Human Rett-derived neuronal progenitor cells in 3D graphene scaffold as an <i>in vitro</i> platform to study the effect of electrical stimulation on neuronal differentiation
Why this work is in the frame
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Bibliographic record
Abstract
Studies of electrical stimulation therapies for the treatment of neurological disorders, such as deep brain stimulation, have almost exclusively been performed using animal-models. However, because animal-models can only approximate human brain disorders, these studies should be supplemented with an in vitro human cell-culture based model to substantiate the results of animal-based studies and further investigate therapeutic benefit in humans. This study presents a novel approach to analyze the effect of electrical stimulation on the neurogenesis of patient-induced pluripotent stem cell (iPSC) derived neural progenitor cell (NPC) lines, in vitro using a 3D graphene scaffold system. The iPSC-derived hNPCs used to demonstrate the system were collected from patients with Rett syndrome, a debilitating neurodevelopmental disorder. The graphene scaffold readily supported both the wild-type and Rett NPCs. Electrical stimulation parameters were optimized to accommodate both wild-type and Rett cells. Increased cell maturation and improvements in cell morphology of the Rett cells was observed after electrical stimulation. The results of the pilot study of electrical stimulation to enhance Rett NPCs neurogenesis were promising and support further investigation of the therapy. Overall, this system provides a valuable tool to study electrical stimulation as a potential therapy for neurological disorders using patient-specific cells.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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