Dynamic localization and persistent stimulation of factor‐dependent cells by a stem cell factor / cellulose binding domain fusion protein
Bibliographic record
Abstract
The extracellular matrix provides structural components that support the development of tissue morphology and the distribution of growth factors that modulate the overall cellular response to those growth factors. The ability to manipulate the presentation of factors in culture systems should provide an additional degree of control in regulating the stimulation of factor-dependent cells for tissue engineering applications. Cellulose binding domain (CBD) fusion protein technology facilitates the binding of bioactive cytokines to cellulose materials, and has permitted the analysis of several aspects of cell stimulation by surface-localized growth factors. We previously reported the synthesis and initial characterization of a fusion protein comprised of a CBD and murine stem cell factor (SCF) (Doheny et al. [1999] Biochem J 339:429-434). A significant advantage of the CBD fusion protein system is that it permits the stimulation of factor-dependent cells with localized growth factor, essentially free of nonfactor-derived interactions between the cell and matrix. In this work, the long-term stability and bioactivity of SCF-CBD fusions adsorbed to microcrystalline cellulose under cell culture conditions is demonstrated. Cellulose-bound SCF-CBD is shown to stimulate receptor polarization in the cell membrane and adherence to the cellulose matrix. In addition, cellulose-surface presentation of the SCF-CBD attenuates c-kit dephosphorylation kinetics, potentially modulating the overall response of the cell to the SCF signal.
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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".