The Effect of Layer-by-Layer Assembly Coating on the Proliferation and Differentiation of Neural Stem Cells
Bibliographic record
Abstract
Nanocoating of a single-cell with biocompatible materials creates a defined microenvironment for cell differentiation and proliferation, as well as a model for studies in cell biology. In addition, the acidic environment in the tissue of stroke victims necessitates drug release upon pH stimuli. Here, we report the encapsulation of single neural stem cells (NSCs) using a layer-by-layer (LbL) self-assembly technique with polyelectrolytes gelatin and alginate. Analysis of the NSCs showed that the LbL encapsulation would not affect the viability, proliferation, or differentiation of the cells. When insulin-like growth factor-1 (IGF-1) was loaded on the coating material alginate, its release from alginate into the medium presented in a time-dependent and pH-dependent way. IGF-1 significantly enhanced the proliferation of the encapsulated NSCs, demonstrating a drug-carrier function of the LbL single-cell nanocoating. It provided a potential treatment strategy for nervous system disorders such as stroke.
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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 | 0.000 | 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 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".