Role of Oxygen Tension on the Transport and Retention of Two Pathogenic Bacteria in Saturated Porous Media
Bibliographic record
Abstract
To examine the influence of variations in the dissolved oxygen (DO) concentration on pathogen mobility, laboratory-scale filtration experiments were performed using the enterohemorrhagic strain Escherichia coli O157:H7 and the enteroinvasive organism Yersinia enterocolitica. Cells were incubated either in the absence (anaerobic) or in the presence (aerobic) of oxygen to understand how these two growth conditions may affect bacterial transport and retention in water-saturated granular porous media. The influence of DO during growth is found to be organism dependent, whereby E. coli O157:H7 exhibits decreased transport potential when grown in the presence of 02 and Y. enterocolitica exhibits greater transport when grown aerobically. To understand the influence of DO changes during cell acclimation and transport, bacteria were resuspended and acclimated in either oxygen-depleted (low DO) or oxygen-rich (saturated DO) electrolytes prior to conduction of filtration experiments. The effect of DO on bacterial transport and retention is shown to be dependent on the antecedent growth conditions and on the organism studied. Measurements of the cell surface charge, shape, and size reveal some variability when the oxygen tension is changed during bacterial growth or acclimation and are linked to the observed bacterial transport behavior.
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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 | 0.001 |
| 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 | 0.001 | 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".