Predicting climate change using response theory: global averages and spatial patterns

The provision of accurate methods for predicting the climate response to anthropogenic and natural forcings is a key contemporary scientific challenge. Using a simplified and efficient open-source general circulation model of the atmosphere featuring O(105105) degrees of freedom, we show how it is possible to approach such a problem using nonequilibrium statistical mechanics. Response theory allows one to practically compute the time-dependent measure supported on the pullback attractor of the climate system, whose dynamics is non-autonomous as a result of time-dependent forcings. We propose a simple yet efficient method for predicting—at any lead time and in an ensemble sense—the change in climate properties resulting from increase in the concentration of CO22 using test perturbation model runs. We assess strengths and limitations of the response theory in predicting the changes in the globally averaged values of surface temperature and of the yearly total precipitation, as well as in their spatial patterns. The quality of the predictions obtained for the surface temperature fields is rather good, while in the case of precipitation a good skill is observed only for the global average. We also show how it is possible to define accurately concepts like the inertia of the climate system or to predict when climate change is detectable given a scenario of forcing. Our analysis can be extended for dealing with more complex portfolios of forcings and can be adapted to treat, in principle, any climate observable. Our conclusion is that climate change is indeed a problem that can be effectively seen through a statistical mechanical lens, and that there is great potential for optimizing the current coordinated modelling exercises run for the preparation of the subsequent reports of the Intergovernmental Panel for Climate Change

A Minimum of Three Motifs Is Essential for Optimal Binding of Pseudomurein Cell Wall-Binding Domain of Methanothermobacter thermautotrophicus

We have biochemically and functionally characterized the pseudomurein cell wall-binding (PMB) domain that is present at the C-terminus of the Surface (S)-layer protein MTH719 from Methanothermobacter thermautotrophicus. Chemical denaturation of the protein with guanidinium hydrochloride occurred at 3.8 M. A PMB-GFP fusion protein not only binds to intact pseudomurein of methanogenic archaea, but also to spheroplasts of lysozyme-treated bacterial cells. This binding is pH dependent. At least two of the three motifs that are present in the domain are necessary for binding. Limited proteolysis revealed a possible cleavage site in the spacing sequence between motifs 1 and 2 of the PMB domain, indicating that the motif region itself is protected from proteases

A single-blind randomised controlled trial of the effects of a web-based decision aid on self-testing for cholesterol and diabetes. study protocol

Background: Self-tests, tests on body materials to detect medical conditions, are widely available to the general public. Self-testing does have advantages as well as disadvantages, and the debate on whether self-testing should be encouraged or rather discouraged is still ongoing. One of the concerns is whether consumers have sufficient knowledge to perform the test and interpret the results. An online decision aid (DA) with information on self-testing in general, and test specific information on cholesterol and diabetes self-testing was developed. The DA aims to provide objective information on these self-tests as well as a decision support tool to weigh the pros and cons of self-testing. The aim of this study is to evaluate the effect of the online decision aid on knowledge on self-testing, informed choice, ambivalence and psychosocial determinants. Methods/Design: A single blind randomised controlled trial in which the online decision aid 'zelftestwijzer' is compared to short, non-interactive information on self-testing in general. The entire trial will be conducted online. Participants will be selected from an existing Internet panel. Consumers who are considering doing a cholesterol or diabetes self-test in the future will be included. Outcome measures will be assessed directly after participants have viewed either the DA or the control condition. Weblog files will be used to record participants' use of the decision aid. Discussion: Self-testing does have important pros and cons, and it is important that consumers base their decision whether they want to do a self-test or not on knowledge and personal values. This study is the first to evaluate the effect of an online decision aid for self-testing

A Computational Framework Discovers New Copy Number Variants with Functional Importance

Structural variants which cause changes in copy numbers constitute an important component of genomic variability. They account for 0.7% of genomic differences in two individual genomes, of which copy number variants (CNVs) are the largest component. A recent population-based CNV study revealed the need of better characterization of CNVs, especially the small ones (<500 bp).We propose a three step computational framework (Identification of germline Changes in Copy Number or IgC2N) to discover and genotype germline CNVs. First, we detect candidate CNV loci by combining information across multiple samples without imposing restrictions to the number of coverage markers or to the variant size. Secondly, we fine tune the detection of rare variants and infer the putative copy number classes for each locus. Last, for each variant we combine the relative distance between consecutive copy number classes with genetic information in a novel attempt to estimate the reference model bias. This computational approach is applied to genome-wide data from 1250 HapMap individuals. Novel variants were discovered and characterized in terms of size, minor allele frequency, type of polymorphism (gains, losses or both), and mechanism of formation. Using data generated for a subset of individuals by a 42 million marker platform, we validated the majority of the variants with the highest validation rate (66.7%) was for variants of size larger than 1 kb. Finally, we queried transcriptomic data from 129 individuals determined by RNA-sequencing as further validation and to assess the functional role of the new variants. We investigated the possible enrichment for variant's regulatory effect and found that smaller variants (<1 Kb) are more likely to regulate gene transcript than larger variants (p-value = 2.04e-08). Our results support the validity of the computational framework to detect novel variants relevant to disease susceptibility studies and provide evidence of the importance of genetic variants in regulatory network studies

Effectiveness of the universal prevention program 'Healthy School and Drugs': Study protocol of a randomized clustered trial

Contains fulltext : 90260.pdf (publisher's version ) (Open Access)Background: Substance use is highly prevalent among Dutch adolescents. The Healthy School and Drugs program is a nationally implemented school-based prevention program aimed at reducing early and excessive substance use among adolescents. Although the program's effectiveness was tested in a quasi-experimental design before, many program changes were made afterwards. The present study, therefore, aims to test the effects of this widely used, renewed universal prevention program. Methods/Design: A randomized clustered trial will be conducted among 3,784 adolescents of 23 secondary schools in The Netherlands. The trial has three conditions; two intervention conditions (i.e., e-learning and integral) and a control condition. The e-learning condition consists of three digital learning modules (i.e., about alcohol, tobacco, and marijuana) that are sequentially offered over the course of three school years (i.e., grade 1, grade 2, and grade 3). The integral condition consists of parental participation in a parental meeting on substance use, regulation of substance use, and monitoring and counseling of students' substance use at school, over and above the three digital modules. The control condition is characterized as business as usual. Participating schools were randomly assigned to either an intervention or control condition. Participants filled out a digital questionnaire at baseline and will fill out the same questionnaire three more times at follow-up measurements (8, 20, and 32 months after baseline). Outcome variables included in the questionnaire are the percentage of binge drinking (more than five drinks per occasion), the average weekly number of drinks, and the percentage of adolescents who ever drunk a glass of alcohol and the percentage of adolescents who ever smoked a cigarette or a joint respectively for tobacco and marijuana. Discussion: This study protocol describes the design of a randomized clustered trial that evaluates the effectiveness of a school-based prevention program. We expect that significantly fewer adolescents will engage in early or excessive substance use behaviors in the intervention conditions compared to the control condition as a direct result of the intervention. We expect that the integral condition will yield most positive results, compared with the e-learning condition and control condition.10 p

Understanding Communication Signals during Mycobacterial Latency through Predicted Genome-Wide Protein Interactions and Boolean Modeling

About 90% of the people infected with Mycobacterium tuberculosis carry latent bacteria that are believed to get activated upon immune suppression. One of the fundamental challenges in the control of tuberculosis is therefore to understand molecular mechanisms involved in the onset of latency and/or reactivation. We have attempted to address this problem at the systems level by a combination of predicted functional protein∶protein interactions, integration of functional interactions with large scale gene expression studies, predicted transcription regulatory network and finally simulations with a Boolean model of the network. Initially a prediction for genome-wide protein functional linkages was obtained based on genome-context methods using a Support Vector Machine. This set of protein functional linkages along with gene expression data of the available models of latency was employed to identify proteins involved in mediating switch signals during dormancy. We show that genes that are up and down regulated during dormancy are not only coordinately regulated under dormancy-like conditions but also under a variety of other experimental conditions. Their synchronized regulation indicates that they form a tightly regulated gene cluster and might form a latency-regulon. Conservation of these genes across bacterial species suggests a unique evolutionary history that might be associated with M. tuberculosis dormancy. Finally, simulations with a Boolean model based on the regulatory network with logical relationships derived from gene expression data reveals a bistable switch suggesting alternating latent and actively growing states. Our analysis based on the interaction network therefore reveals a potential model of M. tuberculosis latency

Controlled membrane translocation provides a mechanism for signal transduction and amplification.

Transmission and amplification of chemical signals across lipid bilayer membranes is of profound significance in many biological processes, from the development of multicellular organisms to information processing in the nervous system. In biology, membrane-spanning proteins are responsible for the transmission of chemical signals across membranes, and signal transduction is often associated with an amplified signalling cascade. The ability to reproduce such processes in artificial systems has potential applications in sensing, controlled drug delivery and communication between compartments in tissue-like constructs of synthetic vesicles. Here we describe a mechanism for transmitting a chemical signal across a membrane based on the controlled translocation of a synthetic molecular transducer from one side of a lipid bilayer membrane to the other. The controlled molecular motion has been coupled to the activation of a catalyst on the inside of a vesicle, which leads to a signal-amplification process analogous to the biological counterpart.We thank the University of Cambridge Oppenheimer Fund for an Early Career Research Fellowship (M.J.L); the Wiener-Anspach Foundation (FWA) for postdoctoral fellowship (FK) ; and Franziska Kundel and David Klenerman for TIRFM imaging experiments

Neuronal Chemokines: Versatile Messengers In Central Nervous System Cell Interaction

Whereas chemokines are well known for their ability to induce cell migration, only recently it became evident that chemokines also control a variety of other cell functions and are versatile messengers in the interaction between a diversity of cell types. In the central nervous system (CNS), chemokines are generally found under both physiological and pathological conditions. Whereas many reports describe chemokine expression in astrocytes and microglia and their role in the migration of leukocytes into the CNS, only few studies describe chemokine expression in neurons. Nevertheless, the expression of neuronal chemokines and the corresponding chemokine receptors in CNS cells under physiological and pathological conditions indicates that neuronal chemokines contribute to CNS cell interaction. In this study, we review recent studies describing neuronal chemokine expression and discuss potential roles of neuronal chemokines in neuron–astrocyte, neuron–microglia, and neuron–neuron interaction