Autonomous Cell Migration to CSF1 Sources <i>via</i> a Synthetic Protein-Based System
Bibliographic record
Abstract
Inflammatory lesions, often seen in diseases such as rheumatoid arthritis, atherosclerosis and cancer, feature an acidic ( i.e., low pH) microenvironment rampant with cytokines, such as CSF1. For potential therapeutic intervention targeted at these CSF1 sources, we have assembled a system of four proteins inside a cell ( i.e., HEK293) that initially had no natural CSF1-seeking ability. This system included a newly engineered CSF1 chimera receptor (named CSF1Rchi), the previously engineered Ca 2+ activated RhoA ( i.e., CaRQ), vesicular stomatitis virus glycoprotein G (VSVG) and thymidine kinase (TK). The binding of CSF1 to the CSF1Rchi generated a Ca 2+ signal that activated CaRQ-mediated cellular blebbing, allowing autonomous cell migration toward the CSF1 source. Next, the VSVG protein allowed these engineered cells to fuse with the CSF1 source cells, upon low pH induction. Finally, these cells underwent death postganciclovir treatment, via the TK suicide mechanism. Hence, this protein system could potentially serve as the basis of engineering a cell to target inflammatory lesions in diseases featuring a microenvironment with high levels of CSF1 and low pH.
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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".