Induction of <i>Escherichia coli</i> O157:H7 into the viable but non‐culturable state by chloraminated water and river water, and subsequent resuscitation
Bibliographic record
Abstract
Induction of culturable Escherichia coli O157:H7 cells into a viable but non-culturable (VBNC) state by chloraminated tap water was carefully investigated; as many as 90% of initial cells entered into a VBNC state within 15 min, compared with 14% in river water within 14 weeks. To understand what specific stresses may induce E. coli O157:H7 into a VBNC state, chloraminated tap water, autoclaved river water, and media with known ingredients (PBS buffer and deionized water) at 4°C or 25°C were used to examine induction efficiency. Chloramination alone, or the combination of starvation with either low temperature or osmotic pressure, induced E. coli O157:H7 into a VBNC state, while starvation alone did not induce the bacteria into a VBNC state within 1.5 years. The mRNA of the rfbE and fliC genes was detected in the 10-month-old VBNC cells induced by river water, confirming the viability of E. coli O157:H7 VBNC cells. The VBNC cells induced by chloraminated water and the 10-month-old VBNC cells induced by river water were first resuscitated using autoinducers produced by E. coli O157:H7 itself in a serum-based medium; the VBNC cells of bovine isolates recovered more efficiently compared with those of clinical isolates. These results demonstrate a potential health risk of VBNC E. coli O157:H7 in environmental water and the utility of monitoring viable E. coli O157:H7 including VBNC cells based on the mRNA of the rfbE and fliC genes.
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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 | 0.001 |
| 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".