Facultative Anaerobes Shape Multispecies Biofilms Composed of Meat Processing Surface Bacteria and Escherichia coli O157:H7 or Salmonella enterica Serovar Typhimurium
Bibliographic record
Abstract
Results of this study demonstrate that Salmonella enterica serovar Typhimurium and E. coli O157:H7 can integrate into biofilms when cocultured with bacteria from meat plant processing surfaces. However, the degree of biofilm formation for both pathogens was substantially reduced in the presence of the competing microbiota, with S. Typhimurium more greatly affected than E. coli O157:H7. The expression of extracellular determinants such as curli and cellulose appears to be less important for biofilm formation of the pathogens in multispecies cultures than in monoculture. In contrast to previous reports regarding food processing surface bacteria, data collected here also demonstrate that facultative anaerobes may have a competitive edge over strict aerobes in establishing multispecies biofilms. It would be important to take into account the presence of background bacteria when evaluating the potential persistence of a pathogen in food processing facilities.
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 | 0.000 | 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 | 0.001 |
| 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".