Brain Delivery of IGF1R5, a Single-Domain Antibody Targeting Insulin-like Growth Factor-1 Receptor
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Bibliographic record
Abstract
The ability of drugs and therapeutic antibodies to reach central nervous system (CNS) targets is greatly diminished by the blood-brain barrier (BBB). Receptor-mediated transcytosis (RMT), which is responsible for the transport of natural protein ligands across the BBB, was identified as a way to increase drug delivery to the brain. In this study, we characterized IGF1R5, which is a single-domain antibody (sdAb) that binds to insulin-like growth factor-1 receptor (IGF1R) at the BBB, as a ligand that triggers RMT and could deliver cargo molecules that otherwise do not cross the BBB. Surface plasmon resonance binding analyses demonstrated the species cross-reactivity of IGF1R5 toward IGF1R from multiple species. To overcome the short serum half-life of sdAbs, we fused IGF1R5 to the human (hFc) or mouse Fc domain (mFc). IGF1R5 in both N- and C-terminal mFc fusion showed enhanced transmigration across a rat BBB model (SV-ARBEC) in vitro. Increased levels of hFc-IGF1R5 in the cerebrospinal fluid and vessel-depleted brain parenchyma fractions further confirmed the ability of IGF1R5 to cross the BBB in vivo. We next tested whether this carrier was able to ferry a pharmacologically active payload across the BBB by measuring the hypothermic and analgesic properties of neurotensin and galanin, respectively. The fusion of IGF1R5-hFc to neurotensin induced a dose-dependent reduction in the core temperature. The reversal of hyperalgesia by galanin that was chemically linked to IGF1R5-mFc was demonstrated using the Hargreaves model of inflammatory pain. Taken together, our results provided a proof of concept that appropriate antibodies, such as IGF1R5 against IGF1R, are suitable as RMT carriers for the delivery of therapeutic cargos for CNS applications.
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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 | 0.001 | 0.001 |
| 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 it