Electrical Stimulation and Cellular Behaviors in Electric Field in Biomedical Research
Bibliographic record
Abstract
Research on the cellular response to electrical stimulation (ES) and its mechanisms focusing on potential clinic applications has been quietly intensified recently. However, the unconventional nature of this methodology has fertilized a great variety of techniques that make the interpretation and comparison of experimental outcomes complicated. This work reviews more than a hundred publications identified mostly from Medline, categorizes the techniques, and comments on their merits and weaknesses. Electrode-based ES, conductive substrate-mediated ES, and noninvasive stimulation are the three principal categories used in biomedical research and clinic. ES has been found to enhance cell proliferation, growth, migration, and stem cell differentiation, showing an important potential in manipulating cellular activities in both normal and pathological conditions. However, inappropriate parameters or setup can have negative effects. The complexity of the delivered electric signals depends on how they are generated and in what form. It is also difficult to equate one set of parameters with another. Mechanistic studies are rare and badly needed. Even so, ES in combination with advanced materials and nanotechnology is developing a strong footing in biomedical research and regenerative medicine.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".