Frontoparietal representations of task context support the flexible control of goal-directed cognition.

Cognitive control allows stimulus-response processing to be aligned with internal goals and is thus central to intelligent, purposeful behavior. Control is thought to depend in part on the active representation of task information in prefrontal cortex (PFC), which provides a source of contextual bias on perception, decision making, and action. In the present study, we investigated the organization, influences, and consequences of context representation as human subjects performed a cued sorting task that required them to flexibly judge the relationship between pairs of multivalent stimuli. Using a connectivity-based parcellation of PFC and multivariate decoding analyses, we determined that context is specifically and transiently represented in a region spanning the inferior frontal sulcus during context-dependent decision making. We also found strong evidence that decision context is represented within the intraparietal sulcus, an area previously shown to be functionally networked with the inferior frontal sulcus at rest and during task performance. Rule-guided allocation of attention to different stimulus dimensions produced discriminable patterns of activation in visual cortex, providing a signature of top-down bias over perception. Furthermore, demands on cognitive control arising from the task structure modulated context representation, which was found to be strongest after a shift in task rules. When context representation in frontoparietal areas increased in strength, as measured by the discriminability of high-dimensional activation patterns, the bias on attended stimulus features was enhanced. These results provide novel evidence that illuminates the mechanisms by which humans flexibly guide behavior in complex environments

Primate modularity and evolution: first anatomical network analysis of primate head and neck musculoskeletal system

Network theory is increasingly being used to study morphological modularity and integration. Anatomical network analysis (AnNA) is a framework for quantitatively characterizing the topological organization of anatomical structures and providing an operational way to compare structural integration and modularity. Here we apply AnNA for the first time to study the macroevolution of the musculoskeletal system of the head and neck in primates and their closest living relatives, paying special attention to the evolution of structures associated with facial and vocal communication. We show that well-defined left and right facial modules are plesiomorphic for primates, while anthropoids consistently have asymmetrical facial modules that include structures of both sides, a change likely related to the ability to display more complex, asymmetrical facial expressions. However, no clear trends in network organization were found regarding the evolution of structures related to speech. Remarkably, the increase in the number of head and neck muscles – and thus of musculoskeletal structures – in human evolution led to a decrease in network density and complexity in humans

Social representations of HIV/AIDS in five Central European and Eastern European countries: A multidimensional analysis

Cognitive processing models of risky sexual behaviour have proliferated in the two decades since the first reporting of HIV/AIDS, but far less attention has been paid to individual and group representations of the epidemic and the relationship between these representations and reported sexual behaviours. In this study, 494 business people and medics from Estonia, Georgia, Hungary, Poland and Russia sorted free associations around HIV/AIDS in a matrix completion task. Exploratory factor and multidimensional scaling analyses revealed two main dimensions (labelled ‘Sex’ and ‘Deadly disease’), with significant cultural and gender variations along both dimension scores. Possible explanations for these results are discussed in the light of growing concerns over the spread of the epidemic in this region

Iron oxidation at low temperature (260–500 C) in air and the effect of water vapor

The oxidation of iron has been studied at low temperatures (between 260 and 500 C) in dry air or air with 2 vol% H2O, in the framework of research on dry corrosion of nuclear waste containers during long-term interim storage. Pure iron is regarded as a model material for low-alloyed steel. Oxidation tests were performed in a thermobalance (up to 250 h) or in a laboratory furnace (up to 1000 h). The oxide scales formed were characterized using SEM-EDX, TEM, XRD, SIMS and EBSD techniques. The parabolic rate constants deduced from microbalance experiments were found to be in good agreement with the few existing values of the literature. The presence of water vapor in air was found to strongly influence the transitory stages of the kinetics. The entire structure of the oxide scale was composed of an internal duplex magnetite scale made of columnar grains and an external hematite scale made of equiaxed grains. 18O tracer experiments performed at 400 C allowed to propose a growth mechanism of the scale

Evolution of Robustness to Noise and Mutation in Gene Expression Dynamics

Phenotype of biological systems needs to be robust against mutation in order to sustain themselves between generations. On the other hand, phenotype of an individual also needs to be robust against fluctuations of both internal and external origins that are encountered during growth and development. Is there a relationship between these two types of robustness, one during a single generation and the other during evolution? Could stochasticity in gene expression have any relevance to the evolution of these robustness? Robustness can be defined by the sharpness of the distribution of phenotype; the variance of phenotype distribution due to genetic variation gives a measure of `genetic robustness' while that of isogenic individuals gives a measure of `developmental robustness'. Through simulations of a simple stochastic gene expression network that undergoes mutation and selection, we show that in order for the network to acquire both types of robustness, the phenotypic variance induced by mutations must be smaller than that observed in an isogenic population. As the latter originates from noise in gene expression, this signifies that the genetic robustness evolves only when the noise strength in gene expression is larger than some threshold. In such a case, the two variances decrease throughout the evolutionary time course, indicating increase in robustness. The results reveal how noise that cells encounter during growth and development shapes networks' robustness to stochasticity in gene expression, which in turn shapes networks' robustness to mutation. The condition for evolution of robustness as well as relationship between genetic and developmental robustness is derived through the variance of phenotypic fluctuations, which are measurable experimentally.Comment: 25 page

Anatomical Network Comparison of Human Upper and Lower, Newborn and Adult, and Normal and Abnormal Limbs, with Notes on Development, Pathology and Limb Serial Homology vs. Homoplasy

How do the various anatomical parts (modules) of the animal body evolve into very different integrated forms (integration) yet still function properly without decreasing the individual's survival? This long-standing question remains unanswered for multiple reasons, including lack of consensus about conceptual definitions and approaches, as well as a reasonable bias toward the study of hard tissues over soft tissues. A major difficulty concerns the non-trivial technical hurdles of addressing this problem, specifically the lack of quantitative tools to quantify and compare variation across multiple disparate anatomical parts and tissue types. In this paper we apply for the first time a powerful new quantitative tool, Anatomical Network Analysis (AnNA), to examine and compare in detail the musculoskeletal modularity and integration of normal and abnormal human upper and lower limbs. In contrast to other morphological methods, the strength of AnNA is that it allows efficient and direct empirical comparisons among body parts with even vastly different architectures (e.g. upper and lower limbs) and diverse or complex tissue composition (e.g. bones, cartilages and muscles), by quantifying the spatial organization of these parts-their topological patterns relative to each other-using tools borrowed from network theory. Our results reveal similarities between the skeletal networks of the normal newborn/adult upper limb vs. lower limb, with exception to the shoulder vs. pelvis. However, when muscles are included, the overall musculoskeletal network organization of the upper limb is strikingly different from that of the lower limb, particularly that of the more proximal structures of each limb. Importantly, the obtained data provide further evidence to be added to the vast amount of paleontological, gross anatomical, developmental, molecular and embryological data recently obtained that contradicts the long-standing dogma that the upper and lower limbs are serial homologues. In addition, the AnNA of the limbs of a trisomy 18 human fetus strongly supports Pere Alberch's ill-named "logic of monsters" hypothesis, and contradicts the commonly accepted idea that birth defects often lead to lower integration (i.e. more parcellation) of anatomical structures

Evolutionary connectionism: algorithmic principles underlying the evolution of biological organisation in evo-devo, evo-eco and evolutionary transitions

The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term “evolutionary connectionism” to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions

Multi-level suppression of receptor-PI3K-mTORC1 by fatty acid synthase inhibitors is crucial for their efficacy against ovarian cancer cells

Receptor-PI3K-mTORC1 signaling and fatty acid synthase (FASN)-regulated lipid biosynthesis harbor numerous drug targets and are molecularly connected. We hypothesize that unraveling the mechanisms of pathway cross-talk will be useful for designing novel co-targeting strategies for ovarian cancer (OC). The impact of receptor-PI3K-mTORC1 onto FASN is already well-characterized. However, reverse actions–from FASN towards receptor-PI3K-mTORC1–are still elusive. We show that FASN-blockade impairs receptor-PI3K-mTORC1 signaling at multiple levels. Thin-layer chromatography and MALDI-MS/MS reveals that FASN-inhibitors (C75, G28UCM) augment polyunsaturated fatty acids and diminish signaling lipids diacylglycerol (DAG) and phosphatidylinositol 3,4,5-trisphosphate (PIP3) in OC cells (SKOV3, OVCAR-3, A2780, HOC-7). Western blotting and micropatterning demonstrate that FASN-blockers impair phosphorylation/expression of EGF-receptor/ERBB/HER and decrease GRB2–EGF-receptor recruitment leading to PI3K-AKT suppression. FASN-inhibitors activate stress response-genes HIF-1α-REDD1 (RTP801/DIG2/DDIT4) and AMPKα causing mTORC1- and S6-repression. We conclude that FASN-inhibitor-mediated blockade of receptor-PI3K-mTORC1 occurs due to a number of distinct but cooperating processes. Moreover, decrease of PI3K-mTORC1 abolishes cross-repression of MEK-ERK causing ERK activation. Consequently, the MEK-inhibitor selumetinib/AZD6244, in contrast to the PI3K/mTOR-inhibitor dactolisib/NVP-BEZ235, increases growth inhibition when given together with a FASN-blocker. We are the first to provide deep insight on how FASN-inhibition blocks ERBB-PI3K-mTORC1 activity at multiple molecular levels. Moreover, our data encourage therapeutic approaches using FASN-antagonists together with MEK-ERK-inhibitors

Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems

A generic mechanism - networked buffering - is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems. \ud \u

Proteomics: in pursuit of effective traumatic brain injury therapeutics

Effective traumatic brain injury (TBI) therapeutics remain stubbornly elusive. Efforts in the field have been challenged by the heterogeneity of clinical TBI, with greater complexity among underlying molecular phenotypes than initially conceived. Future research must confront the multitude of factors comprising this heterogeneity, representing a big data challenge befitting the coming informatics age. Proteomics is poised to serve a central role in prescriptive therapeutic development, as it offers an efficient endpoint within which to assess post-TBI biochemistry. We examine rationale for multifactor TBI proteomic studies and the particular importance of temporal profiling in defining biochemical sequences and guiding therapeutic development. Lastly, we offer perspective on repurposing biofluid proteomics to develop theragnostic assays with which to prescribe, monitor and assess pharmaceutics for improved translation and outcome for TBI patients