IL‐1 induced release of Ca <sup>2+</sup> from internal stores is dependent on cell‐matrix interactions and regulates ERK activation
Bibliographic record
Abstract
The cellular mechanisms that modulate interleukin-1 (IL-1) signaling are not defined. In fibroblasts, IL-1 signaling is affected by the nature of cell-matrix adhesions including focal adhesions, adhesive domains that sequester IL-1 receptors. We conducted studies to elucidate which steps of cellular Ca2+ handling are affected by focal adhesions and by which mechanisms focal adhesions modulate IL-1-induced Ca2+ signals and ERK activation in human gingival fibroblasts. Cells were plated on poly-l-lysine or fibronectin and treated with tenascin, Hep-I, or SPARC peptides to inhibit focal adhesion formation. These treatments blocked IL-1 and thapsigargin-induced Ca2+ release from the endoplasmic reticulum, indicating that the ER-release pathway is focal adhesion dependent. Focal adhesions were also required for Ca2+ entry through store-operated channels and for IL-1-induced ERK activation. Thus interactions with the extracellular matrix and focal adhesion formation regulate IL-1-induced generation of intracellular Ca2+ signals that in turn are required for ERK activation.
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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".