Transport characteristics of a novel peptide platform for CNS therapeutics
Bibliographic record
Abstract
New and effective therapeutics that cross the blood-brain barrier (BBB) are critically needed for treatment of many brain diseases. We characterize here a novel drug development platform that is broadly applicable for the development of new therapeutics with increased brain penetration. The platform is based on the Angiopep-2 peptide, a sequence derived from ligands that bind to low-density lipoprotein receptor-related protein-1 (LRP-1), a receptor expressed on the BBB. Fluorescent imaging studies of a Cy5.5Angiopep-2 conjugate and immunohistochemical studies of injected Angiopep-2 in mice demonstrated efficient transport across the BBB into brain parenchyma and subsequent co-localization with the neuronal nuclei-selective marker NeuN and the glial marker glial fibrillary acidic protein (GFAP). Uptake of [(¹²⁵I]-Angiopep-2 into brain endothelial cells occurred by a saturable mechanism involving LRP-1. The primary sequence and charge of Angiopep-2 were crucial for its passage across the BBB. Overall, the results demonstrate the significant potential of this platform for the development of novel neurotherapeutics.
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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".