Excitation-transcription coupling in smooth muscle is associated with vascular remodeling
Bibliographic record
Abstract
Various stresses loaded on the arteries induce vascular remodeling. Macrophages accumulated in the vascular wall promote dedifferentiation and proliferation of smooth muscle cells (SMC) and induce vascular remodeling. However, it remains unclear how arteries sense various stresses and accumulate macrophages. We found that Ca2+ signals in SMCs are converted into gene transcription via excitation-transcription (E-T) coupling, which recruits macrophages to the vascular wall. Imaging analyses revealed that the activation of a complex consisting of voltage-dependent Ca2+ channel (Cav1.2), Ca2+/CaM dependent kinase kinase (CaMKK)-2, and CaMK1α formed in caveolae induces transcription of genes, such as chemokines, cytokines, and leukocyte adhesion molecules. When pressure overload was applied to mouse mesenteric arteries in vivo, migration of macrophages to the vascular adventitia and medial hypertrophy were detected. These changes were attenuated in deletion of caveolin-1 or CaMKK2 genes as well as the administration of a CaMKK2 inhibitor. These data suggest that the sustained increase in intracellular Ca2+ level due to mechanical stress is converted into the transcription of proinflammatory genes through E-T coupling, which results in the accumulation of macrophages and subsequent inflammation causes vascular remodeling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".