Identification and Characterization of a Novel Gene, dapr, Involved in Skeletal Muscle Differentiation and Protein Kinase B Signaling
Bibliographic record
Abstract
The phosphatidylinositol 3-kinase (PI3K) signaling pathway has been associated with a variety of cellular functions ranging from cell cycle regulation to tissue development. Although years of research have extensively characterized this signaling pathway, little is known as to how specific cellular events are coordinated by its activation. Here we demonstrate that Dapr (differentiation-associated protein), a novel protein, appears to focus one aspect of this pathway by acting as a putative scaffold protein during skeletal muscle differentiation. We present for the first time a description of this protein using in silico analysis. dapr was discovered through a previous study employing chromatin immunoprecipitation and CpG microarray analysis experiments as being regulated by myocyte-enhancing factor 2, a key transcription factor involved in the differentiation of skeletal muscle tissue. In this study we show that during the course of differentiation, Dapr binds to the PI3K signaling pathway member protein kinase B (PKB). In C2C12 myoblast cells before differentiation Dapr is localized to the cytosol, migrating with PKB to the membrane after initiation of muscle differentiation. Knockdown of Dapr by RNAi resulted in inhibition of myotube formation. Our findings indicate that Dapr is a key component required by myoblasts for orchestrating their differentiation during myogenesis. Furthermore, it appears that Dapr is involved in the PI3K signaling cascade, potentially acting as a scaffold protein for PKB and coordinating its compartmentalization during differentiation.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".