Imaging <i>in Vivo</i> Glutamate Fluctuations with [ <sup>11</sup> C]ABP688: A GLT-1 Challenge with Ceftriaxone
Bibliographic record
Abstract
Molecular imaging offers unprecedented opportunities for investigating dynamic changes underlying neuropsychiatric conditions. Here, we evaluated whether [(11)C]ABP688, a positron emission tomography (PET) ligand that binds to the allosteric site of the metabotropic glutamate receptor type 5 (mGluR5), is sensitive to glutamate fluctuations after a pharmacological challenge. For this, we used ceftriaxone (CEF) administration in rats, an activator of the GLT-1 transporter (EAAT2), which is known to decrease extracellular levels of glutamate. MicroPET [(11)C]ABP688 dynamic acquisitions were conducted in rats after a venous injection of either saline (baseline) or CEF 200 mg/kg (challenge). Binding potentials (BP(ND)) were obtained using the simplified reference tissue method. Between-condition statistical parametric maps indicating brain regions showing the highest CEF effects guided placement of microdialysis probes for subsequent assessment of extracellular levels of glutamate. The CEF administration increased [(11)C]ABP688 BP(ND) in the thalamic ventral anterior (VA) nucleus bilaterally. Subsequent microdialysis assessment revealed declines in extracellular glutamate concentrations in the VA. The present results support the concept that availability of mGluR5 allosteric binding sites is sensitive to extracellular concentrations of glutamate. This interesting property of mGluR5 allosteric binding sites has potential applications for assessing the role of glutamate in the pathogenesis of neuropsychiatric conditions.
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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 | 0.001 |
| 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".