Antimicrobial susceptibility and genetic mechanisms of resistance of <i>Ureaplasma</i> isolates in North America between 2012 and 2023
Bibliographic record
Abstract
ABSTRACT We analyzed antimicrobial susceptibilities of 415 Ureaplasma isolates from various sample types derived from different regions of the United States and Canada from 2012 to 2023 and investigated the genetic mechanisms of antimicrobial resistance. Minimum inhibitory concentration (MIC) ranges for erythromycin, tetracycline, and levofloxacin were 0.063–256, 0.016–64, and 0.063–32 µg/mL, respectively. MIC 50 values for erythromycin, tetracycline, and levofloxacin were 2, 0.25, and 1 µg/mL, and MIC 90 values were 4, 1, and 2 µg/mL, respectively. According to Clinical and Laboratory Standards Institute breakpoints, there were 61 (14.7%) isolates resistant to one or more drugs, and resistance rates for erythromycin, tetracycline, and levofloxacin were 2.4% (10/415), 6.5% (27/413), and 6.7% (28/415), respectively. Four isolates (1.0%) were resistant to two drugs. Mutations in domain V of 23S rRNA, mainly A2058G ( Escherichia coli numbering), and/or in the rpl D gene encoding ribosomal protein L4 were identified in most erythromycin-resistant isolates. Tet (M) was detected in all isolates with tetracycline MIC ≥4 µg/mL but absent in 64.7% (11/17) of isolates with MIC of 2 µg/mL. For fluoroquinolone-resistant isolates, C248T (S83L) and G259A (E87K) mutations in parC were identified in most cases (23/26). In summary, erythromycin, tetracycline, and levofloxacin are still effective in vitro against most Ureaplasma isolates in North America.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".