Modulation of Blood–Brain Barrier Permeability in Mice Using Synthetic E-Cadherin Peptide
Bibliographic record
Abstract
The present work characterizes the effects of synthetic E-cadherin peptide (HAV) on blood-brain barrier (BBB) integrity using various techniques including magnetic resonance imaging (MRI) and near-infrared fluorescent imaging (NIRF). The permeability of small molecular weight permeability marker gadolinium diethylenetriaminepentaacetate (Gd-DTPA) contrast agent, the large molecular weight permeability marker, IRDye 800CW PEG, and the P-glycoprotein (P-gp) efflux transporter contrast agent, rhodamine 800 (R800), were examined in the presence and absence of HAV peptide. The results consistently demonstrated that systemic iv administration of HAV peptide resulted in a reversible disruption of BBB integrity and enhanced the accumulation of all the dyes examined. The magnitude of increase ranged from 2-fold to 5-fold depending on the size and the properties of the permeability markers. The time frame for BBB disruption with HAV peptide was rapid, occurring within 3-6 min following injection of the peptide. Furthermore, modulation of BBB permeability was reversible with the barrier integrity being restored within 60 min of the injection. The increased BBB permeability observed following HAV peptide administration was not attributable to changes in cerebral blood flow. These studies support the potential use of cadherin peptides to rapidly and reversibly modulate BBB permeability of a variety of therapeutic agents.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".