Regulator of Calcineurin 1 Gene Transcription is Regulated by Nuclear Factor-kappaB
Bibliographic record
Abstract
Regulator of calcineurin 1 (RCAN1) has been implicated in pathogenesis of neurodegeneration and various cancers. Recently, we showed that RCAN1 expression was elevated in Down Syndrome and Alzheimer's disease and its expression transpose over induced neuronal apoptosis. As NF-κB is an important transcription factor involved in cell survival and RCAN1 played vital roles in cell viability, we examined whether NF-κB regulates RCAN1 gene expression. Our results here showed that the RCAN1 isoform 4 gene transcription can be activated by NF-κB signaling. NF-κB activated RCAN1 isoform 4 gene promoter. Luciferase assay, electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation identified a NF-κB responsive element in the region of -576-554bp of the RCAN1 isoform 4 promoter. Activation of RCAN1 gene expression by NF-κB is independent from the calcineurin-NFAT signaling since the NF-κB responsive element was distinct from the NFAT binding sites that was previously identified in the region of -350-166bp. Indeed, activation of calcineurin-NFAT signaling decreased NF-κB transcriptional activity, while activation of NF-κB elevated NFAT transcriptional activity. RCAN1 isoform 4 gene transcription was repressed by its own protein expression in a negative feedback loop. Our findings about RCAN1 gene transcription regulated by NF-κB further supported the vital roles of RCAN1 in cellular functions and its involvement in AD pathogenesis.
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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) | 0.001 | 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 | 0.000 |
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".