An antiviral factor fromMelia azedarach L. prevents Tacaribe virus encephalitis in mice

Summary Treatment of neonatal mice with an antiviral factor, (AVF), obtained from the leaves ofMelia azederach L. protected them against lethal encephalitis caused by Tacaribe virus inoculation. The degree of protection obtained varied from 66% to 100% depending on the virus dose. Similarly, administration of AVF to nursing mothers protected their offspring from developing virus encephalitis. AVF does not directly inactivate Tacaribe virus; it inhibits an early step (s) in the replication process in cell cultures.Dedicated to Prof. Luis Leloir on his 80th birthday.Acknowledgment. This study was supported by Grant 9353/84 from the Consejo Nacional de Investigaciones Cientificas y Técnicas (CONICET), Argentina.     

Structural basis for translation termination on the 70S ribosome

At termination of protein synthesis, type I release factors promote hydrolysis of the peptidyl-transfer RNA linkage in response to recognition of a stop codon. Here we describe the crystal structure of the Thermus thermophilus 70S ribosome in complex with the release factor RF1, tRNA and a messenger RNA containing a UAA stop codon, at 3.2 A resolution. The stop codon is recognized in a pocket formed by conserved elements of RF1, including its PxT recognition motif, and 16S ribosomal RNA. The codon and the 30S subunit A site undergo an induced fit that results in stabilization of a conformation of RF1 that promotes its interaction with the peptidyl transferase centre. Unexpectedly, the main-chain amide group of Gln 230 in the universally conserved GGQ motif of the factor is positioned to contribute directly to peptidyl-tRNA hydrolysis.     

A variant associated with nicotine dependence, lung cancer and peripheral arterial disease

Smoking is a leading cause of preventable death, causing about 5 million premature deaths worldwide each year. Evidence for genetic influence on smoking behaviour and nicotine dependence (ND) has prompted a search for susceptibility genes. Furthermore, assessing the impact of sequence variants on smoking-related diseases is important to public health. Smoking is the major risk factor for lung cancer (LC) and is one of the main risk factors for peripheral arterial disease (PAD). Here we identify a common variant in the nicotinic acetylcholine receptor gene cluster on chromosome 15q24 with an effect on smoking quantity, ND and the risk of two smoking-related diseases in populations of European descent. The variant has an effect on the number of cigarettes smoked per day in our sample of smokers. The same variant was associated with ND in a previous genome-wide association study that used low-quantity smokers as controls, and with a similar approach we observe a highly significant association with ND. A comparison of cases of LC and PAD with population controls each showed that the variant confers risk of LC and PAD. The findings provide a case study of a gene-environment interaction, highlighting the role of nicotine addiction in the pathology of other serious diseases.     

Synergistic response to oncogenic mutations defines gene class critical to cancer phenotype

Understanding the molecular underpinnings of cancer is of critical importance to the development of targeted intervention strategies. Identification of such targets, however, is notoriously difficult and unpredictable. Malignant cell transformation requires the cooperation of a few oncogenic mutations that cause substantial reorganization of many cell features and induce complex changes in gene expression patterns. Genes critical to this multifaceted cellular phenotype have therefore only been identified after signalling pathway analysis or on an ad hoc basis. Our observations that cell transformation by cooperating oncogenic lesions depends on synergistic modulation of downstream signalling circuitry suggest that malignant transformation is a highly cooperative process, involving synergy at multiple levels of regulation, including gene expression. Here we show that a large proportion of genes controlled synergistically by loss-of-function p53 and Ras activation are critical to the malignant state of murine and human colon cells. Notably, 14 out of 24 'cooperation response genes' were found to contribute to tumour formation in gene perturbation experiments. In contrast, only 1 in 14 perturbations of the genes responding in a non-synergistic manner had a similar effect. Synergistic control of gene expression by oncogenic mutations thus emerges as an underlying key to malignancy, and provides an attractive rationale for identifying intervention targets in gene networks downstream of oncogenic gain- and loss-of-function mutations.     

Risk factor beta conditional value‐at‐risk

We propose a new approach to the estimation of the portfolio Value‐at‐Risk. Based on the assumption that the same macroeconomic factors affect returns of all assets in a portfolio, this methodology allows the generation of the sequence of hypothetical future equilibrium portfolio returns given the historical values of the underlying macroeconomic factors and the asset betas with respect to these factors. Value‐at‐Risk is then found as an appropriate percentile of the corresponding hypothetical distribution of the portfolio profits and losses. The backtesting results for the six Fama–French benchmark portfolios and the S&P500 index show that this approach yields reasonably accurate estimates of the portfolio Value‐at‐Risk. Copyright © 2008 John Wiley & Sons, Ltd.     

Supercompiler Scp4: Use of quasi-distributive laws in program transformation

The author constructed a transformer Scp4 of functional programs. The transformer uses the technology known as Turchin’s supercompilation. Scp4 was implemented in a functional language Refal-5. The input language for Scp4 is also Refal-5. In the present paper we give an outline of the supercompilar and consider a number of tools of the transformer in details. The tools can be formally thought of as quasi-distributive laws.     

Adaptive filtering enhances information transmission in visual cortex

Sensory neuroscience seeks to understand how the brain encodes natural environments. However, neural coding has largely been studied using simplified stimuli. In order to assess whether the brain's coding strategy depends on the stimulus ensemble, we apply a new information-theoretic method that allows unbiased calculation of neural filters (receptive fields) from responses to natural scenes or other complex signals with strong multipoint correlations. In the cat primary visual cortex we compare responses to natural inputs with those to noise inputs matched for luminance and contrast. We find that neural filters adaptively change with the input ensemble so as to increase the information carried by the neural response about the filtered stimulus. Adaptation affects the spatial frequency composition of the filter, enhancing sensitivity to under-represented frequencies in agreement with optimal encoding arguments. Adaptation occurs over 40 s to many minutes, longer than most previously reported forms of adaptation.     

Global landscape of protein complexes in the yeast Saccharomyces cerevisiae

Identification of protein-protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization-time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein-protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein-protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology.