Effects of aging on 5‐HT<sub>2A</sub>R binding: a HRRT PET study with and without partial volume corrections
Bibliographic record
Abstract
OBJECTIVE: We explored whether prior findings of reduction in serotonin 2A receptor (5-HT(2A) R) binding with age could be replicated and whether high resolution research tomography (HRRT) for positron emission tomography could compensate for partial volume effects in the presence of age-related brain atrophy, which has been a traditional concern for radioligand PET studies in the elderly. METHODS: We derived 5-HT(2A) R nondisplaceable binding potentials (BP(ND) ) in frontal, temporal, anterior-cingulate, insula, caudate and putamen volumes of interest (VOIs) for 28 healthy subjects (mean ± SD age = 43.9 ± 17.0 years, range: 19-78 years) using HRRT. Partial volume correction (PVC) was performed in the VOI analysis. RESULTS: The 5-HT(2A) R BP(ND) s decreased with age, a relationship best described by an exponential-decay regression. The BP(ND) s were found to be consistent before and after PVC, with an intra-class correlation coefficient of 0.84 and 95% confidence interval = 0.78-0.88. CONCLUSIONS: These new findings update current knowledge, in that the aging process is not always uniform across the life span and suggest that PVC may not be necessary with HRRT in healthy subjects.
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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 | 0.001 | 0.001 |
| 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".