Pharmacology and Functional Properties of NTS2 Neurotensin Receptors in Cerebellar Granule Cells
Bibliographic record
Abstract
The binding and signaling properties of neuronal NTS2 neurotensin (NT) receptors were examined in cultured rat cerebellar granule cells. As shown by reverse transcription-PCR, receptor autoradiography, and confocal microscopic localization of fluorescent NT, these cells selectively express the NTS2 receptor subtype. Accordingly, a single apparent class of (125)I-NT-binding sites, with an affinity of 3.1 nm, was detected in cerebellar granule cell cultures. This binding was competed for with high affinity (IC(50) = 5.7 nm) by the NTS2 ligand levocabastine and with low affinity (IC(50) = 203 nm) by the NTS1 antagonist SR48692. Hypertonic acid stripping of surface-bound ligand and hyperosmolar sucrose treatment revealed that 64% of specifically bound (125)I-NT was internalized at equilibrium via a clathrin-dependent pathway. In cells loaded with the Ca(2+)-sensitive fluorescent dye Fluo4, SR48692, but neither NT nor levocabastine, triggered a marked increase in cytosolic [Ca(2+)](i). By contrast, both NT and levocabastine, but not SR48692, induced a sustained (>60 min) activation of the mitogen-activated protein kinases, p42/p44, indicating functional coupling of NTS2 receptors. Complementary experiments carried out on synaptosomes from adult rat cerebellum demonstrated the presence of presynaptic NTS2 receptors. However, in contrast to perikaryal NTS2 sites, these presynaptic receptors did not internalize in response to NT stimulation. Taken together, the present results demonstrate that NTS2 receptors are present both presynaptically and postsynaptically in central neurons and that NT and levocabastine act as agonists on these receptors.
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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".