Linear models for endocytic transformations from live cell imaging

Endocytosis is the process by which cells internalise molecules including nutrient proteins from the extracellular media. In one form, macropinocytosis, the membrane at the cell surface ruffles and folds over to give rise to an internalised vesicle. Negatively charged phospholipids within the membrane called phosphoinositides then undergo a series of transformations that are critical for the correct trafficking of the vesicle within the cell, and which are often pirated by pathogens such as Salmonella. Advanced fluorescent video microscopy imaging now allows the detailed observation and quantification of these events in live cells over time. Here we use these observations as a basis for building differential equation models of the transformations. An initial investigation of these interactions was modelled with reaction rates proportional to the sum of the concentrations of the individual constituents. A first order linear system for the concentrations results. The structure of the system enables analytical expressions to be obtained and the problem becomes one of determining the reaction rates which generate the observed data plots. We present results with reaction rates which capture the general behaviour of the reactions so that we now have a complete mathematical model of phosphoinositide transformations that fits the experimental observations. Some excellent fits are obtained with modulated exponential functions; however, these are not solutions of the linear system. The question arises as to how the model may be modified to obtain a system whose solution provides a more accurate fit.

Sensors and imaging for wound healing : a review

Wound healing involves a complex series of biochemical events and has traditionally been managed with 'low tech' dressings and bandages. The concept that diagnostic and theranostic sensors can complement wound management is rapidly growing in popularity as there is tremendous potential to apply this technology to both acute and chronic wounds. Benefits in sensing the wound environment include reduction of hospitalization time, prevention of amputations and better understanding of the processes which impair healing. This review discusses the state-of-the-art in detection of markers associated with wound healing and infection, utilizing devices imbedded within dressings or as point-of-care techniques to allow for continual or rapid wound assessment and monitoring. Approaches include using biological or chemical sensors of wound exudates and volatiles to directly or indirectly detect bacteria, monitor pH, temperature, oxygen and enzymes. Spectroscopic and imaging techniques are also reviewed as advanced wound monitoring techniques. The review concludes with a discussion of the limitations of and future directions for this field.

Traits of fear resistance and susceptibility in an advanced intercross line

Genetic variability in the strength and precision of fear memory is hypothesised to contribute to the etiology of anxiety disorders, including post-traumatic stress disorder. We generated fear-susceptible (F-S) or fear-resistant (F-R) phenotypes from an F8 advanced intercross line (AIL) of C57BL/6J and DBA/2J inbred mice by selective breeding. We identified specific traits underlying individual variability in Pavlovian conditioned fear learning and memory. Offspring of selected lines differed in the acquisition of conditioned fear. Furthermore, F-S mice showed greater cued fear memory and generalised fear in response to a novel context than F-R mice. F-S mice showed greater basal corticosterone levels and hypothalamic corticotrophin-releasing hormone (CRH) mRNA levels than F-R mice, consistent with higher hypothalamic-pituitary-adrenal (HPA) axis drive. Hypothalamic mineralocorticoid receptor and CRH receptor 1 mRNA levels were decreased in F-S mice as compared with F-R mice. Manganese-enhanced magnetic resonance imaging (MEMRI) was used to investigate basal levels of brain activity. MEMRI identified a pattern of increased brain activity in F-S mice that was driven primarily by the hippocampus and amygdala, indicating excessive limbic circuit activity in F-S mice as compared with F-R mice. Thus, selection pressure applied to the AIL population leads to the accumulation of heritable trait-relevant characteristics within each line, whereas non-behaviorally relevant traits remain distributed. Selected lines therefore minimise false-positive associations between behavioral phenotypes and physiology. We demonstrate that intrinsic differences in HPA axis function and limbic excitability contribute to phenotypic differences in the acquisition and consolidation of associative fear memory. Identification of system-wide traits predisposing to variability in fear memory may help in the direction of more targeted and efficacious treatments for fear-related pathology. Through short-term selection in a B6D2 advanced intercross line we created mouse populations divergent for the retention of Pavlovian fear memory. Trait distinctions in HPA-axis drive and fear network circuitry could be made between naïve animals in the two lines. These data demonstrate underlying physiological and neurological differences between Fear-Susceptible and Fear-Resistant animals in a natural population. F-S and F-R mice may therefore be relevant to a spectrum of disorders including depression, anxiety disorders and PTSD for which altered fear processing occurs.

MITIE C-Arm - Advanced innovation in education

Aim: In 2013 QUT introduced the Medical Imaging Training Immersive Environment (MITIE) as a virtual reality (VR) platform that allowed students to practice general radiography. The system software has been expanded to now include C-Arm. The aim of this project was to investigate the use of this technology in the pedagogy of undergraduate medical imaging students who have limited to no experience in the use of the C-Arm clinically. Method: The Medical Imaging Training Immersive Environment (MITIE) application provides students with realistic and fully interactive 3D models of C-Arm equipment. As with VR initiatives in other health disciplines (1–2) the software mimics clinical practice as much as possible and uses 3D technology to enhance 3D spatial awareness and realism. The application allows students to set up and expose a virtual patient in a 3D environment as well as creating the resultant “image” for comparison with a gold standard. Automated feedback highlights ways for the student to improve their patient positioning, equipment setup or exposure factors. The students' equipment knowledge was tested using an on line assessment quiz and surveys provided information on the students' pre-clinical confidence scale, with post-clinical data comparisons. Ethical approval for the project was provided by the university ethics panel. Results: This study is currently under way and this paper will present analysis of initial student feedback relating to the perceived value of the application for confidence in a high risk environment (i.e. operating theatre) and related clinical skills development. Further in-depth evaluation is ongoing with full results to be presented. Conclusion: MITIE C-Arm has a development role to play in the pre-clinical skills training for Medical Radiation Science students. It will augment their theoretical understanding prior to their clinical experience. References 1. Bridge P, Appleyard R, Ward J, Phillips R, Beavis A. The development and evaluation of a virtual radiotherapy treatment machine using an immersive visualisation environment. Computers and Education 2007; 49(2): 481–494. 2. Gunn T, Berry C, Bridge P et al. 3D Virtual Radiography: Development and Initial Feedback. Paper presented at the 10th Annual Scientific Meeting of Medical Imaging and Radiation Therapy, March 2013 Hobart, Tasmania.

Visualization tools for high angular resolution diffusion imaging

There is a major effort in medical imaging to develop algorithms to extract information from DTI and HARDI, which provide detailed information on brain integrity and connectivity. As the images have recently advanced to provide extraordinarily high angular resolution and spatial detail, including an entire manifold of information at each point in the 3D images, there has been no readily available means to view the results. This impedes developments in HARDI research, which need some method to check the plausibility and validity of image processing operations on HARDI data or to appreciate data features or invariants that might serve as a basis for new directions in image segmentation, registration, and statistics. We present a set of tools to provide interactive display of HARDI data, including both a local rendering application and an off-screen renderer that works with a web-based viewer. Visualizations are presented after registration and averaging of HARDI data from 90 human subjects, revealing important details for which there would be no direct way to appreciate using conventional display of scalar images.

Functional imaging of peripheral vision and dorsal stream function in the human cerebral cortex

Visual information processing in brain proceeds in both serial and parallel fashion throughout various functionally distinct hierarchically organised cortical areas. Feedforward signals from retina and hierarchically lower cortical levels are the major activators of visual neurons, but top-down and feedback signals from higher level cortical areas have a modulating effect on neural processing. My work concentrates on visual encoding in hierarchically low level cortical visual areas in human brain and examines neural processing especially in cortical representation of visual field periphery. I use magnetoencephalography and functional magnetic resonance imaging to measure neuromagnetic and hemodynamic responses during visual stimulation and oculomotor and cognitive tasks from healthy volunteers. My thesis comprises six publications. Visual cortex forms a great challenge for modeling of neuromagnetic sources. My work shows that a priori information of source locations are needed for modeling of neuromagnetic sources in visual cortex. In addition, my work examines other potential confounding factors in vision studies such as light scatter inside the eye which may result in erroneous responses in cortex outside the representation of stimulated region, and eye movements and attention. I mapped cortical representations of peripheral visual field and identified a putative human homologue of functional area V6 of the macaque in the posterior bank of parieto-occipital sulcus. My work shows that human V6 activates during eye-movements and that it responds to visual motion at short latencies. These findings suggest that human V6, like its monkey homologue, is related to fast processing of visual stimuli and visually guided movements. I demonstrate that peripheral vision is functionally related to eye-movements and connected to rapid stream of functional areas that process visual motion. In addition, my work shows two different forms of top-down modulation of neural processing in the hierachically lowest cortical levels; one that is related to dorsal stream activation and may reflect motor processing or resetting signals that prepare visual cortex for change in the environment and another local signal enhancement at the attended region that reflects local feed-back signal and may perceptionally increase the stimulus saliency.

Brain imaging of chronic pain

Acute pain has substantial survival value because of its protective function in the everyday environment. Instead, chronic pain lacks survival and adaptive function, causes great amount of individual suffering, and consumes the resources of the society due to the treatment costs and loss of production. The treatment of chronic pain has remained challenging because of inadequate understanding of mechanisms working at different levels of the nervous system in the development, modulation, and maintenance of chronic pain. Especially in unclear chronic pain conditions the treatment may be suboptimal because it can not be targeted to the underlying mechanisms. Noninvasive neuroimaging techniques have greatly contributed to our understanding of brain activity associated with pain in healthy individuals. Many previous studies, focusing on brain activations to acute experimental pain in healthy individuals, have consistently demonstrated a widely-distributed network of brain regions that participate in the processing of acute pain. The aim of the present thesis was to employ non-invasive brain imaging to better understand the brain mechanisms in patients suffering from chronic pain. In Study I, we used magnetoencephalography (MEG) to measure cortical responses to painful laser stimulation in healthy individuals for optimization of the stimulus parameters for patient studies. In Studies II and III, we monitored with MEG the cortical processing of touch and acute pain in patients with complex regional pain syndrome (CRPS). We found persisting plastic changes in the hand representation area of the primary somatosensory (SI) cortex, suggesting that chronic pain causes cortical reorganization. Responses in the posterior parietal cortex to both tactile and painful laser stimulation were attenuated, which could be associated with neglect-like symptoms of the patients. The primary motor cortex reactivity to acute pain was reduced in patients who had stronger spontaneous pain and weaker grip strength in the painful hand. The tight coupling between spontaneous pain and motor dysfunction supports the idea that motor rehabilitation is important in CRPS. In Studies IV and V we used MEG and functional magnetic resonance imaging (fMRI) to investigate the central processing of touch and acute pain in patients who suffered from recurrent herpes simplex virus infections and from chronic widespread pain in one side of the body. With MEG, we found plastic changes in the SI cortex, suggesting that many different types of chronic pain may be associated with similar cortical reorganization. With fMRI, we found functional and morphological changes in the central pain circuitry, as an indication of central contribution for the pain. These results show that chronic pain is associated with morphological and functional changes in the brain, and that such changes can be measured with functional imaging.

Magnetic Resonance Imaging of Atherosclerotic Manifestations in Familial Hypercholesterolemia

Cardiovascular diseases (CVD) are, in developed countries, the leading cause of mortality. The majority of premature deaths and disability caused by CVD are due to atherosclerosis, a degenerating inflammatory disease affecting arterial walls. Early identification of lesions and initiation of treatment is crucial because the first manifestations quite often are major disabling cardiovascular events. Methods of finding individuals at high risk for these events are under development. Because magnetic resonance imaging (MRI) is an excellent non-invasive tool to study the structure and function of vascular system, we sought to discover whether existing MRI methods are able to show any difference in aortic and intracranial atherosclerotic lesions between patients at high risk for atherosclerosis and healthy controls. Our younger group (age 6-48) comprised 39 symptomless familial hypercholesterolemia (FH) patients and 25 healthy controls. Our older group (age 48-64) comprised 19 FH patients and 18 type 2 diabetes mellitus (DM) patients with coronary heart disease (CHD) and 29 healthy controls. Intracranial and aortic MRI was compared with carotid and femoral ultrasound (US). In neither age-group did MRI reveal any difference in the number of ischemic brain lesions or white matter hyperintensities (WMHIs) - possible signs of intracranial atherosclerosis - between patients and controls. Furthermore, MRI showed no difference in the structure or function of the aorta between FH patients and controls in either group. DM patients had lower compliance of the aorta than did controls, while no difference appeared between DM and FH patients. However, ultrasound showed greater plaque burden and increased thickness of carotid arterial walls in FH and DM patients in both age-groups, suggesting a more advanced atherosclerosis. The mortality of FH patients has decreased substantially after the late 1980´s when statin treatment became available. With statins, the progression of atherosclerotic lesions slows. We think that this, in concert with improvements in treatment of other risk factors, is one reason for the lack of differences between FH patients and controls in MRI measurements of the aorta and brain despite the more advanced disease of the carotid arteries assessed with US. Furthermore, whereas atherosclerotic lesions between different vascular territories correlate, differences might still exist in the extent and location of these lesions among different diseases. Small (<5 mm in diameter) WMHIs are more likely a phenomenon related to aging, but the larger ones may be the ones related to CVD and may be intermediate surrogates of stroke. The image quality in aortic imaging, although constantly improving, is not yet optimal and thus is a source of bias.

Nanomaterial based Magnetic Resonance Imaging of Cancer

Magnetic Resonance Imaging (MRI) is a widely used non-invasive medical tool for detection and diagnosis of cancer. In recent years, MRI has witnessed significant contributions from nanotechnology to incorporate advanced features such as multimodality of nanoparticles, therapeutic delivery, specific targeting and the optical detectability for molecular imaging. Accurate composition, right scheme of surface chemistry and properly designed structure is essential for achieving desired properties of nanomaterials such as non-fouling surface, high imaging contrast, chemical stability, target specificity and/or multimodality. This review provides an overview of the recent progress in theranostic nanomaterials in imaging and the development of nanomaterial based magnetic resonance imaging of cancer. In particular, targeted theranostics is a promising approach along with its targeting strategy in cancer treatment using MRI and multimodal imaging. We also discuss recent advances in integrin mediated targeted MRI of cancer.

Design and synthesis of biofunctional magnetic/fluorescent glyco-nanoparticles and quantum dots and their application as specific molecular imaging probes

206 p.

Advanced Monte Carlo Simulation and Machine Learning for Frequency Domain Optical Coherence Tomography

Optical Coherence Tomography(OCT) is a popular, rapidly growing imaging technique with an increasing number of bio-medical applications due to its noninvasive nature. However, there are three major challenges in understanding and improving an OCT system: (1) Obtaining an OCT image is not easy. It either takes a real medical experiment or requires days of computer simulation. Without much data, it is difficult to study the physical processes underlying OCT imaging of different objects simply because there aren't many imaged objects. (2) Interpretation of an OCT image is also hard. This challenge is more profound than it appears. For instance, it would require a trained expert to tell from an OCT image of human skin whether there is a lesion or not. This is expensive in its own right, but even the expert cannot be sure about the exact size of the lesion or the width of the various skin layers. The take-away message is that analyzing an OCT image even from a high level would usually require a trained expert, and pixel-level interpretation is simply unrealistic. The reason is simple: we have OCT images but not their underlying ground-truth structure, so there is nothing to learn from. (3) The imaging depth of OCT is very limited (millimeter or sub-millimeter on human tissues). While OCT utilizes infrared light for illumination to stay noninvasive, the downside of this is that photons at such long wavelengths can only penetrate a limited depth into the tissue before getting back-scattered. To image a particular region of a tissue, photons first need to reach that region. As a result, OCT signals from deeper regions of the tissue are both weak (since few photons reached there) and distorted (due to multiple scatterings of the contributing photons). This fact alone makes OCT images very hard to interpret.

This thesis addresses the above challenges by successfully developing an advanced Monte Carlo simulation platform which is 10000 times faster than the state-of-the-art simulator in the literature, bringing down the simulation time from 360 hours to a single minute. This powerful simulation tool not only enables us to efficiently generate as many OCT images of objects with arbitrary structure and shape as we want on a common desktop computer, but it also provides us the underlying ground-truth of the simulated images at the same time because we dictate them at the beginning of the simulation. This is one of the key contributions of this thesis. What allows us to build such a powerful simulation tool includes a thorough understanding of the signal formation process, clever implementation of the importance sampling/photon splitting procedure, efficient use of a voxel-based mesh system in determining photon-mesh interception, and a parallel computation of different A-scans that consist a full OCT image, among other programming and mathematical tricks, which will be explained in detail later in the thesis.

Next we aim at the inverse problem: given an OCT image, predict/reconstruct its ground-truth structure on a pixel level. By solving this problem we would be able to interpret an OCT image completely and precisely without the help from a trained expert. It turns out that we can do much better. For simple structures we are able to reconstruct the ground-truth of an OCT image more than 98% correctly, and for more complicated structures (e.g., a multi-layered brain structure) we are looking at 93%. We achieved this through extensive uses of Machine Learning. The success of the Monte Carlo simulation already puts us in a great position by providing us with a great deal of data (effectively unlimited), in the form of (image, truth) pairs. Through a transformation of the high-dimensional response variable, we convert the learning task into a multi-output multi-class classification problem and a multi-output regression problem. We then build a hierarchy architecture of machine learning models (committee of experts) and train different parts of the architecture with specifically designed data sets. In prediction, an unseen OCT image first goes through a classification model to determine its structure (e.g., the number and the types of layers present in the image); then the image is handed to a regression model that is trained specifically for that particular structure to predict the length of the different layers and by doing so reconstruct the ground-truth of the image. We also demonstrate that ideas from Deep Learning can be useful to further improve the performance.

It is worth pointing out that solving the inverse problem automatically improves the imaging depth, since previously the lower half of an OCT image (i.e., greater depth) can be hardly seen but now becomes fully resolved. Interestingly, although OCT signals consisting the lower half of the image are weak, messy, and uninterpretable to human eyes, they still carry enough information which when fed into a well-trained machine learning model spits out precisely the true structure of the object being imaged. This is just another case where Artificial Intelligence (AI) outperforms human. To the best knowledge of the author, this thesis is not only a success but also the first attempt to reconstruct an OCT image at a pixel level. To even give a try on this kind of task, it would require fully annotated OCT images and a lot of them (hundreds or even thousands). This is clearly impossible without a powerful simulation tool like the one developed in this thesis.

Transparent oxide semiconductors for advanced display applications

The article discusses the progress and issues related to transparent oxide semiconductor (TOS) TFTs for advanced display and imaging applications. Amorphous oxide semiconductors continue to spark new technological developments in transparent electronics on a multitude of non-conventional substrates. Applications range from high-frame-rate interactive displays with embedded imaging to flexible electronics, where speed and transparency are essential requirements. TOS TFTs exhibit high transparency as well as high electron mobility even when fabricated at room temperature. Compared to conventional a-Si TFT technology, TOS TFTs have higher mobility and sufficiently good uniformity over large areas, similar in many ways to LTPS TFTs. Moreover, because the amorphous oxide semiconductor has higher mobility compared to that of conventional a-Si TFT technology, this allows higher-frame-rate display operation. This would greatly benefit OLED displays in particular because of the need for lower-cost higher-mobility analog circuits at every subpixel.

Amorphous oxide semiconductor TFTs for displays and imaging

© 2013 IEEE. This paper reviews the mechanisms underlying visible light detection based on phototransistors fabricated using amorphous oxide semiconductor technology. Although this family of materials is perceived to be optically transparent, the presence of oxygen deficiency defects, such as vacancies, located at subgap states, and their ionization under illumination, gives rise to absorption of blue and green photons. At higher energies, we have the usual band-to-band absorption. In particular, the oxygen defects remain ionized even after illumination ceases, leading to persistent photoconductivity, which can limit the frame-rate of active matrix imaging arrays. However, the persistence in photoconductivity can be overcome through deployment of a gate pulsing scheme enabling realistic frame rates for advanced applications such as sensor-embedded display for touch-free interaction.

Beyond simple imaging with energetic beams – nanopatterning, correlative microscopy and statistical analysis of inclusions

Electron microscopy (EM) has advanced in an exponential way since the first transmission electron microscope (TEM) was built in the 1930’s. The urge to ‘see’ things is an essential part of human nature (talk of ‘seeing is believing’) and apart from scanning tunnel microscopes which give information about the surface, EM is the only imaging technology capable of really visualising atomic structures in depth down to single atoms. With the development of nanotechnology the demand to image and analyse small things has become even greater and electron microscopes have found their way from highly delicate and sophisticated research grade instruments to key-turn and even bench-top instruments for everyday use in every materials research lab on the planet. The semiconductor industry is as dependent on the use of EM as life sciences and pharmaceutical industry. With this generalisation of use for imaging, the need to deploy advanced uses of EM has become more and more apparent. The combination of several coinciding beams (electron, ion and even light) to create DualBeam or TripleBeam instruments for instance enhances the usefulness from pure imaging to manipulating on the nanoscale. And when it comes to the analytic power of EM with the many ways the highly energetic electrons and ions interact with the matter in the specimen there is a plethora of niches which evolved during the last two decades, specialising in every kind of analysis that can be thought of and combined with EM. In the course of this study the emphasis was placed on the application of these advanced analytical EM techniques in the context of multiscale and multimodal microscopy – multiscale meaning across length scales from micrometres or larger to nanometres, multimodal meaning numerous techniques applied to the same sample volume in a correlative manner. In order to demonstrate the breadth and potential of the multiscale and multimodal concept an integration of it was attempted in two areas: I) Biocompatible materials using polycrystalline stainless steel and II) Semiconductors using thin multiferroic films. I) The motivation to use stainless steel (316L medical grade) comes from the potential modulation of endothelial cell growth which can have a big impact on the improvement of cardio-vascular stents – which are mainly made of 316L – through nano-texturing of the stent surface by focused ion beam (FIB) lithography. Patterning with FIB has never been reported before in connection with stents and cell growth and in order to gain a better understanding of the beam-substrate interaction during patterning a correlative microscopy approach was used to illuminate the patterning process from many possible angles. Electron backscattering diffraction (EBSD) was used to analyse the crystallographic structure, FIB was used for the patterning and simultaneously visualising the crystal structure as part of the monitoring process, scanning electron microscopy (SEM) and atomic force microscopy (AFM) were employed to analyse the topography and the final step being 3D visualisation through serial FIB/SEM sectioning. II) The motivation for the use of thin multiferroic films stems from the ever-growing demand for increased data storage at lesser and lesser energy consumption. The Aurivillius phase material used in this study has a high potential in this area. Yet it is necessary to show clearly that the film is really multiferroic and no second phase inclusions are present even at very low concentrations – ~0.1vol% could already be problematic. Thus, in this study a technique was developed to analyse ultra-low density inclusions in thin multiferroic films down to concentrations of 0.01%. The goal achieved was a complete structural and compositional analysis of the films which required identification of second phase inclusions (through elemental analysis EDX(Energy Dispersive X-ray)), localise them (employing 72 hour EDX mapping in the SEM), isolate them for the TEM (using FIB) and give an upper confidence limit of 99.5% to the influence of the inclusions on the magnetic behaviour of the main phase (statistical analysis).