Brain Bioavailability of Human Intravenous Immunoglobulin and its Transport through the Murine Blood–Brain Barrier
Bibliographic record
Abstract
Intravenous immunoglobulin (IVIg) is currently evaluated in clinical trials for the treatment of various disorders of the central nervous system. To assess its capacity to reach central therapeutic targets, the brain bioavailability of IVIg must be determined. We thus quantified the passage of IVIg through the blood-brain barrier (BBB) of C57Bl/6 mice using complementary quantitative and qualitative methodologies. As determined by enzyme-linked immunosorbent assay, a small proportion of systemically injected IVIg was detected in the brain of mice (0.009±0.001% of injected dose in the cortex) whereas immunostaining revealed localization mainly within microvessels and less frequently in neurons. Pharmacokinetic analyses evidenced a low elimination rate constant (0.0053 per hour) in the cortex, consistent with accumulation within cerebral tissue. In situ cerebral perfusion experiments revealed that a fraction of IVIg crossed the BBB without causing leakage. A dose-dependent decrease of brain uptake was consistent with a saturable blood-to-brain transport mechanism. Finally, brain uptake of IVIg after a subchronic treatment was similar in the 3xTg-AD mouse model of Alzheimer disease compared with nontransgenic controls. In summary, our results provide evidence of BBB passage and bioavailability of IVIg into the brain in the absence of BBB leakage and in sufficient concentration to interact with the therapeutic targets.
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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".