The <i>Drosophila</i> wing is a high-throughput and versatile screening tool for Tau-mediated disease mechanisms and drug discovery
Bibliographic record
Abstract
Abstract Tau protein contributes to microtubule stability, which is disrupted in Alzheimer’s disease and other Tauopathies. In these diseases, Tau molecules become hyperphosphorylated, misfolded and aggregated, propagating pathology across the brain. Studies dissecting disease mechanisms or screening disease-modifying therapies rely on animal models that unveil pathogenic events in vivo but also take several weeks or months to complete. Here we describe a versatile experimental paradigm that yields results in days and yet offers all the advantages of a genetically tractable in vivo system: the Drosophila wing disc. Mimicking neurotoxicity, human Tau expression causes cell death in the wing disc leading to quantifiable phenotypes in the adult wing. The neuroprotective peptide NAP ameliorates Tau toxicity in this system, validating it as a cost-effective drug screening tool. Phenocopying adult neurons, Tau toxicity in the wing disc is exacerbated by simulating hyper-phosphorylation and prevented by suppressing aggregation. Additionally, we show that the wing disc can dissect disease mechanisms that underpin clinically relevant Tau variants. Thus, the wing disc offers an in vivo experimental paradigm for fast and efficient exploration of disease mechanism and screening.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.007 | 0.005 |
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".