Age related changes in the dopamine system of the Sprague-Dawley rat measured via positron emission tomography
Bibliographic record
Abstract
249 Objectives Positron emission tomography (PET) allows the performance of longitudinal in-vivo studies. In order to correctly interpret longitudinal results, it is important to understand aging effects on tracers’ binding parameters, such as tissue input binding potential BPND. In this retrospective study we evaluate the effect of age on BPND values for three tracers related to the dopaminergic (DA) system in Sprague-Dawley rats. Methods DA neuronal terminal integrity was monitored using (+)-11C-dihydrotetrabenazine (DTBZ), DA transporter density using 11C-methylphenidate (MP), and binding to D2/3-DA receptors using 11C-raclopride (RAC). Cross-sectional data were compiled from healthy rats, and from the contralateral striatum of unilaterally 6-OHDA lesioned rats (imaged a minimum of 1 month post-lesion), at 3 to 24 months of age. Data were collected on the Siemens microPET Focus120. BPND values were extracted from the reconstructed images using regions of interest placed on the striatum and cerebellum (reference region) using the Logan graphical method. Results No correlation was found between age and DTBZ BPND (average BPND 4.0±0.4, n=58). A significant negative correlation was found between age and BPND for both the MP (p=0.017, linear relationship, n=36) and RAC (p Conclusions PET imaging in the rat brain is sensitive to age related changes in the DA transporter and D2/3-DA receptors, therefore longitudinal imaging studies with RAC and MP should be designed to control for age related changes. Conversely, longitudinal studies carried out with DTBZ may be simplified due to the lack of an age effect. Research Support Natural Sciences and Engineering Research Council, Canadian Institutes of Health Research, Michael Smith Foundation for Health Research
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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".