Pulmonary and systemic vascular tissue collagen, growth factor, and cytokine gene expression in the rabbit
Bibliographic record
Abstract
During development, the vascular wall composition of the pulmonary and systemic capacitance vessels and their intravascular pressure changes. Little is known, however, about the factors controlling vascular collagen gene expression in both circulations during growth and development. The purpose of this study was to compare the developmental changes in collagen, major growth factors, and cytokines gene expression, in order to ascertain whether a circulation specific pattern is present in the rabbit. Fetal, neonatal, and adult rabbit extrapulmonary and aortic tissues were obtained and the mRNA levels for collagen I and III, as well as major growth factors and cytokines, were measured by a semi-quantitative RT-PCR technique. Collagen I, but not collagen III, expression was developmentally regulated in pulmonary vascular and aorta tissues. Collagen I expression was greatest during the fetal and neonatal period (P < 0.01) and higher in the aorta as compared with the pulmonary artery at these ages (P < 0.05). Significant developmental changes in growth factor mRNA levels were observed for TGF-beta, IGF-2, and bFGF (P < 0.01). IGF-2 mRNA levels significantly declined in both arteries from neonatal to adult, but bFGF increased only in the pulmonary artery during this transition. With regards to inducible enzymes, COX-2 mRNA levels changed developmentally, whereas iNOS mRNA levels were similar for both vessels at all ages. When comparing the two vessels, COX-2 transcripts were relatively more abundant in the adult pulmonary artery tissue and fetal aorta, with similar levels in the newborn. We conclude that circulation specific developmental regulation of collagen gene expression is present in the rabbit in a pattern that is unrelated to the intravascular pressure. Key words: developmental changes, vascular, collagen, mRNA expression, growth factors.
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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 | 0.001 |
| 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".