Effect of mechanical stretch on HIF-1α and MMP-2 expression in capillaries isolated from overloaded skeletal muscles: laser capture microdissection study
Bibliographic record
Abstract
Under physiological nonhypoxic conditions, angiogenesis can be driven by mechanical forces. However, because of the limitations of the specific gene expression analysis of microvessels from in vivo experiments, the mechanisms regulating the coordinated expression of angiogenic factors implicated in the process remain intangible. In this study, the technique of laser capture microdissection (LCM) was adapted for the study of angiogenesis in skeletal muscles. With a combination of LCM and real-time quantitative PCR it was demonstrated that capillary endothelial cells produce matrix metalloproteinase (MMP)-2 and that mechanical stretch of capillaries within muscle tissue markedly increases MMP-2 mRNA (2.5-fold increase vs. control; P < 0.05). In addition, we showed that transcription factor hypoxia-inducible factor (HIF)-1alpha expression was 13.5-fold higher in capillaries subjected to stretch compared with controls (P < 0.05). These findings demonstrate the feasibility of this approach to study angiogenic gene regulation and provide novel evidence of HIF-1alpha induction in stretched capillary endothelial cells.
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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".