Modulation of TGFâβ Receptor 1 signalling in Live Cells
Bibliographic record
Abstract
TGF-β negatively affects the maintenance and expansion of hematopoietic stem cells ex vivo and its inhibition has been widely studied as a treatment for numerous hematopoietic disorders and cancers. Current inhibitory strategies (small molecule ATP competitors and neutralizing antibodies) are compared to a novel cell-permeable peptide-based inhibitor of TGF-β RI. Multiple levels of assay from biochemical to functional are utilized with the aim of applying the most successful inhibitor to hematopoietic stem cell culture. The neutralizing antibody proved ineffective in the short-term biochemical assay but was extremely effective at neutralizing TGF-β signalling in proliferation and hematopoietic colony-forming cell assays with no evidence of toxicity. The small molecule inhibitors (SD-208 and Pyrazole TGF-β RI inhibitor) were equally effective at micromolar levels in all forms of assay, with SD-208 being slightly more potent. The novel peptide inhibitor proved ineffective in all assays, which is likely a result of its rapid degradation in live cells.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".