Inhibition of <i>foxo</i> and <i>minibrain</i> in Dopaminergic Neurons Can Model Aspects of Parkinson Disease in <i>Drosophila melanogaster</i>
Bibliographic record
Abstract
Symptoms of Parkinson Disease (PD), the second most common neurodegenerative disease, emerge due to degeneration of dopaminergic neurons. Recently, a genome wide study revealed a role for a foxo transcription factor in PD. In the model organism Drosophila melanogaster, we have attempted 1) to inhibit the sole Drosophila homologue of foxo through the directed expression of a stable inducible RNAi transgene and 2) to indirectly increase foxo transcription activity through the inhibition of the kinase minibrain (mnb), a foxo transcriptional inhibitor. To evaluate the lifetime consequences upon the flies, longevity assays and locomotion over time assays were conducted. The inhibition of foxo by foxo-RNAi decreases life span significantly when expressed under the control of Tyrosine Hydroxylase-Gal4 (TH-Gal4). The targeted expression of mnb-RNAi, in the dopaminergic neurons, with an expected loss of suppression of foxo transcriptional activity, results in a significant loss of climbing ability. Thus alteration of foxo activity, both by RNA-inhibition and by down-regulation of an inhibitor of foxo, minibrain, produces novel Drosophila models of Parkinson Disease.
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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) | 0.001 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".