Nucleus tractus solitarii (NTS) expression of GAD67 and neurokinin receptors (NK1‐R) in transgenic GAD67‐eGFP mice
Bibliographic record
Abstract
Glutamic acid decarboxylase (GAD67) and NK1‐R are important components of autonomic circuits controlling cardiorespiratory function. The purpose of this study was to determine the distribution of GAD67 neurons in the NTS using transgenic mice expressing enhanced green fluorescent protein (eGFP) controlled by the GAD67 promoter. Adult mice (n=2) were anesthetized and transcardially‐perfused. Cryostat sections (30μm) containing the NTS were stained with a polyclonal antibody against NK1‐Rs and visualized with Cy3 secondary antibody. GAD67 and NK1‐R expressing cells were counted and sections reconstructed using Neurolucida software. A total of 15,404 medullary neurons were counted. Of the total cells, 4,767±756 were GAD67 cells and 2,830±941 were NK1‐R positive, while 106±31 were double‐labeled. Within the NTS, 822±152 were GAD67 positive, 335±83 expressed NK1‐Rs and only 7±4 were double‐labeled. At caudal levels of the NTS (Bregma −14.3 to −13.1), GAD67 cells were predominantly clustered around the solitary tract, while at more rostral levels (Bregma −13.24) they were localized to the medial and ventrolateral subdivisions. GAD67 labeling in mice was different than the pattern recently reported in rats (Stornetta & Guyenet, 1999; Fong et al., 2005). This may suggest a difference in inhibitory modulation of afferent signals by the NTS. Supported by NIH HL059167 (JTP).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".