Is body weight the most appropriate criterion to select patients eligible for low-dose pulmonary CT angiography? Analysis of objective and subjective image quality at 80 kVp in 100 patients

The objective of this retrospective study was to assess image quality with pulmonary CT angiography (CTA) using 80 kVp and to find anthropomorphic parameters other than body weight (BW) to serve as selection criteria for low-dose CTA. Attenuation in the pulmonary arteries, anteroposterior and lateral diameters, cross-sectional area and soft-tissue thickness of the chest were measured in 100 consecutive patients weighing less than 100 kg with 80 kVp pulmonary CTA. Body surface area (BSA) and contrast-to-noise ratios (CNR) were calculated. Three radiologists analyzed arterial enhancement, noise, and image quality. Image parameters between patients grouped by BW (group 1: 0-50 kg; groups 2-6: 51-100 kg, decadally increasing) were compared. CNR was higher in patients weighing less than 60 kg than in the BW groups 71-99 kg (P between 0.025 and <0.001). Subjective ranking of enhancement (P = 0.165-0.605), noise (P = 0.063), and image quality (P = 0.079) did not differ significantly across all patient groups. CNR correlated moderately strongly with weight (R = -0.585), BSA (R = -0.582), cross-sectional area (R = -0.544), and anteroposterior diameter of the chest (R = -0.457; P < 0.001 all parameters). We conclude that 80 kVp pulmonary CTA permits diagnostic image quality in patients weighing up to 100 kg. Body weight is a suitable criterion to select patients for low-dose pulmonary CTA.

Estimation of male-to-female ratios of mutation rate in primates and rodents

Haldane (1935) developed a method for estimating the male-to-female ratio of mutation rate ($\alpha$) by using sex-linked recessive genetic disease, but in six different studies using hemophilia A data the estimates of $\alpha$ varied from 1.2 to 29.3. Direct genomic sequencing is a better approach, but it is laborious and not readily applicable to non-human organisms. To study the sex ratios of mutation rate in various mammals, I used an indirect method proposed by Miyata et al. (1987). This method takes advantage of the fact that different chromosomes segregate differently between males and females, and uses the ratios of mutation rate in sequences on different chromosomes to estimate the male-to-female ratio of mutation rate. I sequenced the last intron of ZFX and ZFY genes in 6 species of primates and 2 species of rodents; I also sequenced the partial genomic sequence of the Ube1x and Ube1y genes of mice and rats. The purposes of my study in addition to estimation of $\alpha$'s in different mammalian species, are to test the hypothesis that most mutations are replication dependent and to examine the generation-time effect on $\alpha$. The $\alpha$ value estimated from the ZFX and ZFY introns of the six primate specise is ${\sim}$6. This estimate is the same as an earlier estimate using only 4 species of primates, but the 95% confidence interval has been reduced from (2, 84) to (2, 33). The estimate of $\alpha$ in the rodents obtained from Zfx and Zfy introns is ${\sim}$1.9, and that deriving from Ube1x and Ube1y introns is ${\sim}$2. Both estimates have a 95% confidence interval from 1 to 3. These two estimates are very close to each other, but are only one-third of that of the primates, suggesting a generation-time effect on $\alpha$. An $\alpha$ of 6 in primates and 2 in rodents are close to the estimates of the male-to-female ratio of the number of germ-cell divisions per generation in humans and mice, which are 6 and 2, respectively, assuming the generation time in humans is 20 years and that in mice is 5 months. These findings suggest that errors during germ-cell DNA replication are the primary source of mutation and that $\alpha$ decreases with decreasing length of generation time. ^

Response to LIVint-15-00100

Although AST-to-platelet ratio index (APRI) and FIB-4 have been compared with liver biopsy in patients with hepatitis C virus (HCV), hepatitis B virus (HBV), HIV/HCV co-infection, and HIV/HBV co-infection, Johannessen and Lemoine stress that they have not been validated in HIV mono-infected populations in SSA. However, this is unlikely to occur because liver biopsy does not play a role in HIV management and the procedure carries its own risks for complication. Clinicians using APRI and FIB-4 in this setting should be aware of this limitation and should interpret test results in the context of each patient's clinical scenario. This article is protected by copyright. All rights reserved.

Positron emission tomography (PET) imaging of prostate cancer with a gastrin releasing peptide receptor antagonist - from mice to men

UNLABELLED Ex vivo studies have shown that the gastrin releasing peptide receptor (GRPr) is overexpressed on almost all primary prostate cancers, making it a promising target for prostate cancer imaging and targeted radiotherapy. METHODS Biodistribution, dosimetry and tumor uptake of the GRPr antagonist ⁶⁴Cu-CB-TE2A-AR06 [(⁶⁴Cu-4,11-bis(carboxymethyl)-1,4,8,11-tetraazabicyclo(6.6.2)hexadecane)-PEG₄-D-Phe-Gln-Trp-Ala-Val-Gly-His-Sta-LeuNH₂] were studied by PET/CT in four patients with newly diagnosed prostate cancer (T1c-T2b, Gleason 6-7). RESULTS No adverse events were observed after injection of ⁶⁴Cu-CB-TE2A-AR06. Three of four tumors were visualized with high contrast [tumor-to-prostate ratio > 4 at 4 hours (h) post injection (p.i.)], one small tumor (T1c, < 5% tumor on biopsy specimens) showed moderate contrast (tumor-to-prostate ratio at 4 h: 1.9). Radioactivity was cleared by the kidneys and only the pancreas demonstrated significant accumulation of radioactivity, which rapidly decreased over time. CONCLUSION ⁶⁴Cu-CB-TE2A-AR06 shows very favorable characteristics for imaging prostate cancer. Future studies evaluating ⁶⁴Cu-CB-TE2A-AR06 PET/CT for prostate cancer detection, staging, active surveillance, and radiation treatment planning are necessary.

SALSA: a tool to estimate the stray light contamination for low-Earth orbit observatories

Stray light contamination reduces considerably the precision of photometric of faint stars for low altitude spaceborne observatories. When measuring faint objects, the necessity of coping with stray light contamination arises in order to avoid systematic impacts on low signal-to-noise images. Stray light contamination can be represented by a flat offset in CCD data. Mitigation techniques begin by a comprehensive study during the design phase, followed by the use of target pointing optimisation and post-processing methods. We present a code that aims at simulating the stray-light contamination in low-Earth orbit coming from reflexion of solar light by the Earth. StrAy Light SimulAtor (SALSA) is a tool intended to be used at an early stage as a tool to evaluate the effective visible region in the sky and, therefore to optimise the observation sequence. SALSA can compute Earth stray light contamination for significant periods of time allowing missionwide parameters to be optimised (e.g. impose constraints on the point source transmission function (PST) and/or on the altitude of the satellite). It can also be used to study the behaviour of the stray light at different seasons or latitudes. Given the position of the satellite with respect to the Earth and the Sun, SALSA computes the stray light at the entrance of the telescope following a geometrical technique. After characterising the illuminated region of the Earth, the portion of illuminated Earth that affects the satellite is calculated. Then, the flux of reflected solar photons is evaluated at the entrance of the telescope. Using the PST of the instrument, the final stray light contamination at the detector is calculated. The analysis tools include time series analysis of the contamination, evaluation of the sky coverage and an objects visibility predictor. Effects of the South Atlantic Anomaly and of any shutdown periods of the instrument can be added. Several designs or mission concepts can be easily tested and compared. The code is not thought as a stand-alone mission designer. Its mandatory inputs are a time series describing the trajectory of the satellite and the characteristics of the instrument. This software suite has been applied to the design and analysis of CHEOPS (CHaracterizing ExOPlanet Satellite). This mission requires very high precision photometry to detect very shallow transits of exoplanets. Different altitudes and characteristics of the detector have been studied in order to find the best parameters, that reduce the effect of contamination. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Graphics Processor Unit Based Parallelization of Optimized Baseline Wander Filtering Algorithms for Long-term Electrocardiography

Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here we present a graphics processor unit (GPU) based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to auto-regressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and 4 times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a 7-day high-resolution ECG is computed within less than 3 seconds. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced.

Optical Light Curve Observations to Determine Attitude States of Space Debris

The currently proposed space debris remediation measures include the active removal of large objects and “just in time” collision avoidance by deviating the objects using, e.g., ground-based lasers. Both techniques require precise knowledge of the attitude state and state changes of the target objects. In the former case, to devise methods to grapple the target by a tug spacecraft, in the latter, to precisely propagate the orbits of potential collision partners as disturbing forces like air drag and solar radiation pressure depend on the attitude of the objects. Non-resolving optical observations of the magnitude variations, so-called light curves, are a promising technique to determine rotation or tumbling rates and the orientations of the actual rotation axis of objects, as well as their temporal changes. The 1-meter telescope ZIMLAT of the Astronomical Institute of the University of Bern has been used to collect light curves of MEO and GEO objects for a considerable period of time. Recently, light curves of Low Earth Orbit (LEO) targets were acquired as well. We present different observation methods, including active tracking using a CCD subframe readout technique, and the use of a high-speed scientific CMOS camera. Technical challenges when tracking objects with poor orbit redictions, as well as different data reduction methods are addressed. Results from a survey of abandoned rocket upper stages in LEO, examples of abandoned payloads and observations of high area-to-mass ratio debris will be resented. Eventually, first results of the analysis of these light curves are provided.

Unearthing the roots of degradation of Quercus pyrenaica coppices: A root-to-shoot imbalance caused by historical management?

Slow growth, branch dieback and scarce acorn yield are visible symptoms of decay in abandoned Quercus pyrenaica coppices. A hypothetical root-to-shoot (R:S) imbalance provoked by historical coppicing is investigated as the underlying driver of stand degradation. After stem genotyping, 12 stems belonging to two clones covering 81 and 16 m2 were harvested and excavated to measure above- and below-ground biomass and nonstructural carbohydrate (NSC) pools. To study root system functionality, root connections and root longevity were assessed by radiocarbon analysis. Seasonality of NSC was monitored on five additional clones. NSC pools, R:S biomass ratio and fine roots-to-foliage ratio were higher in the large clone, whose centennial root system, estimated to be 550 years old, maintained large amounts of sapwood (51.8%) for NSC storage. 248 root connections were observed within the large clone, whereas the small clone showed comparatively simpler root structure (26 connections). NSC concentrations were higher in spring (before bud burst) and autumn (before leaf fall), and lower in summer (after complete leaf expansion); they were always higher in roots than in stems or twigs. The persistence of massive and highly inter-connected root systems after coppicing may lead to increasing R:S biomass ratios and root NSC pools over time. We highlight the need of surveying belowground organs to understand aboveground dynamics of Q. pyrenaica, and suggest that enhanced belowground NSC storage and consumption reflect a trade-off between clonal vegetative resilience and aboveground performance.

An empirical evaluation of the Random Forests classifier models for variable selection in a large-scale lung cancer case-control study

Random Forests™ is reported to be one of the most accurate classification algorithms in complex data analysis. It shows excellent performance even when most predictors are noisy and the number of variables is much larger than the number of observations. In this thesis Random Forests was applied to a large-scale lung cancer case-control study. A novel way of automatically selecting prognostic factors was proposed. Also, synthetic positive control was used to validate Random Forests method. Throughout this study we showed that Random Forests can deal with large number of weak input variables without overfitting. It can account for non-additive interactions between these input variables. Random Forests can also be used for variable selection without being adversely affected by collinearities. ^ Random Forests can deal with the large-scale data sets without rigorous data preprocessing. It has robust variable importance ranking measure. Proposed is a novel variable selection method in context of Random Forests that uses the data noise level as the cut-off value to determine the subset of the important predictors. This new approach enhanced the ability of the Random Forests algorithm to automatically identify important predictors for complex data. The cut-off value can also be adjusted based on the results of the synthetic positive control experiments. ^ When the data set had high variables to observations ratio, Random Forests complemented the established logistic regression. This study suggested that Random Forests is recommended for such high dimensionality data. One can use Random Forests to select the important variables and then use logistic regression or Random Forests itself to estimate the effect size of the predictors and to classify new observations. ^ We also found that the mean decrease of accuracy is a more reliable variable ranking measurement than mean decrease of Gini. ^

Intensive care noise and mean arterial blood pressure in ELBW neonates

Objective. Loud noises in neonatal intensive care units (NICUs) may impede growth and development for extremely low birthweight (ELBW, < 1000 grams) newborns. The objective of this study was to measure the association between NICU sound levels and ELBW neonates' arterial blood pressure to determine whether these newborns experience noise-induced stress. ^ Methods. Noise and arterial blood pressure recordings were collected for 9 ELBW neonates during the first week of life. Sound levels were measured inside the incubator, and each subject's arterial blood pressures were simultaneously recorded for 15 minutes (at 1 sec intervals). Time series cross-correlation functions were calculated for NICU noise and mean arterial blood pressure (MABP) recordings for each subject. The grand mean noise-MABP cross-correlation was calculated for all subjects and for lower and higher birthweight groups for comparison. ^ Results. The grand mean noise-MABP cross-correlation for all subjects was mostly negative (through 300 sec lag time) and nearly reached significance at the 95% level at 111 sec lag (mean r = -0.062). Lower birthweight newborns (454-709 g) experienced significant decreases in blood pressure with increasing NICU noise after 145 sec lag (peak r = -0.074). Higher birthweight newborns had an immediate negative correlation with NICU sound levels (at 3 sec lag, r = -0.071), but arterial blood pressures increased to a positive correlation with noise levels at 197 sec lag (r = 0.075). ^ Conclusions. ELBW newborns' arterial blood pressure was influenced by NICU noise levels during the first week of life. Lower birthweight newborns may have experienced an orienting reflex to NICU sounds. Higher birthweight newborns experienced an immediate orienting reflex to increasing sound levels, but arterial blood pressure increased approximately 3 minutes after increases in noise levels. Increases in arterial blood pressure following increased NICU sound levels may result from a stress response to noise. ^

Nosocomial infections and their relationship to non-traditional risk factors in a medical intensive care unit

Background. Nosocomial infections are a source of concern for many hospitals in the United States and worldwide. These infections are associated with increased morbidity, mortality and hospital costs. Nosocomial infections occur in ICUs at a rate which is five times greater than those in general wards. Understanding the reasons for the higher rates can ultimately help reduce these infections. The literature has been weak in documenting a direct relationship between nosocomial infections and non-traditional risk factors, such as unit staffing or patient acuity.^ Objective. To examine the relationship, if any, between nosocomial infections and non-traditional risk factors. The potential non-traditional risk factors we studied were the patient acuity (which comprised of the mortality and illness rating of the patient), patient days for patients hospitalized in the ICU, and the patient to nurse ratio.^ Method. We conducted a secondary data analysis on patients hospitalized in the Medical Intensive Care Unit (MICU) of the Memorial Hermann- Texas Medical Center in Houston during the months of March 2008- May 2009. The average monthly values for the patient acuity (mortality and illness Diagnostic Related Group (DRG) scores), patient days for patients hospitalized in the ICU and average patient to nurse ratio were calculated during this time period. Active surveillance of Bloodstream Infections (BSIs), Urinary Tract Infections (UTIs) and Ventilator Associated Pneumonias (VAPs) was performed by Infection Control practitioners, who visited the MICU and performed a personal infection record for each patient. Spearman's rank correlation was performed to determine the relationship between these nosocomial infections and the non-traditional risk factors.^ Results. We found weak negative correlations between BSIs and two measures (illness and mortality DRG). We also found a weak negative correlation between UTI and unit staffing (patient to nurse ratio). The strongest positive correlation was found between illness DRG and mortality DRG, validating our methodology.^ Conclusion. From this analysis, we were able to infer that non-traditional risk factors do not appear to play a significant role in transmission of infection in the units we evaluated.^

G-force measurements at Mount Nyiragongo

To evaluate the mechanical stress on the volcanic edifice that results from lava lake level variations, we deployed a self-recording, differential capacitance (MEMS Inertial Sensor STMicroelectronics LIS3LV02DQ), 3-axis X6-1A accelerometer (Gulf Coast Data Concepts, LLC) at a distance of ~100m from the center of the Nyiragongo lava lake on freshly erupted lava flows. The device range was used in high (12-bit) resolution mode, which corresponds to a sensitivity of about 1 mg. The device was set to high-sensitivity mode with four additional bits to improve resolution, yet with a much lower signal-noise ratio. Once in position, the accelerometer continuously recorded data for three-day periods in June 2010. The system was oriented so that the X- and Y-axes form a plain parallel to the lava lake. During data collection, we did not attempt to calibrate the precision of the angle because relative G-force measurements were required instead of absolute G-force measurements. To distinguish the tiny accelerations caused by temperature differentials of the atmosphere, from the forces caused by magma movements, the temperature of the X6-1A device was continuously recorded. Temperature variations were corrected for by applying a de-correlation method to the recorded signal. Data was collected at 20 Hz, regrouped into batches that cover 1 hour per observation and associated with one averaged temperature measurement. This method was reproducible because diurnal temperature variations were the main cause for heating and cooling.

Molecular composition in surface and subsurface sediments of the Helgoland mud area, North Sea

The role of microorganisms in the cycling of sedimentary organic carbon is a crucial one. To better understand relationships between molecular composition of a potentially bioavailable fraction of organic matter and microbial populations, bacterial and archaeal communities were characterized using pyrosequencing-based 16S rRNA gene analysis in surface (top 30 cm) and subsurface/deeper sediments (30-530 cm) of the Helgoland mud area, North Sea. Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) was used to characterize a potentially bioavailable organic matter fraction (hot-water extractable organic matter, WE-OM). Algal polymer-associated microbial populations such as members of the Gammaproteobacteria, Bacteroidetes, and Verrucomicrobia were dominant in surface sediments while members of the Chloroflexi (Dehalococcoidales and candidate order GIF9) and Miscellaneous Crenarchaeota Groups (MCG), both of which are linked to degradation of more recalcitrant, aromatic compounds and detrital proteins, were dominant in subsurface sediments. Microbial populations dominant in subsurface sediments (Chloroflexi, members of MCG, and Thermoplasmata) showed strong correlations to total organic carbon (TOC) content. Changes of WE-OM with sediment depth reveal molecular transformations from oxygen-rich [high oxygen to carbon (O/C), low hydrogen to carbon (H/C) ratios] aromatic compounds and highly unsaturated compounds toward compounds with lower O/C and higher H/C ratios. The observed molecular changes were most pronounced in organic compounds containing only CHO atoms. Our data thus, highlights classes of sedimentary organic compounds that may serve as microbial energy sources in methanic marine subsurface environments.

Phytoplankton pigments and biomass in the northeastern Sea of Okhotsk from March 23 to April 14, 1998

Studies were carried out in the northeastern Sea of Okhotsk, in the zone of interaction of the West Kamchatka and Compensating Currents at the beginning of spring seasonal succession from March 23 to April 14,1998. Samples for analysis of pigmentary and species compositions of phytoplankton were taken from the sea surface layer, depth 0.5 m. To reduce influence of micropatchiness on phytoplankon distribution at each station subsamples 0.7-1 l were collected every 50-100 m. These subsamples were used to make integral samples 4.5-8.0 l. Phytoplankton biomass and concentration of chlorophyll a varied from 18.7 to 490.9 mg/m**3 and from 0.129 to 2.422 mg/m**3, respectively. Total concentration of phytoplankton pigments varied from 0.622 to 6.679 mg/m**3. In samples studied 51 species of microalgae from 5 orders were found. In terms of the number of species, Bacillariophyta (31 species) and Dinophyta (15 species) prevailed. Diatomaceous algae make up more than 80% of the total phytoplankton biomass in waters of the Compensating Current, from 50 to 80% in intermediate waters, and less than 50% in waters of the West Kamchatka Current. Phytoplankton populations consisting primarily of diatoms were characterized by very low chlorophyll a to biomass ratio (0.1 %). It is three times lower than the ratio observed in phytoplankton populations that were close by species composition and size composition in this area in the late April-early May 1996.

Global macrozoobenthos production and energy budget data base V150731, with link to database

I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e., an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.