Cytoplasmic Domain of proEGF Affects Distribution and Post-Translational Modification of Microtubuli and Increases Microtubule-Associated Proteins 1b and 2 Production in Human Thyroid Carcinoma Cells
Bibliographic record
Abstract
We studied the distribution of transcripts encoding the cytoplasmic domain of the membrane-anchored precursor epidermal growth factor (proEGFcyt) and a novel cytoplasmic proEGF splice isoform with a deleted exon 23 and an out-of-frame fusion of exon 24 (proEGFdel23) in human normal and neoplastic thyroid tissues. In papillary thyroid carcinoma (PTC), coexpression of transcripts encoding for both proEGFcyt and proEGFdel23 correlated with poor differentiation of PTC. To determine potential roles of the cytoplasmic proEGF domain in human thyroid cells, we generated stable transfectants of the human follicular thyroid carcinoma cell line FTC-133 overexpressing the normal cytoplasmic domain proEGFcyt, a truncated proEGFcyt composed of the peptide sequence encoded by exons 22 and 23 (proEGF22.23) and proEGFdel23. The proEGFcyt and proEGF22.23 transfectants displayed significantly reduced proliferation rates, an enlarged cellular phenotype, and alterations in the distribution and post-translational modification of the microtubular system. These transfectants also displayed increased production of microtubule-associated proteins 1b and 2c, which was absent in FTC-133-proEGFdel23 or FTC-133-empty plasmid transfectants. This is the first evidence of an involvement of proEGF cytoplasmic domain in microtubular stability in the human thyroid carcinoma cell line FTC-133 and may suggest a specific role for the cytoplasmic domain of membrane-anchored proEGF, particularly exon 23, in thyroid carcinoma. The up-regulation of proEGFdel23 in poorly differentiated PTC and the exclusive detection of both proEGF isoforms in undifferentiated thyroid carcinoma may indicate an involvement of this novel truncated proEGFdel23 cytoplasmic domain during dedifferentiation processes of human thyroid cells.
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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 | 0.000 |
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".