Distinguishing the Role of the c-myb Proto-Oncogene in Mouse Models of Cardiovascular Disease
Bibliographic record
Abstract
Despite considerable advances in our understanding of disease processes, cardiovascular diseases remain the top cause of mortality and morbidity in society today. Investigating the molecular and cellular mechanisms involved in the pathogenesis of these diseases to discover new therapeutic targets is of utmost importance. While much is known about the specific roles of transcription factor c-myb in leukocytes, comparatively little is known about c-myb in the context of cardiovascular disease. c-myb regulates vascular smooth muscle cell (VSMC) differentiation from embryonic stem cells, as well as the proliferation of mature VSMCs. The literature points toward several areas of opportunity to examine the role of c-myb in cardiovascular biology: first, to examine the role of c-myb in the regulation of adult vessel-resident VSMC progenitor cell proliferation and differentiation in response to vessel injury and the molecular mechanisms involved in c-myb-mediated VSMC differentiation. Second, while transgenic models manipulating c-myb have yielded significant insight in regards to homeostasis of the immune system, little is known about a role for c-myb in the regulation of baseline function of the cardiovascular system. While c-myb regulates VSMC differentiation and pathological VSMC proliferation, it is not known if it regulates VSMC contractile function and vascular contractility, and more generally, blood pressure homeostasis. Lastly, this dissertation examines the involvement of c-myb in experimental atherosclerosis, a disease model involving both leukocytes and vessel-resident cells such as VSMCs. Therefore, work of this dissertation aims to elucidate the role of c-myb in these areas and thus further the collective understanding of the mechanisms involved in cardiovascular pathophysiology.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".