Literature DB >> 21807974

Quantitative impact of neutrophils on bacterial clearance in a murine pneumonia model.

Beining Guo1, Kamilia Abdelraouf, Kimberly R Ledesma, Kai-Tai Chang, Michael Nikolaou, Vincent H Tam.   

Abstract

The rapid increase in the prevalence of antibiotic-resistant pathogens is a global problem that has challenged our ability to treat serious infections. Currently, clinical decisions on treatment are often based on in vitro susceptibility data. The role of the immune system in combating bacterial infections is unequivocal, but it is not well captured quantitatively. In this study, the impact of neutrophils on bacterial clearance was quantitatively assessed in a murine pneumonia model. In vitro time-growth studies were performed to determine the growth rate constants of Acinetobacter baumannii ATCC BAA 747 and Pseudomonas aeruginosa PAO1. The absolute neutrophil count in mice resulting from different cyclophosphamide preparatory regimens was determined. The dynamic change of bacterial (A. baumannii BAA 747) burden in mice with graded immunosuppression over 24 h was captured by a mathematical model. The fit to the data was satisfactory (r(2) = 0.945). The best-fit maximal kill rate (K(k)) of the bacterial population by neutrophils was 1.743 h(-1), the number of neutrophils necessary for 50% maximal killing was 190.8/μl, and the maximal population size was 1.8 × 10(9) CFU/g, respectively. Using these model parameter estimates, the model predictions were subsequently validated by the bacterial burden change of P. aeruginosa PAO1 at 24 h. A simple mathematical model was proposed to quantify the contribution of neutrophils to bacterial clearance and predict the bacterial growth/suppression in animals. Our results provide a novel framework to link in vitro and in vivo information and may be used to improve clinical treatment of bacterial infections.

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Year:  2011        PMID: 21807974      PMCID: PMC3186951          DOI: 10.1128/AAC.00508-11

Source DB:  PubMed          Journal:  Antimicrob Agents Chemother        ISSN: 0066-4804            Impact factor:   5.191


  17 in total

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Review 4.  Clinical impact and pathogenicity of Acinetobacter.

Authors:  M-L Joly-Guillou
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5.  Modelling time-kill studies to discern the pharmacodynamics of meropenem.

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6.  The impact of multidrug resistance on the outcomes of critically ill patients with Gram-negative bacterial pneumonia.

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  13 in total

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3.  Therapeutic Efficacy of LN-1-255 in Combination with Imipenem in Severe Infection Caused by Carbapenem-Resistant Acinetobacter baumannii.

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Journal:  Antimicrob Agents Chemother       Date:  2019-09-23       Impact factor: 5.191

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Review 5.  Multiplicity of Mathematical Modeling Strategies to Search for Molecular and Cellular Insights into Bacteria Lung Infection.

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Journal:  Front Physiol       Date:  2017-08-30       Impact factor: 4.566

Review 6.  Setting the Beta-Lactam Therapeutic Range for Critically Ill Patients: Is There a Floor or Even a Ceiling?

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7.  A Biomathematical Model of Pneumococcal Lung Infection and Antibiotic Treatment in Mice.

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8.  Dynamic Computational Model of Symptomatic Bacteremia to Inform Bacterial Separation Treatment Requirements.

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9.  Human neutrophils phagocytose and kill Acinetobacter baumannii and A. pittii.

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Journal:  Sci Rep       Date:  2017-07-04       Impact factor: 4.379

10.  A whole-body physiologically based pharmacokinetic (WB-PBPK) model of ciprofloxacin: a step towards predicting bacterial killing at sites of infection.

Authors:  Muhammad W Sadiq; Elisabet I Nielsen; Dalia Khachman; Jean-Marie Conil; Bernard Georges; Georges Houin; Celine M Laffont; Mats O Karlsson; Lena E Friberg
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