Kinetics of biofilm formation and desiccation survival of<i>Listeria monocytogenes</i>in single and dual species biofilms with<i>Pseudomonas fluorescens</i>,<i>Serratia proteamaculans</i>or<i>Shewanella baltica</i>on food-grade stainless steel surfaces
Bibliographic record
Abstract
This study investigated the dynamics of static biofilm formation (100% RH, 15 °C, 48-72 h) and desiccation survival (43% RH, 15 °C, 21 days) of Listeria monocytogenes, in dual species biofilms with the common spoilage bacteria, Pseudomonas fluorescens, Serratia proteamaculans and Shewanella baltica, on the surface of food grade stainless steel. The Gram-negative bacteria reduced the maximum biofilm population of L. monocytogenes in dual species biofilms and increased its inactivation during desiccation. However, due to the higher desiccation resistance of Listeria relative to P. fluorescens and S. baltica, the pathogen survived in greater final numbers. In contrast, S. proteamaculans outcompeted the pathogen during the biofilm formation and exhibited similar desiccation survival, causing the N21 days of Serratia to be ca 3 Log10(CFU cm(-2)) greater than that of Listeria in the dual species biofilm. Microscopy revealed biofilm morphologies with variable amounts of exopolymeric substance and the presence of separate microcolonies. Under these simulated food plant conditions, the fate of L. monocytogenes during formation of mixed biofilms and desiccation depended on the implicit characteristics of the co-cultured bacterium.
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 | 0.000 |
| 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".