Transforming Growth Factor-β Superfamily: Evaluation as Breast Cancer Biomarkers and Preventive Agents
Bibliographic record
Abstract
The Transforming Growth Factor-beta (TGFbeta) superfamily of cytokines is comprised of a number of structurally-related, secreted polypeptides that regulate a multitude of cellular processes including proliferation, differentiation and neoplastic transformation. These growth regulatory molecules induce ligand-mediated hetero-oligomerization of distinct type II and type I serine/threonine kinase receptors that transmit signals predominantly through receptor-activated Smad proteins but also induce Smad-independent pathways. Ligands, receptors and intracellular mediators of signaling initiated by members of the TGFbeta family are expressed in the mammary gland and disruption of these pathways may contribute to the development and progression of human breast cancer. Since many facets of TGFbeta and breast cancer have been recently reviewed in several articles, except for discussion of recent developments on some aspects of TGFbeta, the major focus of this review will be on the role of activins, inhibins, BMPs, nodal and MIS-signaling in breast cancer with emphasis on their utility as potential diagnostic, prognostic and therapeutic targets.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".