Beyond PIB: the next generation of amyloid‐imaging ligands
Bibliographic record
Abstract
Pittsburgh Compound B (PIB) is the commonly used name for N-methyl-[ 11 C]2-(4′-methylaminophenyl)-6hydroxybenzothiazole (6-OH-BTA-1), an amyloidimaging ligand that is widely used in the US, Europe, Australia, and Japan.Before Klunk and Mathis 1 developed [ 11 C]-PIB successfully at Pittsburgh University, a number of research groups had worked to find appropriate compounds as amyloid-imaging ligands in vivo.Attempts to find suitable compounds for positron emission tomography (PET) or single photon emission computed tomography (SPECT) studies started in the early 1990s.Radiolabelled monoclonal antibodies targeted to b-amyloid (Ab) peptide were exploited as amyloid-imaging agents in vivo. 2 However, the primary limitation of this approach is that large molecular weight biomolecules cannot efficiently cross the blood-brain barrier (BBB) and bind to amyloid plaques contained within the parenchyma of the Alzheimer's disease (AD) brain.Mathis et al. 1 at Pittsburgh University initially focused their attention on Congo red, an amyloid-staining agent widely used in histological studies of post-mortem AD brain tissue sections.Congo red is a large molecule, a negatively charged sulfonate under physiological conditions, and is too hydrophilic to penetrate the BBB.Mathis et al. 1 then investigated the binding properties of Chrysamine G, a more lipophilic and potent Ab ligand.However, efforts over more than 10 years to develop radiolabelled analogs of Congo red and Chrysamine G as amyloid-imaging agents for PET and SPECT were hampered by the relatively poor brain penetration of these compounds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".