Bibliographic record
Abstract
Rab GTPases are critical regulators of membrane trafficking and not surprisingly defects in Rabs contribute to various human diseases. For example, Rab13 is associated with several phenotypes associated with cancer, but the regulation of Rab13 in membrane trafficking is poorly understood. The general objective of this doctoral research was to study the function and regulation of Rab13 in endosomal trafficking. Rabs cycle between an active GTP-bound form and an inactive GDP-bound form. Upon activation by guanine nucleotide exchange factors, Rabs associate with membranes where they recruit effector molecules to mediate their downstream response. However, the spatio-temporal activation of Rab13 was unknown. Furthermore, the DENN-domain is an evolutionarily conserved protein module that functions enzymatically as guanine nucleotide exchange factors for Rabs. Here, we identified the DENN containing protein DENND2B as guanine nucleotide exchange factor for Rab13 and uncover a mechanism whereby activation of Rab13 by DENND2B in a complex with the Rab13 effector MICAL-L2 at the cell periphery drives cancer cell migration, invasion, and tumor metastasis. Furthermore, active Rabs typically anchor to membranes using a hydrophobic prenyl modification and dissociate from membranes upon inactivation. Here we discovered that Rab13 traffics on vesicles in its inactive form as part of a protein complex independent of prenylation. Therefore, in this doctoral thesis we have provided a detailed characterization of the regulation of Rab13 in endosomal trafficking.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".