Quantification of [<sup>11</sup>C]ABP688 Binding to mGluR5 in Human Brain using Cerebellum as Reference Region: Biological Interpretation and Limitations
Bibliographic record
Abstract
Introduction: In vitro data from primates provide conflicting evidence about the suitability of the cerebellum as a reference region for quantifying type 5 metabotropic glutamate receptor (mGluR5) binding parameters with positron emission tomography (PET). Methods: We first measured mGluR5 density in postmortem human cerebellum using [3H]ABP688 autoradiography (n=5) and immunohistochemistry (n=6). Next, in vivo experiments were conducted in healthy volunteers (n=6) using a high-resolution PET scanner (HRRT) to compare [11C]ABP688 binding potential (BPND) values obtained with reference tissue methods and the two-tissue compartment model vs. metabolite-corrected arterial input function. Results: The postmortem data showed that, relative to the hippocampus, the cerebellum had 35% less mGluR5 immunoreactivity and 94% fewer [3H]ABP688 binding sites. In vivo brain regional [11C]ABP688 BPND values using the cerebellum as a reference region were highly correlated with BPND values and distribution volumes derived by arterial input methods (R2 > 0.9). Conclusion: The scarce availability of cerebellar allosteric binding sites at autoradiography, compared to immunohistochemistry results, might reflect the presence of distinct mGluR5 isoforms or conformational state. Together with our PET data, these data support the proposition that [11C]ABP688 BPND using the cerebellum as a reference region provides accurate quantification of mGluR5 allosteric binding in vivo. Studies relying on this method could, therefore, be used in clinical populations, providing that stronger initial assumptions are met.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".