NMDA Currents Modulate the Synaptic Input–Output Functions of Neurons in the Dorsal Nucleus of the Lateral Lemniscus in Mongolian Gerbils

Neurons in the dorsal nucleus of the lateral lemniscus (DNLL) receive excitatory and inhibitory inputs from the superior olivary complex (SOC) and convey GABAergic inhibition to the contralateral DNLL and the inferior colliculi. Unlike the fast glycinergic inhibition in the SOC, this GABAergic inhibition outlasts auditory stimulation by tens of milliseconds. Two mechanisms have been postulated to explain this persistent inhibition. One, an “integration-based” mechanism, suggests that postsynaptic excitatory integration in DNLL neurons generates prolonged activity, and the other favors the synaptic time course of the DNLL output itself. The feasibility of the integration-based mechanism was tested in vitro in DNLL neurons of Mongolian gerbils by quantifying the cellular excitability and synaptic input–output functions (IO-Fs). All neurons were sustained firing and generated a near monotonic IO-F on current injections. From synaptic stimulations, we estimate that activation of approximately five fibers, each on average liberating ∼18 vesicles, is sufficient to trigger a single postsynaptic action potential. A strong single pulse of afferent fiber stimulation triggered multiple postsynaptic action potentials. The steepness of the synaptic IO-F was dependent on the synaptic NMDA component. The synaptic NMDA receptor current defines the slope of the synaptic IO-F by enhancing the temporal and spatial EPSP summation. Blocking this NMDA-dependent amplification during postsynaptic integration of train stimulations resulted into a ∼20% reduction of the decay time course of the GABAergic inhibition. Thus, our data show that the NMDA-dependent amplification of the postsynaptic activity contributes to the GABAergic persistent inhibition generated by DNLL neurons

Pro-Secretory Activity and Pharmacology in Rabbits of an Aminophenyl-1,3,5-Triazine CFTR Activator for Dry Eye Disorders.

PurposePharmacological activation of ocular surface cystic fibrosis transmembrane conductance regulator (CFTR) chloride channels is a potential pro-secretory approach to treat dry eye disorders. We previously reported the discovery of aminophenyl-1,3,5-triazines, one of which, N-methyl-N-phenyl-6-(2,2,3,3-tetrafluoropropoxy)-1,3,5-triazine-2,4-diamine (herein called CFTRact-K267), fully activated human wildtype CFTR with EC50 ∼ 30 nM and increased tear volume for 8 hours in mice. Here, functional and pharmacological studies of CFTRact-K267 were done in adult New Zealand white rabbits.MethodsCFTR chloride conductance was measured in vivo by ocular surface potential differences and in ex vivo conjunctiva by short-circuit current. Tear volume was measured by the Schirmer tear test II and CFTRact-K267 pharmacokinetics and tissue distribution by liquid chromatography/mass spectrometry. Toxicity profile was studied for 28 days with twice-daily topical administration.ResultsElectrophysiological measurements in vivo and in ex vivo conjunctiva demonstrated CFTR activation by CFTRact-K267. A single topical dose of 3 nmol CFTRact-K267 increased tear production by >5 mm for 9 hours by the Schirmer tear test, with predicted therapeutic concentrations maintained in tear fluid. No tachyphylaxis was seen following 28-day twice-daily administration, and changes were not observed in corneal surface integrity or thickness, intraocular pressure, or ocular histology. At day 28, CFTRact-K267 was concentrated in the cornea and conjunctiva and was not detectable in blood or peripheral organs.ConclusionsThese studies support the development of CFTRact-K267 as a pro-secretory therapy for dry eye disorders

InterAKTions with FKBPs - mutational and pharmacological exploration

The FK506-binding protein 51 (FKBP51) is an Hsp90-associated co-chaperone which regulates steroid receptors and kinases. In pancreatic cancer cell lines, FKBP51 was shown to recruit the phosphatase PHLPP to facilitate dephosphorylation of the kinase Akt, which was associated with reduced chemoresistance. Here we show that in addition to FKBP51 several other members of the FKBP family bind directly to Akt. FKBP51 can also form complexes with other AGC kinases and mapping studies revealed that FKBP51 interacts with Akt via multiple domains independent of their activation or phosphorylation status. The FKBP51-Akt1 interaction was not affected by FK506 analogs or Akt active site inhibitors, but was abolished by the allosteric Akt inhibitor VIII. None of the FKBP51 inhibitors affected AktS473 phosphorylation or downstream targets of Akt. In summary, we show that FKBP51 binds to Akt directly as well as via Hsp90. The FKBP51-Akt interaction is sensitive to the conformation of Akt1, but does not depend on the FK506-binding pocket of FKBP51. Therefore, FKBP inhibitors are unlikely to inhibit the Akt-FKBP-PHLPP network

A Retrospective Analysis of the Fake News Challenge Stance Detection Task

The 2017 Fake News Challenge Stage 1 (FNC-1) shared task addressed a stance classification task as a crucial first step towards detecting fake news. To date, there is no in-depth analysis paper to critically discuss FNC-1's experimental setup, reproduce the results, and draw conclusions for next-generation stance classification methods. In this paper, we provide such an in-depth analysis for the three top-performing systems. We first find that FNC-1's proposed evaluation metric favors the majority class, which can be easily classified, and thus overestimates the true discriminative power of the methods. Therefore, we propose a new F1-based metric yielding a changed system ranking. Next, we compare the features and architectures used, which leads to a novel feature-rich stacked LSTM model that performs on par with the best systems, but is superior in predicting minority classes. To understand the methods' ability to generalize, we derive a new dataset and perform both in-domain and cross-domain experiments. Our qualitative and quantitative study helps interpreting the original FNC-1 scores and understand which features help improving performance and why. Our new dataset and all source code used during the reproduction study are publicly available for future research

Quantum Oscillations Can Prevent the Big Bang Singularity in an Einstein-Dirac Cosmology

We consider a spatially homogeneous and isotropic system of Dirac particles coupled to classical gravity. The dust and radiation dominated closed Friedmann-Robertson-Walker space-times are recovered as limiting cases. We find a mechanism where quantum oscillations of the Dirac wave functions can prevent the formation of the big bang or big crunch singularity. Thus before the big crunch, the collapse of the universe is stopped by quantum effects and reversed to an expansion, so that the universe opens up entering a new era of classical behavior. Numerical examples of such space-times are given, and the dependence on various parameters is discussed. Generically, one has a collapse after a finite number of cycles. By fine-tuning the parameters we construct an example of a space-time which is time-periodic, thus running through an infinite number of contraction and expansion cycles.Comment: 8 pages, LaTeX, 4 figures, statement on energy conditions correcte

Transitional Delayed Detached-Eddy Simulation for a Compressor Cascade:A Critical Assessment

The accurate prediction of transitional flows is crucial for the industrial turbomachinery design process. While a Reynolds-averaged Navier–Stokes approach inherently brings conceptual weaknesses, large-eddy simulation will still be too expensive in the near future to affordably analyze complex turbomachinery configurations. We introduce a transitional delayed detached-eddy simulation (DDES) model, namely, DDES-γ, and analyze the numerical results of the compressor cascade V103. A comparison with the fullyturbulent DDES approach emphasizes the benefit of coupling DDES with a transition model. Issues with undesired decay of modeled turbulent kinetic energy in the freestream are improved when running DDES-γin combination with the synthetic turbulence generator method. The best results for DDES-γ are obtained when changing the inviscid flux solver blending from dynamic to constant mode. We show that DDES-γ is capable ofpredicting the transitional flow through a linear compressor cascade, but we also critically discuss the general concept and results

Adaptive SDE based interpolation for random PDEs

A numerical method for the fully adaptive sampling and interpolation of PDE with random data is presented. It is based on the idea that the solution of the PDE with stochastic data can be represented as conditional expectation of a functional of a corresponding stochastic differential equation (SDE). The physical domain is decomposed subject to a non-uniform grid and a classical Euler scheme is employed to approximately solve the SDE at grid vertices. Interpolation with a conforming finite element basis is employed to reconstruct a global solution of the problem. An a posteriori error estimator is introduced which provides a measure of the different error contributions. This facilitates the formulation of an adaptive algorithm to control the overall error by either reducing the stochastic error by locally evaluating more samples, or the approximation error by locally refining the underlying mesh. Numerical examples illustrate the performance of the presented novel method