Natural freeze-thaw cycles may increase the risk associated with Salmonella contamination in surface and groundwater environments
Bibliographic record
Abstract
Groundwater contamination by bacteria poses a serious threat to our drinking water supplies. In cold climate regions, microorganisms introduced to upper soil layers by spreading of animal manure are subject to low temperatures and multiple cycles of freezing and thawing at the beginning of winter and during spring melt. We investigated the influence of temperature fluctuations around the freezing point, known as freeze-thaw (FT), on the inactivation rates, growth, and biofilm formation of a manure-isolated strain of Salmonella typhimurium. Moreover, the effects of FT on the transport characteristics of S. typhimurium in quartz sand were monitored in model porewater solutions of two different ionic strengths (IS: 10 and 100 mM KCl) and two different humic acid (HA) concentrations (1 and 5 mg/L). Increasing numbers of FT cycles were found to decrease the deposition of S. typhimurium onto quartz sand and increase the percentage of detached cells in sand-packed column experiments. Based on the calculated bacterial attachment efficiencies, the predicted minimum setback distances between the location of water supply wells and manure spreading activities are higher when the effects of FT are taken into consideration. While FT treatment significantly affected cell viability (in the presence of HA), most cells were in a viable but non-culturable (VBNC) state with compromised ability to form biofilm. This investigation demonstrates the effects of spring temperature variations in upper soil layers on S. typhimurium properties and the potential increased risk of bacterial contamination in representative aquifer environments in cold climate regions.
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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 | 0.001 |
| 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".