Engineering Neural Tissue from Human Pluripotent Stem Cells Using Novel Small Molecule Releasing Microspheres
Bibliographic record
Abstract
Here a novel technique for engineering neural tissue consisting of motor neurons by combining human-induced pluripotent stem cells (hiPSCs) with small molecules releasing microspheres is demonstrated. First, the small molecule purmorphamine (puro) is successfully encapsulated into poly ε-caprolactone (PCL) microspheres using a single emulsion oil-in-water (o/w) method for the first time with an efficiency of (84% ± 2.12%). These microspheres release 91% ± 1.7% of the encapsulated puro in a controlled fashion over 46 days. Puro microspheres, along with previously characterized retinoic acid (RA) releasing microspheres, are then incorporated into hiPSC aggregates to engineer neural tissue. The combination of puro and RA microspheres promotes hiPSC differentiation as indicated by the expression of multiple neural markers, including the neuronal marker β-tubulin III (βT-III), and the transcription factor Olig2 (7.69 ± 8.38%) on day 28. These tissues express the motor neuron marker HB9 (24.85 ± 4.51%) on day 35, and the mature motor neuron marker ChaT (12.35 ± 4.17%) on day 60. These engineered tissues can be used for regenerative medicine applications such as treating spinal cord injury (SCI), disease modeling, and drug screening.
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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) | 0.001 | 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".