Non-thermal Plasma Exposure Rapidly Attenuates Bacterial AHL-Dependent Quorum Sensing and Virulence.

The antimicrobial activity of atmospheric pressure non-thermal plasma has been exhaustively characterised, however elucidation of the interactions between biomolecules produced and utilised by bacteria and short plasma exposures are required for optimisation and clinical translation of cold plasma technology. This study characterizes the effects of non-thermal plasma exposure on acyl homoserine lactone (AHL)-dependent quorum sensing (QS). Plasma exposure of AHLs reduced the ability of such molecules to elicit a QS response in bacterial reporter strains in a dose-dependent manner. Short exposures (30-60 s) produce of a series of secondary compounds capable of eliciting a QS response, followed by the complete loss of AHL-dependent signalling following longer exposures. UPLC-MS analysis confirmed the time-dependent degradation of AHL molecules and their conversion into a series of by-products. FT-IR analysis of plasma-exposed AHLs highlighted the appearance of an OH group. In vivo assessment of the exposure of AHLs to plasma was examined using a standard in vivo model. Lettuce leaves injected with the rhlI/lasI mutant PAO-MW1 alongside plasma treated N-butyryl-homoserine lactone and n-(3-oxo-dodecanoyl)-homoserine lactone, exhibited marked attenuation of virulence. This study highlights the capacity of atmospheric pressure non-thermal plasma to modify and degrade AHL autoinducers thereby attenuating QS-dependent virulence in P. aeruginosa.

Data-Driven Dynamic Modeling of Coupled Thermal and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Detector for imaging and dosimetry of laser-driven epithermal neutrons by alpha conversion

An epithermal neutron imager based on detecting alpha particles created via boron neutron capture mechanism is discussed. The diagnostic mainly consists of a mm thick Boron Nitride (BN) sheet (as an alpha converter) in contact with a non-borated cellulose nitride film (LR115 type-II) detector. While the BN absorbs the neutrons in the thermal and epithermal ranges, the fast neutrons register insignificantly on the detector due to their low neutron capture and recoil cross-sections. The use of solid-state nuclear track detectors (SSNTD), unlike image plates, micro-channel plates and scintillators, provide safeguard from the x-rays, gamma-rays and electrons. The diagnostic was tested on a proof-of-principle basis, in front of a laser driven source of moderated neutrons, which suggests the potential of using this diagnostic (BN+SSNTD) for dosimetry and imaging applications.