Causal connectivity of evolved neural networks during behavior

To show how causal interactions in neural dynamics are modulated by behavior, it is valuable to analyze these interactions without perturbing or lesioning the neural mechanism. This paper proposes a method, based on a graph-theoretic extension of vector autoregressive modeling and 'Granger causality,' for characterizing causal interactions generated within intact neural mechanisms. This method, called 'causal connectivity analysis' is illustrated via model neural networks optimized for controlling target fixation in a simulated head-eye system, in which the structure of the environment can be experimentally varied. Causal connectivity analysis of this model yields novel insights into neural mechanisms underlying sensorimotor coordination. In contrast to networks supporting comparatively simple behavior, networks supporting rich adaptive behavior show a higher density of causal interactions, as well as a stronger causal flow from sensory inputs to motor outputs. They also show different arrangements of 'causal sources' and 'causal sinks': nodes that differentially affect, or are affected by, the remainder of the network. Finally, analysis of causal connectivity can predict the functional consequences of network lesions. These results suggest that causal connectivity analysis may have useful applications in the analysis of neural dynamics

Integrated multiple mediation analysis: A robustness–specificity trade-off in causal structure

Recent methodological developments in causal mediation analysis have addressed several issues regarding multiple mediators. However, these developed methods differ in their definitions of causal parameters, assumptions for identification, and interpretations of causal effects, making it unclear which method ought to be selected when investigating a given causal effect. Thus, in this study, we construct an integrated framework, which unifies all existing methodologies, as a standard for mediation analysis with multiple mediators. To clarify the relationship between existing methods, we propose four strategies for effect decomposition: two-way, partially forward, partially backward, and complete decompositions. This study reveals how the direct and indirect effects of each strategy are explicitly and correctly interpreted as path-specific effects under different causal mediation structures. In the integrated framework, we further verify the utility of the interventional analogues of direct and indirect effects, especially when natural direct and indirect effects cannot be identified or when cross-world exchangeability is invalid. Consequently, this study yields a robustness–specificity trade-off in the choice of strategies. Inverse probability weighting is considered for estimation. The four strategies are further applied to a simulation study for performance evaluation and for analyzing the Risk Evaluation of Viral Load Elevation and Associated Liver Disease/Cancer data set from Taiwan to investigate the causal effect of hepatitis C virus infection on mortality

Big-Data-Driven Materials Science and its FAIR Data Infrastructure

This chapter addresses the forth paradigm of materials research -- big-data driven materials science. Its concepts and state-of-the-art are described, and its challenges and chances are discussed. For furthering the field, Open Data and an all-embracing sharing, an efficient data infrastructure, and the rich ecosystem of computer codes used in the community are of critical importance. For shaping this forth paradigm and contributing to the development or discovery of improved and novel materials, data must be what is now called FAIR -- Findable, Accessible, Interoperable and Re-purposable/Re-usable. This sets the stage for advances of methods from artificial intelligence that operate on large data sets to find trends and patterns that cannot be obtained from individual calculations and not even directly from high-throughput studies. Recent progress is reviewed and demonstrated, and the chapter is concluded by a forward-looking perspective, addressing important not yet solved challenges.Comment: submitted to the Handbook of Materials Modeling (eds. S. Yip and W. Andreoni), Springer 2018/201

Simpson's Paradox, Lord's Paradox, and Suppression Effects are the same phenomenon – the reversal paradox

This article discusses three statistical paradoxes that pervade epidemiological research: Simpson's paradox, Lord's paradox, and suppression. These paradoxes have important implications for the interpretation of evidence from observational studies. This article uses hypothetical scenarios to illustrate how the three paradoxes are different manifestations of one phenomenon – the reversal paradox – depending on whether the outcome and explanatory variables are categorical, continuous or a combination of both; this renders the issues and remedies for any one to be similar for all three. Although the three statistical paradoxes occur in different types of variables, they share the same characteristic: the association between two variables can be reversed, diminished, or enhanced when another variable is statistically controlled for. Understanding the concepts and theory behind these paradoxes provides insights into some controversial or contradictory research findings. These paradoxes show that prior knowledge and underlying causal theory play an important role in the statistical modelling of epidemiological data, where incorrect use of statistical models might produce consistent, replicable, yet erroneous results

Fidelity to a motivational interviewing intervention for those with post-stroke aphasia: A small scale feasibility study

Objective: Depression after stroke is common, and talk-based psychological therapies can be a useful intervention. Whilst a third of stroke survivors will experience communication difficulties impeding participation in talk-based therapies, little guidance exists to guide delivery for those with aphasia. We need to understand how to adapt talk-based therapies in the presence of aphasia. This study aimed to explore the feasibility of motivational interviewing (MI) in people with post-stroke aphasia. Methods: In a small-scale feasibility study, consecutive patients admitted to an acute stroke ward were screened for eligibility. People with moderate to severe aphasia were eligible. Those consenting received an intervention consisting of up to eight MI sessions delivered twice per week over four weeks. Sessions were modified using aids and adaptations for aphasia. Session quality was measured using the Motivational Interviewing Skills Code (MISC) to assess MI fidelity. Results: Three consenting patients identified early post-stroke took part; one male and two females ages ranging between 40s to 80s. Participants attended between five to eight MI sessions over four weeks. Aids and adaptations included visual cues, rating scales and modified reflections incorporating verbal and non-verbal behaviours. Sessions were tailored to individual participant need. Threshold MISC ratings could be achieved for all participants however, ratings were reduced when aids and adaptations were not used. Discussion: This small-scale feasibility study suggests that it is feasible to adapt MI for people with moderate to severe post-stroke aphasia. These findings merit further exploration of adapted MI as an intervention for this patient group. Key words: Stroke; Stroke survivors; Aphasia; Motivational interviewing; Feasibility studies

Immunogenicity of PE18, PE31, and PPE26 proteins from Mycobacterium tuberculosis in humans and mice.

INTRODUCTION: The large family of PE and PPE proteins accounts for as much as 10% of the genome of Mycobacterium tuberculosis. In this study, we explored the immunogenicity of three proteins from this family, PE18, PE31, and PPE26, in humans and mice. METHODS: The investigation involved analyzing the immunoreactivity of the selected proteins using sera from TB patients, IGRA-positive household contacts, and IGRA-negative BCG vaccinated healthy donors from the TB endemic country Mozambique. Antigen-recall responses were examined in PBMC from these groups, including the evaluation of cellular responses in healthy unexposed individuals. Moreover, systemic priming and intranasal boosting with each protein, combined with the Quil-A adjuvant, were conducted in mice. RESULTS: We found that all three proteins are immunoreactive with sera from TB patients, IGRA-positive household contacts, and IGRA-negative BCG vaccinated healthy controls. Likewise, antigen-recall responses were induced in PBMC from all groups, and the proteins stimulated proliferation of peripheral blood mononuclear cells from healthy unexposed individuals. In mice, all three antigens induced IgG antibody responses in sera and predominantly IgG, rather than IgA, responses in bronchoalveolar lavage. Additionally, CD4+ and CD8+ effector memory T cell responses were observed in the spleen, with PE18 demonstrating the ability to induce tissue-resident memory T cells in the lungs. DISCUSSION: Having demonstrated immunogenicity in both humans and mice, the protective capacity of these antigens was evaluated by challenging immunized mice with low-dose aerosol of Mycobacterium tuberculosis H37Rv. The in vitro Mycobacterial Growth Inhibition Assay (MGIA) and assessment of viable bacteria in the lung did not demonstrate any ability of the vaccination protocol to reduce bacterial growth. We therefore concluded that these three specific PE/PPE proteins, while immunogenic in both humans and mice, were unable to confer protective immunity under these conditions

Financial considerations in the conduct of multi-centre randomised controlled trials: evidence from a qualitative study.

National Coordinating Centre for Research Methodology; Medical Research Council, UK Department of Health; Chief Scientist OfficeNot peer reviewedPublisher PD

Emergence of Variability in Isogenic Escherichia coli Populations Infected by a Filamentous Virus

The spread of epidemics not only depends on the average number of parasites produced per host, but also on the existence of highly infectious individuals. It is widely accepted that infectiousness depends on genetic and environmental determinants. However, even in clonal populations of host and viruses growing in homogeneous conditions, high variability can exist. Here we show that Escherichia coli cells commonly display high differentials in viral burst size, and address the kinetics of emergence of such variability with the non-lytic filamentous virus M13. By single-cell imaging of a virally-encoded fluorescent reporter, we monitor the viral charge distribution in infected bacterial populations at different time following infection. A mathematical model assuming autocatalytic virus replication and inheritance of bacterial growth rates quantitatively reproduces the experimental distributions, demonstrating that deterministic amplification of small host inhomogeneities is a mechanism sufficient to explain large and highly skewed distributions. This mechanism of amplification is general and may occur whenever a parasite has an initial phase of exponential growth within its host. Moreover, it naturally reproduces the shift towards higher virulence when the host is experimenting poor conditions, as observed commonly in host-parasite systems

A Predictive Model of Intein Insertion Site for Use in the Engineering of Molecular Switches

Inteins are intervening protein domains with self-splicing ability that can be used as molecular switches to control activity of their host protein. Successfully engineering an intein into a host protein requires identifying an insertion site that permits intein insertion and splicing while allowing for proper folding of the mature protein post-splicing. By analyzing sequence and structure based properties of native intein insertion sites we have identified four features that showed significant correlation with the location of the intein insertion sites, and therefore may be useful in predicting insertion sites in other proteins that provide native-like intein function. Three of these properties, the distance to the active site and dimer interface site, the SVM score of the splice site cassette, and the sequence conservation of the site showed statistically significant correlation and strong predictive power, with area under the curve (AUC) values of 0.79, 0.76, and 0.73 respectively, while the distance to secondary structure/loop junction showed significance but with less predictive power (AUC of 0.54). In a case study of 20 insertion sites in the XynB xylanase, two features of native insertion sites showed correlation with the splice sites and demonstrated predictive value in selecting non-native splice sites. Structural modeling of intein insertions at two sites highlighted the role that the insertion site location could play on the ability of the intein to modulate activity of the host protein. These findings can be used to enrich the selection of insertion sites capable of supporting intein splicing and hosting an intein switch

DNA repair, genome stability and cancer: a historical perspective

The multistep process of cancer progresses over many years. The prevention of mutations by DNA repair pathways led to an early appreciation of a role for repair in cancer avoidance. However, the broader role of the DNA damage response (DDR) emerged more slowly. In this Timeline article, we reflect on how our understanding of the steps leading to cancer developed, focusing on the role of the DDR. We also consider how our current knowledge can be exploited for cancer therapy