The effect of striatal pre‐enkephalin overexpression in the basal ganglia of the 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine mouse model of Parkinson's disease
Bibliographic record
Abstract
The midbrain dopamine (DA) cell death underlying Parkinson's disease (PD) is associated with upregulation of pre-enkephalin (pENK) in striatopallidal neurons. Our previous results obtained with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) parkinsonian monkeys suggest that increased striatal expression of pENK mRNA is a compensatory mechanism to alleviate PD-related motor symptoms. In this study, we tested the hypothesis that increased pENK expression in the striatum protects against the neurotoxic insults of MPTP in mice. To this end, recombinant adeno-associated virus serotype 2 also containing green fluorescent protein was used to overexpress pENK prior to DA depletion. Our results showed that overexpression of pENK in the striatum of MPTP mice induced: (i) increased levels of the opioid peptide enkephalin (ENK) in the striatum; (ii) higher densities of ENK-positive fibers in both the globus pallidus (GP) and the substantia nigra; (iii) higher locomotor activity; and (iv) a higher density of striatal tyrosine hydroxylase-positive fibers in the striatum. In addition, striatal overexpression of pENK in MPTP -treated mice led to 52 and 43% higher DA concentrations and DA turnover, respectively, in the GP compared to sham-treated MPTP mice. These observations are in agreement with the idea that increased expression of pENK at an early stage of disease can improve PD symptoms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".