Low-Virulence <i>Citrobacter</i> Species Encode Resistance to Multiple Antimicrobials
Bibliographic record
Abstract
Citrobacter spp. are gram-negative commensal bacteria that infrequently cause serious nosocomial infections in compromised hosts. They are often resistant to cephalosporins due to overexpression of their chromosomal beta-lactamase. During a recent study of multidrug-resistant Enterobacteriaceae (MDRE) in solid-organ transplant patients, we found that almost half of patients colonized with MDRE carried one or more cefpodoxime-resistant Citrobacter freundii, Citrobacter braakii, or Citrobacter amalonaticus strains. Pulsed-field gel electrophoresis showed that 36 unique strains of Citrobacter were present among 32 patients. Genetic and phenotypic analysis of the resistance mechanisms of these bacteria showed that the extended-spectrum beta-lactamase (ESBL) SHV-5 or SHV-12 was encoded by 8 strains (26%) and expressed by 7 strains (19%). A number of strains were resistant to other drug classes, including aminoglycosides (28%), trimethoprim-sulfamethoxazole (31%), and fluoroquinolones (8%). PCR and DNA analysis of these multiresistant strains revealed the presence of class I integrons, including the first integrons reported for C. braakii and C. amalonaticus. The integrons encoded aminoglycoside resistance, trimethoprim resistance, or both. Despite the prevalence of MDR Citrobacter spp. in our solid-organ transplant patients, only a single infection with a colonizing strain was recorded over 18 months. Low-virulence Citrobacter spp., which can persist in the host for long periods, could influence pathogen evolution by accumulation of genes encoding resistance to multiple antimicrobial classes.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".