Patient reported outcome measures in a cohort of patients at high risk of breast cancer treated by bilateral risk reducing mastectomy and breast reconstruction.

BACKGROUND: Many women with increased lifetime risk of developing breast cancer, due to pathogenic gene variants or family history, choose to undergo bilateral risk reducing mastectomies (BRRM). Patient reported outcome measures (PROMS) are an increasingly important part of informed consent but are little studied in women undergoing BRRM. METHODS: We used a validated PROMS tool for breast reconstruction (BREAST-Q) in 297 women who had BRRM and breast reconstruction, 81% of whom had no malignancy (Benign Group, BG) and 19% in whom a perioperative breast cancer was diagnosed (Cancer Group, CG). 128 women also completed a Hospital Anxiety & Depression Score (HADS) questionnaire to test if preoperative HADS score could predict PROMS outcomes. RESULTS: Women in the CG had lower PROMS scores for satisfaction with their breasts, nipple reconstruction and sexual wellbeing. Both groups reported equal satisfaction with BRRM outcome and psychosocial well-being. Physical well-being PROMS of the abdomen and chest were high in women in both groups as were scores for satisfaction with the care they received. The CG group reported suboptimal quality of patient information. A higher presurgical HADS anxiety score predicted less favourable postoperative psychosocial well-being despite similar levels of satisfaction with aesthetic outcome. CONCLUSION: We show a high degree of patient reported satisfaction by woman undergoing BRRM and reconstruction. There was a negative association with a cancer diagnosis on quality of life PROMS and higher preoperative anxiety levels negatively affected postoperative psychosocial well-being. These important findings should be part of the informed consent process during preoperative counselling.

Longitudinal crossover and the dynamics of uniform electron ellipsoids focused by a linear chirp.

High-resolution single-shot nonrelativistic ultrafast electron microscopy (UEM) relies on adaptive optics to compress high-intensity bunches using radio frequency (RF) cavities. We present a comprehensive discussion of the analytic approaches available to characterize bunch dynamics as an electron bunch goes through a longitudinal focal point after an RF cavity where space charge effects can be large. Methods drawn from the Coulomb explosion literature, the accelerator physics literature, and the analytic Gaussian model developed for UEM are compared, utilized, and extended in some cases. In particular the longitudinal focus may occur in two different regimes, a bounce-back regime and a crossover regime; and we characterize the critical point separating these regimes in the zero-emittance model. Results from N-particle simulations using efficient multipole methods are compared to the theoretical models revealing features requiring extensions of the analytic approaches; and in particular mechanisms for emittance growth and transfer are discussed.

Active control of bright electron beams with RF optics for femtosecond microscopy.

A frontier challenge in implementing femtosecond electron microscopy is to gain precise optical control of intense beams to mitigate collective space charge effects for significantly improving the throughput. Here, we explore the flexible uses of an RF cavity as a longitudinal lens in a high-intensity beam column for condensing the electron beams both temporally and spectrally, relevant to the design of ultrafast electron microscopy. Through the introduction of a novel atomic grating approach for characterization of electron bunch phase space and control optics, we elucidate the principles for predicting and controlling the phase space dynamics to reach optimal compressions at various electron densities and generating conditions. We provide strategies to identify high-brightness modes, achieving ∼100 fs and ∼1 eV resolutions with 106 electrons per bunch, and establish the scaling of performance for different bunch charges. These results benchmark the sensitivity and resolution from the fundamental beam brightness perspective and also validate the adaptive optics concept to enable delicate control of the density-dependent phase space structures to optimize the performance, including delivering ultrashort, monochromatic, high-dose, or coherent electron bunches.

Algorithm for systematic peak extraction from atomic pair distribution functions.

The study presents an algorithm, ParSCAPE, for model-independent extraction of peak positions and intensities from atomic pair distribution functions (PDFs). It provides a statistically motivated method for determining parsimony of extracted peak models using the information-theoretic Akaike information criterion (AIC) applied to plausible models generated within an iterative framework of clustering and chi-square fitting. All parameters the algorithm uses are in principle known or estimable from experiment, though careful judgment must be applied when estimating the PDF baseline of nanostructured materials. ParSCAPE has been implemented in the Python program SrMise. Algorithm performance is examined on synchrotron X-ray PDFs of 16 bulk crystals and two nanoparticles using AIC-based multimodeling techniques, and particularly the impact of experimental uncertainties on extracted models. It is quite resistant to misidentification of spurious peaks coming from noise and termination effects, even in the absence of a constraining structural model. Structure solution from automatically extracted peaks using the Liga algorithm is demonstrated for 14 crystals and for C60. Special attention is given to the information content of the PDF, theory and practice of the AIC, as well as the algorithm's limitations.

Ab-initio reconstruction of complex Euclidean networks in two dimensions.

Reconstruction of complex structures is an inverse problem arising in virtually all areas of science and technology, from protein structure determination to bulk heterostructure solar cells and the structure of nanoparticles. We cast this problem as a complex network problem where the edges in a network have weights equal to the Euclidean distance between their endpoints. We present a method for reconstruction of the locations of the nodes of the network given only the edge weights of the Euclidean network. The theoretical foundations of the method are based on rigidity theory, which enables derivation of a polynomial bound on its efficiency. An efficient implementation of the method is discussed and timing results indicate that the run time of the algorithm is polynomial in the number of nodes in the network. We have reconstructed Euclidean networks of about 1000 nodes in approximately 24 h on a desktop computer using this implementation. We also reconstruct Euclidean networks corresponding to polymer chains in two dimensions and planar graphene nanoparticles. We have also modified our base algorithm so that it can successfully solve random point sets when the input data are less precise.

Exploring the needs, concerns and behaviours of people with existing respiratory conditions in relation to the H1N1 'swine influenza' pandemic: a multicentre survey and qualitative study.

BACKGROUND: People with respiratory conditions are a 'high-risk' group for H1N1 pandemic swine influenza ('swine flu'), hence they and their families may have information needs, worries and concerns regarding the condition. Health-related behaviours, including vaccination, are recommended during the pandemic; understanding uptake of these is important. OBJECTIVES: To explore and compare information needs, worries and concerns, and health-related behaviours regarding swine flu in people with respiratory conditions and their family members. METHODS: Mixed-methods study - cross-sectional survey (253 patients, 101 family members); one-to-one interviews (13 patients, seven family members) and focus groups (n = three groups, 30 participants). Data collected October 2009-January 2010 from hospital chest clinics (n = 7) and patient support groups (n = 10) in North West England. RESULTS: Most patients (P) and family members (FM) wanted more information (n = 158, 62.5% P; n = 55, 54.4% FM), but few felt completely uninformed (n = 15, 5.9% P; n = 3, 3.0% FM). Most had already received information about swine flu (n = 187, 73.9% P; n = 78, 77.2% FM), mainly via a leaflet delivered to their home (n = 125, 49.4% P; n = 55, 54.5% FM). Information received was considered helpful (n = 154, 60.9% P; n = 77, 72.6% FM), but many wanted more condition-specific information (n = 141, 55.7% P; n = 60, 59.4% FM). More patients were worried (n = 147, 58.3%) than not worried (n = 99, 39.3%) about swine flu. FM were less often concerned about personal risk (n = 47, 46.6% worried) than about risk to patients (n = 76, 77.6%). Two-thirds (n = 161, 63.6% P; 65, 65.6% FM) incorrectly believed patients had increased risk of developing swine flu, but most (n = 204, 81.0% P; 89, 89.9% FM) correctly identified patients' greater risk of developing complications. Commonly adopted preventative measures were more frequent hand-washing (107, 42.8% P; 38, 37.6% FM) and greater use of sanitising hand gel (n = 100, 40.5% P; 37, 36.6% FM). In total, 212 patients (83.8%) and 69 family members (68.3%) were very/fairly likely to take up swine flu vaccination. Qualitative data mirrored survey findings. CONCLUSIONS: Participants were generally well-informed about swine flu, but more targeted information would have been welcomed. Participants were not highly anxious about swine flu, but did recognise risks for patients. Behaviour change was modest, but in line with recommendations. Vaccination intent was high. STUDY REGISTRATION: The study has been registered as REC/IRAS (Ref 09/H1015/76) and NIHR CSP (Ref 32483).

The Liga algorithm for ab initio determination of nanostructure.

Computational techniques for nanostructure determination of substances that resist standard crystallographic methods are often laborious processes starting from initial guess solutions not derived from experimental data. The Liga algorithm can create nanostructures using only lists of lengths or distances between atom pairs, providing an experimental basis for starting structures. These distance lists may be extracted from a variety of experimental probes and we illustrate the procedure with distances determined from the pair distribution function. Candidate subclusters that are a subset of a structure's atoms compete based on adherence to the length list. Atoms are added to well performing candidates and removed from poor ones, until a complete structure with sufficient agreement to the length list emerges. The Liga algorithm is shown to reliably recreate Lennard-Jones clusters from ideal length lists and the C60 structure from neutron-scattering data. The correct fullerene structure was obtained with experimental data which missed several distances and had loosened constraints on distance multiplicity. This suggests that the Liga algorithm may have robust applicability for a wide range of nanostructures even in the absence of ideal data.

Maximum independent set on diluted triangular lattices.

Core percolation and maximum independent set on random graphs have recently been characterized using the methods of statistical physics. Here we present a statistical physics study of these problems on bond diluted triangular lattices. Core percolation critical behavior is found to be consistent with the standard percolation values, though there are strong finite size effects. A transfer matrix method is developed and applied to find accurate values of the density and degeneracy of the maximum independent set on lattices of limited width but large length. An extrapolation of these results to the infinite lattice limit yields high precision results, which are tabulated. These results are compared to results found using both vertex based and edge based local probability recursion algorithms, which have proven useful in the analysis of hard computational problems, such as the satisfiability problem.

Ab initio determination of solid-state nanostructure.

Advances in materials science and molecular biology followed rapidly from the ability to characterize atomic structure using single crystals. Structure determination is more difficult if single crystals are not available. Many complex inorganic materials that are of interest in nanotechnology have no periodic long-range order and so their structures cannot be solved using crystallographic methods. Here we demonstrate that ab initio structure solution of these nanostructured materials is feasible using diffraction data in combination with distance geometry methods. Precise, sub-ångström resolution distance data are experimentally available from the atomic pair distribution function (PDF). Current PDF analysis consists of structure refinement from reasonable initial structure guesses and it is not clear, a priori, that sufficient information exists in the PDF to obtain a unique structural solution. Here we present and validate two algorithms for structure reconstruction from precise unassigned interatomic distances for a range of clusters. We then apply the algorithms to find a unique, ab initio, structural solution for C60 from PDF data alone. This opens the door to sub-ångström resolution structure solution of nanomaterials, even when crystallographic methods fail.

Statistical physics of grain-boundary engineering.

Percolation theory is now standard in the analysis of polycrystalline materials where the grain boundaries can be divided into two distinct classes, namely "good" boundaries that have favorable properties and "bad" boundaries that seriously degrade the material performance. Grain-boundary engineering (GBE) strives to improve material behavior by engineering the volume fraction c and arrangement of good grain boundaries. Two key percolative processes in GBE materials are the onset of percolation of a strongly connected aggregate of grains, and the onset of a connected path of weak grain boundaries. Using realistic polycrystalline microstructures, we find that in two dimensions the threshold for strong aggregate percolation c(SAP) and the threshold for weak boundary percolation c(WBP) are equivalent and have the value c(SAP) = c(WBP) =0.38 (1) , which is slightly higher than the threshold found for regular hexagonal grain structures, c(RH) =2 sin (pi/18) =0.347... . In three dimensions strong aggregate percolation and weak boundary percolation occur at different locations and we find c(SAP) =0.12 (3) and c(WBP) =0.77 (3) . The critical current in high T(c) materials and the cohesive energy in structural systems are related to the critical manifold problem in statistical physics. We develop a theory of critical manifolds in GBE materials, which has three distinct regimes: (i) low concentrations, where random manifold theory applies, (ii) critical concentrations where percolative scaling theory applies, and (iii) high concentrations, c> c(SAP) , where the theory of periodic elastic media applies. Regime (iii) is perhaps most important practically and is characterized by a critical length L(c) , which is the size of cleavage regions on the critical manifold. In the limit of high contrast epsilon-->0 , we find that in two dimensions L(c) proportional, gc/ (1-c) , while in three dimensions L(c) proportional, g exp [ b(0) c/ (1-c) ] / [c (1-c) ](1/2) , where g is the average grain size, epsilon is the ratio of the bonding energy of the weak boundaries to that of the strong boundaries, and b(0) is a constant which is of order 1. Many of the properties of GBE materials can be related to L(c) , which diverges algebraically on approach to c=1 in two dimensions, but diverges exponentially in that limit in three dimensions. We emphasize that GBE percolation processes and critical manifold behavior are very different in two dimensions as compared to three dimensions. For this reason, the use of two dimensional models to understand the behavior of bulk GBE materials can be misleading.

Culling avalanches in bootstrap percolation.

We study the culling avalanches which occur after the "death" of a single randomly chosen site in a network where sites are unstable, and are culled, if they have coordination less than an integer parameter m. Avalanche distributions are presented for triangular and cubic lattices for values of m where the associated bootstrap transitions are either first or second order. In second order cases, the culling avalanche distribution is found to be exponential, while in first order cases it follows a power law. We present an exact relation between culling avalanches and conventional bootstrap percolation and show that a relation proposed by Manna [Physica A 261, 351 (1998)] can be a good approximation for strongly first order bootstrap transitions but not for continuous bootstrap transitions.

Scaling laws for critical manifolds in polycrystalline materials.

We study the surfaces of lowest energy through model polycrystalline materials in two and three dimensions. When the grain boundaries are sufficiently weak, these critical manifolds (CM's) lie entirely on grain boundaries, while when the grain boundaries are strong, cleavage occurs. A scaling theory for the intergranular to transgranular transition of CM's is developed. The key parameters are the average grain size g, the ratio of grain boundary to the grain interior energy, epsilon, and the sample size L. The key result is that a critical length scale exists, L(c)(g,epsilon), so that on short length scales lL(c), the critical manifold is rough. We develop a scaling theory for L(c) and find that in two dimensions L(c) approximately gx(y(2)), while in three dimensions L(c) approximately g exp(bx(y(3))), where x=epsilon/(1-epsilon) and b is a constant. Data from realistic polycrystalline grain structures are used to test the scaling theory. The exact lowest energy surface through model grain structures is found using a mapping to the minimum-cut/maximum-flow problem in computer science. As a function of grain-boundary energy, we observe the crossover from grain-boundary rupture to mixed mode failure (a mixture of transgramular and intergranular modes) and finally cleavage and that the two-dimensional data are consistent with y(2) approximately 3.0+/-0.3, while the three-dimensional data are more difficult to analyze, but are consistent with y(3) approximately 3.5+/-1.0.

Permeability and conductivity of platelet-reinforced membranes and composites.

We present large-scale simulations of the diffusion constant D of a random composite consisting of aligned platelets with aspect ratio a/b>>1 in a matrix (with diffusion constant D0) and find that D/D(0)=1/(1+c(1)x+c(2)x(2)), where x=av(f)/b and v(f) is the platelet volume fraction. We demonstrate that for large aspect ratio platelets the pair term (x(2)) dominates suggesting large property enhancements for these materials. However, a small amount of face-to-face ordering of the platelets markedly degrades the efficiency of platelet reinforcement.

Ground state nonuniversality in the random-field Ising model.

Two attractive and often used ideas, namely, universality and the concept of a zero-temperature fixed point, are violated in the infinite-range random-field Ising model. In the ground state we show that the exponents can depend continuously on the disorder and so are nonuniversal. However, we also show that at finite temperature the thermal order-parameter exponent 1/2 is restored so that temperature is a relevant variable. Broader implications of these results are discussed.

Minimum spanning trees on random networks.

We show that the geometry of minimum spanning trees (MST) on random graphs is universal. Because of this geometric universality, we are able to characterize the energy of MST using a scaling distribution [P(epsilon)] found using uniform disorder. We show that the MST energy for other disorder distributions is simply related to P(epsilon). We discuss the relationship to invasion percolation, to the directed polymer in a random media, to uniform spanning trees, and also the implications for the broader issue of universality in disordered systems.

Extremal statistics in the energetics of domain walls.

We study at T=0 the minimum energy of a domain wall and its gap to the first excited state, concentrating on two-dimensional random-bond Ising magnets. The average gap scales as deltaE1 approximately L(straight theta)f(N(z)), where f(y) approximately [ln y](-1/2), straight theta is the energy fluctuation exponent, L is the length scale, and N(z) is the number of energy valleys. The logarithmic scaling is due to extremal statistics, which is illustrated by mapping the problem into the Kardar-Parisi-Zhang roughening process. It follows that the susceptibility of domain walls also has a logarithmic dependence on the system size.

Intermittence and roughening of periodic elastic media.

We analyze intermittence and roughening of an elastic interface or domain wall pinned in a periodic potential, in the presence of random-bond disorder in 1+1 and 2+1 dimensions. Though the ensemble average behavior is smooth, the typical behavior of a large sample is intermittent, and does not self-average to a smooth behavior. Instead, large fluctuations occur in the mean location of the interface and the onset of interface roughening is via an extensive fluctuation which leads to a jump in the roughness of order lambda, the period of the potential. Analytical arguments based on extreme statistics are given for the number of the minima of the periodicity visited by the interface and for the roughening crossover, which is confirmed by extensive exact ground state calculations.

Atomic diffusion, step relaxation, and step fluctuations.

We show that the dynamics of the pair correlation function in a step train can pinpoint the dominant relaxation mechanism occurring at a crystal surface. Evaporation-condensation and step-edge diffusion do not produce dynamical correlations between neighboring steps, while terrace diffusion may lead to correlations which fall off like a power law with distance and which are peaked at a characteristic time. We derive these results within a "real space" Langevin formalism which is based on diffusion kernels which are different for each mass transport process. We validate this formalism by reproducing the step fluctuation autocorrelation function. We then derive results on the pair correlation between different steps. Results for solvable limiting cases are summarized in Tables I and II of the paper. As an intermediate step in the analysis we also find expressions for the relaxation time tau(pq) of a mode of wave number q along the steps and wave number p perpendicular to the steps, which we also discuss and compare with prior work.

Active clusters in disordered systems.

We introduce an exact algorithm to calculate the distribution of large low energy clusters (droplets) in disordered manifolds and disordered magnets, and we analyze the extent to which these clusters can be treated as independent two-level systems. We show that interfaces in randomly diluted networks always have broad droplet distributions, while diluted antiferromagnets in a field can have either power law or exponential droplet distributions.

Exact Solution to an Interacting Extreme-Value Problem: The Pure-Flaw Model.

Simple models play a key role in the microstructural analysis of mechanical failure in composites and other materials with complex and often disordered microstructures. Although equal load-sharing-models are amenable to rigorous statistical analysis, problems with local load enhancements near failed regions of the material have so far resisted exact analysis. Here we show for the first time, that some of the simpler of these local-load-sharing models can be solved exactly using a sub-stochastic matrix method. For diluted fiber bundles with local load sharing, it is possible to find a compact expression for the characteristic equation of the sub-stochastic matrix, and from it obtain an asymptotic expansion for the largest eigenvalue of the matrix. This in turn gives the asymptotic behavior of the size effect and statistics of the fiber-bundle models. We summarize these results, and show that the important features of the exact result can be obtained from a single scaling analysis we had developed previously. We also compare the statistics of fracture with the appropriate limiting extreme-value survival distribution (a Gumbel distribution), and, as previously indicated by Harlow and Phoenix, note that the Gumbel distribution performs quite poorly in this problem. We comment on the physical origin of this discrepancy.