Differential expression of receptors mediating receptor-mediated transcytosis (RMT) in brain microvessels, brain parenchyma and peripheral tissues of the mouse and the human
Bibliographic record
Abstract
Abstract Receptor-mediated transcytosis (RMT) is a principal pathway for transport of macromolecules essential for brain function across the blood-brain barrier (BBB). Antibodies or peptide ligands which bind RMT receptors are often co-opted for brain delivery of biotherapeutics. Constitutively recycling transferrin receptor (TfR) is a prototype receptor utilized to shuttle therapeutic cargos across the BBB. Several other BBB-expressed receptors have been shown to mediate transcytosis of ligands including insulin receptor (INSR) and insulin-like growth factor-1 receptor (IGF1R), lipid transporters LRP1, LDLR, LRP8 and TMEM30A, solute carrier family transporter LAT1 (subunit CD98hc) and leptin receptor (LEPR). In this study, we analyzed expression patterns of genes encoding RMT receptors in isolated brain microvessels, brain parenchyma and peripheral organs of the mouse and the human using RNA-seq approach. IGF1R, INSR and LRP8 were highly enriched in mouse brain microvessels compared to peripheral tissues. In human brain microvessels only INSR was enriched compared to either the brain or the lung. The expression levels of SLC2A1, LRP1, IGF1R, LRP8 and TFRC were significantly higher in the mouse compared to human brain microvessels. The protein expression of these receptors analyzed by quantitative Western blot and immunofluorescent staining of the brain microvessels correlated with their transcript abundance. This study provides a molecular transcriptomics map of key RMT receptors in mouse and human brain microvessels and peripheral tissues, important to translational studies of biodistribution, efficacy and safety of antibodies developed against these receptors.
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How this classification was reachedexpand
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".