Mutant prevention concentration of tigecycline for clinical isolates of Streptococcus pneumoniae and Staphylococcus aureus
Bibliographic record
Abstract
BACKGROUND: The mutant prevention concentration (MPC) reflects the antimicrobial susceptibility of the resistant mutant subpopulations present in large bacterial populations. In principle, combining the MPC with pharmacokinetic measurements can guide treatment to restrict the enrichment of resistant subpopulations, just as the MIC is used with pharmacokinetics to restrict the growth of bulk, susceptible populations. Little is known about the MPC of tigecycline, one of the more recently approved antimicrobials. Tigecycline is particularly interesting because it shows good activity against Gram-positive pathogens. METHODS: MPCs were determined using tigecycline-containing agar plates for clinical isolates of Streptococcus pneumoniae (n=47), MRSA (n=50) and MSSA (n=50). RESULTS: Trypticase soy agar containing sheep red blood cells, commonly used for the growth of S. pneumoniae, gave tigecycline MPC90 values that were two orders of magnitude higher than expected. The addition of agar to Todd-Hewitt broth (solidified Todd-Hewitt broth) allowed the high-density growth of S. pneumoniae in the absence of red blood cells and lowered the MPC90 of tigecycline by 100-fold to 0.5 mg/L. The addition of red blood cells to solidified Todd-Hewitt broth raised the MPC90 by 100-fold. Thus, red blood cells reduce the efficacy of tigecycline against S. pneumoniae. The growth of Staphylococcus aureus was not sensitive to red blood cells; values of MPC90 were 2 and 4 mg/L for MSSA and MRSA, respectively. CONCLUSIONS: Values of MPC constitute a concentration threshold for restricting the emergence of tigecycline resistance that can now be used in animal studies to determine pharmacodynamic thresholds. The off-label treatment of S. pneumoniae blood infections with tigecycline may require caution due to blood-cell-mediated interference with the antimicrobial.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".