The conventional approach to understanding neural responses underlying complex computations is to study across-trial averages of repeatedly performed computations from single neurons. When neurons perform complex computations, such as processing stimulus-related information or motor planning, it has been repeatedly shown, through measures such as the Fano factor (FF), that neural variability across trials decreases. However, multiple neurons contribute to a common computation on a single trial, rather than a single neuron contributing to a computation across multiple trials. Therefore, at the level of a single trial, the concept of FF loses significance. Here, using a combination of simulations and empirical data, we show that changes in the spiking regularity on single trials produces changes in FF. Further, at the behavioral level, the reaction time of the animal was faster when the neural spiking regularity both within and across trials was lower. Taken together, our results provide further constraints on how, changes in spiking statistics help neurons optimally encode visual and saccade related information across multiple timescales and its implication on behavior.The purpose of this article is to introduce a risk analysis framework to enhance the cyber security of and to protect the critical infrastructure of the electric power grid of the United States. Building on the fundamental questions of risk assessment and management, this framework aims to advance the current risk analysis discussions pertaining to the electric power grid. Most of the previous risk-related studies on the electric power grid focus mainly on the recovery of the network from hurricanes and other natural disasters. In contrast, a disproportionately small number of studies explicitly investigate the vulnerability of the electric power grid to cyber-attack scenarios, and how they could be prevented or mitigated. Such a limited approach leaves the United States vulnerable to foreign and domestic threats (both state-sponsored and "lone wolf") to infiltrate a network that lacks a comprehensive security environment or coordinated government response. By conducting a review of the literature and presenting a risk-based framework, this article underscores the need for a coordinated U.S. cyber security effort toward formulating strategies and responses conducive to protecting the nation against attacks on the electric power grid.We present a robust protocol based on iterations of free energy perturbation (FEP) calculations, chemical synthesis, biophysical mapping and X-ray crystallography to reveal the binding mode of an antagonist series to the adenosine A 2A receptor (AR). Eight A 2A AR binding site mutations from biophysical mapping experiments were initially analysed with sidechain FEP simulations, performed on alternate binding modes. The results distinctively supported one binding mode, which was subsequently used to design new chromone derivatives. Their affinities for the A 2A AR were experimentally determined and investigated through a cycle of ligand-FEP calculations, validating the binding orientation of the different chemical substituents proposed. Subsequent X-ray crystallography of the A2AAR with a low and a high affinity chromone derivative confirmed the predicted binding orientation. The new molecules and structures here reported were driven by free energy calculations, and provide new insights on antagonist binding to the A 2A AR, an emerging target in immuno-oncology.Macromolecular signals are crucial constituents of short echo-time 1 H MR spectra with potential clinical implications in themselves as well as essential ramifications for the quantification of the usually targeted metabolites. Their parameterization, needed for general fitting models, is difficult because of their unknown composition. Here, a macromolecular signal parameterization together with metabolite signal quantification including relaxation properties is investigated by multidimensional modeling of interrelated 2DJ inversion-recovery (2DJ-IR) datasets. Simultaneous and iterative procedures for defining the macromolecular background (MMBG) as mono-exponentially or generally decaying signals over TE are evaluated.  https://www.selleckchem.com/products/CP-690550.html  Varying prior knowledge and restrictions in the metabolite evaluation are tested to examine their impact on results and fitting stability for two sets of three-dimensional spectra acquired with metabolite-cycled PRESS from cerebral gray and white matter locations. One dataset was used for modeal subject data with high fitting precision documented in small Cramér-Rao lower bounds, good repeatability values and a relatively small spread of estimated concentration and relaxation values for a healthy subject cohort.Background It is controversial whether chronic hepatitis B (CHB) patients have more non-liver comorbidities than non-CHB subjects. Aim To characterise the demographics, comorbidity and health utilisation of CHB patients in South Korea and compare them to matched controls. Methods Using the Health Insurance Review & Assessment Service (HIRA) 2007-2016 database, adult patients with claims for CHB analysed. CHB cases and non-CHB controls matched in a 14 ratio using propensity score matching method. Results The age of CHB patients significantly increased from a mean 46.9 years in 2007 to 52.3 years in 2016. The proportions of persons having both liver-related and non-liver related comorbidities were higher in CHB patients compared to matched controls (dyslipidaemia [37.23% vs 23.77%, P less then 0.0001], hypertension [29.39% vs 25.27%, P less then 0.0001] chronic kidney disease (CKD) [3.02% vs 1.14%, P less then 0.0001] and osteoporosis/fracture [OF] [4.09% vs 3.23%, P less then 0.0001]). Approximately 50% of CHB patients had more than one comorbidity among CKD, diabetes, DLP, and OF. The odds of CKD in CHB patients were 1.42 times higher, and the odds of OF in CHB patients were 1.09 times higher than matched controls after adjustment for confounders (P less then 0.0001). Conclusion Prevalence of liver as well as non-liver comorbidities in patients with CHB was higher than matched controls and increased over time.