HCaRG, a Novel Calcium-regulated Gene Coding for a Nuclear Protein, Is Potentially Involved in the Regulation of Cell Proliferation
Bibliographic record
Abstract
Since a negative calcium balance is present in spontaneously hypertensive rats, we searched for the gene(s) involved in this dysregulation. A cDNA library was constructed from the spontaneously hypertensive rat parathyroid gland, which is a key regulator of serum-ionized calcium. From seven overlapping DNA fragments, a 1100-base pair novel cDNA containing an open reading frame of 224 codons was reconstituted. This novel gene, named HCaRG (hypertension-related, calcium-regulated gene), was negatively regulated by extracellular calcium concentration, and its basal mRNA levels were higher in hypertensive animals. The deduced protein showed no transmembrane domain, 67% alpha-helix content, a mutated calcium-binding site (EF-hand motif), four putative "leucine zipper" motifs, and a nuclear receptor-binding domain. At the subcellular level, HCaRG had a nuclear localization. We cloned the human homolog of this gene. Sequence comparison revealed 80% homology between rats and humans at the nucleotide and amino acid sequences. Tissue distribution showed a preponderance in the heart, stomach, jejunum, kidney (tubular fraction), liver, and adrenal gland (mainly in the medulla). HCaRG mRNA was significantly more expressed in adult than in fetal organs, and its levels were decreased in tumors and cancerous cell lines. We observed that after 60-min ischemia followed by reperfusion, HCaRG mRNA declined rapidly in contrast with an increase in c-myc mRNA. Its levels then rose steadily to exceed base line at 48 h of reperfusion. HEK293 cells stably transfected with HCaRG exhibited much lower proliferation, as shown by cell count and [(3)H]thymidine incorporation. Taken together, our results suggest that HCaRG is a nuclear protein potentially involved in the control of cell proliferation.
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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".