Detection of OXA-181 Carbapenemase in <i>Shigella flexneri</i>
Bibliographic record
Abstract
higella flexnerii infection leads to shigellosis, an acute gastrointestinal disease.Shigellosis affects socioeconomically disadvantaged and densely populated communities that have unsafe water, poor sanitation, and poor hygiene (1).Shigella spp.bacteria are major contributors to acute bloody diarrhea worldwide, adding to disease numbers and death in children under 5 years of age (2).The emergence of multidrug-resistant Shigella strains is a concerning trend.Multidrug-resistant strains resist multiple first-line oral antimicrobials (i.e., ampicillin, trimethoprim/sulfamethoxazole, and ciprofloxacin).The situation is further complicated by enzyme-mediated β-lactam resistance in Shigella bacteria, further impacting empiric therapy and making the isolates extensively drug-resistant (2).Although extensively drug-resistant isolates have remained susceptible to carbapenem therapy, carbapenem resistance in Shigella spp.through imipenemase-type metalloβ-lactamase, New Delhi metallo-β-Lactamase, and Verona integron-encoded metallo-β-lactamase has been reported (3,4).We report a case of OXA-181-producing S. flexneri bacteria recovered from the stool of an immunocompromised patient with B-cell acute lymphoblastic leukemia (B-ALL).OXA-181 is a subtype of the
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".