Effective antibiotic use that minimizes treatment failures remains a challenge. A better understanding of how bacterial populations respond to antibiotics is necessary. Previous studies of large bacterial populations established the deterministic framework of pharmacodynamics. Here, characterizing the dynamics of population extinction, we demonstrated the stochastic nature of eradicating bacteria with antibiotics. Antibiotics known to kill bacteria (bactericidal) induced population fluctuations. Thus, at high antibiotic concentrations, the dynamics of bacterial clearance were heterogeneous. At low concentrations, clearance still occurred with a non-zero probability. These striking outcomes of population fluctuations were well captured by our probabilistic model. Our model further suggested a strategy to facilitate eradication by increasing extinction probability. We experimentally tested this prediction for antibiotic-susceptible and clinically-isolated resistant bacteria. This new knowledge exposes fundamental limits in our ability to predict bacterial eradication. Additionally, it demonstrates the potential of using antibiotic concentrations that were previously deemed inefficacious to eradicate bacteria.

Measurement of measles virus-specific IgG is used to assess presumptive evidence of immunity among immunocompetent individuals with uncertain immune or vaccination status. False-negative test results may lead to unnecessary quarantine and exclusion from activities such as employment, education, and travel or result in unnecessary revaccination. In contrast, false-positive results may fail to identify susceptible individuals and promote spread of disease by those who are exposed and unprotected. To better understand the performance characteristics of tests to detect measles IgG, we compared five widely used, commercially available measles IgG test platforms using a set of 223 well-characterized serum samples. Measles virus neutralizing antibodies were also measured by in vitro plaque reduction neutralization, the gold standard method, and compared to IgG test results. Discrepant results were observed for samples in the low-positive ranges of the most sensitive tests, but there was good agreement across platforms for IgG-negative sera and for samples with intermediate to high levels of IgG. False-negative test results occurred in approximately 11% of sera, which had low levels of neutralizing antibody.

Background Aminoglycosides are potent bactericidal antibiotics naturally produced by soil microorganisms and are commonly used in agriculture. Exposure to these antibiotics has the potential to cause shifts in the microorganisms that impact plant health. The systematic review described in this protocol will compile and synthesize literature on soil and plant root-associated microbiota, with special attention to aminoglycoside exposure. The systematic review should provide insight into how the soil and plant microbiota are impacted by aminoglycoside exposure with specific attention to the changes in the overall species richness and diversity (microbial composition), changes of the resistome (i.e. the changes in the quantification of resistance genes), and maintenance of plant health through suppression of pathogenic bacteria. Moreover, the proposed contribution will provide comprehensive information about data available to guide future primary research studies. This systematic review protocol is based on the question, “What is the impact of aminoglycoside exposure on the soil and plant root-associated microbiota?”. Methods A boolean search of academic databases and specific websites will be used to identify research articles, conference presentations and grey literature meeting the search criteria. All search results will be compiled and duplicates removed before title and abstract screening. Two reviewers will screen all the included titles and abstracts using a set of predefined inclusion criteria. Full-texts of all titles and abstracts meeting the eligibility criteria will be screened independently by two reviewers. Inclusion criteria will describe the eligible soil and plant root-associated microbiome populations of interest and eligible aminoglycosides constituting our exposure. Study validity will be evaluated using the CEE Critical Appraisal Tool Version 0.2 (Prototype) to evaluate the risk of bias in publications. Data from studies with a low risk of bias will be extracted and compiled into a narrative synthesis and summarized into tables and figures. If sufficient evidence is available, findings will be used to perform a meta-analysis.

Effective antibiotic use that minimizes treatment failures remains a challenge. A better understanding of how bacterial populations respond to antibiotics is necessary. Previous studies of large bacterial populations established the deterministic framework of pharmacodynamics. Here, characterizing the dynamics of population extinction, we demonstrated the stochastic nature of eradicating bacteria with antibiotics. Antibiotics known to kill bacteria (bactericidal) induced population fluctuations. Thus, at high antibiotic concentrations, the dynamics of bacterial clearance were heterogeneous. At low concentrations, clearance still occurred with a non-zero probability. These striking outcomes of population fluctuations were well captured by our probabilistic model. Our model further suggested a strategy to facilitate eradication by increasing extinction probability. We experimentally tested this prediction for antibiotic-susceptible and clinicallyisolated resistant bacteria. This new knowledge exposes fundamental limits in our ability to predict bacterial eradication. Additionally, it demonstrates the potential of using antibiotic concentrations that were previously deemed inefficacious to eradicate bacteria.