Identification and characterization of a novel Muscle Lamin A/C (LMNA) Interacting Protein (MLIP): A regulator of Pax7
Bibliographic record
Abstract
Specific missense mutations LMNA have been identified to be associated with muscular dystrophy suggesting that LMNA interacts with a muscle specific factor(s). A yeast two‐hybrid screen with LMNA as bait was employed to identify muscle specific proteins. A previously uncharacterized cDNA clone was identified that interacts with LMNA in muscle, MLIP. Preliminary results show MLIP protein is primarily expressed in brain, heart and skeletal muscle. No structural or functional domains have been identified within MLIP. Objective: To define the function of MLIP in muscle. Results: MLIP is expressed endogenously in a mouse myoblast cell line (C2C12) and is co‐localized to the nuclear envelope and PML bodies. Initiation of C2C12 differentiation led to a 3‐fold increase in MLIP expression peaking at 24hrs and MLIP continued to be expressed in differentiated myotubes. Specific knockdown of MLIP in C2C12 cells by shRNAi led to significant (p<0.01) reduction in Pax7 expression with a concurrent reduction in Myf5, MyoD and myogenin with Pax3 expression being unaffected. To determine whether MLIP is necessary and/or sufficient for myogenic differentiation, stable C2C12 cell lines are being generated that either knockdown MLIP or over‐express MLIP. Conclusion: MLIP is a novel LMNA interacting protein that may regulate Pax7 a myogenic determinant during regenerative myogenesis. Funding: CIHR operating grant to PGB.
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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".