Inhibition of transferrin receptor 1 transcription by a cell density response element
Bibliographic record
Abstract
TfR1 (transferrin receptor 1) mediates the uptake of transferrin-bound iron and thereby plays a critical role in cellular iron metabolism. Its expression is coupled to cell proliferation/differentiation and controlled in response to iron levels and other signals by transcriptional and post-transcriptional mechanisms. It is well established that TfR1 levels decline when cultured cells reach a high density and in the present study we have investigated the underlying mechanisms. Consistent with previous findings, we demonstrate that TfR1 expression is attenuated in a cell-density-dependent manner in human lung cancer H1299 cells and in murine B6 fibroblasts as the result of a marked decrease in mRNA content. This response is not associated with alterations in the RNA-binding activity of iron regulatory proteins that are indicative of a transcriptional mechanism. Reporter assays reveal that the human TfR1 promoters contains sequences mediating cell-density-dependent transcriptional inhibition. Mapping of the human and mouse TfR1 promoters identified a conserved hexa-nucleotide 5'-GAGGGC-3' motif with notable sequence similarity to a previously described element within the IGF-2 (insulin-like growth factor-2) promoter. We show that this motif is necessary for the formation of specific complexes with nuclear extracts and for cell-density-dependent regulation in reporter gene assays. Thus the TfR1 promoter contains a functional 'cell density response element' (CDRE).
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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) | 0.002 | 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".