Distribution of NTS3 receptor/sortilin mRNA and protein in the rat central nervous system
Bibliographic record
Abstract
The neurotensin (NT) receptor, NTS3, originally identified as the intracellular sorting protein sortilin, is a member of a recently discovered family of receptors characterized by a single transmembrane domain. The present study provides the first comprehensive description of the distribution of NTS3/sortilin mRNA and protein in adult rat brain using in situ hybridization and immunocytochemistry. Both NTS3/sortilin mRNA and immunoreactivity displayed a widespread distribution throughout the brain. High levels of NTS3/sortilin expression and immunoreactivity were found in neuronal cell bodies and dendrites of allocortical areas such as the piriform cortex and hippocampus. Regions expressing both high levels of NTS3/sortilin mRNA and protein also included several neocortical areas, the islands of Calleja, medial and lateral septal nuclei, amygdaloid nuclei, thalamic nuclei, the supraoptic nucleus, the substantia nigra, and the Purkinje cell layer of the cerebellar cortex. In the brainstem, all cranial nerve motor nuclei were strongly labeled. NTS3/sortilin mRNA and immunoreactivity were also detected over oligodendrocytes in major fiber tracts. Subcellularly, NTS3/sortilin was predominantly concentrated over intracytoplasmic membrane-bound organelles. Many of the areas exhibiting high levels of NTS3/sortilin (e.g., olfactory cortex, medial septum, and periaqueductal gray) have been documented to contain high concentrations of NT nerve cell bodies and axons, supporting the concept that NTS3/sortilin may play a role in NT sorting and/or signaling. Other areas (e.g., hippocampal CA fields, cerebellar cortex, and cranial nerve motor nuclei), however, are NT-negative, suggesting that NTS3/sortilin also exerts functions unrelated to NT signaling.
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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 | 0.001 | 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".