Cloning and Characterization of a Novel Gene That Is Regulated by Estrogen and Is Associated with Mammary Gland Carcinogenesis*
Bibliographic record
Abstract
Estrogens play a role in mammary gland function and are implicated in mammary carcinogenesis. We report the cloning of a novel gene [steroid-sensitive gene 1 (SSG1)] that is regulated by E(2) in the rat uterus and mammary gland. The full-length SSG1 complementary DNA has an open reading frame of 1158 nucleotides encoding a putative protein of 385 amino acids. A SSG1-specific antibody recognizes a 40-kDa protein localized to myoepithelial cells of normal mammary tissue and to endothelial cells of 7,12-dimethylbenz(a)antracene-induced mammary tumors. Treatment of rats with E(2) at 1.2 or 2.4 microg/kg.day for 21 days increases SSG1 protein levels in mammary tissue by 16-fold compared with controls. Removal of E(2) after a 14-day treatment decreases SSG1 protein levels 6-fold and 3-fold at 120 and 144 h, respectively. Treatment of rats with the estrogen antagonists tamoxifen or ICI 182,780 did not affect SSG1 protein levels compared with controls. SSG1 protein levels in 7,12-dimethylbenz(a)antracene-induced rat mammary tumors were 23-fold greater than SSG1 levels in resting mammary tissue, and 8-fold higher than protein levels expressed in lactating mammary glands. We propose that SSG1 plays a role in estrogen functions, and its overexpression is correlated with mammary carcinogenesis.
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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 | 0.001 |
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".