattern of accumulation and distribution at baseline as well as after a BBBD procedure was observed for both agents, which is consistent with their different molecular size and weight. Baseline tumor exposure was threefold higher for Magnevist compared with Gadomer, whereas postBBBD tumor exposure was twofold higher for Magnevist. Our study clearly showed that the time window and the extent of delivery across the intact, as well as permeabilized BTB and BBB are influenced by drug size.
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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".