Impact of long-term starvation on adhesion to and biofilm formation on stainless steel 316 L and gold surfaces of Salmonella enterica serovar Typhimurium
Bibliographic record
Abstract
The objective of this study was to evaluate the effect of 3-year starvation in seawater microcosms on adhesion to and biofilm formation of two Salmonella enterica serovar Typhimurium strains on model stainless steel 316 L and gold surfaces. The bacteria were characterized in terms of morphological alteration, electrophoretic mobility, and affinity to various solvent interfaces. Scanning electron micrographs showed the appearance of coccoid and elongated cells after starvation. All stressed cells were characterized by a hyperflagellation, a significant increase in the global surface charge, and a conservation of their hydrophilic character. Epifluorescence microscopy highlighted an increase in the levels of adhered cells to stainless steel and gold surfaces after starvation stress. Confocal laser scanning microscopy produced evidence of variability between the three-dimensional biofilm architectures of the control and stressed cells on gold compared to stainless steel. The results obtained so far led us to hypothesize that the pervasiveness of nutrient deficiency in natural environments may generate new adaptation strategies for long-term starved Salmonella Typhimurium and probably create protection against other types of stress. The stress adaptation mechanisms identified in this study may induce a genetic instability and change virulence state of starved bacteria. This fundamental study provides information which may aid in the development of sanitation programs for effective pathogen removal in the food industry or from medical devices. The task is certainly complex given that several concomitant physicochemical parameters affect the adhesion to and biofilm formation on model surfaces of stressed bacteria.
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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 | 0.000 |
| 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) | 0.001 | 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".