Recent developments on PET radiotracers for TSPO and their applications in neuroimaging
Bibliographic record
Abstract
The 18 kDa translocator protein (TSPO), previously known as the peripheral benzodiazepine receptor, is predominately localized to the outer mitochondrial membrane in steroidogenic cells. Brain TSPO expression is relatively low under physiological conditions, but is upregulated in response to glial cell activation. As the primary index of neuroinflammation, TSPO is implicated in the pathogenesis and progression of numerous neuropsychiatric disorders and neurodegenerative diseases, including Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), multiple sclerosis (MS), major depressive disorder (MDD) and obsessive compulsive disorder (OCD). In this context, numerous TSPO-targeted positron emission tomography (PET) tracers have been developed. Among them, several radioligands have advanced to clinical research studies. In this review, we will overview the recent development of TSPO PET tracers, focusing on the radioligand design, radioisotope labeling, pharmacokinetics, and PET imaging evaluation. Additionally, we will consider current limitations, as well as translational potential for future application of TSPO radiopharmaceuticals. This review aims to not only present the challenges in current TSPO PET imaging, but to also provide a new perspective on TSPO targeted PET tracer discovery efforts. Addressing these challenges will facilitate the translation of TSPO in clinical studies of neuroinflammation associated with central nervous system diseases.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".