To sonicate or not to sonicate PM filters: Reactive Oxygen Species generation upon ultrasonic irradiation

In aerosol research, a common approach for the collection of particulate matter (PM) is the use of filters in order to obtain sufficient material to undertake analysis. For subsequent chemical and toxicological analyses, in most of cases the PM needs to be extracted from the filters. Sonication is commonly used to most efficiently extract the PM from the filters. Extraction protocols generally involve 10 - 60 min of sonication. The energy of ultrasonic waves causes the formation and collapse of cavitation bubbles in the solution. Inside the collapsing cavities the localised temperatures and pressures can reach extraordinary values. Although fleeting, such conditions can lead to pyrolysis of the molecules present inside the cavitation bubbles (gases dissolved in the liquid and solvent vapours), which results in the production of free radicals and the generation of new compounds formed by reactions with these free radicals. For example, simple sonication of pure water will result in the formation of detectable levels of hydroxyl radicals. As hydroxyl radicals are recognised as playing key roles as oxidants in the atmosphere the extraction of PM from filters using sonication is therefore problematic. Sonication can result in significant chemical and physical changes to PM through thermal degradation and other reactions. In this article, an overview of sonication technique as used in aerosol research is provided, the capacity for radical generation under these conditions is described and an analysis is given of the impact of sonication-derived free radicals on three molecular probes commonly used by researchers in this field to detect Reactive Oxygen Species in PM.

Effects of biodiesel chemical composition on the chemical and physical properties of the primary and secondary diesel particulate matter

This thesis improves our insight towards the effects of using biodiesels on the particulate matter emission of diesel engines and contributes to our understanding of their potential adverse health effects. The novelty of this project is the use of biodiesel fuel with controlled chemical composition that enables us to relate changes of physiochemical properties of particles to specific properties of the biodiesel. For the first time, the possibility of a correlation of the volatility and the Reactive Oxygen Species concentration of the particles is investigated versus the saturation, oxygen content and carbon chain length of the fuel.

Effect of atmospheric aging on volatility and reactive oxygen species of biodiesel exhaust nano-particles

In the prospect of limited energy resources and climate change, effects of alternative biofuels on primary emissions are being extensively studied. Our two recent studies have shown that biodiesel fuel composition has a significant impact on primary particulate matter emissions. It was also shown that particulate matter caused by biodiesels was substantially different from the emissions due to petroleum diesel. Emissions appeared to have higher oxidative potential with the increase in oxygen content and decrease of carbon chain length and unsaturation levels of fuel molecules. Overall, both studies concluded that chemical composition of biodiesel is more important than its physical properties in controlling exhaust particle emissions. This suggests that the atmospheric aging processes, including secondary organic aerosol formation, of emissions from different fuels will be different as well. In this study, measurements were conducted on a modern common-rail diesel engine. To get more information on realistic properties of tested biodiesel particulate matter once they are released into the atmosphere, particulate matter was exposed to atmospheric oxidants, ozone and ultra-violet light; and the change in their properties was monitored for different biodiesel blends. Upon the exposure to oxidative agents, the chemical composition of the exhaust changes. It triggers the cascade of photochemical reactions resulting in the partitioning of semi-volatile compounds between the gas and particulate phase. In most of the cases, aging lead to the increase in volatility and oxidative potential, and the increment of change was mainly dependent on the chemical composition of fuels as the leading cause for the amount and the type of semi-volatile compounds present in the exhaust.

Dynamic, invivo, real-time detection of retinal oxidative status in a model of elevated intraocular pressure using a novel, reversibly responsive, profluorescent nitroxide probe

Changes to the redox status of biological systems have been implicated in the pathogenesis of a wide variety of disorders including cancer, Ischemia-reperfusion (I/R) injury and neurodegeneration. In times of metabolic stress e.g. ischaemia/reperfusion, reactive oxygen species (ROS) production overwhelms the intrinsic antioxidant capacity of the cell, damaging vital cellular components. The ability to quantify ROS changes in vivo, is therefore essential to understanding their biological role. Here we evaluate the suitability of a novel reversible profluorescent probe containing a redox-sensitive nitroxide moiety (methyl ester tetraethylrhodamine nitroxide, ME-TRN), as an in vivo, real-time reporter of retinal oxidative status. The reversible nature of the probe's response offers the unique advantage of being able to monitor redox changes in both oxidizing and reducing directions in real time. After intravitreal administration of the ME-TRN probe, we induced ROS production in rat retina using an established model of complete, acute retinal ischaemia followed by reperfusion. After restoration of blood flow, retinas were imaged using a Micron III rodent fundus fluorescence imaging system, to quantify the redox-response of the probe. Fluorescent intensity declined during the first 60 min of reperfusion. The ROS-induced change in probe fluorescence was ameliorated with the retinal antioxidant, lutein. Fluorescence intensity in non-Ischemia eyes did not change significantly. This new probe and imaging technology provide a reversible and real-time response to oxidative changes and may allow the in vivo testing of antioxidant therapies of potential benefit to a range of diseases linked to oxidative stress

Atmospheric pressure gas plasma-induced colorectal cancer cell death is mediated by Nox2-ASK1 apoptosis pathways and oxidative stress is mitigated by Srx-Nrf2 anti-oxidant system

Atmospheric pressure gas plasma (AGP) generates reactive oxygen species (ROS) that induce apoptosis in cultured cancer cells. The majority of cancer cells develop a ROS-scavenging anti-oxidant system regulated by Nrf2, which confers resistance to ROS-mediated cancer cell death. Generation of ROS is involved in the AGP-induced cancer cell death of several colorectal cancer cells (Caco2, HCT116 and SW480) by activation of ASK1-mediated apoptosis signaling pathway without affecting control cells (human colonic sub-epithelial myofibroblasts; CO18, human fetal lung fibroblast; MRC5 and fetal human colon; FHC). However, the identity of an oxidase participating in AGP-induced cancer cell death is unknown. Here, we report that AGP up-regulates the expression of Nox2 (NADPH oxidase) to produce ROS. RNA interference designed to target Nox2 effectively inhibits the AGP-induced ROS production and cancer cell death. In some cases both colorectal cancer HT29 and control cells showed resistance to AGP treatment. Compared to AGP-sensitive Caco2 cells, HT29 cells show a higher basal level of the anti-oxidant system transcriptional regulator Nrf2 and its target protein sulfiredoxin (Srx) which are involved in cellular redox homeostasis. Silencing of both Nrf2 and Srx sensitized HT29 cells, leads to ROS overproduction and decreased cell viability. This indicates that in HT29 cells, Nrf2/Srx axis is a protective factor against AGP-induced oxidative stress. The inhibition of Nrf2/Srx signaling should be considered as a central target in drug-resistant colorectal cancer treatments.

hSSB1 (NABP2/ OBFC2B) is required for the repair of 8-oxo-guanine by the hOGG1-mediated base excision repair pathway

The maintenance of genome stability is essential to prevent loss of genetic information and the development of diseases such as cancer. One of the most common forms of damage to the genetic code is the oxidation of DNA by reactive oxygen species (ROS), of which 8-oxo-7,8-dihydro-guanine (8-oxoG) is the most frequent modification. Previous studies have established that human single-stranded DNA-binding protein 1 (hSSB1) is essential for the repair of double-stranded DNA breaks by the process of homologous recombination. Here we show that hSSB1 is also required following oxidative damage. Cells lacking hSSB1 are sensitive to oxidizing agents, have deficient ATM and p53 activation and cannot effectively repair 8-oxoGs. Furthermore, we demonstrate that hSSB1 forms a complex with the human oxo-guanine glycosylase 1 (hOGG1) and is important for hOGG1 localization to the damaged chromatin. In vitro, hSSB1 binds directly to DNA containing 8-oxoguanines and enhances hOGG1 activity. These results underpin the crucial role hSSB1 plays as a guardian of the genome.

Artificial Neural Network Based Automatic Emergency Landing Site Selection for UAVs and Highly Automated Aircraft

In this report an artificial neural network (ANN) based automated emergency landing site selection system for unmanned aerial vehicle (UAV) and general aviation (GA) is described. The system aims increase safety of UAV operation by emulating pilot decision making in emergency landing scenarios using an ANN to select a safe landing site from available candidates. The strength of an ANN to model complex input relationships makes it a perfect system to handle the multicriteria decision making (MCDM) process of emergency landing site selection. The ANN operates by identifying the more favorable of two landing sites when provided with an input vector derived from both landing site's parameters, the aircraft's current state and wind measurements. The system consists of a feed forward ANN, a pre-processor class which produces ANN input vectors and a class in charge of creating a ranking of landing site candidates using the ANN. The system was successfully implemented in C++ using the FANN C++ library and ROS. Results obtained from ANN training and simulations using randomly generated landing sites by a site detection simulator data verify the feasibility of an ANN based automated emergency landing site selection system.

Biophysical response of living cells to boron nitride nanoparticles: Uptake mechanism and bio-mechanical characterization

Boron nitride nanomaterials have attracted significant interest due to their superior chemical and physical properties. Despite these novel properties, investigation on the interaction between boron nitride nanoparticle (BN NP) and living systems has been limited. In this study, BN NP (100–250 nm) is assessed as a promising biomaterial for medical applications. The toxicity of BN NP is evaluated by assessing the cells behaviours both biologically (MTT assay, ROS detection etc.) and physically (atomic force microscopy). The uptake mechanism of BN NP is studied by analysing the alternations in cellular morphology based on cell imaging techniques. The results demonstrate in vitro cytocompatibility of BN NP with immense potential for use as an effective nanoparticle for various bio-medical applications.

Intracellular effects of atmospheric-pressure plasmas on melanoma cancer cells

Gas discharge plasmas formed at atmospheric pressure and near room temperature have recently been shown as a promising tool for cancer treatment. The mechanism of the plasma action is attributed to generation of reactive oxygen and nitrogen species, electric fields, charges, and photons. The relative importance of different modes of action of atmospheric-pressure plasmas depends on the process parameters and specific treatment objects. Hence, an in-depth understanding of biological mechanisms that underpin plasma-induced death in cancer cells is required to optimise plasma processing conditions. Here, the intracellular factors involved in the observed anti-cancer activity in melanoma Mel007 cells are studied, focusing on the effect of the plasma treatment dose on the expression of tumour suppressor protein TP73. Over-expression of TP73 causes cell growth arrest and/or apoptosis, and hence can potentially be targeted to enhance killing efficacy and selectivity of the plasma treatment. It is shown that the plasma treatment induces dose-dependent up-regulation of TP73 gene expression, resulting in significantly elevated levels of TP73 RNA and protein in plasma-treated melanoma cells. Silencing of TP73 expression by means of RNA interference inhibited the anticancer effects of the plasma, similar to the effect of caspase inhibitor z-VAD or ROS scavenger N-acetyl cysteine. These results confirm the role of TP73 protein in dose-dependent regulation of anticancer activity of atmospheric-pressure plasmas.

Pro-apoptotic NOXA is implicated in atmospheric-pressure plasma-induced melanoma cell death

Atmospheric-pressure plasma (APP) has been successfully used to treat several types of cancers in vivo and in vitro, with the effect being primarily attributed to the generation of reactive oxygen species (ROS). However, the mechanisms by which APP induces apoptosis in cancer cells require further elucidation. In this study, the effects of APP on the expression of 500 genes in melanoma Mel007 cancer cells were examined. Pro-apoptotic phorbol-12-myristate-13-acetate-induced protein (PMAIP1), also known as NOXA, was highly expressed as a result of APP treatment in a dose-dependent manner. Blocking of ROS using scavenger NAC or silencing of NOXA gene by RNA interference inhibited the APP-induced NOXA genes upregulation and impaired caspases 3/7 mediated apoptosis, confirming the important role plasma-generated ROS species and pro-apoptotic NOXA play in APP-induced cancer cell death.

MPC controlled multirotor with suspended slung load: System architecture and visual load detection

There is an increased interest in the use of Unmanned Aerial Vehicles for load transportation from environmental remote sensing to construction and parcel delivery. One of the main challenges is accurate control of the load position and trajectory. This paper presents an assessment of real flight trials for the control of an autonomous multi-rotor with a suspended slung load using only visual feedback to determine the load position. This method uses an onboard camera to take advantage of a common visual marker detection algorithm to robustly detect the load location. The load position is calculated using an onboard processor, and transmitted over a wireless network to a ground station integrating MATLAB/SIMULINK and Robotic Operating System (ROS) and a Model Predictive Controller (MPC) to control both the load and the UAV. To evaluate the system performance, the position of the load determined by the visual detection system in real flight is compared with data received by a motion tracking system. The multi-rotor position tracking performance is also analyzed by conducting flight trials using perfect load position data and data obtained only from the visual system. Results show very accurate estimation of the load position (~5% Offset) using only the visual system and demonstrate that the need for an external motion tracking system is not needed for this task.

Influence of oxygen content of the certain types of biodiesels on particulate oxidative potential

Oxidative potential (OP) is related to the organic phase, specifically to its oxygenated organic fraction (OOA). Furthermore, the oxygen content of fuel molecules has significant influence on particulate OP. Thus, this study aimed to explore the actual dependency of the OOA and ROS to the oxygen content of the fuel. In order to reach the goal, different biodiesels blends, with various ranges of oxygen content; have been employed. The compact time of flight aerosol mass spectrometer (c-ToF AMS) enabled better identification of OOA. ROS monitored by using two assays: DTT and BPEA-nit. Despite emitting lower mass, both assays agreed that oxygen content of a biodiesel is directly correlated with its OOA, and highly related to its OP. Hence, the more oxygen included in the considered biodiesels, the higher the OP of PM emissions. This highlights the importance of taking oxygen content into account while assessing emissions from new fuel types, which is relevant from a health effects standpoint.

Uncertainty based online planning for UAV target finding in cluttered and GPS-denied environments

There are some scenarios in which Unmmaned Aerial Vehicle (UAV) navigation becomes a challenge due to the occlusion of GPS systems signal, the presence of obstacles and constraints in the space in which a UAV operates. An additional challenge is presented when a target whose location is unknown must be found within a confined space. In this paper we present a UAV navigation and target finding mission, modelled as a Partially Observable Markov Decision Process (POMDP) using a state-of-the-art online solver in a real scenario using a low cost commercial multi rotor UAV and a modular system architecture running under the Robotic Operative System (ROS). Using POMDP has several advantages to conventional approaches as they take into account uncertainties in sensor information. We present a framework for testing the mission with simulation tests and real flight tests in which we model the system dynamics and motion and perception uncertainties. The system uses a quad-copter aircraft with an board downwards looking camera without the need of GPS systems while avoiding obstacles within a confined area. Results indicate that the system has 100% success rate in simulation and 80% rate during flight test for finding targets located at different locations.

Development of salinity tolerance in rice by constitutive-overexpression of genes involved in the regulation of programmed cell death

Environmental factors contribute to over 70% of crop yield losses worldwide. Of these drought and salinity are the most significant causes of crop yield reduction. Rice is an important staple crop that feeds more than half of the world’s population. However among the agronomically important cereals rice is the most sensitive to salinity. In the present study we show that exogenous expression of anti-apoptotic genes from diverse origins, AtBAG4 (Arabidopsis), Hsp70 (Citrus tristeza virus) and p35 (Baculovirus), significantly improves salinity tolerance in rice at the whole plant level. Physiological, biochemical and agronomical analyses of transgenic rice expressing each of the anti-apoptotic genes subjected to salinity treatment demonstrated traits associated with tolerant varieties including, improved photosynthesis, membrane integrity, ion and ROS maintenance systems, growth rate, and yield components. Moreover, FTIR analysis showed that the chemical composition of salinity-treated transgenic plants is reminiscent of non-treated, unstressed controls. In contrast, wild type and vector control plants displayed hallmark features of stress, including pectin degradation upon subjection to salinity treatment. Interestingly, despite their diverse origins, transgenic plants expressing the anti-apoptotic genes assessed in this study displayed similar physiological and biochemical characteristics during salinity treatment thus providing further evidence that cell death pathways are conserved across broad evolutionary kingdoms. Our results reveal that anti-apoptotic genes facilitate maintenance of metabolic activity at the whole plant level to create favorable conditions for cellular survival. It is these conditions that are crucial and conducive to the plants ability to tolerate/adapt to extreme environments.

Place categorization and semantic mapping on a mobile robot

In this paper we focus on the challenging problem of place categorization and semantic mapping on a robot with-out environment-specific training. Motivated by their ongoing success in various visual recognition tasks, we build our system upon a state-of-the-art convolutional network. We overcome its closed-set limitations by complementing the network with a series of one-vs-all classifiers that can learn to recognize new semantic classes online. Prior domain knowledge is incorporated by embedding the classification system into a Bayesian filter framework that also ensures temporal coherence. We evaluate the classification accuracy of the system on a robot that maps a variety of places on our campus in real-time. We show how semantic information can boost robotic object detection performance and how the semantic map can be used to modulate the robot’s behaviour during navigation tasks. The system is made available to the community as a ROS module.