Engineering mammalian cells to seek senescence-associated secretory phenotypes
Bibliographic record
Abstract
ABSTRACT Since the removal of senescent cells in model organisms has been linked to rejuvenation and increased lifespan, senotherapies have emerged to target senescent cells for death. In particular, interleukin-6 (IL6) is a prominent senescence-associated secretory phenotype (SASP) and, thus, seeking IL6 could potentially localize engineered cells to senescent cells for therapeutic intervention. Here, we engineered a chimeric IL6 receptor (IL6Rchi) that generates a Ca2+ signal in response to IL6 stimulation. When IL6Rchi was co-expressed with an engineered Ca2+-activated RhoA (CaRQ), it enabled directed migration to IL6 in cells that have no such natural ability. Next, the removal of target cells was accomplished by the mechanism of membrane fusion and subsequent death. This work represents a first step towards engineering a cell to target senescent cells that secrete high levels of IL6. For increased specificity to senescent cells, it will likely be necessary for an engineered cell to recognize multiple SASPs simultaneously.
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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".