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Extreme Acid Modulates Fitness Tradeoffs of Multidrug Efflux Pumps MdtEF-TolC and AcrAB-TolC in Escherichia coli K-12Bacterial genomes encode various multidrug efflux pumps (MDR) whose specific conditions for fitness advantage are unknown. We show that the efflux pump MdtEF-TolC, in Escherichia coli, confers a fitness advantage during exposure to extreme acid (pH 2). Our flow cytometry method revealed pH-dependent fitness tradeoffs between bile acids (a major pump substrate) and salicylic acid, a membrane-permeant aromatic acid that induces a drug-resistance regulon but depletes proton motive force (PMF). The PMF drives MdtEF-TolC and related pumps such as AcrAB-TolC. Deletion of mdtE (with loss of pump MdtEF-TolC) increased the strain’s relative fitness during growth with or without salicylate ormore »Free, publicly-accessible full text available January 1, 2022
This work presents novel techniques for tightly integrated online information fusion and planning in human-autonomy teams operating in partially known environments. Motivated by dynamic target search problems, we present a new map-based sketch interface for online soft-hard data fusion. This interface lets human collaborators efficiently update map information and continuously build their own highly flexible ad hoc dictionaries for making language-based semantic observations, which can be actively exploited by autonomous agents in optimal search and information gathering problems. We formally link these capabilities to POMDP algorithms for optimal planning under uncertainty, and develop a new Dynamically Observable Monte Carlo planningmore »
One of the primary tasks in neuroimaging is to simplify spatiotemporal scans of the brain (i.e., fMRI scans) by partitioning the voxels into a set of functional brain regions. An emerging line of research utilizes multiple fMRI scans, from a group of subjects, to calculate a single group consensus functional partition. This consensus-based approach is promising as it allows the model to improve the signalto-noise ratio in the data. However, existing approaches are primarily non-parametric which poses problems when new samples are introduced. Furthermore, most existing approaches calculate a single partition for multiple subjects which fails to account for themore »
Abstract—Networks have entered the mainstream lexicon over the last ten years. This coincides with the pervasive use of networks in a host of disciplines of interest to industry and academia, including biology, neurology, genomics, psychology, social sciences, economics, psychology, and cyber-physical systems and infrastructure. Several dozen journals and conferences regularly contain articles related to networks. Yet, there are no general purpose cyberinfrastructures (CI) that can be used across these varied disciplines and domains. Furthermore, while there are scientific gateways that include some network science capabilities for particular domains (e.g., biochemistry, genetics), there are no general-purpose network-based scientific gateways. In thismore »