Isolation of five Enterobacteriaceae species harbouring blaNDM-1 and mcr-1 plasmids from a single paediatric patient
Bibliographic record
Abstract
In Argentina, NDM metallo-β-lactamase was first reported in 2013. By now, it has disseminated throughout the country in diverse Gram negative bacteria. Here, we report the case of a paediatric patient that underwent a 1-year hospitalisation due to erythrodermic psoriasis in 2014 and received multiple antimicrobial treatments. During his stay, five isolates were obtained from rectal swabs (rs) or blood culture (bc) suspicious of carbapenemase production: a K. quasipneumoniae subsp. quasipneumoniae (rs), Citrobacter freundii (rs), Escherichia coli (bc), Enterobacter cloacae (rs), and a Serratia marcescens (bc). The isolates were studied with broth microdilution, biparental conjugation and plasmid and whole genome sequencing (Illumina). All isolates harboured an 138,998-bp type 1 IncC plasmid that carried blaNDM-1, bleMBL, blaCMY-6, rmtC, aac(6')-Ib, and sul1 resistance genes. Additionally, the blaNDM-plasmids contained ISKpn8 an insertion sequence previously described as associated only to blaKPC. One isolate, a colistin-resistant E. coli, also carried a mcr-1-containing an IncI2 plasmid, which did not harbour additional resistance. The whole genome of K. quasipneumoniae subsp. quasipneumoniae isolate was fully sequenced. This isolate harboured, additionally to blaNDM, three plasmid-mediated quinolone resistance genes: qnrB4, qnrB52 and aac(6')-Ib-cr1. The E. cloacae isolate also harboured qnrA1. These findings alert to the underestimated horizontal dissemination of multidrug-resistant plasmids limiting treatment options with last resort antimicrobials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".