Inter- and intra-species interactions between meat plant environmental bacteria and a non-biofilm-forming Escherichia coli O157:H7 strain in co-culture biofilms
Bibliographic record
Abstract
This study evaluated the impact of meat-processing environmental bacteria (MPB) on biofilm formation by Escherichia coli O157:H7 in dual-species cultures. Biofilm development by 50 MPB and E. coli O157:H7 was assessed using crystal violet staining. Four MPB and E. coli O157:H7 combinations were evaluated further for viable cell numbers. A chlorinated alkaline agent and a quaternary ammonium-based agent were evaluated for their ability to remove biofilms. The E. coli O157:H7 strain was a non-biofilm former. In dual-species biofilms, if the companion MPB did not produce detectable biofilm, then the pairing did not produce measurable biofilms either. The interaction effect between MPB and E. coli O157:H7 was predominantly no-effect (neutral). Among the four MPB isolates tested by viable cell enumeration method, only generic E. coli genotype 136 reduced viable numbers of E. coli O157:H7 in dual-strain biofilm. Sequential treatment with cleaning and sanitizing treatment provided a better removal of biofilm than a single-agent treatment.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 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".