Ghrelin Promotes and Protects Nigrostriatal Dopamine Function via a UCP2-Dependent Mitochondrial Mechanism
Bibliographic record
Abstract
Ghrelin targets the hypothalamus to regulate food intake and adiposity. Endogenous ghrelin receptors [growth hormone secretagogue receptor (GHSR)] are also present in extrahypothalamic sites where they promote circuit activity associated with learning and memory, and reward seeking behavior. Here, we show that the substantia nigra pars compacta (SNpc), a brain region where dopamine (DA) cell degeneration leads to Parkinson's disease (PD), expresses GHSR. Ghrelin binds to SNpc cells, electrically activates SNpc DA neurons, increases tyrosine hydroxylase mRNA and increases DA concentration in the dorsal striatum. Exogenous ghrelin administration decreased SNpc DA cell loss and restricted striatal dopamine loss after 1-methyl-4-phenyl-1,2,5,6 tetrahydropyridine (MPTP) treatment. Genetic ablation of ghrelin or the ghrelin receptor (GHSR) increased SNpc DA cell loss and lowered striatal dopamine levels after MPTP treatment, an effect that was reversed by selective reactivation of GHSR in catecholaminergic neurons. Ghrelin-induced neuroprotection was dependent on the mitochondrial redox state via uncoupling protein 2 (UCP2)-dependent alterations in mitochondrial respiration, reactive oxygen species production, and biogenesis. Together, our data reveal that peripheral ghrelin plays an important role in the maintenance and protection of normal nigrostriatal dopamine function by activating UCP2-dependent mitochondrial mechanisms. These studies support ghrelin as a novel therapeutic strategy to combat neurodegeneration, loss of appetite and body weight associated with PD. Finally, we discuss the potential implications of these studies on the link between obesity and neurodegeneration.
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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".