Large Scale Study of Ligand-Protein Relative Binding Free Energy Calculations: Actionable Predictions from Statistically Robust Protocols

The accurate and reliable prediction of protein-ligand binding affinities can play a central role in the drug discovery process as well as in personalised medicine. Of considerable importance during lead optimisation are the alchemical free energy methods that furnish estimation of relative binding free energies (RBFE) of similar molecules. Recent advances in these methods have increased their speed, accuracy and precision. This is evident from the increasing number of retrospective as well as prospective studies employing them. However, such methods still have limited applicability in real-world scenarios due to a number of important yet unresolved issues. Here, we report the findings from a large dataset comprising over 500 ligand transformations spanning over 300 ligands binding to a diverse set of 14 different protein targets which furnish statistically robust results on the accuracy, precision and reproducibility of RBFE calculations. We use ensemble-based methods which are the only way to provide reliable uncertainty quantification given that the underlying molecular dynamics is chaotic. These are implemented using TIES (Thermodynamic Integration with Enhanced Sampling) but are equally applicable to free energy perturbation calculations for which we expect essentially very similar results. Results achieve chemical accuracy in all cases. Ensemble simulations also furnish information on the statistical distributions of the free energy calculations which exhibit non-normal behaviour. We find that the “enhanced sampling” method known as replica exchange with solute tempering degrades RBFE predictions. We also report definitively on numerous associated alchemical factors including the choice of ligand charge method, flexibility in ligand structure and the size of the alchemical region including the number of atoms involved in transforming one ligand into another. Our findings provide a key set of recommendations that should be adopted for the reliable application of RBFE methods.

ACUTE TOXICITY OF Β-KITIN EXTRACTED FROM THE SHELL OF BLUE SWIMMING CRAB (PORTUNUS PELAGICUS LINN.)

Objective: This work aimed to study the acute toxicity of β-chitin extracted from crab shells in Bal b/c mice. Method: The acute toxicity test was performed by following the OECD guidelines. Female mice were given single or divided doses of β-chitin (maximum 24 h) with doses of 500, 1000, 2000, 4000, and 6000 mg/kg of BW. Observations were made for 14 d, including behaviour, body weight, organ weight, and histopathology of vital organs (stomach, heart, liver, kidney, and lung). Results: During 14 d, no deaths and no abnormalities in behaviour, bodyweight or organ weight were observed. Qualitative histopathological observations at the highest dose showed abnormalities of the liver and kidney compared to those of the control group. Nevertheless, the abnormalities did not affect the organ function. Conclusion: This acute toxicity study reveals that β-chitin up to a dose of 6000 mg/kg of BW is not toxic, as proved by the normal behaviour, body weight, and vital organ weight of the animals. Further chronic toxicities study is needed to confirm its safety.

Learning the rules of cell competition without prior scientific knowledge

Deep learning is now a powerful tool in microscopy data analysis, and is routinely used for image processing applications such as segmentation and denoising. However, it has rarely been used to directly learn mechanistic models of a biological system, owing to the complexity of the internal representations. Here, we develop an end-to-end machine learning model capable of learning the rules of a complex biological phenomenon, cell competition, directly from a large corpus of timelapse microscopy data. Cell competition is a quality control mechanism that eliminates unfit cells from a tissue and during which cell fate is thought to be determined by the local cellular neighborhood over time. To investigate this, we developed a new approach (τ-VAE) by coupling a variational autoencoder to a temporal convolution network to predict the fate of each cell in an epithelium. Using the τ-VAE's latent representation of the local tissue organization and the flow of information in the network, we decode the physical parameters responsible for correct prediction of fate in cell competition. Remarkably, the model autonomously learns that cell density is the single most important factor in predicting cell fate -- a conclusion that has taken over a decade of traditional experimental research to reach. Finally, to test the learned internal representation, we challenge the network with experiments performed in the presence of drugs that block signalling pathways involved in competition. We present a novel discriminator network that, using the predictions of the τ-VAE, can identify conditions which deviate from the normal behaviour, paving the way for automated, mechanism-aware drug screening.

Training gender: Discursive analysis

<p>The aim of this thesis is to examine the discursive practices that have arisen from gender training in peace operations with the following research questions: “how is the discourse of ‘gender-awareness’ constructed through UN gender-training material for peacekeepers? How does this discourse contribute to further shaping representations of gender, violence and security?” To help answer my research questions, I proceed to a discourse analysis of the gender-training package created in 2001 by the United Nations Department of Peacekeeping Operations (UN DPKO) called Gender and Peacekeeping In-Mission Training. The analytical frameworks chosen for this research paper are Michel Foucault’s notion of discourse and Laura Shepherd’s ‘analytical strategies’. Using Foucault’s understanding of discourse, this paper examines the social practices of gender in the military field (peace and security): how are these social practices embedded in knowledge (in what ways are the notions of gender approached? Do they form a universal truth?)? How does this discourse act through and upon subjects (male and female peacekeepers)? Building on Shepherd’s work, this thesis seeks to interrogate and deconstruct the concept of ‘gender-awareness’ in the UN training material around three dominant discursive sites (called Shepherd’s ‘nodal points’): [1] ‘how the relations between women and men are structured’ (gender), [2] ‘how they are affected by violent conflict’ (gender and violence), and [3] ‘how the mere presence of peacekeepers further impacts on those relations’ (gender, violence and security). The literature review first addresses the construction of feminities and masculinities in war and peace. It demonstrates that women are constructed as being ‘peacemakers’ and that their feminity is shaped as being ‘peaceful’ and as ‘mother of the nation’ whilst masculinities are shaped through war. Secondly, it looks at the ways in which gender has been integrated (or mainstreamed) into UN policies: showing gender as a synonym for women. The research discovers that ‘gender-awareness’ as a discourse in the UN gender-training material is composed of: [1] gender that equates ‘sex’ and ‘women’, [2] the dichotomy between women positioned as ‘victims’ and men as ‘heroes’ (expected normal behaviour) and [3] universals such as women’s rights, which ignore cultural contexts in their approach to gender. The paper also further investigates the discourse of ‘gender-awareness training’, which I argue has been established as a ‘tool’ in the military field, but not as a critical concept. This tool seeks to produce understanding (knowledge, i.e. what is produced as truth) of gender, violence and security and to regulate the agents’ (i.e. male peacekeepers’) behaviours. These findings are important as they add to the literature which demonstrates how gender is de-politicised while sex is politicised and how women are excluded from both the realm of peace (security) and the realm of war (violence). It reinforces the idea that discourse is repeated and that for the UN to (re-)think gender in meaningful and creative ways, it becomes necessary to deconstruct the way power structures are shared.</p>

Training gender: Discursive analysis

<p>The aim of this thesis is to examine the discursive practices that have arisen from gender training in peace operations with the following research questions: “how is the discourse of ‘gender-awareness’ constructed through UN gender-training material for peacekeepers? How does this discourse contribute to further shaping representations of gender, violence and security?” To help answer my research questions, I proceed to a discourse analysis of the gender-training package created in 2001 by the United Nations Department of Peacekeeping Operations (UN DPKO) called Gender and Peacekeeping In-Mission Training. The analytical frameworks chosen for this research paper are Michel Foucault’s notion of discourse and Laura Shepherd’s ‘analytical strategies’. Using Foucault’s understanding of discourse, this paper examines the social practices of gender in the military field (peace and security): how are these social practices embedded in knowledge (in what ways are the notions of gender approached? Do they form a universal truth?)? How does this discourse act through and upon subjects (male and female peacekeepers)? Building on Shepherd’s work, this thesis seeks to interrogate and deconstruct the concept of ‘gender-awareness’ in the UN training material around three dominant discursive sites (called Shepherd’s ‘nodal points’): [1] ‘how the relations between women and men are structured’ (gender), [2] ‘how they are affected by violent conflict’ (gender and violence), and [3] ‘how the mere presence of peacekeepers further impacts on those relations’ (gender, violence and security). The literature review first addresses the construction of feminities and masculinities in war and peace. It demonstrates that women are constructed as being ‘peacemakers’ and that their feminity is shaped as being ‘peaceful’ and as ‘mother of the nation’ whilst masculinities are shaped through war. Secondly, it looks at the ways in which gender has been integrated (or mainstreamed) into UN policies: showing gender as a synonym for women. The research discovers that ‘gender-awareness’ as a discourse in the UN gender-training material is composed of: [1] gender that equates ‘sex’ and ‘women’, [2] the dichotomy between women positioned as ‘victims’ and men as ‘heroes’ (expected normal behaviour) and [3] universals such as women’s rights, which ignore cultural contexts in their approach to gender. The paper also further investigates the discourse of ‘gender-awareness training’, which I argue has been established as a ‘tool’ in the military field, but not as a critical concept. This tool seeks to produce understanding (knowledge, i.e. what is produced as truth) of gender, violence and security and to regulate the agents’ (i.e. male peacekeepers’) behaviours. These findings are important as they add to the literature which demonstrates how gender is de-politicised while sex is politicised and how women are excluded from both the realm of peace (security) and the realm of war (violence). It reinforces the idea that discourse is repeated and that for the UN to (re-)think gender in meaningful and creative ways, it becomes necessary to deconstruct the way power structures are shared.</p>

Condition-Based Maintenance for Normal Behaviour Characterisation of Railway Car-Body Acceleration Applying Neural Networks

Recently, passenger comfort and user experience are becoming increasingly relevant for the railway operators and, therefore, for railway manufacturers as well. The main reason for this to happen is that comfort is a clear differential value considered by passengers as final customers. Passengers’ comfort is directly related to the accelerations received through the car-body of the train. For this reason, suspension and damping components must be maintained in perfect condition, assuring high levels of comfort quality. An early detection of any potential failure in these systems derives in a better maintenance inspections’ planification and in a more sustainable approach to the whole train maintenance strategy. In this paper, an optimized model based on neural networks is trained in order to predict lateral car-body accelerations. Comparing these predictions to the values measured on the train, a normal characterisation of the lateral dynamic behaviour can be determined. Any deviation from this normal characterisation will imply a comfort loss or a potential degradation of the suspension and damping components. This model has been trained with a dataset from a specific train unit, containing variables recorded every second during the year 2017, including lateral and vertical car-body accelerations, among others. A minimum average error of 0.034 m/s2 is obtained in the prediction of lateral car-body accelerations. This means that the average error is approximately 2.27% of the typical maximum estimated values for accelerations in vehicle body reflected in the EN14363 for the passenger coaches (1.5 m/s2). Thus, a successful model is achieved. In addition, the model is evaluated based on a real situation in which a passenger noticed a lack of comfort, achieving excellent results in the detection of atypical accelerations. Therefore, as it is possible to measure acceleration deviations from the standard behaviour causing lack of comfort in passengers, an alert can be sent to the operator or the maintainer for a non-programmed intervention at depot (predictive maintenance) or on board (prescriptive maintenance). As a result, a condition-based maintenance (CBM) methodology is proposed to avoid comfort degradation that could end in passenger complaints or speed limitation due to safety reasons for excessive acceleration. This methodology highlights a sustainable maintenance concept and an energy efficiency strategy.

Insufficiency of ventral hippocampus to medial prefrontal cortex transmission explains antidepressant non-response

Background: There is extensive evidence that antidepressant drugs restore normal brain function by repairing damage to ventral hippocampus (vHPC) and medial prefrontal cortex (mPFC). While the damage is more extensive in hippocampus, the evidence of treatments, such as deep brain stimulation, suggests that functional changes in prefrontal cortex may be more critical. We hypothesized that antidepressant non-response may result from an insufficiency of transmission from vHPC to mPFC. Method: Antidepressant non-responsive Wistar Kyoto (WKY) rats were subjected to chronic mild stress (CMS), then treated with chronic daily administration of the antidepressant drug venlafaxine (VEN) and/or repeated weekly optogenetic stimulation (OGS) of afferents to mPFC originating from vHPC or dorsal HPC (dHPC). Results: As in many previous studies, CMS decreased sucrose intake, open-arm entries on the elevated plus maze (EPM), and novel object recognition (NOR). Neither VEN nor vHPC–mPFC OGS alone was effective in reversing the effects of CMS, but the combination of chronic VEN and repeated OGS restored normal behaviour on all three measures. dHPC–mPFC OGS restored normal behaviour in the EPM and NOR test irrespective of concomitant VEN treatment, and had no effect on sucrose intake. Conclusions: The synergism between VEN and vHPC–mPFC OGS supports the hypothesis that the antidepressant non-responsiveness of WKY rats results from a failure of antidepressant treatment fully to restore transmission in the vHPC–mPFC pathway.

Analysis of Volcanic Thermohaline Fluctuations of Tagoro Submarine Volcano (El Hierro Island, Canary Islands, Spain)

Temperature and conductivity fluctuations caused by the hydrothermal emissions released during the degasification stage of the Tagoro submarine volcano (Canary Islands, Spain) have been analysed as a robust proxy for characterising and forecasting the activity of the system. A total of 21 conductivity-temperature-depth time series were gathered on a regular high-resolution grid over the main crater of Tagoro volcano. Temperature and conductivity time series, as manifestations of stochastic events, were investigated in terms of variance and analysed by the Generalised Moments Method (GMM). GMM provides the statistical moments, the structure functions of a process whose shape is an indicator of the underlying stochastic mechanisms and the state of activity of the submarine volcano. Our findings confirm an active hydrothermal process in the submarine volcano with a sub-normal behaviour resulting from anti-persistent fluctuations in time. Its hydrothermal emissions are classified as multifractal processes whose structure functions present a crossover between two time scales. In the shorter time scale, findings point to the multiplicative action of two random processes, hydrothermal vents, which carries those fluctuations driving the circulation over the crater, and the overlying aquatic environment. Given that both temperature and conductivity fluctuations are nonstationary, Tagoro submarine volcano can be characterised as an open system exchanging energy to its surroundings.

Vocal correlates of arousal in bottlenose dolphins (Tursiops spp.) in human care

Human-controlled regimes can entrain behavioural responses and may impact animal welfare. Therefore, understanding the influence of schedules on animal behaviour can be a valuable tool to improve welfare, however information on behaviour overnight and in the absence of husbandry staff remains rare. Bottlenose dolphins (Tursiops spp.) are highly social marine mammals and the most common cetacean found in captivity. They communicate using frequency modulated signature whistles, a whistle type that is individually distinctive and used as a contact call. We investigated the vocalisations of ten dolphins housed in three social groups at uShaka Sea World dolphinarium to determine how patterns in acoustic behaviour link to dolphinarium routines. Investigation focused on overnight behaviour, housing decisions, weekly patterns, and transitional periods between the presence and absence of husbandry staff. Recordings were made from 17h00 – 07h00 over 24 nights, spanning May to August 2018. Whistle (including signature whistle) presence and production rate decreased soon after husbandry staff left the facility, was low over night, and increased upon staff arrival. Results indicated elevated arousal states particularly associated with the morning feeding regime. Housing in the pool configuration that allowed observation of staff activities from all social groups was characterised by an increase in whistle presence and rates. Heightened arousal associated with staff presence was reflected in the structural characteristics of signature whistles, particularly maximum frequency, frequency range and number of whistle loops. We identified individual differences in both production rate and the structural modification of signature whistles under different contexts. Overall, these results revealed a link between scheduled activity and associated behavioural responses, which can be used as a baseline for future welfare monitoring where changes from normal behaviour may reflect shifts in welfare state.