Comparison of I-131 Radioimmunotherapy Tumor Dosimetry: Unit Density Sphere Model Versus Patient-Specific Monte Carlo Calculations

High computational requirements restrict the use of Monte Carlo algorithms for dose estimation in a clinical setting, despite the fact that they are considered more accurate than traditional methods. The goal of this study was to compare mean tumor absorbed dose estimates using the unit density sphere model incorporated in OLINDA with previously reported dose estimates from Monte Carlo simulations using the dose planning method (DPMMC) particle transport algorithm. The dataset (57 tumors, 19 lymphoma patients who underwent SPECT/CT imaging during I-131 radioimmunotherapy) included tumors of varying size, shape, and contrast. OLINDA calculations were first carried out using the baseline tumor volume and residence time from SPECT/CT imaging during 6 days post-tracer and 8 days post-therapy. Next, the OLINDA calculation was split over multiple time periods and summed to get the total dose, which accounted for the changes in tumor size. Results from the second calculation were compared with results determined by coupling SPECT/CT images with DPM Monte Carlo algorithms. Results from the OLINDA calculation accounting for changes in tumor size were almost always higher (median 22%, range -1%-68%) than the results from OLINDA using the baseline tumor volume because of tumor shrinkage. There was good agreement (median -5%, range -13%-2%) between the OLINDA results and the self-dose component from Monte Carlo calculations, indicating that tumor shape effects are a minor source of error when using the sphere model. However, because the sphere model ignores cross-irradiation, the OLINDA calculation significantly underestimated (median 14%, range 2%-31%) the total tumor absorbed dose compared with Monte Carlo. These results show that when the quantity of interest is the mean tumor absorbed dose, the unit density sphere model is a practical alternative to Monte Carlo for some applications. For applications requiring higher accuracy, computer-intensive Monte Carlo calculation is needed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90433/1/cbr-2E2011-2E0965.pd

Urinary ATP as an indicator of infection and inflammation of the urinary tract in patients with lower urinary tract symptoms

BACKGROUND: Adenosine-5'-triphosphate (ATP) is a neurotransmitter and inflammatory cytokine implicated in the pathophysiology of lower urinary tract disease. ATP additionally reflects microbial biomass thus has potential as a surrogate marker of urinary tract infection (UTI). The optimum clinical sampling method for ATP urinalysis has not been established. We tested the potential of urinary ATP in the assessment of lower urinary tract symptoms, infection and inflammation, and validated sampling methods for clinical practice. METHODS: A prospective, blinded, cross-sectional observational study of adult patients presenting with lower urinary tract symptoms (LUTS) and asymptomatic controls, was conducted between October 2009 and October 2012. Urinary ATP was assayed by a luciferin-luciferase method, pyuria counted by microscopy of fresh unspun urine and symptoms assessed using validated questionnaires. The sample collection, storage and processing methods were also validated. RESULTS: 75 controls and 340 patients with LUTS were grouped as without pyuria (n = 100), pyuria 1-9 wbc ?l(-1) (n = 120) and pyuria ?10 wbc ?l(-1) (n = 120). Urinary ATP was higher in association with female gender, voiding symptoms, pyuria greater than 10 wbc ?l(-1) and negative MSU culture. ROC curve analysis showed no evidence of diagnostic test potential. The urinary ATP signal decayed with storage at 23°C but was prevented by immediate freezing at ??-20°C, without boric acid preservative and without the need to centrifuge urine prior to freezing. CONCLUSIONS: Urinary ATP may have a role as a research tool but is unconvincing as a surrogate, clinical diagnostic marker

Characterization of complex networks: A survey of measurements

Each complex network (or class of networks) presents specific topological features which characterize its connectivity and highly influence the dynamics of processes executed on the network. The analysis, discrimination, and synthesis of complex networks therefore rely on the use of measurements capable of expressing the most relevant topological features. This article presents a survey of such measurements. It includes general considerations about complex network characterization, a brief review of the principal models, and the presentation of the main existing measurements. Important related issues covered in this work comprise the representation of the evolution of complex networks in terms of trajectories in several measurement spaces, the analysis of the correlations between some of the most traditional measurements, perturbation analysis, as well as the use of multivariate statistics for feature selection and network classification. Depending on the network and the analysis task one has in mind, a specific set of features may be chosen. It is hoped that the present survey will help the proper application and interpretation of measurements.Comment: A working manuscript with 78 pages, 32 figures. Suggestions of measurements for inclusion are welcomed by the author

Search for Gravitational Waves from Primordial Black Hole Binary Coalescences in the Galactic Halo

We use data from the second science run of the LIGO gravitational-wave detectors to search for the gravitational waves from primordial black hole (PBH) binary coalescence with component masses in the range 0.2--$1.0 M_\odot$. The analysis requires a signal to be found in the data from both LIGO observatories, according to a set of coincidence criteria. No inspiral signals were found. Assuming a spherical halo with core radius 5 kpc extending to 50 kpc containing non-spinning black holes with masses in the range 0.2--$1.0 M_\odot$, we place an observational upper limit on the rate of PBH coalescence of 63 per year per Milky Way halo (MWH) with 90% confidence.Comment: 7 pages, 4 figures, to be submitted to Phys. Rev.

Molecular and cellular mechanisms underlying the evolution of form and function in the amniote jaw.

The amniote jaw complex is a remarkable amalgamation of derivatives from distinct embryonic cell lineages. During development, the cells in these lineages experience concerted movements, migrations, and signaling interactions that take them from their initial origins to their final destinations and imbue their derivatives with aspects of form including their axial orientation, anatomical identity, size, and shape. Perturbations along the way can produce defects and disease, but also generate the variation necessary for jaw evolution and adaptation. We focus on molecular and cellular mechanisms that regulate form in the amniote jaw complex, and that enable structural and functional integration. Special emphasis is placed on the role of cranial neural crest mesenchyme (NCM) during the species-specific patterning of bone, cartilage, tendon, muscle, and other jaw tissues. We also address the effects of biomechanical forces during jaw development and discuss ways in which certain molecular and cellular responses add adaptive and evolutionary plasticity to jaw morphology. Overall, we highlight how variation in molecular and cellular programs can promote the phenomenal diversity and functional morphology achieved during amniote jaw evolution or lead to the range of jaw defects and disease that affect the human condition

Assessment of accuracy of liver fluke diagnostic tests using the gold standard of total worm counts.

In many regions of New Zealand liver fluke is endemic, infecting most grazing ruminants, including cattle, sheep, and deer. Restricting the economic losses and welfare costs associated with liver fluke relies on accurately identifying those animals with a production limiting infection. This has proven a difficult goal and although several antemortem quantitative tests are available, including faecal egg counts (FEC), serum ELISA and copro-antigen ELISA, none can be considered a gold standard test of liver fluke infection. The accepted gold standard test for fascioliasis is the total fluke count, which is both laborious and can only be completed at post-mortem. This study aimed to compare the performance of four liver fluke diagnostic tests, against the results of a gold standard total fluke count test. Two groups of cattle were selected, 29 culled mixed age beef cows (MAC) and ten 30-month-old steers. The cattle were blood sampled and faecal sampled prior to slaughter and their whole livers recovered post slaughter at the abattoir. Liveweight was also recorded at slaughter. After collection, each liver was weighed, scored for gross pathology, then serum, faeces and livers were frozen at -20 °C for later analysis. Faecal egg counts and F. hepatica copro-antigen ELISA tests were completed on the faecal samples and total fluke counts were completed on the livers. Fasciola hepatica antibody concentration in serum samples were quantified using a commercial ELISA test. Poisson regression models were built to model the association between each diagnostic test and the total fluke count, and a linear regression model was built to examine the relationship between each diagnostic test and live weight at slaughter. The median fluke count was significantly higher in MAC than steers (p = 0.01), and F. hepatica eggs were present in 100% steers and 66% MAC. There was a significant effect of copro-antigen ELISA value on total fluke count (p < 0.0001), with a coproantigen ELISA value = 20.1 predicting 10 flukes and a value = 44.8 predicting 30 flukes. There was also a significant effect of FEC on total fluke count (p = 0.002) but the R-squared value for this model was lower. There was no association between liver fibrosis score or antibody ELISA test and total fluke count (p = 0.95, p = 0.73, respectively). There was a significant effect of total fluke count (p = 0.03) on liveweight at slaughter, with liveweight falling 20.4 kg for each unit increase in loge (total fluke count). There was no effect of FEC (p = 0.11), antibody ELISA (p = 0.55) or copro-antigen ELISA value (p = 0.16) on liveweight at slaughter. Taken together, these results show that the coproantigen ELISA test is the better test for estimating the true liver fluke burden and that the number of flukes in the liver has a negative effect on cattle live weights at slaughter.fals

The use of a Bayesian latent class model to estimate the test characteristics of three liver fluke diagnostic tests under New Zealand field conditions.

The liver fluke Fasciola hepatica is a trematode parasite of farmed livestock with worldwide distribution, causing chronic production losses and possible death from hepatobiliary damage. The effective management of liver fluke infection requires diagnostic tests which can accurately identify infected animals at both the individual and herd level. However, the accuracy of liver fluke diagnostic tests performed on individual New Zealand cattle is currently unknown. The aim of this study was to use a Bayesian latent class model (LCM) to estimate the test characteristics of three liver fluke diagnostic tests, the coproantigen ELISA, the IDEXX antibody ELISA and the faecal egg count. One hundred and twenty dairy cows each from two dairy farms were blood and faecal sampled in April 2021. The samples were transported to Massey University, Palmerston North, and the three diagnostic tests completed following the respective manufacturer instructions. A Bayesian LCM model, adapted from the original Hui and Walter 2 tests 2 populations model, was built to estimate the test characteristics of the three diagnostic tests in the two dairy herds. The model was implemented in JAGS using Markov chain Monte Carlo sampling. The first 30,000 iterations were discarded as burn-in, and the next 200,000 iterations were used to construct the posterior distributions. Uninformed priors, beta (1,1), were used as the prior distributions for the prevalence estimation and informed beta priors, based on published results, were used as the prior distributions for estimating the sensitivity and specificity of each diagnostic test. Model convergence was confirmed by inspection of trace plots and examination of the results of the Gelman and Rubin test. The results found that the coproantigen ELISA test was the most accurate for diagnosing liver fluke infection in individual animals with a sensitivity = 0.98 (95 % CI 0.95-1.00) and specificity = 0.95 (95 % CI 0.81-1.00) compared to the IDEXX antibody ELISA test, sensitivity = 0.39 (95 % CI 0.32-0.47) and specificity = 0.86 (95 % CI 0.75-0.96) or the FEC, sensitivity = 0.23 (95 % CI 0.17-0.30) and specificity = 0.92 (95 % CI 0.86-0.97). Based on these results clinicians should be encouraged to use the coproantigen ELISA test to diagnose liver fluke infection in individual cattle

Extragalactic Radio Continuum Surveys and the Transformation of Radio Astronomy

Next-generation radio surveys are about to transform radio astronomy by discovering and studying tens of millions of previously unknown radio sources. These surveys will provide new insights to understand the evolution of galaxies, measuring the evolution of the cosmic star formation rate, and rivalling traditional techniques in the measurement of fundamental cosmological parameters. By observing a new volume of observational parameter space, they are also likely to discover unexpected new phenomena. This review traces the evolution of extragalactic radio continuum surveys from the earliest days of radio astronomy to the present, and identifies the challenges that must be overcome to achieve this transformational change.Comment: To be published in Nature Astronomy 18 Sept 201