Identification of Leptin Receptor–Expressing Cells in the Nodose Ganglion of Male Mice
Bibliographic record
Abstract
Leptin has been proposed to modulate viscerosensory information directly at the level of vagal afferents. In support of this view, broad expression for the leptin receptor (Lepr) has previously been reported in vagal afferents. However, the exact identity and distribution of leptin-sensitive vagal afferents has not been elucidated. Using quantitative PCR, we found that the whole mouse nodose ganglion was predominantly enriched in the short form of Lepr, rather than its long form. Consistent with this observation, the acute administration of leptin did not stimulate JAK-STAT signaling in the nodose ganglion. Using chromogenic in situ hybridization in wild-type mice and several reporter mouse models, we demonstrated that Lepr mRNA was restricted to nonneuronal cells in the epineurium and parenchyma of the nodose ganglion and a subset of vagal afferents, which accounted for only 3% of all neuronal profiles. Double labeling studies further established that Lepr-expressing vagal afferents were Nav1.8-negative fibers that did not supply the peritoneal cavity. Finally, double chromogenic in situ hybridization revealed that many Lepr-expressing neurons coexpressed the angiotensin 1a receptor (At1ar), which is a gene expressed in baroreceptors. Taken together, our data challenge the commonly held view that Lepr is broadly expressed in vagal afferents. Instead, our data suggest that leptin may exert a previously unrecognized role, mainly via its short form, as a direct modulator of a very small group of At1ar-positive vagal fibers.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".