A Structure-Activity Relationship Study of Bimodal BODIPY-Labeled PSMA-Targeting Bioconjugates

The aim of this study was to identify a high-affinity BODIPY peptidomimetic that targets the prostate-specific membrane antigen (PSMA) as a potential bimodal imaging probe for prostate cancer. For the structure-activity study, several BODIPY (difluoroboron dipyrromethene) derivatives with varying spacers between the BODIPY dye and the PSMA Glu-CO-Lys binding motif were prepared. Corresponding affinities were determined by competitive binding assays in PSMA-positive LNCaP cells. One compound was identified with comparable affinity (IC50=21.5±0.1 nM) to Glu-CO-Lys-Ahx-HBED-CC (PSMA-11) (IC50=18.4±0.2 nM). Radiolabeling was achieved by Lewis-acid-mediated 19F/18F exchange in moderate molar activities (∼0.7 MBq nmol−1) and high radiochemical purities (>99 %) with mean radiochemical yields of 20–30 %. Cell internalization of the 18F-labeled high-affinity conjugate was demonstrated in LNCaP cells showing gradual increasing PSMA-mediated internalization over time. By fluorescence microscopy, localization of the high-affinity BODIPY-PSMA conjugate was found in the cell membrane at early time points and also in subcellular compartments at later time points. In summary, a high-affinity BODIPY-PSMA conjugate has been identified as a suitable candidate for the development of PSMA-specific dual-imaging agents

Empowerment for Continuous Agent-Environment Systems

This paper develops generalizations of empowerment to continuous states. Empowerment is a recently introduced information-theoretic quantity motivated by hypotheses about the efficiency of the sensorimotor loop in biological organisms, but also from considerations stemming from curiosity-driven learning. Empowemerment measures, for agent-environment systems with stochastic transitions, how much influence an agent has on its environment, but only that influence that can be sensed by the agent sensors. It is an information-theoretic generalization of joint controllability (influence on environment) and observability (measurement by sensors) of the environment by the agent, both controllability and observability being usually defined in control theory as the dimensionality of the control/observation spaces. Earlier work has shown that empowerment has various interesting and relevant properties, e.g., it allows us to identify salient states using only the dynamics, and it can act as intrinsic reward without requiring an external reward. However, in this previous work empowerment was limited to the case of small-scale and discrete domains and furthermore state transition probabilities were assumed to be known. The goal of this paper is to extend empowerment to the significantly more important and relevant case of continuous vector-valued state spaces and initially unknown state transition probabilities. The continuous state space is addressed by Monte-Carlo approximation; the unknown transitions are addressed by model learning and prediction for which we apply Gaussian processes regression with iterated forecasting. In a number of well-known continuous control tasks we examine the dynamics induced by empowerment and include an application to exploration and online model learning

High-fat, sucrose and salt-rich diet during rat spermatogenesis lead to the development of chronic kidney disease in the female offspring of the F2 generation

Effects of feeding male rats during spermatogenesis a high-fat, high-sucrose and high-salt diet (HFSSD) over two generations (F0 and F1) on renal outcomes are unknown. Male F0 and F1 rats were fed either control diet (F0CD+F1CD) or HFSSD (F0HD+F1HD). The outcomes were glomerular filtration rate and urinary albumin excretion in F1 and F2 offspring. If both outcomes were altered a morphological and molecular assessment was done. F2 offspring of both sexes had a decreased GFR. However, increased urinary albumin excretion was only observed in female F2 F0HD+F1HD offspring compared with controls. F0HD+F1HD female F2 offspring developed glomerulosclerosis (+31%; p < .01) and increased renal interstitial fibrosis (+52%; p < .05). RNA sequencing followed by qRT-PCR validation showed that four genes (Enpp6, Tmem144, Cd300lf, and Actr3b) were differentially regulated in the kidneys of female F2 offspring. lncRNA XR-146683.1 expression decreased in female F0HD+F1HD F2 offspring and its expression was (r = 0.44, p = .027) correlated with the expression of Tmem144. Methylation of CpG islands in the promoter region of the Cd300lf gene was increased (p = .001) in female F2 F0HD+F1HD offspring compared to controls. Promoter CpG island methylation rate of Cd300lf was inversely correlated with Cd300lf mRNA expression in F2 female offspring (r = −0.483, p = .012). Cd300lf mRNA expression was inversely correlated with the urinary albumin-to-creatinine ratio in female F2 offspring (r = −0.588, p = .005). Paternal pre-conceptional unhealthy diet given for two generations predispose female F2 offspring to chronic kidney disease due to epigenetic alterations of renal gene expression. Particularly, Cd300lf gene promotor methylation was inversely associated with Cd300lf mRNA expression and Cd300lf mRNA expression itself was inversely associated with urinary albumin excretion in F2 female offspring whose fathers and grandfathers got a pre-conceptional unhealthy diet

Machine Learning Approach to Investigating the Relative Importance of Meteorological and Aerosol-Related Parameters in Determining Cloud Microphysical Properties

Aerosol effects on cloud properties are notoriously difficult to disentangle from variations driven by meteorological factors. Here, a machine learning model is trained on reanalysis data and satellite retrievals to predict cloud microphysical properties, as a way to illustrate the relative importance of meteorology and aerosol, respectively, on cloud properties. It is found that cloud droplet effective radius can be predicted with some skill from only meteorological information, including estimated air mass origin and cloud top height. For ten geographical regions the mean coefficient of determination is 0.41 and normalised root-mean square error 24%. The machine learning model thereby performs better than a reference linear regression model, and a model predicting the climatological mean. A gradient boosting regression performs on par with a neural network regression model. Adding aerosol information as input to the model improves its skill somewhat, but the difference is small and the direction of the influence of changing aerosol burden on cloud droplet effective radius is not consistent across regions, and thereby also not always consistent with what is expected from cloud brightening

Suv4-20h Histone Methyltransferases Promote Neuroectodermal Differentiation by Silencing the Pluripotency-Associated Oct-25 Gene

Post-translational modifications (PTMs) of histones exert fundamental roles in regulating gene expression. During development, groups of PTMs are constrained by unknown mechanisms into combinatorial patterns, which facilitate transitions from uncommitted embryonic cells into differentiated somatic cell lineages. Repressive histone modifications such as H3K9me3 or H3K27me3 have been investigated in detail, but the role of H4K20me3 in development is currently unknown. Here we show that Xenopus laevis Suv4-20h1 and h2 histone methyltransferases (HMTases) are essential for induction and differentiation of the neuroectoderm. Morpholino-mediated knockdown of the two HMTases leads to a selective and specific downregulation of genes controlling neural induction, thereby effectively blocking differentiation of the neuroectoderm. Global transcriptome analysis supports the notion that these effects arise from the transcriptional deregulation of specific genes rather than widespread, pleiotropic effects. Interestingly, morphant embryos fail to repress the Oct4-related Xenopus gene Oct-25. We validate Oct-25 as a direct target of xSu4-20h enzyme mediated gene repression, showing by chromatin immunoprecipitaton that it is decorated with the H4K20me3 mark downstream of the promoter in normal, but not in double-morphant, embryos. Since knockdown of Oct-25 protein significantly rescues the neural differentiation defect in xSuv4-20h double-morphant embryos, we conclude that the epistatic relationship between Suv4-20h enzymes and Oct-25 controls the transit from pluripotent to differentiation-competent neural cells. Consistent with these results in Xenopus, murine Suv4-20h1/h2 double-knockout embryonic stem (DKO ES) cells exhibit increased Oct4 protein levels before and during EB formation, and reveal a compromised and biased capacity for in vitro differentiation, when compared to normal ES cells. Together, these results suggest a regulatory mechanism, conserved between amphibians and mammals, in which H4K20me3-dependent restriction of specific POU-V genes directs cell fate decisions, when embryonic cells exit the pluripotent state

A discrete geometric approach for simulating the dynamics of thin viscous threads

We present a numerical model for the dynamics of thin viscous threads based on a discrete, Lagrangian formulation of the smooth equations. The model makes use of a condensed set of coordinates, called the centerline/spin representation: the kinematical constraints linking the centerline's tangent to the orientation of the material frame is used to eliminate two out of three degrees of freedom associated with rotations. Based on a description of twist inspired from discrete differential geometry and from variational principles, we build a full-fledged discrete viscous thread model, which includes in particular a discrete representation of the internal viscous stress. Consistency of the discrete model with the classical, smooth equations is established formally in the limit of a vanishing discretization length. The discrete models lends itself naturally to numerical implementation. Our numerical method is validated against reference solutions for steady coiling. The method makes it possible to simulate the unsteady behavior of thin viscous jets in a robust and efficient way, including the combined effects of inertia, stretching, bending, twisting, large rotations and surface tension

Large tunable valley splitting in edge-free graphene quantum dots on boron nitride

Coherent manipulation of binary degrees of freedom is at the heart of modern quantum technologies. Graphene offers two binary degrees: the electron spin and the valley. Efficient spin control has been demonstrated in many solid state systems, while exploitation of the valley has only recently been started, yet without control on the single electron level. Here, we show that van-der Waals stacking of graphene onto hexagonal boron nitride offers a natural platform for valley control. We use a graphene quantum dot induced by the tip of a scanning tunneling microscope and demonstrate valley splitting that is tunable from -5 to +10 meV (including valley inversion) by sub-10-nm displacements of the quantum dot position. This boosts the range of controlled valley splitting by about one order of magnitude. The tunable inversion of spin and valley states should enable coherent superposition of these degrees of freedom as a first step towards graphene-based qubits

Hidden Charge Order in an Iron Oxide Square-Lattice Compound

Since the discovery of charge disproportionation in the FeO2 square-lattice compound Sr3Fe2O7 by Mössbauer spectroscopy more than fifty years ago, the spatial ordering pattern of the disproportionated charges has remained “hidden” to conventional diffraction probes, despite numerous x-ray and neutron scattering studies. We have used neutron Larmor diffraction and Fe K-edge resonant x-ray scattering to demonstrate checkerboard charge order in the FeO2 planes that vanishes at a sharp second-order phase transition upon heating above 332 K. Stacking disorder of the checkerboard pattern due to frustrated interlayer interactions broadens the corresponding superstructure reflections and greatly reduces their amplitude, thus explaining the difficulty of detecting them by conventional probes. We discuss the implications of these findings for research on “hidden order” in other materials

Clinical Frailty Scale (CFS) reliably stratifies octogenarians in German ICUs: a multicentre prospective cohort study

Background: In intensive care units (ICU) octogenarians become a routine patients group with aggravated therapeutic and diagnostic decision-making. Due to increased mortality and a reduced quality of life in this high-risk population, medical decision-making a fortiori requires an optimum of risk stratification. Recently, the VIP-1 trial prospectively observed that the clinical frailty scale (CFS) performed well in ICU patients in overall-survival and short-term outcome prediction. However, it is known that healthcare systems differ in the 21 countries contributing to the VIP-1 trial. Hence, our main focus was to investigate whether the CFS is usable for risk stratification in octogenarians admitted to diversified and high tech German ICUs. Methods: This multicentre prospective cohort study analyses very old patients admitted to 20 German ICUs as a sub-analysis of the VIP-1 trial. Three hundred and eight patients of 80 years of age or older admitted consecutively to participating ICUs. CFS, cause of admission, APACHE II, SAPS II and SOFA scores, use of ICU resources and ICU- and 30-day mortality were recorded. Multivariate logistic regression analysis was used to identify factors associated with 30-day mortality. Results: Patients had a median age of 84 [IQR 82–87] years and a mean CFS of 4.75 (± 1.6 standard-deviation) points. More than half of the patients (53.6%) were classified as frail (CFS ≥ 5). ICU-mortality was 17.3% and 30-day mortality was 31.2%. The cause of admission (planned vs. unplanned), (OR 5.74) and the CFS (OR 1.44 per point increase) were independent predictors of 30-day survival. Conclusions: The CFS is an easy determinable valuable tool for prediction of 30-day ICU survival in octogenarians, thus, it may facilitate decision-making for intensive care givers in Germany. Trial registration: The VIP-1 study was retrospectively registered on ClinicalTrials.gov (ID: NCT03134807 ) on May 1, 2017