Iron-based magnetic nanosystems for diagnostic imaging and drug delivery : towards transformative biomedical applications

The advancement of biomedicine in a socioeconomically sustainable manner while achieving efficient patient-care is imperative to the health and well-being of society. Magnetic systems consisting of iron based nanosized components have gained prominence among researchers in a multitude of biomedical applications. This review focuses on recent trends in the areas of diagnostic imaging and drug delivery that have benefited from iron-incorporated nanosystems, especially in cancer treatment, diagnosis and wound care applications. Discussion on imaging will emphasise on developments in MRI technology and hyperthermia based diagnosis, while advanced material synthesis and targeted, triggered transport will be the focus for drug delivery. Insights onto the challenges in transforming these technologies into day-to-day applications will also be explored with perceptions onto potential for patient-centred healthcare

Magnetic Field Generation in Stars

Enormous progress has been made on observing stellar magnetism in stars from the main sequence through to compact objects. Recent data have thrown into sharper relief the vexed question of the origin of stellar magnetic fields, which remains one of the main unanswered questions in astrophysics. In this chapter we review recent work in this area of research. In particular, we look at the fossil field hypothesis which links magnetism in compact stars to magnetism in main sequence and pre-main sequence stars and we consider why its feasibility has now been questioned particularly in the context of highly magnetic white dwarfs. We also review the fossil versus dynamo debate in the context of neutron stars and the roles played by key physical processes such as buoyancy, helicity, and superfluid turbulence,in the generation and stability of neutron star fields. Independent information on the internal magnetic field of neutron stars will come from future gravitational wave detections. Thus we maybe at the dawn of a new era of exciting discoveries in compact star magnetism driven by the opening of a new, non-electromagnetic observational window. We also review recent advances in the theory and computation of magnetohydrodynamic turbulence as it applies to stellar magnetism and dynamo theory. These advances offer insight into the action of stellar dynamos as well as processes whichcontrol the diffusive magnetic flux transport in stars.Comment: 41 pages, 7 figures. Invited review chapter on on magnetic field generation in stars to appear in Space Science Reviews, Springe

Anaerobiosis revisited: growth of Saccharomyces cerevisiae under extremely low oxygen availability

The budding yeast Saccharomyces cerevisiae plays an important role in biotechnological applications, ranging from fuel ethanol to recombinant protein production. It is also a model organism for studies on cell physiology and genetic regulation. Its ability to grow under anaerobic conditions is of interest in many industrial applications. Unlike industrial bioreactors with their low surface area relative to volume, ensuring a complete anaerobic atmosphere during microbial cultivations in the laboratory is rather difficult. Tiny amounts of O2 that enter the system can vastly influence product yields and microbial physiology. A common procedure in the laboratory is to sparge the culture vessel with ultrapure N2 gas; together with the use of butyl rubber stoppers and norprene tubing, O2 diffusion into the system can be strongly minimized. With insights from some studies conducted in our laboratory, we explore the question ‘how anaerobic is anaerobiosis?’. We briefly discuss the role of O2 in non-respiratory pathways in S. cerevisiae and provide a systematic survey of the attempts made thus far to cultivate yeast under anaerobic conditions. We conclude that very few data exist on the physiology of S. cerevisiae under anaerobiosis in the absence of the anaerobic growth factors ergosterol and unsaturated fatty acids. Anaerobicity should be treated as a relative condition since complete anaerobiosis is hardly achievable in the laboratory. Ideally, researchers should provide all the details of their anaerobic set-up, to ensure reproducibility of results among different laboratories. A correction to this article is available online at http://eprints.whiterose.ac.uk/131930/ https://doi.org/10.1007/s00253-018-9036-

Practical imaging and analyses for qMRI

Doctor of PhilosophyDepartment of ChemistryChristine M AikensStefan BossmannMagnetic resonance imaging (MRI) is a powerful tool to gain insight into physiological structures and processes, molecular behavior, and psychological conditions. It has a broad range of applications, including, but not limited to, medical imaging, such as the insight it can provide towards medicinal chemistry regarding the appropriate targeting and efficiency of new drug candidates. While the fundamentals of MRI are thoroughly understood at this point of its development, the ability to extrapolate results beyond the qualitative data often seen with anatomical imaging to reach new levels of insight regarding the aforementioned uses has gained burgeoning attention from physicists, chemists, and mathematicians. Through exploitation of the meta-data and manipulation of multi-image acquisition, it has been demonstrated that ultra-high-resolution imaging, quantitative imaging, and real-time data analyses are possible. This provides critical information for clinicians and fellow researchers towards understanding disease progression, treatment efficacy, and treatment behavior in infinitesimal steps, providing new methods to investigate mode of action in combination with other monitoring methodology. Quantitative MRI (qMRI) requires the application of rigorous acquisition methods, sophisticated post-processing techniques, and fastidious analysis to be relevant and replicable. However, should all these qualifications be executed appropriately, it can provide verifiable, repeatable, and pivotal information regarding enigmatic maladies and treatment pathways. Investigation into the quantitative mapping of longitudinal relaxation times to investigate tumor structures and attempted treatment methods through T1-mapping will provide insight into the specificity and sensitivity of qMRI. The use of T1-mapping has been shown to be a non-invasive methodology to gain deeper insight and understanding into cellular level changes as the result of inflammation and stromal barrier formation. It is sensitive enough to distinguish between ascites and tumor formations, can provide information regarding tumor heterogeneity, and is a quick non-invasive method in which to do so. Sensitivity is demonstrated by the differences of T1-mapping behavior based upon different cell lines compared to normal tissue, and its quick acquisition time makes it a promising method for clinical applications. Diffusion tensor imaging, one of the leading modalities under study with qMRI, will be assessed for faster image acquisition. Through prioritizing different parameters in order to monitor the impact alterations have on image quality and information available, a template of key characteristics that can be monitored in varying degrees of depth will be investigated. This will provide insight into how alteration of parameters affect final data acquisition and potential remedies to condense imaging time that can be altered based upon study design. Furthermore, the inverse of this investigation will determine which key parameters will yield the highest quality data possible and examine the impacts of obtaining ultra-high-direction diffusion tensor images and optimal resolutions, as well as the consequences to signal when resolutions are too high. Additionally, a new method of analysis through an integrated pipeline that will accommodate artifact correction, tensor calculation, and yield multiple diffusion metrics will be presented that is compatible with various forms of instrumentation in order to correct for limited compatibility, un-intuitive application, and difficulty of use seen in many commercially available platforms available today. Finally, investigation into next generation steps for qMRI which look to further increase the depths of information gained through imaging will be examined through iterative back projection to calculate ultra-high-resolution images at a fraction of the time cost seen with traditional imaging. This provides insight into the application of super resolution techniques to gain higher level information regarding diffusion tensors and anatomical structures without suffering from signal loss due to nominal voxel sizes. The ultimate goal is to generate data sets which no longer hinge upon subjective interpretation and progress the field towards machine learning techniques which can be used to identify anomalies present post-imaging