Identifying genes that interact with <i>Drosophila</i> presenilin and amyloid precursor protein
Bibliographic record
Abstract
The gamma-secretase complex is involved in cleaving transmembrane proteins such as Notch and one of the genes targeted in Alzheimer's disease known as amyloid precursor protein (APP). Presenilins function within the catalytic core of gamma-secretase, and mutated forms of presenilins were identified as causative factors in familial Alzheimer's disease. Recent studies show that in addition to Notch and APP, numerous signal transduction pathways are modulated by presenilins, including intracellular calcium signaling. Thus, presenilins appear to have diverse roles. To further understand presenilin function, we searched for Presenilin-interacting genes in Drosophila by performing a genetic modifier screen for enhancers and suppressors of Presenilin-dependent Notch-related phenotypes. We identified 177 modifiers, including known members of the Notch pathway and genes involved in intracellular calcium homeostasis. We further demonstrate that 53 of these modifiers genetically interacted with APP. Characterization of these genes may provide valuable insights into Presenilin function in development and disease.
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 | 0.000 | 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) | 0.002 | 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".