The mutant-prevention concentration concept and its application to Staphylococcus aureus
Bibliographic record
Abstract
Staphylococcus aureus is a ubiquitous organism causing world-wide morbidity and mortality.This species readily develops resistance to antimicrobial agents.Current dosing strategies are based, in part, on minimum inhibitory concentrations (MICs).This susceptibility test fails to detect the presence of first-step resistant mutants often present in large heterogeneous populations of infecting bacteria.Dosing strategies based on MIC results may, in fact, allow for the selective proliferation of resistant subpopulations.The mutant-prevention concentration (MPC) is the drug concentration at which all first-step resistant mutants will be eradicated along with the susceptible cells.Determination of the mutant-selection window (MSW) is possible using MIC and MPC data.When considered together with achievable drug concentrations in human bodily sites, the MSW helps determine which antimicrobials are likely to select for resistance.MIC and MPC testing on clinical isolates of methicillin-susceptible (MSSA) and -resistant (MRSA) S. aureus was performed.Characterization via the polymerase chain reaction, sequencing, and electron microscopy (EM) was done on selected organisms recovered from MPC studies (MPC-recovered).MIC and MPC testing was performed on organisms isolated sequentially from patients with recurring S. aureus infections.Pulsed field gel electrophoresis was performed on these sequential isolates.Based on the MIC and the MPC values, the most potent agents for systemic MSSA and MRSA infections are gemifloxacin and vancomycin, respectively.Retesting MPC-recovered populations by the MIC showed increased MIC results compared to the parent populations.Macrolide-resistance genes were discovered in S. aureus MPC-recovered populations; in contrast, parental isolates lacked these resistance determinants.EM revealed an increase in cell wall thickness of a vancomycin MPCrecovered population compared to its parental population.Moxifloxacin and vancomycin had the lowest and narrowest MSWs for systemic MSSA and MRSA allowing me this special experience as his graduate student.Also, I would like to thank Pfizer Canada for the research grant that made this study possible.An appreciation goes out to all my committee members including Dr. Deneer, Dr. Sanche, Dr.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".