Bibliographic record
Abstract
We examined myofibroblast differentiation in VICs from porcine aortic valves. In normal valves, cells positive for a-SMA were rare, but spatially abundant in sclerotic valves. Hoechst 33342 dye identified 0.5% of VICs that are side population cells, none stained for SMA. Upon culture, sorted side population cells generated ∼85% SMA positive cells, indicating that some myofibroblasts originate from a rare population. Formation of myofibroblast is observed after 5 days in culture on rigid substrate, in contrast to compliant substrate. Exogenous tensile force also significantly increased SMA expression in VICs. ICAT and mass spectrometry identified cofilin as being differentially expressed in myofibroblast. Knockdown of cofilin with siRNA inhibited collagen gel contraction and reduced myofibroblast differentiation. Compared to normal valves, diseased valves showed strong immunostaining for cofilin that co-localized with SMA. Thus, in VICs, cofilin is a marker for myofibroblasts that arise from a rare population of stem cells and require a rigid matrix for formation.
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 | 0.001 |
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".