Thyroid pathology in transgenic mice overexpressing betacellulin
Bibliographic record
Abstract
The epidermal growth factor receptor (EGFR) and many of its ligands are expressed in the thyroid. Although abnormally high activity of the EGFR has been associated with thyroid cancer, little is known about the role of this growth factor family in the development and physiology of the thyroid gland. We recently generated transgenic mice with ubiquitous overexpression of betacellulin (BTC), a ligand of the EGFR (Schneider et al., Endocrinology 146, 5237–5246, 2005). BTC transgenic mice display a whole array of phenotypical alterations including lung pathology, nasal and palatinal mucoid gland pathology, and increased cortical bone mass. In order to study possible effects of this growth factor in the thyroid, we evaluated this tissue histologically. We found the thyroid gland of BTC transgenic mice to comprise of multiple colloid cysts and focal degeneration resulting in a reduction of normal thyroid structure. This finding is particularly interesting since no pathological alterations of the thyroid gland have been described before in transgenic mice overexpressing other EGFR ligands. This may indicate a specific role for BTC in this tissue. Current studies are focusing on the spatial localization of BTC in the thyroid gland by immunohistochemistry, determination of circulating levels of thyroid-derived hormones as well as immunohistological analyses of relevant thyroid-specific markers.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".