A Review of Using Mathematical Modeling to Improve Our Understanding of Bacteriophage, Bacteria, and Eukaryotic Interactions

Phage therapy, the therapeutic usage of viruses to treat bacterial infections, has many theoretical benefits in the ‘post antibiotic era’. Nevertheless, there are currently no approved mainstream phage therapies. One reason for this is a lack of understanding of the complex interactions between bacteriophage, bacteria and eukaryotic hosts. These three-component interactions are complex, with non-linear or synergistic relationships, anatomical barriers and genetic or phenotypic heterogeneity all leading to disparity between performance and efficacy in in vivo versus in vitro environments. Realistic computer or mathematical models of these complex environments are a potential route to improve the predictive power of in vitro studies and to streamline lab work. Here, we review the current status of mathematical modelling and highlight that data on mutational stochasticity, time delays and population densities could be critical in the development of realistic phage therapy models. With this in mind, we aim to inform and encourage the collaboration and sharing of knowledge and expertise between microbiologists and theoretical modellers, smoothing the road to regulatory approval and widespread use of phage therapy

Geodynamic setting and origin of the Oman/UAE ophiolite

The ~500km-long mid-Cretaceous Semail nappe of the Sultanate of Oman and UAE (henceforth referred to as the Oman ophiolite) is the largest and best-preserved ophiolite complex known. It is of particular importance because it is generally believed to have an internal structure and composition closely comparable to that of crust formed at the present-day East Pacific Rise (EPR), making it our only known on-land analogue for ocean lithosphere formed at a fast spreading rate. On the basis of this assumption Oman has long played a pivotal role in guiding our conceptual understanding of fast-spreading ridge processes, as modern fast-spread ocean crust is largely inaccessible

The variation in composition of ultramafic rocks and the effect on their suitability for carbon dioxide sequestration by mineralization following acid leaching

Carbon dioxide capture and storage by mineralization has been proposed as a possible technology to contribute to the reduction of global CO2 levels. A main candidate as a feed material, to supply Mg cations for combination with CO2 to form carbonate, is the family of ultramafi c rocks, Mgrich silicate rocks with a range of naturally occurring mineralogical compositions. A classifi cation scheme is described and a diagram is proposed to display the full range of both fresh and altered ultramafi c rock compositions. This is particularly for the benefi t of technologists to raise the awareness of the variation in possible feedstock materials. A systematic set of acid leaching experiments, in the presence of recyclable ammonium bisulphate, has been carried out covering the range of ultramafi c rock compositions. The results show that lizardite serpentinite releases the most Mg with 78% removed after 1 h, while an olivine rock (dunite) gave 55% and serpentinized peridotites intermediate values. Antigorite serpentinite only released 40% and pyroxene- and amphibole-rich rocks only 25%, showing they are unsuitable for the acid leaching method used. This wide variation in rock compositions highlights the necessity for accurate mineralogical characterization of potential resources and for technologists to be aware of the impact of feed material variations on process effi ciency and development

Acid-dissolution of antigorite, chrysotile and lizardite for ex situ carbon capture and storage by mineralisation

Serpentine minerals serve as a Mg donor in carbon capture and storage by mineralisation (CCSM). The acid-treatment of nine comprehensively-examined serpentine polymorphs and polytypes, and the subsequent microanalysis of their post-test residues highlighted several aspects of great importance to the choice of the optimal feed material for CCSM. Compelling evidence for the non-uniformity of serpentine mineral performance was revealed, and the following order of increasing Mg extraction efficiency after three hours of acid-leaching was established: Al-bearing polygonal serpentine (<5%) ≤ Al-bearing lizardite 1T (≈5%) < antigorite (24-29%) < well-ordered lizardite 2H1 (≈65%) ≤ Al-poor lizardite 1T (≈68%) < chrysotile (≈70%) < poorly-ordered lizardite 2H1 (≈80%) < nanotubular chrysotile (≈85%). It was recognised that the Mg extraction efficiency of the minerals depended greatly on the intrinsic properties of crystal structure, chemistry and rock microtexture. On this basis, antigorite and Al-bearing well-ordered lizardite were rejected as potential feedstock material whereas any chrysotile, non-aluminous, widely spaced lizardite and/or disordered serpentine were recommended. The formation of peripheral siliceous layers, tens of microns thick, was not universal and depended greatly upon the intrinsic microtexture of the leached particles. This study provides the first comprehensive investigation of nine, carefully-selected serpentine minerals, covering most varieties and polytypes, under the same experimental conditions. We focused on material characterisation and the identification of the intrinsic properties of the minerals that affect particle’s reactivity. It can therefore serve as a generic basis for any acid-based CCSM pre-treatment

Quantification of passivation layer growth in inert anodes for molten salt electrochemistry by in situ energy-dispersive diffraction

An in situ energy-dispersive X-ray diffraction experiment was undertaken on operational titanium electrowinning cells to observe the formation of rutile (TiO2) passivation layers on Magnéli-phase (TinO2n-1; n = 4-6) anodes and thus determine the relationship between passivation layer formation and electrolysis time. Quantitative phase analysis of the energy-dispersive data was undertaken using a crystal-structure-based Rietveld refinement. Layer formation was successfully observed and it was found that the rate of increase in layer thickness decreased with time, rather than remaining constant as observed in previous studies. The limiting step in rutile formation is thought to be the rate of solid-state diffusion of oxygen within the anode structure

Benchtop magnetic shielding for benchmarking atomic magnetometers

Here, a benchtop hybrid magnetic shield containing four mumetal cylinders and nine internal flexible printed circuit boards is designed, constructed, tested, and operated. The shield is designed specifically as a test-bed for building and operating ultra-sensitive quantum magnetometers. The geometry and spacing of the mumetal cylinders are optimized to maximize shielding efficiency while maintaining Johnson noise $<15$ fT/$\sqrt{}$Hz. Experimental measurements at the shield's center show passive shielding efficiency of $\left(1.0\pm0.1\right){\times}10^6$ for a $0.2$ Hz oscillating field applied along the shield's axis. The nine flexible printed circuit boards generate three uniform fields, which all deviate from perfect uniformity by ${\leq}0.5$% along $50$% of the inner shield axis, and five linear field gradients and one second-order gradient, which all deviate by ${\leq}4$% from perfect linearity and curvature, respectively, over measured target regions. Together, the target field amplitudes are adjusted to minimize the remnant static field along $40$% of the inner shield axis, as mapped using an atomic magnetometer. In this region, the active null reduces the norm of the magnitudes of the three uniform fields and six gradients by factors of $19.5$ and $19.8$, respectively, thereby reducing the total static field from $1.68$ nT to $0.23$ nT.Comment: 8 pages, 9 figures; This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

An Earth Observation Land Data Assimilation System (EO-LDAS)

Current methods for estimating vegetation parameters are generally sub-optimal in the way they exploit information and do not generally consider uncertainties. We look forward to a future where operational data assimilation schemes improve estimates by tracking land surface processes and exploiting multiple types of observations. Data assimilation schemes seek to combine observations and models in a statistically optimal way taking into account uncertainty in both, but have not yet been much exploited in this area. The EO-LDAS scheme and prototype, developed under ESA funding, is designed to exploit the anticipated wealth of data that will be available under GMES missions, such as the Sentinel family of satellites, to provide improved mapping of land surface biophysical parameters. This paper describes the EO-LDAS implementation, and explores some of its core functionality. EO-LDAS is a weak constraint variational data assimilation system. The prototype provides a mechanism for constraint based on a prior estimate of the state vector, a linear dynamic model, and Earth Observation data (top-of-canopy reflectance here). The observation operator is a non-linear optical radiative transfer model for a vegetation canopy with a soil lower boundary, operating over the range 400 to 2500 nm. Adjoint codes for all model and operator components are provided in the prototype by automatic differentiation of the computer codes. In this paper, EO-LDAS is applied to the problem of daily estimation of six of the parameters controlling the radiative transfer operator over the course of a year (> 2000 state vector elements). Zero and first order process model constraints are implemented and explored as the dynamic model. The assimilation estimates all state vector elements simultaneously. This is performed in the context of a typical Sentinel-2 MSI operating scenario, using synthetic MSI observations simulated with the observation operator, with uncertainties typical of those achieved by optical sensors supposed for the data. The experiments consider a baseline state vector estimation case where dynamic constraints are applied, and assess the impact of dynamic constraints on the a posteriori uncertainties. The results demonstrate that reductions in uncertainty by a factor of up to two might be obtained by applying the sorts of dynamic constraints used here. The hyperparameter (dynamic model uncertainty) required to control the assimilation are estimated by a cross-validation exercise. The result of the assimilation is seen to be robust to missing observations with quite large data gaps