Characterization of <i>cis</i>‐acting elements in the promoter of the mouse metallothionein‐3 gene
Bibliographic record
Abstract
The metallothionein (MT)3 gene is expressed predominantly in the brain and the organs of the reproductive system, and fails to respond to metal ions in vivo. A CTG repeat was proposed to function as a potential repressor element in nonpermissive cells, and a sequence similar to the JC virus silencer element was found to function as a negative element in permissive primary astrocytes. The objective of this study was to characterize further the mechanisms governing cell-type specific MT-3 gene transcription. We searched for a suitable cell line expressing the MT-3 gene to be used for determination of MT-3 promoter tissue specificity, and showed that MT-3 expression is activated during neuroectodermal differentiation of P19 cells induced by retinoic acid to levels similar to those found in whole brain. Deletion of the CTG repeat or of the JC virus silencer did not promote MT-3 promoter activity in nonpermissive cells, or enhance expression in permissive cells. We identified MT-3 promoter sequences interacting with liver and brain nuclear proteins, as assayed by DNase I footprinting analyses and electrophoretic mobility shift assay, and assessed the role of these sequences in the regulation of MT-3 expression by cotransfection experiments. We generated stable transfectants in permissive C6 and nonpermissive NIH-3T3 cells, and analysed the methylation status of the MT-3 gene. These studies show that regulation of tissue-specific MT-3 gene expression does not appear to involve a repressor, and suggest that other mechanisms such as chromatin organization and epigenetic modifications could account for the absence of MT-3 gene transcription in nonpermissive cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".