Peripheral Neuroprotective and Immunomodulatory Effects of 5α-Reductase Inhibitors in Parkinson’s Disease Models
Bibliographic record
Abstract
Gastrointestinal disorders in Parkinson’s disease (PD) have been associated with neuronal alteration in the plexus of the gut. We previously demonstrated the immunomodulatory effect of female hormones to treat enteric neurodegeneration in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) mouse model of PD. This study made the hypothesis of obtaining similar neuroprotection as with hormone treatments by affecting steroidogenesis with two 5α-reductase inhibitors, finasteride and dutasteride. These drugs are approved to treat benign prostatic hyperplasia and alopecia and display mitochondrial effects. In MPTP-treated mice, the dopaminergic and vasoactive intestinal peptide (VIP) neurons alteration was prevented by finasteride and dutasteride, while the increase in proinflammatory macrophages density was inhibited by dutasteride treatment but not finasteride. NF-κB response, oxidative stress, and nitric oxide and proinflammatory cytokines production in vitro were only prevented by dutasteride. In addition, mitochondrial production of free radicals, membrane depolarization, decreased basal respiration, and ATP production were inhibited by dutasteride, while finasteride had no effect. In conclusion, the present results indicate that dutasteride treatment prevents enteric neuronal damages in the MPTP mouse model, at least in part through anti-inflammatory and mitochondrial effects. This suggests that drug repurposing of dutasteride might be a promising avenue to treat enteric neuroinflammation in early PD.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".