Regulation of α1G T‐type calcium channel gene (CACNA1G) expression during neuronal differentiation
Bibliographic record
Abstract
Down-regulation of T-type Ca channel current and mRNA occurs following differentiation of Y79 retinoblastoma cells. To understand how the decrease in expression is linked to cell differentiation, we examined transcriptional regulation of the Cav3.1 Ca channel gene, CACNA1G. We identified two putative promoters (A and B) in 1.3 kb of cloned genomic DNA. Reverse transcriptase-polymerase chain reaction and 5' rapid amplification of cDNA ends-polymerase chain reaction analyses demonstrated that two transcripts with different 5' untranslated regions are generated by different transcription start sites, with promoter A favoured in undifferentiated cells and promoter B favoured in differentiated cells. Functional analyses of the promoter sequence revealed that both promoters are active. Enhancer and repressor sequences were identified upstream of promoter A and B, respectively. These results suggest that the down-regulation of alpha1G mRNA in differentiated Y79 cells is mediated primarily by decreased activity of promoter A, which could occur in conjunction with repression of the activity of promoter B. The decrease in T-type Ca channel expression in Y79 cells may be an essential signal affecting phenotypic maturation and expression of other ion channel subtypes in the differentiated 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".