3‐aminohydantoin derivate as a promising scaffold in dopaminergic neuroprotection and neurorescue in the in vivo and in vitro 6‐hydroxydopamine models of Parkinson's disease
Bibliographic record
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder characterized by a progressive loss of dopaminergic neurons in the substantia nigra, for which no disease-modifying treatments are available yet. Thus, developing new neuroprotective drugs with the potential to delay or stop the natural course of the disease is necessary. The aim of the present study was to evaluate the neuroprotective effects of a newly synthesized 3-aminohydantoin derivative named 3-amino-5-benzylimidazolidine-2,4-dione (PHAH). The possible neuroprotective and neurorescue effects of the synthesized compound were tested: (i) in N27 dopaminergic and BV-2 microglial cell lines treated with 6-hydroxydopamine (6-OHDA) and (ii) in the 6-OHDA rat model of PD. PHAH administration reduced proinflammatory markers, including nitric oxide synthase and interleukin-1β, in BV-2 cells activated by lipopolysaccharide. Although PHAH did not restore cell death induced by 6-OHDA, it was not cytotoxic for dopaminergic cells since cell viability, under the effect of the two concentrations, remained comparable to that of the control cells. Most interestingly, PHAH restored 6-OHDA-induced dopaminergic neurodegeneration in the substantia nigra and striatum and ameliorated 6-OHDA-induced oxidative stress in the rat brain. In summary, we have proven that in PD models, PHAH has neuroprotective effects in vivo and anti-inflammatory effects in vitro; however, these effects remain to be confirmed by carrying out certain specific behavioural tests as well as by exploring other neuroinflammatory markers. The present work also suggests that PHAH is a promising scaffold that can serve as the basis for the design and synthesis of other derivatives that can be potent antiparkinsonian agents.
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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".