Electroresponsive Hydrogels for Therapeutic Applications in the Brain
Bibliographic record
Abstract
Electroresponsive hydrogels possess a conducting material component and respond to electric stimulation through reversible absorption and expulsion of water. The high level of hydration, soft elastomeric compliance, biocompatibility, and enhanced electrochemical properties render these hydrogels suitable for implantation in the brain to enhance the transmission of neural electric signals and ion transport. This review provides an overview of critical electroresponsive hydrogel properties for augmenting electric stimulation in the brain. A background on electric stimulation in the brain through electroresponsive hydrogels is provided. Common conducting materials and general techniques to integrate them into hydrogels are briefly discussed. This review focuses on and summarizes advances in electric stimulation of electroconductive hydrogels for therapeutic applications in the brain, such as for controlling delivery of drugs, directing neural stem cell differentiation and neurogenesis, improving neural biosensor capabilities, and enhancing neural electrode-tissue interfaces. The key challenges in each of these applications are discussed and recommendations for future research are also provided.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".