Interaction of Pseudomonas putida and Listeria monocytogenes in mixed culture biofilms / by Greg Kepka.
Bibliographic record
Abstract
"Listeria monocytogenes is a foodborne pathogen that causes problems in many food processing plants because it produces biofilms and thus is difficult to control by regular cleaning and sanitizing procedures. It has been stated that the growth of L. monocytogenes is enhanced in mixed culture biofilms, but little information is available that provides a mechanistic explanation for this. Mixed culture biofilms with Pseudomonas putida (labeled with green fluorescent protein) and L. monocytogenes EGD were examined to determine whether one organism would enhance growth of the other. Mono and mixed culture biofilms were grown on glass cover slips, in M9 1x minimal salt medium supplemented with 1mM glucose at 22C for 24 hours using a flow cell. Images were taken using a scanning electron microscope and with a confocal scanning laser microscope, after staining Listeria cells with a Texas Red-X conjugate of wheat germ agglutinin. Confocal images captured at inlet, middle and outlet of the flow cell were analyzed with the novel biofilm program PHLIP for total biovolume and mean thickness. At the inlet, almost all biofilms produced highest total biovolume and mean thickness; this was significant for P. putida (P < 0.05). In mixed culture biofilms at the inlet of the flow cell, biovolume contributed by L. monocytogenes cells, though not statistically significant, was higher than in monoculture L. monocytogenes biofilms (532% increase). In contrast, in mixed biofilms in the middle section and at the outlet, biovolume contributed by P. putida cells was much lower than in monoculture P. putida biofilms, with reductions of 183 % (middle) and 793% (outlet).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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".