Preliminary studies for proteomic analysis of dystroglycan associated proteins in the brain
Bibliographic record
Abstract
Dystroglycan is a ubiquitous protein that links the extracellular matrix to the cytoskeleton and is the central unit of the dystrophin glycoprotein complex (DGC), a membrane complex that connects the cytoskeleton to the extracellular matrix (ECM). Dystroglycan is composed of two subunits that are tightly but non-covalently linked. alpha Dystroglycan (alpha DG) is located extracellularly and it is the only component of the DGC linked to the ECM, while beta Dystroglycan (beta DG) spans the plasma membrane and has both an extracellular and a cytoplasmic domain. The DGC is involved in skeletal muscle maintenance and viability, and in the organization and stabilization of the neuromuscular junction, but its function in brain is poorly understood. DGC components are target of several protein kinases, indicating that they are involved in cell signalling pathways. The finding of new dystroglycan interacting proteins could help to obtain some insights in its function in brain tissues. Previous immunoprecipitation and pull down experiments have been used to identify proteins interacting with the cytoplasmic tail of beta DG in brain tissues. Here, we attempt to extend the use of these techniques by using pull down experiments performed with the Glutathione-S-transferase (GST) fusion expression system as a tool for the proteomic analysis of Dystroglycan interacting proteins in the brain.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".