The blood–brain barrier transmigrating single domain antibody: mechanisms of transport and antigenic epitopes in human brain endothelial cells
Bibliographic record
Abstract
Antibodies against receptors that undergo transcytosis across the blood-brain barrier (BBB) have been used as vectors to target drugs or therapeutic peptides into the brain. We have recently discovered a novel single domain antibody, FC5, which transmigrates across human cerebral endothelial cells in vitro and the BBB in vivo. The purpose of this study was to characterize mechanisms of FC5 endocytosis and transcytosis across the BBB and its putative receptor on human brain endothelial cells. The transport of FC5 across human brain endothelial cells was polarized, charge independent and temperature dependent, suggesting a receptor-mediated process. FC5 taken up by human brain endothelial cells co-localized with clathrin but not with caveolin-1 by immunochemistry and was detected in clathrin-enriched subcellular fractions by western blot. The transendothelial migration of FC5 was reduced by inhibitors of clathrin-mediated endocytosis, K+ depletion and chlorpromazine, but was insensitive to caveolae inhibitors, filipin, nystatin or methyl-beta-cyclodextrin. Following internalization, FC5 was targeted to early endosomes, bypassed late endosomes/lysosomes and remained intact after transcytosis. The transcytosis process was inhibited by agents that affect actin cytoskeleton or intracellular signaling through PI3-kinase. Pretreatment of human brain endothelial cells with wheatgerm agglutinin, sialic acid, alpha(2,3)-neuraminidase or Maackia amurensis agglutinin that recognizes alpha(2,3)-, but not with Sambucus nigra agglutinin that recognizes alpha(2,6) sialylgalactosyl residues, significantly reduced FC5 transcytosis. FC5 failed to recognize brain endothelial cells-derived lipids, suggesting that it binds luminal alpha(2,3)-sialoglycoprotein receptor which triggers clathrin-mediated endocytosis. This putative receptor may be a new target for developing brain-targeting drug delivery vectors.
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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".