Skeletal Muscle Troponin C: Expression and Purification of the Recombinant Intact Protein and Its Isolated N- and C-Domain Fragments
Bibliographic record
Abstract
The use of skeletal muscle troponin C (TnC) in structural and functional studies ranging from characterization of its Ca 2+ -binding properties to interaction with troponin I (TnI) and troponin T (TnT), the other two members of the tripartite troponin regulatory complex, has necessitated the purification of large quantities of protein. The procedures for purification of the naturally occurring troponin components from muscle tissue, including preparation of a muscle ether powder, isolation of the crude troponin complex, and further fractionation using column chromatography to obtain the individual subunits, have been described in detail by Potter ( 1 ), and therefore, will not be discussed in this chapter. Owing to the problems with heterogeneity arising from copurification of different isoforms and/or variation in the extent of phosphorylation of the final isolated protein from muscle tissue, methodologies have since been developed using molecular biology strategies to express and purify homogeneous preparations of TnC, TnI, and TnT. Other advantages of these recombinant techniques include the ability of producing site-specific mutants and isolated fragments for studying specific regions without interference from the rest of the molecule, as well as 15 N- and 13 C-labeled derivatives for NMR studies. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".