Structure and Activity of the Human Growth Hormone Receptor (<i>hGHR</i>) Gene V2 Promoter
Bibliographic record
Abstract
Human GH (hGH) has important effects on growth as well as carbohydrate, fat, and protein metabolism. These actions require the presence of normal levels of a functional hGH receptor (hGHR) on the surface of target cells. hGHR gene expression is characterized by the use of several 5'-noncoding exons and alternative splicing, resulting in the generation of multiple mRNA isoforms. The hGHR V2 transcript is predominant in most tissues, including human fat. However, factors regulating its ubiquitous expression have remained unidentified. The present study was aimed at characterizing the mechanisms regulating hGHR V2 transcription. Two major V2 transcriptional start sites were identified by primer extension assays. The V2 proximal promoter is TATA-less, with several characteristics of a housekeeping gene promoter. Transient transfection analyses of 2.6 kb of the 5'-flanking region of V2 confirmed its promoter activity in multiple primate cell lines. Similar promoter activity patterns were observed in human SGBS preadipocytes and mature adipocytes but with much higher V2 promoter activity in mature adipocytes, suggesting that changes in the availability of specific factors during adipocyte differentiation play a role in V2 promoter regulation. Serial deletion and mutation analyses revealed that transcription of hGHR V2 in different cell types, including adipocytes, is determined by a core promoter and distinct inhibitory and activation domains in the 5'-promoter region as well as within the V2 exon. Our data suggest that V2 transcription is the result of a complex interplay involving multiple factors, to ensure appropriate expression of hGHR in different hGH target 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 | 0.001 | 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".