Assessing the Downstream Targets of Calmodulin-like Protein 43 in Calcium Signaling in Arabidopsis Thaliana
Bibliographic record
Abstract
As sessile organisms, plants are unable to escape environmental stressors that they may be faced with. As a result, they have developed a unique stress detection and response system involving calcium signals. These signals are received by calcium binding proteins, which are able to alter the gene expression, or metabolic activity of the cell. Calmodulin (CaM) is one of the primary calcium binding proteins. In addition to CaM, plants have evolved a family of calmodulin-like proteins (CMLs) that also function in calcium signaling. One particular CML, CML43, has been found to be linked with bacterial and viral pathogen detection and response in a few species of plants, including Arabidopsis thaliana and tomato. This study attempted to discover the protein targets of CML43 during calcium signaling, and its role in stress recognition and response. Yeast two hybrid analysis was found to be the best method for this particular kind of study because it allows for a high-throughput method of determining protein-protein interactions. Many putative interactors were found, and results from the purification and sequences of these interactors will be presented.
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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) | 0.001 | 0.000 |
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".