Single-cell magnetotaxis in mucus-mimicking polymeric solutions
Bibliographic record
Abstract
Magnetotactic bacteria (MTB) are promising candidates for use as biomicrorobots in biomedical applications due to their motility, self-propulsion, and the ability to direct their navigation with an applied magnetic field. When in the body, the MTB may encounter non-Newtonian fluids such as blood plasma or mucus. However, their motility and the effectiveness of directed navigation in non-Newtonian fluids has yet to be studied on a single-cell level. In this work, we investigate motility of Magnetospirillum magneticum AMB-1 in three concentrations of polyacrylamide (PAM) solution, a mucus-mimicking fluid. The swimming speeds increase from 44.0 ± 13.6 μm/s in 0 mg/mL of PAM to 52.73 ± 15.6 μm/s in 1 mg/mL then decreases to 24.51 ± 11.7 μm/s in 2 mg/mL and 21.23 ± 10.5 μm/s in 3 mg/mL. This trend of a speed increase in low polymer concentrations followed by a decrease in speed as the concentration increases past a threshold concentration is consistent with other studies of motile, flagellated bacteria. Past this threshold concentration of PAM, there is a higher percentage of cells with an overall trajectory angle deviating from the angle of the magnetic field lines. There is also less linearity in the trajectories and an increase in reversals of swimming direction. Altogether, we show that MTB can be directed in polymer concentrations mimicking biological mucus, demonstrating the influence of the medium viscosity on the linearity of their trajectories which alters the effective path that could be predefined in Newtonian fluids when transport is achieved by magnetotaxis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".