Synthetic metabolism: metabolic engineering meets enzyme design.

Metabolic engineering aims at modifying the endogenous metabolic network of an organism to harness it for a useful biotechnological task, for example, production of a value-added compound. Several levels of metabolic engineering can be defined and are the topic of this review. Basic 'copy, paste and fine-tuning' approaches are limited to the structure of naturally existing pathways. 'Mix and match' approaches freely recombine the repertoire of existing enzymes to create synthetic metabolic networks that are able to outcompete naturally evolved pathways or redirect flux toward non-natural products. The space of possible metabolic solution can be further increased through approaches including 'new enzyme reactions', which are engineered on the basis of known enzyme mechanisms. Finally, by considering completely 'novel enzyme chemistries' with de novo enzyme design, the limits of nature can be breached to derive the most advanced form of synthetic pathways. We discuss the challenges and promises associated with these different metabolic engineering approaches and illuminate how enzyme engineering is expected to take a prime role in synthetic metabolic engineering for biotechnology, chemical industry and agriculture of the future

Characterization of complex networks: A survey of measurements

Each complex network (or class of networks) presents specific topological features which characterize its connectivity and highly influence the dynamics of processes executed on the network. The analysis, discrimination, and synthesis of complex networks therefore rely on the use of measurements capable of expressing the most relevant topological features. This article presents a survey of such measurements. It includes general considerations about complex network characterization, a brief review of the principal models, and the presentation of the main existing measurements. Important related issues covered in this work comprise the representation of the evolution of complex networks in terms of trajectories in several measurement spaces, the analysis of the correlations between some of the most traditional measurements, perturbation analysis, as well as the use of multivariate statistics for feature selection and network classification. Depending on the network and the analysis task one has in mind, a specific set of features may be chosen. It is hoped that the present survey will help the proper application and interpretation of measurements.Comment: A working manuscript with 78 pages, 32 figures. Suggestions of measurements for inclusion are welcomed by the author

Sensors for Cure Monitoring of Composite Materials

Monitoring and control of the integrity and properties of materials at all stages of structural life, from cradle to retirement, is a growing NDE field. A typical system consists of a sensor, data acquisition, processing and control setup with a host personal computer. For composites, the stage of cure is the only time when an adequate actuation can easily affect the cause of unacceptable characteristics or possibly eliminate the formation of defects. Real-time monitoring of the cure process of plastic-reinforced composites can prevent overbleeding, minimize trapped volatiles, alert of vacuum leak, indicate cure rate and optimize the material properties. For many years, the process of curing composites has been an empirical science and has evolved through a trial-and-error approach. In recent years, significant progress has been made towards understanding the process as a result of data accumulation and progress in mathematical modelling of the composite cure process. Computer science is increasingly applied to support the process analysis using artificial intelligence and knowledge base systems

Early invaders - Farmers, the granary weevil and other uninvited guests in the Neolithic

The Neolithic and the spread of agriculture saw several introductions of insect species associated with the environments and activities of the first farmers. Fossil insect research from the Neolithic lake settlement of Dispilio in Macedonia, northern Greece, provides evidence for the early European introduction of a flightless weevil, the granary weevil, Sitophilus granarius, which has since become cosmopolitan and one of the most important pests of stored cereals. The records of the granary weevil from the Middle Neolithic in northern Greece illuminate the significance of surplus storage for the spread of agriculture. The granary weevil and the house fly, Musca domestica were also introduced in the Neolithic of central Europe, with the expansion of Linear Band Keramik (LBK) culture groups. This paper reviews Neolithic insect introductions in Europe, including storage pests, discusses their distribution during different periods and the reasons behind the trends observed. Storage farming may be differentiated from pastoral farming on the basis of insect introductions arriving with incoming agricultural groups

Impact of the provision of safe drinking water on school absence rates in Cambodia:a quasi-experimental study

Education is one of the most important drivers behind helping people in developing countries lift themselves out of poverty. However, even when schooling is available absenteeism rates can be high. Recently interest has focussed on whether or not WASH interventions can help reduce absenteeism in developing countries. However, none has focused exclusively on the role of drinking water provision. We report a study of the association between absenteeism and provision of treated water in containers into schools

Valence-Specific Modulation in the Accumulation of Perceptual Evidence Prior to Visual Scene Recognition

Visual scene recognition is a dynamic process through which incoming sensory information is iteratively compared with predictions regarding the most likely identity of the input stimulus. In this study, we used a novel progressive unfolding task to characterize the accumulation of perceptual evidence prior to scene recognition, and its potential modulation by the emotional valence of these scenes. Our results show that emotional (pleasant and unpleasant) scenes led to slower accumulation of evidence compared to neutral scenes. In addition, when controlling for the potential contribution of non-emotional factors (i.e., familiarity and complexity of the pictures), our results confirm a reliable shift in the accumulation of evidence for pleasant relative to neutral and unpleasant scenes, suggesting a valence-specific effect. These findings indicate that proactive iterations between sensory processing and top-down predictions during scene recognition are reliably influenced by the rapidly extracted (positive) emotional valence of the visual stimuli. We interpret these findings in accordance with the notion of a genuine positivity offset during emotional scene recognition

A Bayesian Approach to Analyse Genetic Variation within RNA Viral Populations

The development of modern and affordable sequencing technologies has allowed the study of viral populations to an unprecedented depth. This is of particular interest for the study of within-host RNA viral populations, where variation due to error-prone polymerases can lead to immune escape, antiviral resistance and adaptation to new host species. Methods to sequence RNA virus genomes include reverse transcription (RT) and polymerase chain reaction (PCR). RT-PCR is a molecular biology technique widely used to amplify DNA from an RNA template. The method itself relies on the in vitro synthesis of copy DNA from RNA followed by multiple cycles of DNA amplification. However, this method introduces artefactual errors that can act as confounding factors when the sequence data are analysed. Although there are a growing number of published studies exploring the intra- and inter-host evolutionary dynamics of RNA viruses, the complexity of the methods used to generate sequences makes it difficult to produce probabilistic statements about the likely sources of observed sequence variants. This complexity is further compounded as both the depth of sequencing and the length of the genome segment of interest increase. Here we develop a Bayesian method to characterise and differentiate between likely structures for the background viral population. This approach can then be used to identify nucleotide sites that show evidence of change in the within-host viral population structure, either over time or relative to a reference sequence (e.g. an inoculum or another source of infection), or both, without having to build complex evolutionary models. Identification of these sites can help to inform the design of more focussed experiments using molecular biology tools, such as site-directed mutagenesis, to assess the function of specific amino acids. We illustrate the method by applying to datasets from experimental transmission of equine influenza, and a pre-clinical vaccine trial for HIV-1

First Impressions of HIV Risk: It Takes Only Milliseconds to Scan a Stranger

Research indicates that many people do not use condoms consistently but instead rely on intuition to identify sexual partners high at risk for HIV infection. The present studies examined neural correlates for first impressions of HIV risk and determined the association of perceived HIV risk with other trait characteristics. Participants were presented with 120 self-portraits retrieved from a popular online photo-sharing community (www.flickr.com). Factor analysis of various explicit ratings of trait characteristics yielded two orthogonal factors: (1) a ‘valence-approach’ factor encompassing perceived attractiveness, healthiness, valence, and approach tendencies, and (2) a ‘safeness’ factor, entailing judgments of HIV risk, trustworthiness, and responsibility. These findings suggest that HIV risk ratings systematically relate to cardinal features of a high-risk HIV stereotype. Furthermore, event-related brain potential recordings revealed neural correlates of first impressions about HIV risk. Target persons perceived as risky elicited a differential brain response in a time window from 220–340 ms and an increased late positive potential in a time window from 350–700 ms compared to those perceived as safe. These data suggest that impressions about HIV risk can be formed in a split second and despite a lack of information about the actual risk profile. Findings of neural correlates of risk impressions and their relationship to key features of the HIV risk stereotype are discussed in the context of the ‘risk as feelings’ theory

The Generation of Promoter-Mediated Transcriptional Noise in Bacteria

Noise in the expression of a gene produces fluctuations in the concentration of the gene product. These fluctuations can interfere with optimal function or can be exploited to generate beneficial diversity between cells; gene expression noise is therefore expected to be subject to evolutionary pressure. Shifts between modes of high and low rates of transcription initiation at a promoter appear to contribute to this noise both in eukaryotes and prokaryotes. However, models invoked for eukaryotic promoter noise such as stable activation scaffolds or persistent nucleosome alterations seem unlikely to apply to prokaryotic promoters. We consider the relative importance of the steps required for transcription initiation. The 3-step transcription initiation model of McClure is extended into a mathematical model that can be used to predict consequences of additional promoter properties. We show in principle that the transcriptional bursting observed at an E. coli promoter by Golding et al. (2005) can be explained by stimulation of initiation by the negative supercoiling behind a transcribing RNA polymerase (RNAP) or by the formation of moribund or dead-end RNAP-promoter complexes. Both mechanisms are tunable by the alteration of promoter kinetics and therefore allow the optimization of promoter mediated noise.Comment: 4 figures, 1 table. Supplemental materials are also include