Characterization of VPS33B and VPS16B in α-Granule Biogenesis in Megakaryocytes
Bibliographic record
Abstract
Platelets contain storage vesicles known as α-granules, made by their precursor megakaryocytes. Loss of α-granule biogenesis causes arthrogryposis, renal dysfunction and cholestasis syndrome when VPS33B, encoding vacuolar protein sorting-associated protein 33B (VPS33B), or VIPAS39, encoding VPS33B-interacting protein apical-basolateral polarity regulator spe-39 (VPS16B), undergo loss-of-function mutations. VPS33B and VPS16B form a complex, which I hypothesize interacts with other proteins to facilitate α-granule cargo sorting and synthesis. Using a VPS33B antibody, I localized this protein within primary human megakaryocytes via confocal immunofluorescence microscopy. This represents the first time that endogenous VPS33B has been localized in megakaryocytes, removing the potential for experimental artefacts present in previous fusion-tagged imaging attempts. I have also investigated the interactome of VPS33B using a combination of affinity purification mass spectrometry analysis and co-immunoprecipitation experiments. These experiments identified several novel VPS33B interactors, including proteins involved in early and late endosomal trafficking pathways, and in the regulation of cytoskeletal networks.
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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) | 0.002 | 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".