8 research outputs found
Efficacy of Combined Therapy with Amantadine, Oseltamivir, and Ribavirin In Vivo against Susceptible and Amantadine-Resistant Influenza A Viruses
The limited efficacy of existing antiviral therapies for influenza – coupled with widespread baseline antiviral resistance – highlights the urgent need for more effective therapy. We describe a triple combination antiviral drug (TCAD) regimen composed of amantadine, oseltamivir, and ribavirin that is highly efficacious at reducing mortality and weight loss in mouse models of influenza infection. TCAD therapy was superior to dual and single drug regimens in mice infected with drug-susceptible, low pathogenic A/H5N1 (A/Duck/MN/1525/81) and amantadine-resistant 2009 A/H1N1 influenza (A/California/04/09). Treatment with TCAD afforded >90% survival in mice infected with both viruses, whereas treatment with dual and single drug regimens resulted in 0% to 60% survival. Importantly, amantadine had no activity as monotherapy against the amantadine-resistant virus, but demonstrated dose-dependent protection in combination with oseltamivir and ribavirin, indicative that amantadine's activity had been restored in the context of TCAD therapy. Furthermore, TCAD therapy provided survival benefit when treatment was delayed until 72 hours post-infection, whereas oseltamivir monotherapy was not protective after 24 hours post-infection. These findings demonstrate in vivo efficacy of TCAD therapy and confirm previous reports of the synergy and broad spectrum activity of TCAD therapy against susceptible and resistant influenza strains in vitro
Rapid Cytometric Antibiotic Susceptibility Testing Utilizing Adaptive Multidimensional Statistical Metrics
Flow cytometry holds promise to accelerate
antibiotic susceptibility
determinations; however, without robust multidimensional statistical
analysis, general discrimination criteria have remained elusive. In
this study, a new statistical method, probability binning signature
quadratic form (PB-sQF), was developed and applied to analyze flow
cytometric data of bacterial responses to antibiotic exposure. Both
sensitive lab strains (<i>Escherichia coli</i> and <i>Pseudomonas aeruginosa</i>) and a multidrug resistant, clinically
isolated strain (<i>E. coli</i>) were incubated with the
bacteria-targeted dye, maltohexaose-conjugated IR786, and each of
many bactericidal or bacteriostatic antibiotics to identify changes
induced around corresponding minimum inhibition concentrations (MIC).
The antibiotic-induced damages were monitored by flow cytometry after
1-h incubation through forward scatter, side scatter, and fluorescence
channels. The 3-dimensional differences between the flow cytometric
data of the no-antibiotic treated bacteria and the antibiotic-treated
bacteria were characterized by PB-sQF into a 1-dimensional linear
distance. A 99% confidence level was established by statistical bootstrapping
for each antibiotic-bacteria pair. For the susceptible <i>E.
coli</i> strain, statistically significant increments from this
99% confidence level were observed from 1/16x MIC to 1x MIC for all
the antibiotics. The same increments were recorded for <i>P.
aeruginosa</i>, which has been reported to cause difficulty in
flow-based viability tests. For the multidrug resistant <i>E.
coli</i>, significant distances from control samples were observed
only when an effective antibiotic treatment was utilized. Our results
suggest that a rapid and robust antimicrobial susceptibility test
(AST) can be constructed by statistically characterizing the differences
between sample and control flow cytometric populations, even in a
label-free scheme with scattered light alone. These distances vs paired
controls coupled with rigorous statistical confidence limits offer
a new path toward investigating initial biological responses, screening
for drugs, and shortening time to result in antimicrobial sensitivity
testing