Innovative approach for a classic target: fragment screening on trypanothione reductase reveals new opportunities for drug design

Trypanothione reductase (TR) is a key factor in the redox homeostasis of trypanosomatid parasites, critical for survival in the hostile oxidative environment generated by the host to fight infection. TR is considered an attractive target for the development of new trypanocidal agents as it is essential for parasite survival but has no close homolog in humans. However, the high efficiency and turnover of TR challenging targets since only potent inhibitors, with nanomolar IC50, can significantly affect parasite redox state and viability. To aid the design of effective compounds targeting TR, we performed a fragment-based crystal screening at the Diamond Light Source XChem facility using a library optimized for follow-up synthesis steps. The experiment, allowing for testing over 300 compounds, resulted in the identification of 12 new ligands binding five different sites. Interestingly, the screening revealed the existence of an allosteric pocket close to the NADPH binding site, named the "doorstop pocket" since ligands binding at this site interfere with TR activity by hampering the "opening movement" needed to allow cofactor binding. The second remarkable site, known as the Z-site, identified by the screening, is located within the large trypanothione cavity but corresponds to a region not yet exploited for inhibition. The fragments binding to this site are close to each other and have some remarkable features making them ideal for follow-up optimization as a piperazine moiety in three out of five fragments

GIADA performance during Rosetta mission scientific operations at comet 67P

The Grain Impact Analyser and Dust Accumulator (GIADA) instrument onboard Rosetta studied the dust environment of comet 67P/Churyumov–Gerasimenko from 3.7 au inbound, through perihelion, to 3.8 au outbound, measuring the dust flow and the dynamic properties of individual particles. GIADA is composed of three subsystems: 1) Grain Detection System (GDS); 2) Impact Sensor (IS); and 3) Micro-Balances System (MBS). Monitoring the subsystems’ performance during operations is an important element for the correct calibration of scientific measurements. In this paper, we analyse the GIADA inflight calibration data obtained by internal calibration devices for the three subsystems during the period from 1 August 2014 to 31 October 2015. The calibration data testify a nominal behaviour of the instrument during these fifteen months of mission; the only exception is a minor loss of sensitivity for one of the two GDS receivers, attributed to dust contamination

An 18F-labeled poly(ADP-ribose) polymerase positron emission tomography imaging agent

Poly(ADP-ribose) polymerase (PARP) is involved in repair of DNA breaks and is over-expressed in a wide variety of tumors, making PARP an attractive biomarker for positron emission tomography (PET) and single photon emission computed tomography imaging. Consequently, over the past decade, there has been a drive to develop nuclear imaging agents targeting PARP. Here, we report the discovery of a PET tracer that is based on the potent PARP inhibitor olaparib (1). Our lead PET tracer candidate, [18F]20, was synthesized and evaluated as a potential PARP PET radiotracer in mice bearing subcutaneous glioblastoma xenografts using ex vivo biodistribution and PET−magnetic resonance imaging techniques. Results showed that [18F]20 could be produced in a good radioactivity yield and exhibited specific PARP binding allowing visualization of tumors overexpressing PARP. [18F]20 is therefore a potential candidate radiotracer for in vivo PARP PET imaging

Validation of statistical clustering on TES dataset using synthetic Martian spectra

In this work we present some results concerning the analysis of Thermal Emission Spectrometer (TES) data, looking at the methane Q-branch spectral signature at 1304 cm-1. Such analysis has been enabled by producing some synthetic spectral datasets, simulating the atmospheric and surface variability observed on Mars, excluding the high latitude regions. The use of synthetic spectra is aimed to provide a better comprehension of the influence that the atmospheric state vector and its composition have on the spectral behavior. This effort is important, because the TES data are characterized by a low resolution (10 cm-1) and a significant random and systematic noise which could, in principle, give results whose quality needs to be improved. We apply statistical clustering of the synthetic spectra to evaluate the effectiveness of detecting methane, and estimating its abundance

Grid-Based Atmospheric Retrievals for Reflected-Light Spectra of Exoplanets using PSGnest

Techniques to retrieve the atmospheric properties of exoplanets via direct observation of their reflected light have often been limited in scope due to computational constraints imposed by the forward-model calculations. We have developed a new set of techniques which significantly decreases the time required to perform a retrieval while maintaining accurate results. We constructed a grid of 1.4 million pre-computed geometric albedo spectra valued at discrete sets of parameter points. Spectra from this grid are used to produce models for a fast and efficient nested sampling routine called PSGnest. Beyond the upfront time to construct a spectral grid, the amount of time to complete a full retrieval using PSGnest is on the order of seconds to minutes using a personal computer. An extensive evaluation of the error induced from interpolating intermediate spectra from the grid indicates that this bias is insignificant compared to other retrieval error sources, with an average coefficient of determination between interpolated and true spectra of 0.998. We apply these new retrieval techniques to help constrain the optimal bandpass centers for retrieving various atmospheric and bulk parameters from a LuvEx-type mission observing several planetary archetypes. We show that spectral observations made using a 20\% bandpass centered at 0.73 microns can be used alongside our new techniques to make detections of $H_2O$ and $O_2$ without the need to increase observing time beyond what is necessary for a signal-to-noise ratio of 10. The methods introduced here will enable robust studies of the capabilities of future observatories to characterize exoplanets.Comment: 32 pages, 17 figures. Accepted for publication in The Astronomical Journa

A Linesearch-based Derivative-free Approach for Nonsmooth Constrained Optimization

In this paper, we propose new linesearch-based methods for nonsmooth constrained optimization problems when first-order information on the problem functions is not available. In the first part, we describe a general framework for bound-constrained problems and analyze its convergence toward stationary points, using the Clarke-Jahn directional derivative. In the second part, we consider inequality constrained optimization problems where both objective function and constraints can possibly be nonsmooth. In this case, we first split the constraints into two subsets: difficult general nonlinear constraints and simple bound constraints on the variables. Then, we use an exact penalty function to tackle the difficult constraints and we prove that the original problem can be reformulated as the bound-constrained minimization of the proposed exact penalty function. Finally, we use the framework developed for the bound-constrained case to solve the penalized problem. Moreover, we prove that every accumulation point, under standard assumptions on the search directions, of the generated sequence of iterates is a stationary point of the original constrained problem. In the last part of the paper, we report extended numerical results on both bound-constrained and nonlinearly constrained problems, showing that our approach is promising when compared to some state-of-the-art codes from the literature

Differential behavioral and physiological effects of anodal transcranial direct current stimulation in healthy adults of younger and older age

Changes in γ-aminobutyric acid (GABA) mediated synaptic transmission have been associated with age-related motor and cognitive functional decline. Since anodal transcranial direct current stimulation (atDCS) has been suggested to target cortical GABAergic inhibitory interneurons, its potential for the treatment of deficient inhibitory activity and functional decline is being increasingly discussed. Therefore, after-effects of a single session of atDCS on resting-state and event-related short-interval intracortical inhibition (SICI) as evaluated with double-pulse TMS and dexterous manual performance were examined using a sham-controlled cross-over design in a sample of older and younger participants. The atDCS effect on resting-state inhibition differed in direction, magnitude, and timing, i.e., late relative release of inhibition in the younger and early relative increase in inhibition in the older. More pronounced release of event-related inhibition after atDCS was exclusively seen in the older. Event-related modulation of inhibition prior to stimulation predicted the magnitude of atDCS-induced effects on resting-state inhibition. Specifically, older participants with high modulatory capacity showed a disinhibitory effect comparable to the younger. Beneficial effects on behavior were mainly seen in the older and in tasks requiring higher dexterity, no clear association with physiological changes was found. Differential effects of atDCS on SICI, discussed to reflect GABAergic inhibition at the level of the primary motor cortex, might be distinct in older and younger participants depending on the functional integrity of the underlying neural network. Older participants with preserved modulatory capacity, i.e., a physiologically "young" motor network, were more likely to show a disinhibitory effect of atDCS. These results favor individually tailored application of tDCS with respect to specific target groups

How Sensitive Are Conventional MEG Functional Connectivity Metrics With Sliding Windows to Detect Genuine Fluctuations in Dynamic Functional Connectivity?

Despite advances in the field of dynamic connectivity, fixed sliding window approaches for the detection of fluctuations in functional connectivity are still widely used. The use of conventional connectivity metrics in conjunction with a fixed sliding window comes with the arbitrariness of the chosen window lengths. In this paper we use multivariate autoregressive and neural mass models with a-priori defined ground truths to systematically analyse the sensitivity of conventional metrics in combination with different window lengths to detect genuine fluctuations in connectivity for various underlying state durations. Metrics of interest are the coherence, imaginary coherence, phase lag index, phase locking value and the amplitude envelope correlation. We performed analysis for two nodes and at the network level. We demonstrate that these metrics show indeed higher variability for genuine temporal fluctuations in connectivity compared to a static connectivity state superimposed by noise. Overall, the error of the connectivity estimates themselves decreases for longer state durations (order of seconds), while correlations of the connectivity fluctuations with the ground truth was higher for longer state durations. In general, metrics, in combination with a sliding window, perform poorly for very short state durations. Increasing the SNR of the system only leads to a moderate improvement. In addition, at the network level, only longer window widths were sufficient to detect plausible resting state networks that matched the underlying ground truth, especially for the phase locking value, amplitude envelope correlation and coherence. The length of these longer window widths did not necessarily correspond to the underlying state durations. For short window widths resting state network connectivity patterns could not be retrieved. We conclude that fixed sliding window approaches for connectivity can detect modulations of connectivity, but mostly if the underlying dynamics operate on moderate to slow timescales. In practice, this can be a drawback, as state durations can vary significantly in empirical data