Some assembly required: SOCE and Orai1 channels couple to NFAT transcriptional activity via calmodulin and calcineurin
Bibliographic record
Abstract
Advances in our ability to monitor the temporal and spatial dynamics of intracellular second messengers such as Ca(2+) and cyclic nucleotides at millisecond and sub-micron levels of resolution have greatly increased our understanding of cellular signal transduction mechanisms. Thus, it is now well appreciated that second messengers can rise and fall within discrete regions of the intracellular compartment, as opposed to global changes, and on a time scale determined by the local collection of signaling molecules responsible for the synthesis and degradation/re-uptake of the second messenger. Efforts to identify the components of such macromolecular signaling domains have revealed the presence of hormone receptors, modifying enzymes and scaffolding proteins that tend to assemble and organize these complexes. Emerging evidence now suggests that these signal transduction entities need not be pre-existing, static complexes within the cell, but in fact, may dynamically assemble in response to a specific stimulus. Such an arrangement would thus allow key signaling molecules to be trafficked where they are needed, thereby allowing a cell to utilize these resources more effectively. On the flip side, having such molecules constantly remain within a single cellular domain would facilitate rapid signaling responses and help maintain fidelity of the pathway.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.004 | 0.004 |
| 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".