Electrode stimulation parameter modifications elicit differential glial cell responses in vitro over a short 4-h timecourse
Bibliographic record
Abstract
A cell culture model to assess glial cell responses to electrically stimulating electrodes in real-time was developed. Our previous work measured glial cell responses to stimulation paradigms and highlighted the importance of electrical stimulation considerations when designing a biocompatible neural interfacing device. The formation of voids around stimulating platinum-iridium electrodes also prompted an investigation into the fate of cells that would have once populated that area. Live-imaging experiments involving EGFP-positive microglia from heterozygous CX3CR-1 +/EGFP mice were designed. Live-imaging animations over 4 hours showed necrotic microglial cell death around stimulating electrodes. The degree to which this was occurring was further analyzed by electrically stimulating mixed glia and modifying parameters such as stimulation amplitude (0.1-0.4 mA), waveform shape (rectangular/sinusoidal/ramped), and frequency (25-55 Hz). The different stimulation parameters had differential effects on glial cell biomarker signal outputs (cell density, fluorescence intensity, area coverage). Scanning electron microscopy and energy-dispersive x-ray spectroscopy of the electrode surfaces post-stimulation did not reveal any significant damage or changes to surface elemental composition. Finally, electrochemical testing of the proposed in vitro setup revealed influences of different components of the mixed glial cell cultures towards the electrochemical performance of the electrodes in terms of cathodic charge storage capacity, impedance, phase angle, and voltage transient excursions. The results highlight the impact that electrical stimulation parameters have on glial cell fate at the electrode-cell culture interface, and provide data towards refinement of stimulation paradigms used in electrical neuromodulation applications.
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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) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".