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Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry who underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 who experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases--men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set. Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67-0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression. A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer.

Carbon materials, whether at macro, micro or at nanoscale, play an important role in the battery industry, as they can be used as electrodes, electrode enhancers, bipolar separators, or current collectors. When conducting a Life Cycle Assessment (LCA) of novel batteries manufacturing processes, we also need to consider the fate of potentially emitted carbon based nanomaterials. However, the knowledge generated in the last decade regarding the behavior of such materials in the environment and its toxicological effects has yet to be included in the Life Cycle Impact Assessment (LCIA) methodologies. Conventional databases of chemical products (e.g. ECHA, ECOTOX) offer little information regarding engineered nanomaterials (ENM). It is thus necessary to go one step further and compile physicochemical and toxicological data directly from scientific literature. Such studies do not only differ in their results, but also in their methodologies, and several calls have been made towards a more consistent approach that would allow us model the fate of ENM in the environment as well as their potentially harmful effects. Trying to overcome these limitations we have developed a tool based on Microsoft Excel® combining several methods for the estimation of physicochemical properties of carbon nanotubes (CNT). The information generated with this tool is combined with degradation rates and toxicological data consistent with the methods followed by the USEtox methodology. Thus, it is possible to calculate the characterization factors of CNTs and integrate them as a first proxy in future LCA of products including these ENM.

As revenue management research progresses, simplifying assumptions are removed from the underlying mathematical models. In consequence, these models grow, leading to an increase in complexity that may affect both the performance of automated systems and revenue management analysts. In this article, we demonstrate how both hierarchical and dynamic complexity may increase as revenue management models become more sophisticated. For this purpose, we introduce an example of dynamic complexity based on forecast parameterization based on a simulation study. On the basis of a data analysis created in cooperation with Deutsche Lufthansa, we demonstrate the dependence of state-of-the-art revenue management systems on analyst input. We argue that increased complexity endangers the performance of both analysts and automated systems if it is not deliberately managed. Finally, we discuss five possible strategies for responding to increasing complexity: Ignorance, full automation, visualization, result simulation and input transformation. We describe the possible implementation of each strategy and list the opportunities and challenges that each of these response entails for revenue management.

We present a first-principles explanation of the recombination requirement for benign termination of relativistic electron (RE) beams in tokamaks. Kinetic modeling including neutrals shows that the injection of neutrals over a finite quantity window, together with recombination, increases bulk resistivity. Nonlinear MHD simulations using the JOREK code demonstrate that this preferentially amplifies edge tearing modes, producing a more stochastic edge magnetic field during RE deconfinement, resulting in a larger RE wetted area. We identify resistivity, not the free electron density, to govern access to benign termination. This provides the first broadly applicable and experimentally consistent picture of the MHD mechanisms behind the benign scenario, critical to its extrapolation to next-step devices.

In this paper, an overview of the impurity transport for three H-mode plasmas in the upcoming SPARC tokamak has been provided. The simulations have been performed within the ASTRA+STRAHL framework, using FACIT and TGLF-SAT2 to predict, respectively, neoclassical and turbulent core transport, while a neural network trained on EPED simulations has been employed to calculate the pedestal height and width self-consistently. A benchmark with previous simulations at constant impurity fraction has been provided for three H-modes, spanning different plasma current and magnetic field values. For a scenario, additional simulations have been performed to account for uncertainties in the modeling assumptions. The predictions are nearly insensitive to changes in the top of pedestal W concentrations. Varying the Ar pedestal concentration has shown a small effect on the impurity peaking and nearly constant fusion gain values, due to multiple effects on pedestal pressure, main ion dilution and density peaking. The inclusion of rotation in ASTRA simulations has shown minimal impact on confinement and impurity transport predictions. An exploratory study has been provided with a first set of simulations treating D and T separately, experiencing a maximum fusion power at 55-45% DT fuel composition, and an asymmetric distribution with respect to the D concentration. All the results, including sensitivity scans of toroidal velocity and ion temperature and density gradients, highlighted that turbulent impurity transport prevails on the neoclassical component, aligning with previous ITER predictions, and suggesting that next generation devices like SPARC, operating at low collisionality, will experience low W accumulation.

Aim Climate change is expected to cause mountain species to shift their ranges to higher elevations. Due to the decreasing amounts of habitats with increasing elevation, such shifts are likely to increase their extinction risk. Heterogeneous mountain topography, however, may reduce this risk by providing microclimatic conditions that can buffer macroclimatic warming or provide nearby refugia. As aspect strongly influences the local microclimate, we here assess whether shifts from warm south‐exposed aspects to cool north‐exposed aspects in response to climate change can compensate for an upward shift into cooler elevations. Location Switzerland, Swiss Alps. Methods We built ensemble distribution models using high‐resolution climate data for two mountain‐dwelling viviparous ectotherms, the Alpine salamander and the Common lizard, and projected them into various future scenarios to gain insights into distributional changes. We further compared elevation and aspect (northness) of current and predicted future locations to analyse preferences and future shifts. Results Future ranges were consistently decreasing for the lizard, but for the salamander they were highly variable, depending on the climate scenario and threshold rule. Aspect preferences were elevation‐dependent: warmer, south‐exposed microclimates were clearly preferred at higher compared to lower elevations. In terms of presence and future locations, we observed both elevational upward shifts and northward shifts in aspect. Under future conditions, the shift to cooler north‐exposed aspects was particularly pronounced at already warmer lower elevations. Main conclusions For our study species, shifts in aspect and elevation are complementary strategies to mitigate climatic warming in the complex mountain topography. This complements the long‐standing view of elevational upward shift being their only option to move into areas with suitable future climate. High‐resolution climate data are critical in heterogeneous environments to identify microrefugia and thereby improving future impact assessments of climate change.

Here, we provide a protocol to generate synthetic nanobodies, known as sybodies, against any purified protein or protein complex within a 3-week period. Unlike methods that require animals for antibody generation, sybody selections are carried out entirely in vitro under controlled experimental conditions. This is particularly relevant for the generation of conformation-specific binders against labile membrane proteins or protein complexes and allows selections in the presence of non-covalent ligands. Sybodies are especially suited for cases where binder generation via immune libraries fails due to high sequence conservation, toxicity or insufficient stability of the target protein. The procedure entails a single round of ribosome display using the sybody libraries encoded by mRNA, followed by two rounds of phage display and binder identification by ELISA. The protocol is optimized to avoid undesired reduction in binder diversity and enrichment of non-specific binders to ensure the best possible selection outcome. Using the efficient fragment exchange (FX) cloning method, the sybody sequences are transferred from the phagemid to different expression vectors without the need to amplify them by PCR, which avoids unintentional shuffling of complementary determining regions. Using quantitative PCR (qPCR), the efficiency of each selection round is monitored to provide immediate feedback and guide troubleshooting. Our protocol can be carried out by any trained biochemist or molecular biologist using commercially available reagents and typically gives rise to 10–30 unique sybodies exhibiting binding affinities in the range of 500 pM–500 nM. This protocol describes in vitro procedures for generation of synthetic single-domain antibodies called ‘sybodies’. Sybodies can be engineered to target specific protein conformations, labile membrane proteins or protein complexes.

Through a mutualistic relationship with woody plant roots, ectomycorrhizal fungi provide growth-limiting nutrients, including inorganic phosphate (Pi), to their host. Reciprocal trades occur at the Hartig net, which is the symbiotic interface of ectomycorrhizas where the two partners are symplasmically isolated. Fungal Pi must be exported to the symbiotic interface, but the proteins facilitating this transfer are unknown. In the present study, we combined transcriptomic, microscopy, whole plant physiology, Xray fluorescence mapping, 32P labeling and fungal genetic approaches to unravel the role of HcPT2, a fungal Pi transporter, during the Hebeloma cylindrosporum–Pinus pinaster ectomycorrhizal association. We localized HcPT2 in the extra-radical hyphae and the Hartig net and demonstrated its determinant role for both the establishment of ectomycorrhizas and Pi allocation towards P. pinaster. We showed that the host plant induces HcPT2 expression and that the artificial overexpression of HcPT2 is sufficient to significantly enhance Pi export towards the central cylinder. Together, our results reveal that HcPT2 plays an important role in ectomycorrhizal symbiosis, affecting both Pi influx in the mycelium and efflux towards roots under the control of P. pinaster.

In this study, we developed and validated a CE-TOF-MS method for the quantification of glyphosate (N-(phosphonomethyl)glycine) and its major degradation product aminomethylphosphonic acid (AMPA) in different samples including beer, media from toxicological analysis with Daphnia magna, and sorption experiments. Using a background electrolyte (BGE) of very low pH, where glyphosate is still negatively charged but many matrix components become neutral or protonated, a very high separation selectivity was reached. The presence of inorganic salts in the sample was advantageous with regard to preconcentration via transient isotachophoresis. The advantages of our new method are the following: no derivatization is needed, high separation selectivity and thus matrix tolerance, speed of analysis, limits of detection suitable for many applications in food and environmental science, negligible disturbance by metal chelation. LODs for glyphosate were < 5 μg/L for both aqueous and beer samples, the linear range in aqueous samples was 5–3000 μg/L, for beer samples 10–3000 μg/L. For AMPA, LODs were 3.3 and 30.6 μg/L, and the linear range 10–3000 μg/L and 50–3000 μg/L, for aqueous and beer samples, respectively. Recoveries in beer samples for glyphosate were 94.3–110.7% and for AMPA 80.2–100.4%. We analyzed 12 German and 2 Danish beer samples. Quantification of glyphosate and AMPA was possible using isotopically labeled standards without enrichment, purification, or dilution, only degassing and filtration were required for sample preparation. Finally, we demonstrate the applicability of the method for other strong acids, relevant in food and environmental sciences such as N-acetyl glyphosate, N-acetyl AMPA (present in some glyphosate resistant crop), trifluoroacetic acid, 2-methyl-4-chlorophenoxyacetic acid, glufosinate and its degradation product 3-(methylphosphinico)propionic acid, oxamic acid, and others.

To design, construct and validate radiofrequency (RF) transmit and receive phased array coils for high-resolution visual cortex imaging at 7 Tesla. A 4 channel transmit and 16 channel receive array was constructed on a conformal polycarbonate former. Transmit field efficiency and homogeneity were simulated and validated, along with the Specific Absorption Rate, using [Formula: see text] mapping techniques and electromagnetic simulations. Receiver signal-to-noise ratio (SNR), temporal SNR (tSNR) across EPI time series, g-factors for accelerated imaging and noise correlations were evaluated and compared with a commercial 32 channel whole head coil. The performance of the coil was further evaluated with human subjects through functional MRI (fMRI) studies at standard and submillimeter resolutions of upto 0.8mm isotropic. The transmit and receive sections were characterized using bench tests and showed good interelement decoupling, preamplifier decoupling and sample loading. SNR for the 16 channel coil was ∼ 1.5 times that of the commercial coil in the human occipital lobe, and showed better g-factor values for accelerated imaging. fMRI tests conducted showed better response to Blood Oxygen Level Dependent (BOLD) activation, at resolutions of 1.2mm and 0.8mm isotropic. The 4 channel phased array transmit coil provides homogeneous excitation across the visual cortex, which, in combination with the dual row 16 channel receive array, makes for a valuable research tool for high resolution anatomical and functional imaging of the visual cortex at 7T.