Nursing Peer Review: Raising the Bar on Quality & Safety/A Hospital's Innovative Process for Improving Patient Outcomes
Bibliographic record
Abstract
Shiga toxin (Stx) is the definitive virulence factor of Shiga toxin-producing Escherichia coli (STEC). Stx variants are currently organized into a taxonomic system of three Stx1 (a, c, and d) and seven Stx2 (a, b, c, d, e, f, and g) subtypes. In this study, seven STEC isolates from food and clinical samples possessing <i>stx2</i> sequences that do not fit current Shiga toxin taxonomy were identified. Genome assemblies of the STEC strains were created from Oxford Nanopore and Illumina sequence data. The presence of atypical <i>stx2</i> sequences was confirmed by Sanger sequencing, as were Stx2 expression and cytotoxicity. A strain of O157:H7 was found to possess <i>stx1a</i> and a truncated <i>stx2a</i>, which were originally misidentified as an atypical <i>stx</i><sub>2</sub>. Two strains possessed unreported variants of Stx2a (O8:H28) and Stx2b (O146:H21). In four of the strains, we found three Stx subtypes that are not included in the current taxonomy. Stx2h (O170:H18) was identified in a Canadian sprout isolate; this subtype has only previously been reported in STEC from Tibetan Marmots. Stx2o (O85:H1) was identified in a clinical isolate. Finally, Stx2j (O158:H23 and O33:H14) was found in lettuce and clinical isolates. The results of this study expand the number of known Stx subtypes, the range of STEC serotypes, and isolation sources in which they may be found. The presence of the Stx2j and Stx2o in clinical isolates of STEC indicates that strains carrying these variants are potential human pathogens.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".