Correlation of Amyloid PET Ligand Florbetapir F 18 Binding With Aβ Aggregation and Neuritic Plaque Deposition in Postmortem Brain Tissue
Bibliographic record
Abstract
BACKGROUND: Florbetapir F 18 (F-AV-45) is a positron emission tomography imaging ligand for the detection of amyloid aggregation associated with Alzheimer disease. Earlier data showed that florbetapir F 18 binds with high affinity to β-amyloid (Aβ) plaques in human brain homogenates (Kd=3.7 nM) and has favorable imaging pharmacokinetic properties, including rapid brain penetration and washout. This study used human autopsy brain tissue to evaluate the correlation between in vitro florbetapir F 18 binding and Aβ density measured by established neuropathologic methods. METHODS: The localization and density of florbetapir F 18 binding in frozen and formalin-fixed paraffin-embedded sections of postmortem brain tissue from 40 patients with a varying degree of neurodegenerative pathology was assessed by standard florbetapir F 18 autoradiography and correlated with the localization and density of Aβ identified by silver staining, thioflavin S staining, and immunohistochemistry. RESULTS: There were strong quantitative correlations between florbetapir F 18 tissue binding and both Aβ plaques identified by light microscopy (Silver staining and thioflavin S fluorescence) and by immunohistochemical measurements of Aβ using 3 antibodies recognizing different epitopes of the Aβ peptide. Florbetapir F 18 did not bind to neurofibrillary tangles. CONCLUSIONS: Florbetapir F 18 selectively binds Aβ in human brain tissue. The binding intensity was quantitatively correlated with the density of Aβ plaques identified by standard neuropathologic techniques and correlated with the density of Aβ measured by immunohistochemistry. As Aβ plaques are a defining neuropathologic feature for Alzheimer disease, these results support the use of florbetapir F 18 as an amyloid positron emission tomography ligand to identify the presence of Alzheimer disease pathology in patients with signs and symptoms of progressive late-life cognitive impairment.
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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 | 0.000 | 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) | 0.000 | 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".