Functional immobilization of interferon‐gamma induces neuronal differentiation of neural stem cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Stem cell transplantation provides significant promise to regenerative strategies after injury in the central nervous system. Neural stem/progenitor cells (NSPCs) have been studied in terms of their regenerative capacity and their ability to differentiate into neurons when exposed to various soluble factors. In this study, interferon-gamma (IFN-gamma) was compared with brain-derived neurotrophic factor (BDNF) and erythropoietin and was shown to be the best single growth factor for inducing neuronal differentiation from adult rat brain-derived NSPCs. Next, IFN-gamma was surface immobilized to a methacrylamide chitosan (MAC) scaffold that was specifically designed to match the modulus of brain tissue and neuronal differentiation of NSPCs was examined in vitro by immunohistochemistry. Bioactive IFN-gamma was successfully immobilized and quantified by ELISA. Both soluble and immobilized IFN-gamma on MAC surfaces showed dose dependent neuronal differentiation with soluble saturation occurring at 100 ng/mL and the most effective immobilized IFN-gamma dose at 37.5 ng/cm(2), where significantly more neurons resulted compared with controls including soluble IFN-gamma.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 it