Structural Simplification of Bedaquiline: the Discovery of 3-(4-(N,N-dimethylaminomethyl)phenyl)quinoline Derived Antitubercular Lead Compounds

Bedaquiline (BDQ) is a novel and highly potent last-line antituberculosis drug that was approved by the US FDA in 2013. Owing to its stereo-structural complexity, chemical synthesis and compound optimization are rather difficult and expensive. This study describes the structural simplification of bedaquiline while preserving antitubercular activity. The compound's structure was split into fragments and reassembled in various combinations while replacing the two chiral carbon atoms with an achiral linkage instead. Four series of analogues were designed; these candidates retained their potent antitubercular activity at sub-microgram per mL concentrations against both sensitive and multidrug-resistant (MDR) Mycobacterium tuberculosis strains. Six out of the top nine MIC-ranked candidates were found to inhibit mycobacterial ATP synthesis activity with IC50 values between 20 and 40 μm, one had IC50>66 μm, and two showed no inhibition, despite their antitubercular activity. These results provide a basis for the development of chemically less complex, lower-cost bedaquiline derivatives and describe the identification of two derivatives with antitubercular activity against non-ATP synthase related targets

Accurate Image Analysis of the Retina Using Hessian Matrix and Binarisation of Thresholded Entropy with Application of Texture Mapping

In this paper, we demonstrate a comprehensive method for segmenting the retinal vasculature in camera images of the fundus. This is of interest in the area of diagnostics for eye diseases that affect the blood vessels in the eye. In a departure from other state-of-the-art methods, vessels are first pre-grouped together with graph partitioning, using a spectral clustering technique based on morphological features. Local curvature is estimated over the whole image using eigenvalues of Hessian matrix in order to enhance the vessels, which appear as ridges in images of the retina. The result is combined with a binarized image, obtained using a threshold that maximizes entropy, to extract the retinal vessels from the background. Speckle type noise is reduced by applying a connectivity constraint on the extracted curvature based enhanced image. This constraint is varied over the image according to each region's predominant blood vessel size. The resultant image exhibits the central light reflex of retinal arteries and veins, which prevents the segmentation of whole vessels. To address this, the earlier entropy-based binarization technique is repeated on the original image, but crucially, with a different threshold to incorporate the central reflex vessels. The final segmentation is achieved by combining the segmented vessels with and without central light reflex. We carry out our approach on DRIVE and REVIEW, two publicly available collections of retinal images for research purposes. The obtained results are compared with state-of-the-art methods in the literature using metrics such as sensitivity (true positive rate), selectivity (false positive rate) and accuracy rates for the DRIVE images and measured vessel widths for the REVIEW images. Our approach out-performs the methods in the literature.Xiaoxia Yin, Brian W-H Ng, Jing He, Yanchun Zhang, Derek Abbot

Retrospective model-based inference guides model-free credit assignment

An extensive reinforcement learning literature shows that organisms assign credit efficiently, even under conditions of state uncertainty. However, little is known about credit-assignment when state uncertainty is subsequently resolved. Here, we address this problem within the framework of an interaction between model-free (MF) and model-based (MB) control systems. We present and support experimentally a theory of MB retrospective-inference. Within this framework, a MB system resolves uncertainty that prevailed when actions were taken thus guiding an MF credit-assignment. Using a task in which there was initial uncertainty about the lotteries that were chosen, we found that when participants’ momentary uncertainty about which lottery had generated an outcome was resolved by provision of subsequent information, participants preferentially assigned credit within a MF system to the lottery they retrospectively inferred was responsible for this outcome. These findings extend our knowledge about the range of MB functions and the scope of system interactions

Bayesian Optimization Approaches for Massively Multi-modal Problems

The optimization of massively multi-modal functions is a challenging task, particularly for problems where the search space can lead the op- timization process to local optima. While evolutionary algorithms have been extensively investigated for these optimization problems, Bayesian Optimization algorithms have not been explored to the same extent. In this paper, we study the behavior of Bayesian Optimization as part of a hybrid approach for solving several massively multi-modal functions. We use well-known benchmarks and metrics to evaluate how different variants of Bayesian Optimization deal with multi-modality.TIN2016-78365-

The motivational drive to natural rewards is modulated by prenatal glucocorticoid exposure

Exposure to elevated levels of glucocorticoids (GCs) during neurodevelopment has been identified as a triggering factor for the development of reward-associated disorders in adulthood. Disturbances in the neural networks responsible for the complex processes that assign value to rewards and associated stimuli are critical for disorders such as depression, obsessive–compulsive disorders, obesity and addiction. Essential in the understanding on how cues influence behavior is the Pavlovian–instrumental transfer (PIT), a phenomenon that refers to the capacity of a Pavlovian stimulus that predicts a reward to elicit instrumental responses for that same reward. Here, we demonstrate that in utero exposure to GCs (iuGC) impairs both general and selective versions of the PIT paradigm, suggestive of deficits in motivational drive. The iuGC animals presented impaired neuronal activation pattern upon PIT performance in cortical and limbic regions, as well as morphometric changes and reduced levels of dopamine in prefrontal and orbitofrontal cortices, key regions involved in the integration of Pavlovian and instrumental stimuli. Normalization of dopamine levels rescued this behavior, a process that relied on D2/D3, but not D1, dopamine receptor activation. In summary, iuGC exposure programs the mesocorticolimbic dopaminergic circuitry, leading to a reduction in the attribution of the incentive salience to cues, in a dopamine-D2/D3-dependent manner. Ultimately, these results are important to understand how GCs bias incentive processes, a fact that is particularly relevant for disorders where differential attribution of incentive salience is critical.We thank Pedro Morgado for discussions and help in the technical aspects of PIT procedure. This project was supported by a grant of Institute for the Study of Affective Neuroscience (ISAN) and by Janssen Neuroscience Prize. CS-C, SB, MMC and AJR are recipients of Fundacao para a Ciencia e Tecnologia (FCT) fellowships (CS-C: SFRH/BD/51992/2012; SB: SFRH/BD/89936/2012; MMC: SRFH/BD/51061/2010; AJR: SFRH/BPD/33611/2009)

Efficient numerical computation and experimental study of temporally long equilibrium scour development around abutment

YesFor the abutment bed scour to reach its equilibrium state, a long flow time is needed. Hence, the employment of usual strategy of simulating such scouring event using the 3D numerical model is very time consuming and less practical. In order to develop an applicable model to consider temporally long abutment scouring process, this study modifies the common approach of 2D shallow water equations (SWEs) model to account for the sediment transport and turbulence, and provides a realistic approach to simulate the long scouring process to reach the full scour equilibrium. Due to the high demand of the 2D SWEs numerical scheme performance to simulate the abutment bed scouring, a recently proposed surface gradient upwind method (SGUM) was also used to improve the simulation of the numerical source terms. The abutment scour experiments of this study were conducted using the facility of Hydraulics Laboratory at Nanyang Technological University, Singapore to compare with the presented 2D SGUM-SWEs model. Fifteen experiments were conducted over a total period of 3059.7 hours experimental time (over 4.2 months). The comparison shows that the 2D SGUM-SWEs model gives good representation to the experimental results with the practical advantage

Population pharmacokinetics of the humanised monoclonal antibody, HuHMFG1 (AS1402), derived from a phase I study on breast cancer

International audienceBACKGROUND: HuHMFG1 (AS1402) is a humanised monoclonal antibody that has undergone a phase I trial in metastatic breast cancer. The aim of this study was to characterise the pharmacokinetics (PKs) of HuHMFG1 using a population PK model. METHOD: Data were derived from a phase I study of 26 patients receiving HuHMFG1 at doses ranging from 1 to 16 mg kg(-1). Data were analysed using NONMEM software and covariates were included. A limited sampling strategy (LSS) was developed using training and a validation data set. RESULTS: A linear two-compartment model was shown to be adequate to describe data. Covariate analysis indicated that weight was not related to clearance. An LSS was successfully developed on the basis of the model, in which one sample is collected immediately before the start of an infusion and the second is taken at the end of infusion. CONCLUSION: A two-compartment population PK model successfully describes HuHMFG1 behaviour. The model suggests using a fixed dose of HuHMFG1, which would simplify dosing. The model could be used to optimise dose level and dosing schedule if more data on the correlation between exposure and efficacy become available from future studies. The derived LSS could optimise further PK assessment of this antibody

Magnetic Properties of FePt Nanoparticles Prepared by a Micellar Method

FePt nanoparticles with average size of 9 nm were synthesized using a diblock polymer micellar method combined with plasma treatment. To prevent from oxidation under ambient conditions, immediately after plasma treatment, the FePt nanoparticle arrays were in situ transferred into the film-growth chamber where they were covered by an SiO2 overlayer. A nearly complete transformation of L10 FePt was achieved for samples annealed at temperatures above 700 °C. The well control on the FePt stoichiometry and avoidance from surface oxidation largely enhanced the coercivity, and a value as high as 10 kOe was obtained in this study. An evaluation of magnetic interactions was made using the so-called isothermal remanence (IRM) and dc-demagnetization (DCD) remanence curves and Kelly–Henkel plots (ΔM measurement). The ΔM measurement reveals that the resultant FePt nanoparticles exhibit a rather weak interparticle dipolar coupling, and the absence of interparticle exchange interaction suggests no significant particle agglomeration occurred during the post-annealing. Additionally, a slight parallel magnetic anisotropy was also observed. The results indicate the micellar method has a high potential in preparing FePt nanoparticle arrays used for ultrahigh density recording media