Signaling effects induced by pharmacological Tie2 receptor dimerization in lentivirally transduced cells
Bibliographic record
Abstract
Engineering hematopoietic stem cells (HSCs) to express therapeutic transgenes provides the opportunity to treat various diseases. However, a critical number of transduced cells are required. One approach to increase transduced cell number is to activate modified receptor tyrosine kinases (RTKs) with chemical inducers of dimerization (CIDs), thereby promoting selective expansion. Tie2 is a RTK that modulates HSC function. For this project, a chimeric receptor was constructed with a CID-binding domain fused to the signaling domain of Tie2. Sequences encoding this receptor (termed LFT2) were cloned into a lentiviral vector. HUVEC cells transduced to express LFT2 showed an increase in phosphorylated Akt (p-Akt), which mediates cell survival, when treated with the CID AP20187. Similar increases in p-Akt were also observed in LFT2-expressing UKE-1 cells. Modest increases in proliferation were seen in HUVEC-LFT2 cells in response to AP20187. These results demonstrate the ability of the chimeric receptor system to cause Tie2-mediated signaling changes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
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".