Harnessing electrical energy for anti-biofilm therapies: effects of current on cell morphology and motility
Bibliographic record
Abstract
Preferentially altering bacterial migration could be a successful approach for augmenting the natural wound-healing process. Inducing electrotactic behaviours through the application of physiologically safe currents is one possible strategy for altering bacterial movement. By controlling bacterial movement at the site of infection, healing times and the severity/extent of bacterial infection could be reduced. Here, we deployed microfluidics and atomic force microscopy to determine the effect of an applied electrical current on bacterial motility and cell morphology in wound pathogens namely Pseudomonas aeruginosa, Escherichia coli, and methicillin-resistant Staphylococcus aureus (MRSA). Nanoscale imaging combined with microfluidic platforms allows for the study of single-cell swimming dynamics. Current values of 0, 0.07, and 0.125 mA were applied to bacteria in suspension. E. coli exhibited an increase in directionality and a drop in mean cellular velocity across all voltages. P. aeruginosa showed a significant decrease in mean cellular velocity at 0.07 mA, while all currents increased the directionality of movement. Electrical current had no statistically significant effect on the width or length of individual bacterial cells. A better understanding of how electrical stimulation affects pathogenic bacteria at wound sites may lead to advancements in electrotherapy and help to identify new alternatives to traditional antimicrobial approaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".