Transferrin Receptor-Mediated Uptake at the Blood–Brain Barrier Is Not Impaired by Alzheimer’s Disease Neuropathology
Bibliographic record
Abstract
The transferrin receptor (TfR) is highly expressed by brain capillary endothelial cells (BCECs) forming the blood–brain barrier (BBB) and is therefore considered as a potential target for brain drug delivery. Monoclonal antibodies binding to the TfR, such as clone Ri7, have been shown to internalize into BCECs in vivo. However, since Alzheimer’s disease (AD) is accompanied by a BBB dysfunction, it raises concerns about whether TfR-mediated transport becomes inefficient during the progression of the disease. Measurements of TfR levels using Western blot analysis in whole homogenates from human post-mortem parietal cortex and hippocampus did not reveal any significant difference between individuals with or without a neuropathological diagnosis of AD (respectively, n = 19 and 22 for the parietal cortex and n = 12 and 14 for hippocampus). Similarly, TfR concentrations in isolated human brain microvessels from parietal cortex were similar between controls and AD cases. TfR levels in isolated murine brain microvessels were not significantly different between groups of 12- and 18-month-old NonTg and 3xTg-AD mice, the latter modeling Aβ and τ neuropathologies. In situ brain perfusion assays were then conducted to measure the brain uptake and internalization of fluorolabeled Ri7 in BCECs upon binding. Consistently, TfR-mediated uptake in BCECs was similar between 3xTg-AD mice and nontransgenic controls (∼0.3 μL·g – 1 ·s –1 ) at 12, 18, and 22 months of age. Fluorescence microscopy analysis following intravenous administration of fluorolabeled Ri7 highlighted that the signal from the antibody was widely distributed throughout the cerebral vasculature but not in neurons or astrocytes. Overall, our data suggest that both TfR protein levels and TfR-dependent internalization mechanisms are preserved in the presence of Aβ and τ neuropathologies, supporting the potential of TfR as a vector target for drug delivery into BCECs in AD.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".