Ionizing radiation interactions in matter can trigger a cascade of processes that underpin long-lived damage in the medium. To date, however, a lack of suitable methodologies has precluded our ability to understand the role that material nanostructure plays in this cascade. Here, we use transient photoabsorption to track the lifetime of free electrons (τ_{c}) in bulk and nanostructured SiO_{2} (aerogel) irradiated by picosecond-scale (10^{-12} s) bursts of x rays and protons from a laser-driven accelerator. Optical streaking reveals a sharp increase in τ_{c} from <1 ps to >50 ps over a narrow average density (ρ_{av}) range spanning the expected phonon-fracton crossover in aerogels. Numerical modeling suggests that this discontinuity can be understood by a quenching of rapid, phonon-assisted recovery in irradiated nanostructured SiO_{2}. This is shown to lead to an extended period of enhanced energy density in the excited electron population. Overall, these results open a direct route to tracking how low-level processes in complex systems can underpin macroscopically observed phenomena and, importantly, the conditions that permit them to emerge.

In this paper, inhomogeneous chemical kinetics are simulated by describing the concentrations of interacting chemical species by a linear expansion of basis functions in such a manner that the coupled reaction and diffusion processes are propagated through time efficiently by tailor-made numerical methods. The approach is illustrated through modelling [Formula: see text]- and [Formula: see text]-radiolysis in thin layers of water and at their solid interfaces from the start of the chemical phase until equilibrium was established. The method's efficiency is such that hundreds of such systems can be modelled in a few hours using a single core of a typical laptop, allowing the investigation of the effects of the underlying parameter space. Illustrative calculations showing the effects of changing dose-rate and water-layer thickness are presented. Other simulations are presented which show the approach's capability to solve problems with spherical symmetry (an approximation to an isolated radiolytic spur), where the hollowing out of an initial Gaussian distribution is observed, in line with previous calculations. These illustrative simulations show the generality and the computational efficiency of this approach to solving reaction-diffusion problems. Furthermore, these example simulations illustrate the method's suitability for simulating solid-fluid interfaces, which have received a lot of experimental attention in contrast to the lack of computational studies.

Over 60 samples of plutonium dioxide (PuO2) powders of varying provenance have been exposed to humid atmospheres and the hydrogen (H2) generation rates measured by gas chromatography. The effects of relative humidity (RH), specific surface area (SSA), plutonium isotopic composition (absorbed dose), and overlying atmosphere have been investigated for ‘as received’ PuO2 powders from the United Kingdom’s Thorp and Magnox reprocessing plants, high surface area powder produced in the laboratory and Magnox PuO2 that was recalcined at 800, 900 or 950°C. Hydrogen generation was shown to be susceptible to subtle influences with the most consistent results observed at 95% RH. However, it was shown that the measured (net) hydrogen decreases with decreasing RH and with atmosphere in the order: Air > argon > nitrogen. There was no clear effect of SSA, apart from with the highest SSA samples (∼40 m2.g−1) but these powders also have very different morphology, porosity, and carbon content to the rest. The results presented substantially enhance the growing body of literature on the factors that determine hydrogen and gas generation from PuO2 that has significant implications for long term safe storage of plutonium globally.

Here we show an interplay between the structures present in ionization tracks and nucleocapsid RNA structural biology, using fast ion-beam inactivation of the severe acute respiratory syndrome coronavirus (SARS-CoV) virion as an example. This interplay could be a key factor in predicting dose-inactivation curves for high-energy ion-beam inactivation of virions. We also investigate the adaptation of well-established cross-section data derived from radiation interactions with water to the interactions involving the components of a virion, going beyond the density-scaling approximation developed previously. We conclude that solving one of the grand challenges of structural biology - the determination of RNA tertiary/quaternary structure - is linked to predicting ion-beam inactivation of viruses and that the two problems can be mutually informative. Indeed, our simulations show that fast ion beams have a key role to play in elucidating RNA tertiary/quaternary structure.

Background Nanoparticles play a crucial role in nanodiagnostics, radiation therapy of cancer, and they are now widely used to effectively deliver drugs to specific sites, targeting whole organs and down to single cells, in a controlled manner. Therapeutic efficiency of nanoparticles greatly depends on their clustering distribution inside cells. Our purpose is to find the cluster density using Smoluchowski’s coagulation equation with injections. Results We obtain an exact cluster density of nanoparticles as the steady-state solution of Smoluchowski’s equation describing clustering due to the fusion of endosomes. We also analyze the unsteady cluster distribution and compare it with the experimental data for time evolution of gold nanoparticle clusters in living cells. Conclusions We show the steady cluster density is in good agreement with experimental data on gold nanoparticle distribution inside endosomes. We find that for clusters containing between 1 and 20 nanoparticles, the exact cluster density provides a better description of the existing experimental data than the well-known approximate asymptotic power-law distribution x^-3/2

A multiscale local effect model (LEM)-based framework was implemented to study the cell damage caused by the irradiation of clusters of gold nanoparticles (GNPs) under clinically relevant conditions. The results were compared with those obtained by a homogeneous mixture of water and gold (MixNP) irradiated under similar conditions. To that end, Monte Carlo simulations were performed for the irradiation of GNP clusters of different sizes and MixNPs with a 6 MV Linac spectrum to calculate the dose enhancement factor in water. The capabilities of our framework for the prediction of cell damage trends are examined and discussed. We found that the difference of the main parameter driving the cell damage between a cluster of GNPs and the MixNP was less than 1.6% for all cluster sizes. Our results demonstrate for the first time a simple route to intuit the radiobiological effects of clusters of nanoparticles through the consideration of an equivalent homogenous gold/water mixture. Furthermore, the negligible difference on cell damage between a cluster of GNPs and MixNP simplifies the modelling for the complex geometries of nanoparticle aggregations and saves computational resources.

This article describes the radiation facilities and associated sample preparation, management, and analysis equipment currently in place at the Dalton Cumbrian Facility, a facility which opened in 2011 to support the UK’s nuclear industry. Examples of measurements performed using these facilities are presented to illustrate their versatility and the breadth of research they make possible. Results are presented from research which furthers our understanding of radiation damage to polymeric materials, radiolytic yield of gaseous products in situations relevant to nuclear materials, radiation chemistry in light water reactor cooling systems, material chemistry relevant to immobilization of nuclear waste, and radiation-induced corrosion of fuel cladding elements. Applications of radiation chemistry relevant to health care are also described. Research concerning the mechanisms of radioprotection by dietary carotenoids is reported. An ongoing open-labware project to develop a suite of modular sample handling components suited to radiation research is described, as is the development of a new neutron source able to provide directional beams of neutrons.

Understanding the mechanisms of proton energy deposition in matter and subsequent damage formation is fundamental to radiation science. Here we exploit the picosecond (10^{-12}  s) resolution of laser-driven accelerators to track ultrafast solvation dynamics for electrons due to proton radiolysis in liquid water (H_{2}O). Comparing these results with modeling that assumes initial conditions similar to those found in photolysis reveals that solvation time due to protons is extended by >20  ps. Supported by magnetohydrodynamic theory this indicates a highly dynamic phase in the immediate aftermath of the proton interaction that is not accounted for in current models.

Experiments involving the irradiation of water contained within magnesium hydroxide and alumina nanoparticle sludges were conducted and culminated in observations of an increased yield of molecular hydrogen when compared to the yield from the irradiation of bulk water. We show that there is a relationship linking this increased yield to the direct nanoscale ionization mechanism in the nanoparticles, indicating that electron emission from the nanoparticles drives new radiative pathways in the water. Because the chemical changes in these sludges are introduced by irradiation only, we have a genuinely unstirred system. This feature allows us to determine the diffusivity of the dissolved gas. Using the measured gas production rate, we have developed a method for modelling when hydrogen bubble formation will occur within the nanoparticle sludges. This model facilitates the determination of a consistent radiolytic consumption rate coinciding with the observations of bubble formation. Thus, we demonstrate a nanoscale radiation effect directly influencing the formation of molecular hydrogen.

Computational modelling is an important research tool, helping predict the outcome of proposed treatment plans or to illuminate the mechanics of tumour growth. In silico modelling has been used in every aspect of cancer research from DNA damage and repair, tumour growth, drug/tumour interactions, and mutational status. Indeed, modelling even holds potential in understanding the interactions between individual proteins on a single cell basis. Here, we present a computational model of the cell cycle network of the cyclin family of proteins (cyclin A, B, D and E). This model has been quantised using western blot and flow cytometry data from a synchronised HUVEC line to enable the determination of the absolute number of cyclin protein molecules per cell. This quantification allows the model to have stringent controls over the thresholds between transitions. The results show that the peak values obtained for the four cyclins are similar with cyclin B having a peak values of 5×106 to 9×106 molecules per cell. Comparing this value with the number of actin proteins, 5E8, shows that despite their importance, the level of cyclin family proteins are approximately 2 orders of magnitude lower. The efficiency of the model presented would also allow for its use as an internal component in more complex models such as a tumour growth model, in which each individual cell would have its own cell cycle calculated independently from neighbouring cells. Additionally, the model can also be used to help understand the impact of novel therapeutic interventions on cell cycle progression.Author Summary Protein and gene networks control every physiological behaviour of cells, with the cell cycle being controlled by the network of genes that promote the cyclin family of proteins. These networks hold the key to creating accurate and relevant biological models. Normally these models are presented with relative protein concentrations without any real world counterpart to their outputs. The model presented within shows and advancement of this approach by calculating the absolute concentration of each cyclin protein in one cell as it progresses through the cell cycle. This model employs Boolean variables to represent the genetic network, either the gene is active or not, and continuous variables to represent the concentrations of the proteins. This hybridised approach allows for rapid calculations of the protein concentrations and of the cell cycle progression allowing for a model that could be easily incorporated into larger tumour models, allowing for the tracking of discrete cells within the tumour.

Recently, measurements of few-picosecond (ps, 10 −12 s) pulses of laser-driven protons were realised by the observation of transient opacity in SiO 2 . This ultrafast response could be understood by the formation of self-trapped excitonic states in the material, creating a rapid de-excitation channel for conduction band electrons. Here we extend this work to examine the onset and evolution of an ion-induced opacity in transparent dielectrics, namely multicomponent variants of SiO 2 . The fast recovery observed in SiO 2 is in sharp contrast to borosilicate (BK7) and soda-lime glasses. We find that the opacity decay timescales for BK7 and soda-lime glass are orders of magnitude greater than the 3.5 ps proton pump pulse duration and discuss the underlying processes which may be affecting the extended recovery of the material. Simultaneous probing with 2nd harmonic radiation allows estimates of ultrafast electron dynamics due to proton interactions in matter to be investigated, this indicates that a rapid evolution of an initially unstructured ion-induced dose distribution seeds the longer term recovery pathways in the irradiated dielectrics. When combined, these results demonstrate the efficacy of utilising ultrafast laser-driven ionising radiation along with highly synchronised probe pulses to enable the study of ion-induced damage in matter on ultrafast timescales in real time.

The COVID-19 pandemic has radically changed the world we live in.The novel coronavirus SARS-CoV-2, the infectious agent that causes the disease, is believed to have first appeared around December 2019, and in the months since then it has wreaked havoc on human communities, health systems, and economies worldwide.At the time of writing, it is estimated that more than 12 million individuals have been diagnosed with COVID-19, while approximately 550,000 deaths are attributed to the disease (COVID-19 Dashboard 2020).This has been a topic of constant and intense conversation, quite appropriately.Equally so, there has been a shift in priorities from cancer prevention, treatment and research to COVID-19 prevention, treatment and research.As with rebalancing our investment portfolios during a financial crisis, we view the current landscape of shifting priorities as an opportunity to assess and equilibrate our twin interests in securing the quality and quantity of life of our patients and advancing new science with that of navigating the COVID-19 crisis responsibly and resolutely.Extrapolating from data available from 2018 (Cancer fact sheet 2018), approximately 9 million patients have been newly diagnosed with a malignant disease in the first half of 2020.During that same timeframe, there have been no fewer than 4.75 million deaths from cancer throughout the world.At least 43 million people are currently living with a diagnosis of cancer and are undergoing a variety of treatments.Clearly, the impact from cancer far outstrips that of COVID-19, but does not garner the attention nor sense of panic among governments, businesses, the media, and communities.We do not dispute the importance of taking necessary and sometimes radical actions to prevent the spread of an infectious disease such as COVID-19, but we must remember as individuals involved in looking for better ways to prevent, diagnose, and treat malignant diseases that the current impact of cancer on health worldwide far surpasses that of COVID-19.Cancer is the second leading cause of death globally and its incidence is increasing.As the size of the human population expands worldwide, the number of new cases and deaths from cancer annually continues to increase.Cancer can be caused by genetic or environmental factors, but also by infectious diseases, such as hepatitis B or C virus or human papilloma virus.Furthermore, the COVID-19 crisis has directly impacted the care of cancer patients.One of the co-authors of this editorial (SK) has recently submitted a paper looking at the effect of COVID-19 on cancer care worldwide (Venkatesulu et al. 2020).In this meta-analysis, patients who are being

Studies into the cell nucleus' incorporation of gold nanoparticles (AuNPs) are often limited by ambiguities arising from conventional imaging techniques. Indeed, it is suggested that to date there is no unambiguous imaging evidence for such uptake in whole cells, particularly at the single nanoparticle level. This shortcoming in understanding exists despite the nucleus being the most important subcellular compartment in eukaryotes and gold being the most commonly used metal nanoparticle in medical applications. Here, dual‐angle X‐ray flouresence is used to show individually resolved nanoparticles within the cell nucleus, finding them to be well separated and 79% of the intranuclear population to be monodispersed. These findings have important implications for nanomedicine, illustrated here through a specific exemplar of the predicted enhancement of radiation effects arising from the observed AuNPs, finding intranuclear dose enhancements spanning nearly five orders of magnitude.

Here we show that the determining factor for physical radiation enhancement effects for a clinically realistic cluster of heavy-atom bearing nanoparticles is the total number of heavy atoms packed into the cluster. We do this through a multiscale Monte Carlo approach which permits the consideration of radiation transport through clusters of millions of nanoparticles. The finding is in contrast to that predicted when isolated nanoparticles are considered and is a direct consequence of the Auger electrons playing less of a role for clusters compared to isolate nanoparticles. We further show that this result is agnostic to selection of the subcellular region considered to be sensitive to the effects of radiation, provided the inside the cluster of nanoparticles is not considered to be biologically active.

Absolute measurements of the radiolytic yield of Fe3+ in a ferrous sulphate dosimeter formulation (6 mM Fe2+), with a 20 keV x-ray monoenergetic beam, are reported. Dose-rate suppression of the radiolytic yield was observed at dose rates lower than and different in nature to those previously reported with x-rays. We present evidence that this effect is most likely to be due to recombination of free radicals radiolytically produced from water. The method used to make these measurements is also new and it provides radiolytic yields which are directly traceable to the SI standards system. The data presented provides new and exacting tests of radiation chemistry codes.

The passage of energetic ions through tissue initiates a series of physico-chemical events which leads to biodamage. The study of such ion-induced biodamage using a multiscale approach to the physics of radiation damage with ions has led to the prediction of shock waves being initiated by concentrated energy deposition along the ion track. In this work the radial energy deposition around carbon ion paths, calculated solving diffusion equations, is augmented with the inclusion of more energetic δ-electrons. The radial profiles of energy deposition and the induced concentrations of free radicals are used to simulate the shock waves by means of reactive classical molecular dynamics, which predict a characteristic distribution of reactive chemical species which may have an as yet unrecognised contribution to the nascent biodamage. The paper also suggests some experimental methods by which such a shock wave may be detected and the predictions of these simulations verified.

Oxygen plays a central role in cellular metabolism, in both healthy and tumour tissue. The presence and concentration of molecular oxygen in tumours has a substantial effect on both radiotherapy response and tumour evolution, and as a result the oxygen micro-environment is an area of intense research interest. Multi-cellular tumour spheroids closely mimic real avascular tumours, and in particular they exhibit physiologically relevant heterogeneous oxygen distribution. This property has made them a vital part of in vitro experimentation. For ideal spheroids, their heterogeneous oxygen distributions can be predicted from theory, allowing determination of cellular oxygen consumption rate (OCR) and anoxic extent. However, experimental tumour spheroids often depart markedly from perfect sphericity. There has been little consideration of this reality. To date, the question of how far an ellipsoid can diverge from perfect sphericity before spherical assumptions break down remains unanswered. In this work, we derive equations governing oxygen distribution (and, more generally, nutrient and drug distribution) in both prolate and oblate tumour ellipsoids, and quantify the theoretical limits of the assumption that the spheroid is a perfect sphere. Results of this analysis yield new methods for quantifying OCR in ellipsoidal spheroids, and how this can be applied to markedly increase experimental throughput and quality.

A scheme has been developed permitting the spatial and temporal characterisation of ultrafast dynamics induced by laser driven proton bursts in transparent dielectrics. Advantage is taken of the high degree of synchronicity between the proton bursts generated during laser-foil target interactions and the probing laser to provide the basis for streaking of the dynamics. Relaxation times of electrons (<10−12 s) are measured following swift excitation across the optical band gap for various glass samples. A temporal resolution of <500 fs is achieved demonstrating that these ultrafast dynamics can be characterized on a single-shot basis.

Abstract Today, more than half of all cancer patients receive radiotherapy as part of their treatment. However, radiotherapy efficacy is often limited by healthy tissues toxicity and needs to be optimized. One relevant solution is to increase the radiation dose deposition from within the tumor cells. The presence of high atomic number (high-Z) elements within the X-ray pathway increases the probability of interaction with ionizing radiation as compared with tissues (composed of low-Z elements). Likewise, mammalian cells can handle materials at the nanoscale. Therefore, materials made of high-Z elements designed at the nanoscale can enhance the deposit of the radiation dose at the cancer cell level. Still, the most relevant design of these nano-objects has been scarcely explored. Here, we hypothesize that the packing of high-Z elements within the nano-object is a key parameter when considering its design. We used gold and probe how its packing at the nanoscale can achieve the best probability of interaction with ionizing radiation. 50 nm and 2 nm diameter gold nanoparticles coated with 1 nm citrate groups and the gold complex Auranofin (2,3,4,6-tetra-O-acetyl-1-thio-b-D-glucopyranosato-S-[triethyl-phosphine] gold) were considered as representative nano-objects. Many copies of each nano-object were randomly distributed within an artificial cluster to take up 10% of its volume and placed within a cell, reflecting general observation of nanoparticles bioavailability at the subcellular level. Using Monte Carlo simulation, we calculated the energy dose deposition from each cluster when activated by 6 MV energy X-ray source at a depth of 3 cm into the patient. The ratio of energy dose deposition between 50 nm and 2 nm gold nanoparticles and between 50 nm gold nanoparticles and Auranofin was approximately 8 and 70 respectively, regardless of the location of the cluster within the cell. In each case, this reflects the reduced fraction of gold atoms in the nano-object. Indeed, when compared to the 50 nm gold nanoparticle, the 2 nm gold nanoparticle is surrounded by fractionally more citrate, the atoms of which act as passive ‘spectators’ (low-Z atoms). For Auranofin, each gold atom is complexed by organic ligands (low-Z atoms), again acting as passive ‘spectators’. The reduced number of gold atoms per cluster for the 2 nm gold nanoparticles and the gold complexes respectively results in a lower average electron density per cluster. Therefore, for a given cluster filling fraction, the electron density per cluster is the highest for the 50 nm gold nanoparticles. Nanosized objects made of high-Z elements may unlock the potential of radiation therapy by rendering the introduction of a greater energy dose, exactly within the tumor structure without passing through surrounding tissues. Here, taking a realistic approach, we show 50 nm gold nanoparticles achieve better radiation dose deposition than 2 nm gold nanoparticles and gold complexes respectively. Hence, the packing of high-Z element at the nanoscale emerges as a key parameter to achieve effective nanoparticle design and optimize the benefit / risk ratio of radiation therapy. Citation Format: Agnès Pottier, Elsa Borghi, Balder Villagomez-Bernabe, Fred Currell. Radiation therapy with presence of nanoparticles at the tumor cell level: optimizing treatment efficacy through nanoparticle design [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr LB-B18.

A novel treatment planning framework, the Relative Biological Effective Dose (RBED), for high Z nanoparticle (NP)-enhanced photon radiotherapy is developed and tested in silico for the medical exemplar of neoadjuvant (preoperative) breast cancer MV photon radiotherapy. Two different treatment scenarios, conventional and high Z NP enhanced, were explored with a custom Geant4 application that was developed to emulate the administration of a single 2 Gy fraction as part of a 50 Gy radiotherapy treatment plan. It was illustrated that there was less than a 1% difference in the dose deposition throughout the standard and high Z NP-doped adult female phantom. Application of the RBED framework found that the extent of possible biological response with high Z NP doping was great than expected via the dose deposition alone. It is anticipated that this framework will assist the scientific community in future high Z NP-enhanced in-silico, pre-clinical and clinical trials.