The SM Protein Car/Vps33A Regulates SNARE-mediated Trafficking to Lysosomes and Lysosome-related Organelles
Bibliographic record
Abstract
The SM proteins Vps33A and Vps33B are believed to act in membrane fusions in endosomal pathways, but their specific roles are controversial. In Drosophila, Vps33A is the product of the carnation (car) gene. We generated a null allele of car to test its requirement for trafficking to different organelles. Complete loss of car function is lethal during larval development. Eye-specific loss of Car causes late, light-independent degeneration of photoreceptor cells. Earlier in these cells, two distinct phenotypes were detected. In young adults, autophagosomes amassed indicating that their fusion with lysosomes requires Car. In eye discs, endocytosed receptors and ligands accumulate in Rab7-positive prelysosomal compartments. The requirement of Car for late endosome-to-lysosome fusion in imaginal discs is specific as early endosomes are unaffected. Furthermore, lysosomal delivery is not restored by expression of dVps33B. This specificity reflects the distinct pattern of binding to different Syntaxins in vitro: dVps33B predominantly binds the early endosomal Avl and Car to dSyntaxin16. Consistent with a role in Car-mediated fusion, dSyntaxin16 is not restricted to Golgi membranes but also present on lysosomes.
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) | 0.001 | 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".