Single cell swimming dynamics of Listeria monocytogenes using a nanoporous microfluidic platform
Bibliographic record
Abstract
Listeria monocytogenes remains a significant foodborne pathogen due to its virulence and ability to become established in food processing facilities. The pathogen is characterized by its ability to grow over a wide temperature range and withstand a broad range of stresses. The following reports on the chemotaxis and motility of the L. monocytogenes when exposed to relatively small concentrations of acetic acid. Using the developed nanoporous microfluidic device to precisely modulate the cellular environment, we exposed the individual Listeria cells to acetic acid and, in real time and with high resolution, observed how the cells reacted to the change in their surroundings. Our results showed that concentrations of acetic acid below 10 mM had very little, if any, effect on the motility. However, when exposed to 100 mM acetic acid, the cells exhibited a sharp drop in velocity and displayed a more random pattern of motion. These results indicate that at appropriate concentrations, acetic acid has the ability to disable the flagellum of the cells, thus impairing their motility. This drop in motility has numerous effects on the cell; its main effects being the obstruction of the cell's ability to properly form biofilms and a reduction in the overall infectivity of the cells. Since these characteristics are especially useful in controlling the proliferation of L. monocytogenes, acetic acid shows potential for application in the food industry as an active compound in designing a food packaging environment and as an antimicrobial agent.
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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) | 0.000 | 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 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".