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ATCC
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Millipore
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Becton Dickinson
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ATCC
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Image Search Results
Journal: Antimicrobial Agents and Chemotherapy
Article Title: Identifying and mathematically modeling the time-course of extracellular metabolic markers associated with resistance to ceftolozane/tazobactam in Pseudomonas aeruginosa
doi: 10.1128/aac.01081-23
Figure Lengend Snippet: Heatmap with hierarchical clustering ( A–E ) of dynamic metabolite profiles, which correlated with the total bacterial population, resistant subpopulation, and/or the log 10 -change of the total population (<-0.6 or >0.6, shaded green) of P. aeruginosa CW41 challenged with ceftolozane-tazobactam (C/T) in a hollow-fiber infection model ( n = 5). Metabolites notated with ** had MSI level 1 identification.
Article Snippet: A hypermutable P. aeruginosa clinical isolate, CW41, was challenged with ceftolozane-tazobactam (Zerbaxa, MSD, Australia) in the
Techniques: Infection
Journal: Antimicrobial Agents and Chemotherapy
Article Title: Identifying and mathematically modeling the time-course of extracellular metabolic markers associated with resistance to ceftolozane/tazobactam in Pseudomonas aeruginosa
doi: 10.1128/aac.01081-23
Figure Lengend Snippet: Population model fits from the mathematical modeling of ornithine (panel B) and arginine (panel C); extracellular metabolites related to the total bacterial population of P. aeruginosa CW41 (panel A) challenged with continuous infusion (CI) regimens of ceftolozane-tazobactam (C/T) in a hollow-fiber infection model ( n =5).
Article Snippet: A hypermutable P. aeruginosa clinical isolate, CW41, was challenged with ceftolozane-tazobactam (Zerbaxa, MSD, Australia) in the
Techniques: Infection
Journal: Antimicrobial Agents and Chemotherapy
Article Title: Identifying and mathematically modeling the time-course of extracellular metabolic markers associated with resistance to ceftolozane/tazobactam in Pseudomonas aeruginosa
doi: 10.1128/aac.01081-23
Figure Lengend Snippet: Population model fits from the mathematical modeling of D-ribose 5-phosphate (panel B), trehalose 6-phosphate (panel C), and D-sedoheptulose 7-phosphate (panel D); extracellular metabolites related to the resistant subpopulation of P. aeruginosa CW41 (panel A) challenged with continuous infusion (CI) regimens of ceftolozane-tazobactam (C/T) in a hollow-fiber infection model ( n = 5).
Article Snippet: A hypermutable P. aeruginosa clinical isolate, CW41, was challenged with ceftolozane-tazobactam (Zerbaxa, MSD, Australia) in the
Techniques: Infection
Journal: Antimicrobial Agents and Chemotherapy
Article Title: Identifying and mathematically modeling the time-course of extracellular metabolic markers associated with resistance to ceftolozane/tazobactam in Pseudomonas aeruginosa
doi: 10.1128/aac.01081-23
Figure Lengend Snippet: Parameter estimates of the mathematical models describing the relationship between measured extracellular metabolites and the bacterial pharmacodynamic data of P. aeruginosa CW41 challenged with ceftolozane-tazobactam in the hollow-fiber infection model
Article Snippet: A hypermutable P. aeruginosa clinical isolate, CW41, was challenged with ceftolozane-tazobactam (Zerbaxa, MSD, Australia) in the
Techniques: Infection
Journal: Journal of Antimicrobial Chemotherapy
Article Title: Evaluation of temocillin efficacy against KPC-2-producing Klebsiella pneumoniae isolates in a hollow-fibre infection model
doi: 10.1093/jac/dkae027
Figure Lengend Snippet: Pharmacokinetic profiles in the HFIM after dosages of temocillin 2 g q8h. (a) The solid line shows the predicted concentrations and open circles the observed concentrations. (b) Scatterplot showing observed versus predicted antimicrobial concentrations. The open circles and the solid line represent individual observed-predicted data points and the linear regression of observed/predicted values, respectively.
Article Snippet: Molecular typing and characterization of the antimicrobial resistance determinants of the clinical isolates and those derived from the
Techniques: