Bibliographic record
Abstract
The study of disease in model organisms is a fundamental and important stepping-stone in understanding and uncovering the mechanisms behind disease pathology in humans. The purpose of this work was to identify potential targets for the treatment and prevention of Parkinson disease using Drosophila melanogaster. Commonly known as the fruit fly, D. melanogaster is one of the important model organisms used extensively in biological research. Moreover, it has conserved developmental processes and mechanisms shared with human neurodegenerative disorders. Parkinson disease (PD) is a progressive neurodegenerative disorder characterized by death of dopamine producing cells of the substantia nigra affects about 1% of people over 60 years old worldwide. In mammals, Fbxo9 is a substrate recognition component of the SCF (SKP1-cullin-Fbox)-type E3 ubiquitin ligase complex. Some targets of Fbxo9, including an extensive array of proteins, are degraded via the ubiquitin-proteasome system. In this study, a potential D. melanogaster homologue of Fbxo9, CG5961, was identified. The Fbxo9 homologue in D. melanogaster has been conserved through evolution and retains many of the functional domains. The main goal of this project was to determine if Fbxo9 can be implicated in modeling PD in D. melanogaster. To investigate its role in neuronal survival, I over-expressed and down-regulated Fbxo9 in neuron-rich eye and dopaminergic neurons. Through assessments of eye morphology, climbing ability and ageing analysis, it was found that loss-of-function of Fbxo9 causes a PD like symptom. I expect that the knowledge obtained by determining the pathways involved in PD in D. melanogaster will help uncover potential new therapeutic approaches for research in human as well as other genes in both humans and flies.
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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 | 0.001 |
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".