Engineering Synthetic Proteins to Generate Ca<sup>2+</sup> Signals in Mammalian Cells
Bibliographic record
Abstract
The versatility of Ca 2+ signals allows it to regulate diverse cellular processes such as migration, apoptosis, motility and exocytosis. In some receptors ( e.g., VEGFR2), Ca 2+ signals are generated upon binding their ligand(s) ( e.g., VEGF-A). Here, we employed a design strategy to engineer proteins that generate a Ca 2+ signal upon binding various extracellular stimuli by creating fusions of protein domains that oligomerize to the transmembrane domain and the cytoplasmic tail of the VEGFR2. To test the strategy, we created chimeric proteins that generate Ca 2+ signals upon stimulation with various extracellular stimuli ( e.g., rapamycin, EDTA or extracellular free Ca 2+ ). By coupling these chimeric proteins that generate Ca 2+ signals with proteins that respond to Ca 2+ signals, we rewired, for example, dynamic cellular blebbing to increases in extracellular free Ca 2+ . Thus, using this design strategy, it is possible to engineer proteins to generate a Ca 2+ signal to rewire a wide range of extracellular stimuli to a wide range of Ca 2+ -activated processes.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".