Creation of a synthesis-friendly inflammation-inducible promoter suitable for cell therapy
Bibliographic record
Abstract
The development of 'smart' cell-based therapeutics requires cells that first recognize conditions consistent with disease (e.g. inflammation) and then subsequently release therapeutic proteins, thereby reducing potential toxicity from otherwise continuous expression. Promoters containing NF-κB response elements are often used as reporters of inflammation; however, endogenous promoters have crosstalk with other pathways, and current synthetic promoters have many exact sequence repeats of NF-κB response elements which make them both difficult to synthesize and inherently genetically unstable. Herein, a synthesis-friendly inflammation-inducible promoter (named SFNp) was created by the packing of 14 NF-κB response elements, which have no repeats >9 bp, followed by a minimal cytomegalovirus promoter. In stably expressing human embryonic kidney 293 cells, we assessed the ability of SFNp to inducibly transcribe genes for reporting expression, changing cell morphology, and performing cell fusion. These experiments represent simple milestones for potentially using SFNp in the development of cell-based therapeutics. As strongly repeated DNA can compromise the long-term stability of genetic circuits, new designs used in 'smart' cell therapy will become more reliant on synthesis-friendly components like SFNp.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".