Lipid-poor adenomas on unenhanced CT: does histogram analysis increase sensitivity compared with a mean attenuation threshold?

OBJECTIVE: The purpose of our study was to evaluate the efficacy of CT histogram analysis for further characterization of lipid-poor adenomas on unenhanced CT. MATERIALS AND METHODS: One hundred thirty-two adrenal nodules were identified in 104 patients with lung cancer who underwent PET/CT. Sixty-five nodules were classified as lipid-rich adenomas if they had an unenhanced CT attenuation of less than or equal to 10 H. Thirty-one masses were classified as lipid-poor adenomas if they had an unenhanced CT attenuation greater than 10 H and stability for more than 1 year. Thirty-six masses were classified as lung cancer metastases if they showed rapid growth in 1 year (n = 27) or were biopsy-proven (n = 9). Histogram analysis was performed for all lesions to provide the mean attenuation value and percentage of negative pixels. RESULTS: All lipid-rich adenomas had more than 10% negative pixels; 51.6% of lipid-poor adenomas had more than 10% negative pixels and would have been classified as indeterminate nodules on the basis of mean attenuation alone. None of the metastases had more than 10% negative pixels. Using an unenhanced CT mean attenuation threshold of less than 10 H yielded a sensitivity of 68% and specificity of 100% for the diagnosis of an adenoma. Using an unenhanced CT threshold of more than 10% negative pixels yielded a sensitivity of 84% and specificity of 100% for the diagnosis of an adenoma. CONCLUSION: CT histogram analysis is superior to mean CT attenuation analysis for the evaluation of adrenal nodules and may help decrease referrals for additional imaging or biopsy.

Mean 20-year followup of Bernese periacetabular osteotomy

The goal of the Bernese periacetabular osteotomy is to correct the deficient acetabular coverage in hips with developmental dysplasia to prevent secondary osteoarthrosis. We determined the 20-year survivorship of symptomatic patients treated with this procedure, determined the clinical and radiographic outcomes of the surviving hips, and identified factors predicting poor outcome. We retrospectively evaluated the first 63 patients (75 hips) who underwent periacetabular osteotomy at the institution where this technique was developed. The mean age of the patients at surgery was 29 years (range, 13-56 years), and preoperatively 24% presented with advanced grades of osteoarthritis. Four patients (five hips) were lost to followup and one patient (two hips) died. The remaining 58 patients (68 hips) were followed for a minimum of 19 years (mean, 20.4 years; range, 19-23 years) and 41 hips (60%) were preserved at last followup. The overall mean Merle d'Aubigné and Postel score decreased in comparison to the 10-year value and was similar to the preoperative score. We observed no major changes in any of the radiographic parameters during the 20-year postoperative period except the osteoarthritis score. We identified six factors predicting poor outcome: age at surgery, preoperative Merle d'Aubigné and Postel score, positive anterior impingement test, limp, osteoarthrosis grade, and the postoperative extrusion index. Periacetabular osteotomy is an effective technique for treating symptomatic developmental dysplasia of the hip and can maintain the natural hip at least 19 years in selected patients. LEVEL OF EVIDENCE: Level III, prognostic study.

The mean anatomical shape of the tibial plateau at the knee arthroplasty resection level: an investigation using MRI

Clinical assessments after Total Knee Arthroplasty (TKA) show persisting pain after implantation in over 20% of patients. Impingement of soft tissue around the knee, due to imprecise geometry of the tibial implant, can be one reason for persisting ailment. Two hundred and thirty seven MRI scans were evaluated using an active contour detection algorithm (snake) to obtain a high-resolution mean anatomical shape of the tibial plateau. Differences between female and male, older and younger (40) and left and right averaged shapes were determined. The shapes obtained were asymmetric throughout. Absolute differences between the subgroups fell short of inter-individual variations represented by calculated one-sigma confidence intervals. Our results indicate that a differentiation in TKA tibial plateau design by gender, age, or side is of minor relevance.

Meta-model for calculating the mean energy demand of automated storage and retrieval systems

Energy efficiency has become an important research topic in intralogistics. Especially in this field the focus is placed on automated storage and retrieval systems (AS/RS) utilizing stacker cranes as these systems are widespread and consume a significant portion of the total energy demand of intralogistical systems. Numerical simulation models were developed to calculate the energy demand rather precisely for discrete single and dual command cycles. Unfortunately these simulation models are not suitable to perform fast calculations to determine a mean energy demand value of a complete storage aisle. For this purpose analytical approaches would be more convenient but until now analytical approaches only deliver results for certain configurations. In particular, for commonly used stacker cranes equipped with an intermediate circuit connection within their drive configuration there is no analytical approach available to calculate the mean energy demand. This article should address this research gap and present a calculation approach which enables planners to quickly calculate the energy demand of these systems.

Community mean traits as additional indicators to monitor effects of land-use intensity on grassland plant diversity

Semi-natural grasslands, biodiversity hotspots in Central-Europe, suffer from the cessation of traditional land-use. Amount and intensity of these changes challenge current monitoring frameworks typically based on classic indicators such as selected target species or diversity indices. Indicators based on plant functional traits provide an interesting extension since they reflect ecological strategies at individual and ecological processes at community levels. They typically show convergent responses to gradients of land-use intensity over scales and regions, are more directly related to environmental drivers than diversity components themselves and enable detecting directional changes in whole community dynamics. However, probably due to their labor- and cost intensive assessment in the field, they have been rarely applied as indicators so far. Here we suggest overcoming these limitations by calculating indicators with plant traits derived from online accessible databases. Aiming to provide a minimal trait set to monitor effects of land-use intensification on plant diversity we investigated relationships between 12 community mean traits, 2 diversity indices and 6 predictors of land-use intensity within grassland communities of 3 different regions in Germany (part of the German ‘Biodiversity Exploratory’ research network). By standardization of traits and diversity measures, use of null models and linear mixed models we confirmed (i) strong links between functional community composition and plant diversity, (ii) that traits are closely related to land-use intensity, and (iii) that functional indicators are equally, or even more sensitive to land-use intensity than traditional diversity indices. The deduced trait set consisted of 5 traits, i.e., specific leaf area (SLA), leaf dry matter content (LDMC), seed release height, leaf distribution, and onset of flowering. These database derived traits enable the early detection of changes in community structure indicative for future diversity loss. As an addition to current monitoring measures they allow to better link environmental drivers to processes controlling community dynamics.

Mean age of carbon in fine roots from temperate forests and grasslands with different management

Fine roots are the most dynamic portion of a plant's root system and a major source of soil organic matter. By altering plant species diversity and composition, soil conditions and nutrient availability, and consequently belowground allocation and dynamics of root carbon (C) inputs, land-use and management changes may influence organic C storage in terrestrial ecosystems. In three German regions, we measured fine root radiocarbon (14C) content to estimate the mean time since C in root tissues was fixed from the atmosphere in 54 grassland and forest plots with different management and soil conditions. Although root biomass was on average greater in grasslands 5.1 ± 0.8 g (mean ± SE, n = 27) than in forests 3.1 ± 0.5 g (n = 27) (p < 0.05), the mean age of C in fine roots in forests averaged 11.3 ± 1.8 yr and was older and more variable compared to grasslands 1.7 ± 0.4 yr (p < 0.001). We further found that management affects the mean age of fine root C in temperate grasslands mediated by changes in plant species diversity and composition. Fine root mean C age is positively correlated with plant diversity (r = 0.65) and with the number of perennial species (r = 0.77). Fine root mean C age in grasslands was also affected by study region with averages of 0.7 ± 0.1 yr (n = 9) on mostly organic soils in northern Germany and of 1.8 ± 0.3 yr (n = 9) and 2.6 ± 0.3 (n = 9) in central and southern Germany (p < 0.05). This was probably due to differences in soil nutrient contents and soil moisture conditions between study regions, which affected plant species diversity and the presence of perennial species. Our results indicate more long-lived roots or internal redistribution of C in perennial species and suggest linkages between fine root C age and management in grasslands. These findings improve our ability to predict and model belowground C fluxes across broader spatial scales.

ANOVA kernels and RKHS of zero mean functions for model-based sensitivity analysis

Given a reproducing kernel Hilbert space (H,〈.,.〉)(H,〈.,.〉) of real-valued functions and a suitable measure μμ over the source space D⊂RD⊂R, we decompose HH as the sum of a subspace of centered functions for μμ and its orthogonal in HH. This decomposition leads to a special case of ANOVA kernels, for which the functional ANOVA representation of the best predictor can be elegantly derived, either in an interpolation or regularization framework. The proposed kernels appear to be particularly convenient for analyzing the effect of each (group of) variable(s) and computing sensitivity indices without recursivity.

Economic efficiency analysis of different strategies to control post-weaning multi-systemic wasting syndrome and porcine circovirus type 2 subclinical infection in 3-weekly batch system farms.

The study assessed the economic efficiency of different strategies for the control of post-weaning multi-systemic wasting syndrome (PMWS) and porcine circovirus type 2 subclinical infection (PCV2SI), which have a major economic impact on the pig farming industry worldwide. The control strategies investigated consisted on the combination of up to 5 different control measures. The control measures considered were: (1) PCV2 vaccination of piglets (vac); (2) ensuring age adjusted diet for growers (diets); (3) reduction of stocking density (stock); (4) improvement of biosecurity measures (bios); and (5) total depopulation and repopulation of the farm for the elimination of other major pathogens (DPRP). A model was developed to simulate 5 years production of a pig farm with a 3-weekly batch system and with 100 sows. A PMWS/PCV2SI disease and economic model, based on PMWS severity scores, was linked to the production model in order to assess disease losses. This PMWS severity scores depends on the combination post-weaning mortality, PMWS morbidity in younger pigs and proportion of PCV2 infected pigs observed on farms. The economic analysis investigated eleven different farm scenarios, depending on the number of risk factors present before the intervention. For each strategy, an investment appraisal assessed the extra costs and benefits of reducing a given PMWS severity score to the average score of a slightly affected farm. The net present value obtained for each strategy was then multiplied by the corresponding probability of success to obtain an expected value. A stochastic simulation was performed to account for uncertainty and variability. For moderately affected farms PCV2 vaccination alone was the most cost-efficient strategy, but for highly affected farms it was either PCV2 vaccination alone or in combination with biosecurity measures, with the marginal profitability between 'vac' and 'vac+bios' being small. Other strategies such as 'diets', 'vac+diets' and 'bios+diets' were frequently identified as the second or third best strategy. The mean expected values of the best strategy for a moderately and a highly affected farm were £14,739 and £57,648 after 5 years, respectively. This is the first study to compare economic efficiency of control strategies for PMWS and PCV2SI. The results demonstrate the economic value of PCV2 vaccination, and highlight that on highly affected farms biosecurity measures are required to achieve optimal profitability. The model developed has potential as a farm-level decision support tool for the control of this economically important syndrome.

What do we mean by Female and Male in Neurocognitive Experiments on Language?

For several years now, neuroscientific research has been striving towards fundamental answers to questions about the relevance of sex/gender to language processing in the brain. This research has been effected through the search for sex/gender differences in the neurobiology of language processing. Thus, the main aim has ever been to focus on the differentiation of the sexes/genders, failing to define what sex, what gender, what female or male is in neurolingustic research. In other words, although neuroscientific findings have provided key insights into the brain functioning of women and men, neuropsychology has rarely questioned the complexity of the sex/gender variable beyond biology. What does “female” or “male” mean in human neurocognition; how are operationalisations implemented along the axes of “femaleness” or “maleness”; or what biological evidence is used to register the variables sex and/or gender? In the neurosciences as well as in neurocognitive research, questions such as these have so far not been studied in detail, even if they are highly significant for the scientific process. Instead, the variable of sex/gender has always been thought as solely dichotomous (as either female or male), oppositional and exclusionary of each other. Here, this theoretical contribution sets in. Based on findings in neuroscience and concepts in gender theory, this poster is dedicated to the reflection about what sex/gender is in the neuroscience of language processing. Following this aim, two levels of interest will be addressed. First: How do we define sex/gender at the level of participants? And second: How do we define sex/gender at the level of the experimental task? For the first, a multifactorial registration (work in progress) of the variable sex/gender will be presented, i.e. a tool that records sex/gender in terms of biology and social issues as well as on a spectrum between femaleness and maleness. For the second, the compulsory dichotomy of a gendered task when neurolinguistically approaching our cognitions of sex/gender will be explored.