Role of tactic response on the mobilization of motile bacteria through micrometer-sized pores
Bibliographic record
Abstract
A major cause of high bioremediation endpoints is the limited bioaccessibility to residual contaminants resting in soil pores with diameters close to the size exclusion limit of bacterial cells. Under nongrowing conditions and in the absence of hydraulic flow, we examined how the tactic behavior of motile, contaminant-degrading Pseudomonas putida G7 cells (2 × 1 μm) influenced passage through membranes with pores ranging in size from 1 μm to 12 μm. The bacteria were spontaneously retained by the membranes - even those with the largest pore size. However, the cells were mobilized through 5 μm and 12 μm pores after the application of an attractant (salicylate). Mobilization also occurred by attraction to the common root exudate constituents γ-aminobutyric acid and citrate and repellence (or negative taxis) to zero-valent iron nanoparticles. The observed pore size threshold for tactic mobilization (5 μm) and unaltered cell fluxes and effective cell diffusion against different chemoeffector strengths and concentrations suggest that there is a physical constraint on the gradient sensing mechanism at the pores that drives the tactic response. Our results indicate that chemically mediated, small-scale tactic reactions of motile bacteria may become relevant to enhance the bioaccessibility of the residual contaminants present in micrometer-sized soil pores.
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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".