Cloning of Human Preprotachykinin-I Promoter and the Role of Cyclic Adenosine 5′-Monophosphate Response Elements in Its Expression by IL-1 and Stem Cell Factor
Bibliographic record
Abstract
Preprotachykinin-I gene (PPT-I) encodes several peptides with organ-specific functions that link the neuroendocrine-immune-hemopoietic axis. We cloned upstream of the initiation site of human PPT-I promoter and identified consensus sequences for two cAMP response elements (CRE). PPT-I is induced by cytokines including those that signal through the cAMP pathway. Therefore, we studied the role of the two CRE in IL-1alpha and stem cell factor (SCF) stimulation of bone marrow stroma because both cytokines induce endogenous PPT-I in these cells and activate the cAMP pathway. Furthermore, bone marrow stroma expresses the transcription factors regulated by the cAMP pathways such as the repressor (ICERIIgamma) and activator (CREMtau). Mutagenesis of the two CRE and/or cotransfection with vectors that express ICERIIgamma or CREMtau indicated that the two CRE have major roles in PPT-I expression. The two CRE are also required for optimal promoter activity by SCF and IL-1alpha. A particular cytokine could concomitantly induce PPT-I and the high affinity G protein-coupled receptor for PPT-I peptides, NK-1R. We showed that SCF, a representative cytokine, induced PPT-I and NK-1R leading to autocrine and/or paracrine cell activation. Because NK-1R activates cAMP through the G protein, the results suggest that the presence of CRE sequences within PPT-I promoter could be important in the regulation of PPT-I expression by cytokines, irrespective of their ability to signal through cAMP. As PPT-I is implicated in hemopoietic regulation, immune responses, breast cancer, and other neural functions, these studies add to the basic biology of these processes and could provide targets for drug development.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".