Measurement of anisotropies of the kinetic energy and anharmonicity in pyrolytic graphite by neutron Compton scattering

Neutron Compton scattering (NCS) measurements of the anisotropy of the momentum distribution and the mean Laplacian of the interatomic potential ∇2V have been performed using electron volt neutrons, with wave vector transfers between 24 Å−1 and 98 Å−1. The measured momentum distribution of the atoms displays significantly more anisotropy than a calculation using a model density of states. We have observed anisotropies in ∇2V for the first time. The results suggest that the atomic potential is harmonic within the graphite planes, but anharmonic for vibrations perpendicular to the planes.

Kinetic energy of He atoms in liquid He-4-He-3 mixtures

Deep inelastic neutron scattering measurements on liquid 3He-4He mixtures in the normal phase have been performed on the VESUVIO spectrometer at the ISIS pulsed neutron source at exchanged wave vectors of about q≃120.0Å-1. The neutron Compton profiles J(y) of the mixtures were measured along the T=1.96K isotherm for 3He concentrations, x, ranging from 0.1 to 1.0 at saturated vapor pressures. Values of kinetic energies 〈T〉 of 3He and 4He atoms as a function of x, 〈T〉(x), were extracted from the second moment of J(y). The present determinations of 〈T〉(x) confirm previous experimental findings for both isotopes and, in the case of 3He, a substantial disagreement with theory is found. In particular 〈T〉(x) for the 3He atoms is found to be independent of concentration yielding a value 〈T〉3(x=0.1)≃12K, much lower than the value suggested by the most recent theoretical estimates of approximately 19 K.

Sensitivity of edge detection methods for quantifying cell migration assays

Quantitative imaging methods to analyze cell migration assays are not standardized. Here we present a suite of two–dimensional barrier assays describing the collective spreading of an initially–confined population of 3T3 fibroblast cells. To quantify the motility rate we apply two different automatic image detection methods to locate the position of the leading edge of the spreading population after 24, 48 and 72 hours. These results are compared with a manual edge detection method where we systematically vary the detection threshold. Our results indicate that the observed spreading rates are very sensitive to the choice of image analysis tools and we show that a standard measure of cell migration can vary by as much as 25% for the same experimental images depending on the details of the image analysis tools. Our results imply that it is very difficult, if not impossible, to meaningfully compare previously published measures of cell migration since previous results have been obtained using different image analysis techniques and the details of these techniques are not always reported. Using a mathematical model, we provide a physical interpretation of our edge detection results. The physical interpretation is important since edge detection algorithms alone do not specify any physical measure, or physical definition, of the leading edge of the spreading population. Our modeling indicates that variations in the image threshold parameter correspond to a consistent variation in the local cell density. This means that varying the threshold parameter is equivalent to varying the location of the leading edge in the range of approximately 1–5% of the maximum cell density.

Design and interpretation of cell trajectory assays

Cell trajectory data is often reported in the experimental cell biology literature to distinguish between different types of cell migration. Unfortunately, there is no accepted protocol for designing or interpreting such experiments and this makes it difficult to quantitatively compare different published data sets and to understand how changes in experimental design influence our ability to interpret different experiments. Here, we use an individual based mathematical model to simulate the key features of a cell trajectory experiment. This shows that our ability to correctly interpret trajectory data is extremely sensitive to the geometry and timing of the experiment, the degree of motility bias and the number of experimental replicates. We show that cell trajectory experiments produce data that is most reliable when the experiment is performed in a quasi 1D geometry with a large number of identically{prepared experiments conducted over a relatively short time interval rather than few trajectories recorded over particularly long time intervals.

Locked nucleic acid (LNA) single nucleotide polymorphism (SNP) genotype analysis and validation using real-time PCR

With an increased emphasis on genotyping of single nucleotide polymorphisms (SNPs) in disease association studies, the genotyping platform of choice is constantly evolving. In addition, the development of more specific SNP assays and appropriate genotype validation applications is becoming increasingly critical to elucidate ambiguous genotypes. In this study, we have used SNP specific Locked Nucleic Acid (LNA) hybridization probes on a real-time PCR platform to genotype an association cohort and propose three criteria to address ambiguous genotypes. Based on the kinetic properties of PCR amplification, the three criteria address PCR amplification efficiency, the net fluorescent difference between maximal and minimal fluorescent signals and the beginning of the exponential growth phase of the reaction. Initially observed SNP allelic discrimination curves were confirmed by DNA sequencing (n = 50) and application of our three genotype criteria corroborated both sequencing and observed real-time PCR results. In addition, the tested Caucasian association cohort was in Hardy-Weinberg equilibrium and observed allele frequencies were very similar to two independently tested Caucasian association cohorts for the same tested SNP. We present here a novel approach to effectively determine ambiguous genotypes generated from a real-time PCR platform. Application of our three novel criteria provides an easy to use semi-automated genotype confirmation protocol.

The effect of surface tension and kinetic undercooling on a radially-symmetric melting problem

The addition of surface tension to the classical Stefan problem for melting a sphere causes the solution to blow up at a finite time before complete melting takes place. This singular behaviour is characterised by the speed of the solid-melt interface and the flux of heat at the interface both becoming unbounded in the blow-up limit. In this paper, we use numerical simulation for a particular energy-conserving one-phase version of the problem to show that kinetic undercooling regularises this blow-up, so that the model with both surface tension and kinetic undercooling has solutions that are regular right up to complete melting. By examining the regime in which the dimensionless kinetic undercooling parameter is small, our results demonstrate how physically realistic solutions to this Stefan problem are consistent with observations of abrupt melting of nanoscaled particles.

Reliability of spatiotemporal and kinetic gait parameters determined by a new instrumented treadmill system

Background Despite the emerging use of treadmills integrated with pressure platforms as outcome tools in both clinical and research settings, published evidence regarding the measurement properties of these new systems is limited. This study evaluated the within– and between–day repeatability of spatial, temporal and vertical ground reaction forces measured by a treadmill system instrumented with a capacitance–based pressure platform. Methods Thirty three healthy adults (mean age, 21.5 ± 2.8 years; height, 168.4 ± 9.9 cm; and mass, 67.8 ± 18.6 kg), walked barefoot on a treadmill system (FDM–THM–S, Zebris Medical GmbH) on three separate occasions. For each testing session, participants set their preferred pace but were blinded to treadmill speed. Spatial (foot rotation, step width, stride and step length), temporal (stride and step times, duration of stance, swing and single and double support) and peak vertical ground reaction force variables were collected over a 30–second capture period, equating to an average of 52 ± 5 steps of steady–state walking. Testing was repeated one week following the initial trial and again, for a third time, 20 minutes later. Repeated measures ANOVAs within a generalized linear modelling framework were used to assess between–session differences in gait parameters. Agreement between gait parameters measured within the same day (session 2 and 3) and between days (session 1 and 2; 1 and 3) were evaluated using the 95% repeatability coefficient. Results There were statistically significant differences in the majority (14/16) of temporal, spatial and kinetic gait parameters over the three test sessions (P < .01). The minimum change that could be detected with 95% confidence ranged between 3% and 17% for temporal parameters, 14% and 33% for spatial parameters, and 4% and 20% for kinetic parameters between days. Within–day repeatability was similar to that observed between days. Temporal and kinetic gait parameters were typically more consistent than spatial parameters. The 95% repeatability coefficient for vertical force peaks ranged between ± 53 and ± 63 N. Conclusions The limits of agreement in spatial parameters and ground reaction forces for the treadmill system encompass previously reported changes with neuromuscular pathology and footwear interventions. These findings provide clinicians and researchers with an indication of the repeatability and sensitivity of the Zebris treadmill system to detect changes in common spatiotemporal gait parameters and vertical ground reaction forces.

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

The salt dependence of DNA recognition by NF-kappaB p50 : a detailed kinetic analysis of the effects on affinityand specificity

The binding kinetics of NF-kappaB p50 to the Ig-kappaB site and to a DNA duplex with no specific binding site were determined under varying conditions of potassium chloride concentration using a surface plasmonresonance biosensor. Association and dissociation rate constants were measured enabling calculation of the dissociation constants. Under previously established high affinity buffer conditions, the k a for both sequences was in the order of 10(7) M-1s-1whilst the k d values varied 600-fold in a sequence-dependent manner between 10(-1) and 10(-4 )s-1, suggesting that the selectivity of p50 for different sequences is mediated primarily through sequence-dependent dissociation rates. The calculated K D value for the Ig-kappaB sequence was 16 pM, whilst the K D for the non-specific sequence was 9.9 nM. As the ionic strength increased to levels which are closer to that of the cellular environment, the binding of p50 to the non-specific sequence was abolished whilst the specific affinity dropped to nanomolar levels. From these results, a mechanism is proposed in which p50 binds specific sequences with high affinity whilst binding non-specific sequences weakly enough to allow efficient searching of the DNA.

Comparison of high sensitivity troponin T and I assays in the diagnosis of non-ST elevation acute myocardial infarction in emergency patients with chest pain

Objectives: Concentrations of troponin measured with high sensitivity troponin assays are raised in a number of emergency department (ED) patients; however many are not diagnosed with acute myocardial infarction (AMI). Clinical comparisons between the early use (2 h after presentation) of high sensitivity cardiac troponin T (hs-cTnT) and I (hs-cTnI) assays for the diagnosis of AMI have not been reported. Design and methods: Early (0 h and 2 h) hs-cTnT and hs-cTnI assay results in 1571 ED patients with potential acute coronary syndrome (ACS) without ST elevation on electrocardiograph (ECG) were evaluated. The primary outcome was diagnosis of index MI adjudicated by cardiologists using the local cTnI assay results taken ≥6 h after presentation, ECGs and clinical information. Stored samples were later analysed with hs-cTnT and hs-cTnI assays. Results: The ROC analysis for AMI (204 patients; 13.0%) for hs-cTnT and hs-cTnI after 2 h was 0.95 (95% CI: 0.94–0.97) and 0.98 (95% CI: 0.97–0.99) respectively. The sensitivity, specificity, PLR, and NLR of hs-cTnT and hs-cTnI for AMI after 2 h were 94.1% (95% CI: 90.0–96.6) and 95.6% (95% CI: 91.8–97.7), 79.0% (95% CI: 76.8–81.1) and 92.5% (95% CI: 90.9–93.7), 4.48 (95% CI: 4.02–5.00) and 12.86 (95% CI: 10.51–15.31), and 0.07 (95% CI: 0.04–0.13) and 0.05 (95% CI:0.03–0.09) respectively. Conclusions: Exclusion of AMI 2 h after presentation in emergency patients with possible ACS can be achieved using hs-cTnT or hs-cTnI assays. Significant differences in specificity of these assays are relevant and if using the hs-cTnT assay, further clinical assessment in a larger proportion of patients would be required.

Molecular and cellular analysis of basement membrane invasion by human breast cancer cells in Matrigel-based in vitro assays

In vitro analyses of basement membrane invasiveness employing Matrigel (a murine tumor extract rich in basement membrane components) have been performed on human breast cancer model systems. Constitutive invasiveness of different human breast cancer (HBC) cell lines has been examined as well as regulation by steroid hormones, growth factors, and oncogenes. Carcinoma cells exhibiting a mesenchymal-like phenotype (vimentin expression, lack of cell border associated uvomorulin) show dramatically increased motility, invasiveness, and metastatic potential in nude mice. These findings support the hypothesis that epithelial to mesenchymal transition (EMT)-like events may be instrumental in the metastatic progression of human breast cancer. The MCF-7 subline MCF-7ADR appears to have undergone such a transition. The importance of such a transition may be reflected in the emergence of vimentin expression as an indicator of poor prognosis in HBC. Matrix degradation and laminin recognition are highlighted as potential targets for antimetastatic therapy, and analyses of laminin attachment and the matrix metalloproteinase (MMP) family in HBC cell lines are summarized. Matrigel-based assays have proved useful in the study of the molecular mechanisms of basement membrane invasiveness, their regulation in HBC cells, and their potential as targets for antimetastatic therapy.

Chemo-enzymatic synthesis of unnatural amino acids

A general chemo-enzymatic process has been developed to prepare enantiomerically pure L- and D-amino acids in high yield by deracemisation of racemic starting materials. The method has been developed from initial academic studies to be a robust, scalable industrial process. Unnatural amino acids, in high optical purity, are a rapidly growing class of intermediates required for pharmaceuticals, agrochemicals and other fine chemical applications. However, no single method has proven sufficiently adaptable to prepare these compounds generally at large scale. Our approach uses an enantioselective oxidase biocatalyst and a non-selective chemical reducing agent to effect the stereoinversion of one enantiomer and can result in an enantiomeric excess of > 99 % from a starting racemate, and product yields over 90 %. The current approach compares very favourably to resolution methods which have a maximum single pass yield of 50 %. Efficient methods have been developed to adapt the biocatalyst used in this process towards new target compounds and to optimise key factors which improve the process efficiency and offer competitive economics at scale.

Assays for the study of human cancer cell invasion and metastasis

Two in vitro and two in vivo assays for the study of human cancer invasion and metastasis are described. The assays include in vitro invasiveness through an artificial basement membrane (Matrigel®), invasiveness and metastasis in nude mice of subcutaneously injected LacZ-transduced human tumor cells, in vitro adherence to basement membrane components, and LacZ-transduced human cancer cells injected intravenously into nude mice. In studies of the processes involved in human cancer cell invasion and metastasis, these four assays were found to be complementary, and thus provide a set of test systems for preclinical screening of agents which interfere with these processes.

Self-organized quantum dot arrays : kinetic mapping of adatom capture

Deterministic synthesis of self-organized quantum dot arrays for renewable energy, biomedical, and optoelectronic applications requires control over adatom capture zones, which are presently mapped using unphysical geometric tessellation. In contrast, the proposed kinetic mapping is based on simulated two-dimensional adatom fluxes in the array and includes the effects of nucleation, dissolution, coalescence, and process parameters such as surface temperature and deposition rate. This approach is generic and can be used to control the nanoarray development in various practical applications. © 2009 American Institute of Physics.

Thermodynamical and plasma-driven kinetic growth of high-aspect-ratio nanostructures : effect of hydrogen termination

The results of studies on the growth of high-aspect nanostructures in low-temperature non-equilibrium plasmas of reactive gas mixtures with or without hydrogen are presented. The results suggest that the hydrogen in the reactive plasma strongly affects the length of the nanostructures. This phenomenon is explained in terms of selective hydrogen passivation of the lateral and top surfaces of the surface-supported nanostructures. The theoretical model describes the effect of the atomic hydrogen passivation on the nanostructure shape and predicts the critical hydrogen coverage of the lateral surfaces necessary to achieve the nanostructure growth with the pre-determined shape. Our results demonstrate that the use of a strongly non-equilibrium plasma is very effective in significantly improving the shape control of quasi-one-dimensional single-crystalline nanostructures.