The Morphological and Molecular Changes of Brain Cells Exposed to Direct Current Electric Field Stimulation
Bibliographic record
Abstract
BACKGROUND: The application of low-intensity direct current electric fields has been experimentally used in the clinic to treat a number of brain disorders, predominantly using transcranial direct current stimulation approaches. However, the cellular and molecular changes induced by such treatment remain largely unknown. METHODS: Here, we tested various intensities of direct current electric fields (0, 25, 50, and 100V/m) in a well-controlled in vitro environment in order to investigate the responses of neurons, microglia, and astrocytes to this type of stimulation. This included morphological assessments of the cells, viability, as well as shape and fiber outgrowth relative to the orientation of the direct current electric field. We also undertook enzyme-linked immunosorbent assays and western immunoblotting to identify which molecular pathways were affected by direct current electric fields. RESULTS: In response to direct current electric field, neurons developed an elongated cell body shape with neurite outgrowth that was associated with a significant increase in growth associated protein-43. Fetal midbrain dopaminergic explants grown in a collagen gel matrix also showed a reorientation of their neurites towards the cathode. BV2 microglial cells adopted distinct morphological changes with an increase in cyclooxygenase-2 expression, but these were dependent on whether they had already been activated with lipopolysaccharide. Finally, astrocytes displayed elongated cell bodies with cellular filopodia that were oriented perpendicularly to the direct current electric field. CONCLUSION: We show that cells of the central nervous system can respond to direct current electric fields both in terms of their morphological shape and molecular expression of certain proteins, and this in turn can help us to begin understand the mechanisms underlying the clinical benefits of direct current electric field.
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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) | 0.001 | 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".