Inter- and intra-observer agreement of BI-RADS-based subjective visual estimation of amount of fibroglandular breast tissue with magnetic resonance imaging: comparison to automated quantitative assessment.

PURPOSE: To evaluate the inter-/intra-observer agreement of BI-RADS-based subjective visual estimation of the amount of fibroglandular tissue (FGT) with magnetic resonance imaging (MRI), and to investigate whether FGT assessment benefits from an automated, observer-independent, quantitative MRI measurement by comparing both approaches. MATERIALS AND METHODS: Eighty women with no imaging abnormalities (BI-RADS 1 and 2) were included in this institutional review board (IRB)-approved prospective study. All women underwent un-enhanced breast MRI. Four radiologists independently assessed FGT with MRI by subjective visual estimation according to BI-RADS. Automated observer-independent quantitative measurement of FGT with MRI was performed using a previously described measurement system. Inter-/intra-observer agreements of qualitative and quantitative FGT measurements were assessed using Cohen's kappa (k). RESULTS: Inexperienced readers achieved moderate inter-/intra-observer agreement and experienced readers a substantial inter- and perfect intra-observer agreement for subjective visual estimation of FGT. Practice and experience reduced observer-dependency. Automated observer-independent quantitative measurement of FGT was successfully performed and revealed only fair to moderate agreement (k = 0.209-0.497) with subjective visual estimations of FGT. CONCLUSION: Subjective visual estimation of FGT with MRI shows moderate intra-/inter-observer agreement, which can be improved by practice and experience. Automated observer-independent quantitative measurements of FGT are necessary to allow a standardized risk evaluation. KEY POINTS: • Subjective FGT estimation with MRI shows moderate intra-/inter-observer agreement in inexperienced readers. • Inter-observer agreement can be improved by practice and experience. • Automated observer-independent quantitative measurements can provide reliable and standardized assessment of FGT with MRI

Scotland's forgotten carbon : a national assessment of mid-latitude fjord sedimentary carbon stocks

This work was supported by the Natural Environment Research Council (grant number: NE/L501852/1) with additional support from the NERC Radiocarbon Facility (Allocation 1934.1015). Further seismic profiles and the CALYPSO long core were acquired within the frame of the French ECLIPSE programme with additional financial support from NERC, SAMS and the University of St Andrews.Fjords are recognised as hotspots for the burial and long-term storage of carbon (C) and potentially provide a significant climate regulation service over multiple timescales. Understanding the magnitude of marine sedimentary C stores and the processes which govern their development is fundamental to understanding the role of the coastal ocean in the global C cycle. In this study, we use the mid-latitude fjords of Scotland as a natural laboratory to further develop methods to quantify these marine sedimentary C stores on both the individual fjord and national scale. Targeted geophysical and geochemical analysis has allowed the quantification of sedimentary C stocks for a number of mid-latitude fjords and, coupled with upscaling techniques based on fjord classification, has generated the first full national sedimentary C inventory for a fjordic system. The sediments within these mid-latitude fjords hold 640.7 ± 46 Mt of C split between 295.6±52 and 345.1 ± 39 Mt of organic and inorganic C, respectively. When compared, these marine mid-latitude sedimentary C stores are of similar magnitude to their terrestrial equivalents, with the exception of the Scottish peatlands, which hold significantly more C. However, when area normalised comparisons are made, these mid-latitude fjords are significantly more effective as C stores than their terrestrial counterparts, including Scottish peatlands. The C held within Scotland’s coastal marine sediments has been largely overlooked as a significant component of the nation’s natural capital; such coastal C stores are likely to be key to understanding and constraining improved global C budgets.Publisher PDFPeer reviewe

Crossing borders to bind proteins—a new concept in protein recognition based on the conjugation of small organic molecules or short peptides to polypeptides from a designed set

A new concept for protein recognition and binding is highlighted. The conjugation of small organic molecules or short peptides to polypeptides from a designed set provides binder molecules that bind proteins with high affinities, and with selectivities that are equal to those of antibodies. The small organic molecules or peptides need to bind the protein targets but only with modest affinities and selectivities, because conjugation to the polypeptides results in molecules with dramatically improved binder performance. The polypeptides are selected from a set of only sixteen sequences designed to bind, in principle, any protein. The small number of polypeptides used to prepare high-affinity binders contrasts sharply with the huge libraries used in binder technologies based on selection or immunization. Also, unlike antibodies and engineered proteins, the polypeptides have unordered three-dimensional structures and adapt to the proteins to which they bind. Binder molecules for the C-reactive protein, human carbonic anhydrase II, acetylcholine esterase, thymidine kinase 1, phosphorylated proteins, the D-dimer, and a number of antibodies are used as examples to demonstrate that affinities are achieved that are higher than those of the small molecules or peptides by as much as four orders of magnitude. Evaluation by pull-down experiments and ELISA-based tests in human serum show selectivities to be equal to those of antibodies. Small organic molecules and peptides are readily available from pools of endogenous ligands, enzyme substrates, inhibitors or products, from screened small molecule libraries, from phage display, and from mRNA display. The technology is an alternative to established binder concepts for applications in drug development, diagnostics, medical imaging, and protein separation

Computer-aided detection in breast MRI: a systematic review and meta-analysis

To evaluate the additional value of computer-aided detection (CAD) in breast MRI by assessing radiologists' accuracy in discriminating benign from malignant breast lesions. A literature search was performed with inclusion of relevant studies using a commercially available CAD system with automatic colour mapping. Two independent researchers assessed the quality of the studies. The accuracy of the radiologists' performance with and without CAD was presented as pooled sensitivity and specificity. Of 587 articles, 10 met the inclusion criteria, all of good methodological quality. Experienced radiologists reached comparable pooled sensitivity and specificity before and after using CAD (sensitivity: without CAD: 89%; 95% CI: 78-94%, with CAD: 89%; 95%CI: 81-94%) (specificity: without CAD: 86%; 95% CI: 79-91%, with CAD: 82%; 95% CI: 76-87%). For residents the pooled sensitivity increased from 72% (95% CI: 62-81%) without CAD to 89% (95% CI: 80-94%) with CAD, however, not significantly. Concerning specificity, the results were similar (without CAD: 79%; 95% CI: 69-86%, with CAD: 78%; 95% CI: 69-84%). CAD in breast MRI has little influence on the sensitivity and specificity of experienced radiologists and therefore their interpretation remains essential. However, residents or inexperienced radiologists seem to benefit from CAD concerning breast MRI evaluation

Clinical and genetic characterisation of dystrophin-deficient muscular dystrophy in a family of Miniature Poodle dogs

Four full-sibling intact male Miniature Poodles were evaluated at 4–19 months of age. One was clinically normal and three were affected. All affected dogs were reluctant to exercise and had generalised muscle atrophy, a stiff gait and a markedly elevated serum creatine kinase activity. Two affected dogs also showed poor development, learning difficulties and episodes of abnormal behaviour. In these two dogs, investigations into forebrain structural and metabolic diseases were unremarkable; electromyography demonstrated fibrillation potentials and complex repetitive discharges in the infraspinatus, supraspinatus and epaxial muscles. Histopathological, immunohistochemical and immunoblotting analyses of muscle biopsies were consistent with dystrophin-deficient muscular dystrophy. DNA samples were obtained from all four full-sibling male Poodles, a healthy female littermate and the dam, which was clinically normal. Whole genome sequencing of one affected dog revealed a >5 Mb deletion on the X chromosome, encompassing the entire DMD gene. The exact deletion breakpoints could not be experimentally ascertained, but we confirmed that this region was deleted in all affected males, but not in the unaffected dogs. Quantitative polymerase chain reaction confirmed all three affected males were hemizygous for the mutant X chromosome, while the wildtype chromosome was observed in the unaffected male littermate. The female littermate and the dam were both heterozygous for the mutant chromosome. Forty-four Miniature Poodles from the general population were screened for the mutation and were homozygous for the wildtype chromosome. The finding represents a naturally-occurring mutation causing dystrophin-deficient muscular dystrophy in the dog

allodb: An R package for biomass estimation at globally distributed extratropical forest plots

Allometric equations for calculation of tree above-ground biomass (AGB) form the basis for estimates of forest carbon storage and exchange with the atmosphere. While standard models exist to calculate forest biomass across the tropics, we lack a standardized tool for computing AGB across boreal and temperate regions that comprise the global extratropics. Here we present an integrated R package, allodb, containing systematically selected published allometric equations and proposed functions to compute AGB. The data component of the package is based on 701 woody species identified at 24 large Forest Global Earth Observatory (ForestGEO) forest dynamics plots representing a wide diversity of extratropical forests. A total of 570 parsed allometric equations to estimate individual tree biomass were retrieved, checked and combined using a weighting function designed to ensure optimal equation selection over the full tree size range with smooth transitions across equations. The equation dataset can be customized with built-in functions that subset the original dataset and add new equations. Although equations were curated based on a limited set of forest communities and number of species, this resource is appropriate for large portions of the global extratropics and can easily be expanded to cover novel forest types

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Novel Pandemic Influenza A(H1N1) Viruses Are Potently Inhibited by DAS181, a Sialidase Fusion Protein

Background: The recent emergence of a novel pandemic influenza A(H1N1) strain in humans exemplifies the rapid and unpredictable nature of influenza virus evolution and the need for effective therapeutics and vaccines to control such outbreaks. However, resistance to antivirals can be a formidable problem as evidenced by the currently widespread oseltamivir- and adamantane-resistant seasonal influenza A viruses (IFV). Additional antiviral approaches with novel mechanisms of action are needed to combat novel and resistant influenza strains. DAS181 (Fludase)™) is a sialidase fusion protein in early clinical development with in vitro and in vivo preclinical activity against a variety of seasonal influenza strains and highly pathogenic avian influenza strains (A/H5N1). Here, we use in vitro, ex vivo, and in vivo models to evaluate the activity of DAS181 against several pandemic influenza A(H1N1) viruses. Methods and Findings: The activity of DAS181 against several pandemic influenza A(H1N1) virus isolates was examined in MDCK cells, differentiated primary human respiratory tract culture, ex-vivo human bronchi tissue and mice. DAS181 efficiently inhibited viral replication in each of these models and against all tested pandemic influenza A(H1N1) strains. DAS181 treatment also protected mice from pandemic influenza A(H1N1)-induced pathogenesis. Furthermore, DAS181 antiviral activity against pandemic influenza A(H1N1) strains was comparable to that observed against seasonal influenza virus including the H274Y oseltamivir-resistant influenza virus. Conclusions: The sialidase fusion protein DAS181 exhibits potent inhibitory activity against pandemic influenza A(H1N1) viruses. As inhibition was also observed with oseltamivir-resistant IFV (H274Y), DAS181 may be active against the antigenically novel pandemic influenza A(H1N1) virus should it acquire the H274Y mutation. Based on these and previous results demonstrating DAS181 broad-spectrum anti-IFV activity, DAS181 represents a potential therapeutic agent for prevention and treatment of infections by both emerging and seasonal strains of IFV.published_or_final_versio