Variability of the North Atlantic eddy-driven jet stream

Much of the atmospheric variability in the North Atlantic sector is associated with variations in the eddy-driven component of the zonal flow. Here we present a simple method to specifically diagnose this component of the flow using the low-level wind field (925–700 hpa ). We focus on the North Atlantic winter season in the ERA-40 reanalysis. Diagnostics of the latitude and speed of the eddy-driven jet stream are compared with conventional diagnostics of the North Atlantic Oscillation (NAO) and the East Atlantic (EA) pattern. This shows that the NAO and the EA both describe combined changes in the latitude and speed of the jet stream. It is therefore necessary, but not always sufficient, to consider both the NAO and the EA in identifying changes in the jet stream. The jet stream analysis suggests that there are three preferred latitudinal positions of the North Atlantic eddy-driven jet stream in winter. This result is in very good agreement with the application of a statistical mixture model to the two-dimensional state space defined by the NAO and the EA. These results are consistent with several other studies which identify four European/Atlantic regimes, comprising three jet stream patterns plus European blocking events.

Time-varying coefficients in the almost ideal demand system: An empirical appraisal

This paper provides a generalisation of the structural time series version of the Almost Ideal Demand System (AIDS) that allows for time-varying coefficients (TVC/AIDS) in the presence of cross-equation constraints. An empirical appraisal of the TVC/AIDS is made using a dynamic AIDS with trending intercept as the baseline model with a data set from the Italian Household Budget Survey (1986-2001). The assessment is based on four criteria: adherence to theoretical constraints, statistical diagnostics on residuals, forecasting performance and economic meaningfulness. No clear evidence is found for superior performance of the TVC/AIDS, apart from improved short-term forecasts.

A structural time series approach to modelling multiple and resurgent meat scares in Italy

This paper exploits a structural time series approach to model the time pattern of multiple and resurgent food scares and their direct and cross-product impacts on consumer response. A structural time series Almost Ideal Demand System (STS-AIDS) is embedded in a vector error correction framework to allow for dynamic effects (VEC-STS-AIDS). Italian aggregate household data on meat demand is used to assess the time-varying impact of a resurgent BSE crisis (1996 and 2000) and the 1999 Dioxin crisis. The VEC-STS-AIDS model monitors the short-run impacts and performs satisfactorily in terms of residuals diagnostics, overcoming the major problems encountered by the customary vector error correction approach.

Influence-matrix diagnostic of a data assimilation system

The influence matrix is used in ordinary least-squares applications for monitoring statistical multiple-regression analyses. Concepts related to the influence matrix provide diagnostics on the influence of individual data on the analysis - the analysis change that would occur by leaving one observation out, and the effective information content (degrees of freedom for signal) in any sub-set of the analysed data. In this paper, the corresponding concepts have been derived in the context of linear statistical data assimilation in numerical weather prediction. An approximate method to compute the diagonal elements of the influence matrix (the self-sensitivities) has been developed for a large-dimension variational data assimilation system (the four-dimensional variational system of the European Centre for Medium-Range Weather Forecasts). Results show that, in the boreal spring 2003 operational system, 15% of the global influence is due to the assimilated observations in any one analysis, and the complementary 85% is the influence of the prior (background) information, a short-range forecast containing information from earlier assimilated observations. About 25% of the observational information is currently provided by surface-based observing systems, and 75% by satellite systems. Low-influence data points usually occur in data-rich areas, while high-influence data points are in data-sparse areas or in dynamically active regions. Background-error correlations also play an important role: high correlation diminishes the observation influence and amplifies the importance of the surrounding real and pseudo observations (prior information in observation space). Incorrect specifications of background and observation-error covariance matrices can be identified, interpreted and better understood by the use of influence-matrix diagnostics for the variety of observation types and observed variables used in the data assimilation system. Copyright © 2004 Royal Meteorological Society

Burkholderia Hep_Hag autotransporter (BuHA) proteins elicit a strong antibody response during experimental glanders but not human melioidosis

BACKGROUND: The bacterial biothreat agents Burkholderia mallei and Burkholderia pseudomallei are the cause of glanders and melioidosis, respectively. Genomic and epidemiological studies have shown that B. mallei is a recently emerged, host restricted clone of B. pseudomallei. RESULTS: Using bacteriophage-mediated immunoscreening we identified genes expressed in vivo during experimental equine glanders infection. A family of immunodominant antigens were identified that share protein domain architectures with hemagglutinins and invasins. These have been designated Burkholderia Hep_Hag autotransporter (BuHA) proteins. A total of 110/207 positive clones (53%) of a B. mallei expression library screened with sera from two infected horses belonged to this family. This contrasted with 6/189 positive clones (3%) of a B. pseudomallei expression library screened with serum from 21 patients with culture-proven melioidosis. CONCLUSION: Members of the BuHA proteins are found in other Gram-negative bacteria and have been shown to have important roles related to virulence. Compared with other bacterial species, the genomes of both B. mallei and B. pseudomallei contain a relative abundance of this family of proteins. The domain structures of these proteins suggest that they function as multimeric surface proteins that modulate interactions of the cell with the host and environment. Their effect on the cellular immune response to B. mallei and their potential as diagnostics for glanders requires further study.

Combined affinity labelling and mass spectrometry analysis of differential cell surface protein expression in normal and prostate cancer cells

Differences in the expression of cell surface proteins between a normal prostate epithelial (1542-NP2TX) and a prostate cancer cell line (1542-CP3TX) derived from the same patient were investigated. A combination of affinity chromatographic purification of biotin-tagged surface proteins with mass spectrometry analysis identified 26 integral membrane proteins and 14 peripheral surface proteins. The findings confirm earlier reports of altered expression in prostate cancer for several cell surface proteins, including ALCAM/CD166, the Ephrin type A receptor, EGFR and the prostaglandin F2 receptor regulatory protein. In addition, several novel findings of differential expression were made, including the voltage-dependent anion selective channel proteins Porin 1 and 2, ecto-5'-nucleotidase (CD73) and Scavenger receptor B1. Cell surface protein expression changed both qualitatively and quantitatively when the cells were grown in the presence of either or both interferon INFalpha and INFgamma. Costimulation with type I and II interferons had additive or synergistic effects on the membrane density of several, mainly peripherally attached surface proteins. Concerted upregulation of surface exposed antigens may be of benefit in immuno-adjuvant-based treatment of interferon-responsive prostate cancer. In conclusion, this study demonstrates that differences in the expression of membrane proteins between normal and prostate cancer cells are reproducibly detectable following vectorial labelling with biotin, and that detailed analysis of extracellular-induced surface changes can be achieved by combining surface-specific labelling with high-resolution two-dimensional gel electrophoresis and mass spectrometry.

Expression profiles in the progression of ductal carcinoma in the breast

An understanding of the multi-step nature of cancer as it is in the breast, as a series of pivotal genetic/epigenetic modifications is irrefutably a milestone in diagnostics, prognostics and eventually providing a cure. Here we have utilised a variant of analysis of variance (ANOVA) as a model for the identification and tracking of specific mRNA species whose transcription has been significantly altered at each grade in the progression of ductal carcinoma, making it possible to correlate histological progression with the genetic events underlying breast cancer. We show that in the progression of ductal carcinomas, from grade 1 to 3, there is a reduction in the actual number of mRNA species, which are significantly over or under expressed. We also show that this technique can be employed to generate differential gene expression patterns, whereby the combined expression profile of the tailored spectra of genes in the comparison of each ductal grade is sufficient to render them on clearly separate arms of an array-wise hierarchical cluster dendrogram.

Design and analysis of climate model experiments for the efficient estimation of anthropogenic signals

Presented herein is an experimental design that allows the effects of several radiative forcing factors on climate to be estimated as precisely as possible from a limited suite of atmosphere-only general circulation model (GCM) integrations. The forcings include the combined effect of observed changes in sea surface temperatures, sea ice extent, stratospheric (volcanic) aerosols, and solar output, plus the individual effects of several anthropogenic forcings. A single linear statistical model is used to estimate the forcing effects, each of which is represented by its global mean radiative forcing. The strong colinearity in time between the various anthropogenic forcings provides a technical problem that is overcome through the design of the experiment. This design uses every combination of anthropogenic forcing rather than having a few highly replicated ensembles, which is more commonly used in climate studies. Not only is this design highly efficient for a given number of integrations, but it also allows the estimation of (nonadditive) interactions between pairs of anthropogenic forcings. The simulated land surface air temperature changes since 1871 have been analyzed. The changes in natural and oceanic forcing, which itself contains some forcing from anthropogenic and natural influences, have the most influence. For the global mean, increasing greenhouse gases and the indirect aerosol effect had the largest anthropogenic effects. It was also found that an interaction between these two anthropogenic effects in the atmosphere-only GCM exists. This interaction is similar in magnitude to the individual effects of changing tropospheric and stratospheric ozone concentrations or to the direct (sulfate) aerosol effect. Various diagnostics are used to evaluate the fit of the statistical model. For the global mean, this shows that the land temperature response is proportional to the global mean radiative forcing, reinforcing the use of radiative forcing as a measure of climate change. The diagnostic tests also show that the linear model was suitable for analyses of land surface air temperature at each GCM grid point. Therefore, the linear model provides precise estimates of the space time signals for all forcing factors under consideration. For simulated 50-hPa temperatures, results show that tropospheric ozone increases have contributed to stratospheric cooling over the twentieth century almost as much as changes in well-mixed greenhouse gases.

Combined affinity labelling and mass spectrometry analysis of differential cell surface protein expression in normal and prostate cancer cells

Differences in the expression of cell surface proteins between a normal prostate epithelial (1542-NP2TX) and a prostate cancer cell line (1542-CP3TX) derived from the same patient were investigated. A combination of affinity chromatographic purification of biotin-tagged surface proteins with mass spectrometry analysis identified 26 integral membrane proteins and 14 peripheral surface proteins. The findings confirm earlier reports of altered expression in prostate cancer for several cell surface proteins, including ALCAM/CD166, the Ephrin type A receptor, EGFR and the prostaglandin F2 receptor regulatory protein. In addition, several novel findings of differential expression were made, including the voltage-dependent anion selective channel proteins Porin 1 and 2, ecto-5'-nucleotidase (CD73) and Scavenger receptor B1. Cell surface protein expression changed both qualitatively and quantitatively when the cells were grown in the presence of either or both interferon INF alpha and INF gamma. Costimulation with type I and II interferons had additive or synergistic effects on the membrane density of several, mainly peripherally attached surface proteins. Concerted upregulation of surface exposed antigens may be of benefit in immuno-adjuvant-based treatment of interferon-responsive prostate cancer. In conclusion, this study demonstrates that differences in the expression of membrane proteins between normal and prostate cancer cells are reproducibly detectable following vectorial labelling with biotin, and that detailed analysis of extracellular-induced surface changes can be achieved by combining surface-specific labelling with high-resolution two-dimensional gel electrophoresis and mass spectrometry.

Mass spectrometry in clinical proteomics - from the present to the future

MS is an important analytical tool in clinical proteomics, primarily in the disease-specific discovery identification and characterisation of proteomic biomarkers and patterns. MS-based proteomics is increasingly used in clinical validation and diagnostic method development. The latter departs from the typical application of MS-based proteomics by exchanging some of the high performance of analysis for the throughput, robustness and simplicity required for clinical diagnostics. Although conventional MS-based proteomics has become an important field in clinical applications, some of the most recent MS technologies have not yet been extensively applied in clinical proteomics. in this review, we will describe the current state of MS in clinical proteomics and look to the future of this field.

From probiotics to prebiotics and a healthy digestive system

Ingestion of probiotics can be recommended as a preventative approach to maintaining intestinal microflora balance and thereby enhance 'well-being'. Undoubtedly, probiotic bacteria will vary in their efficacy. The literature indicates positive results in over 50 human trials with prevention/treatment of infections the most frequently reported. In theory increased levels of probiotics may induce a 'barrier' influence against common pathogens. Mechanisms of effect are likely to include the excretion of acids (lactate, acetate), competition for nutrients and gut receptor sites, immuno-modulation and the formation of specific antimicrobial agents. An alternative, or additional, approach is the prebiotic concept. This takes the view that probiotics are present indigenous to the gut and that a rational approach towards increasing their numbers would be to consume food ingredients (carbohydrates) that have a selective metabolism in the lower gut. A prebiotic is 'a nondigestible food ingredient that beneficially affects the host by selectively stimulating the growth and/or activity of one or a limited number of bacteria in the colon that can improve the host health.' In particular, the ingestion of fructo-oligosaccharides, galacto-oligosaccharides, and lactulose has shown to stimulate bifidobacteria in the lower gut.

Is influenza vaccination cost effective for healthy people between ages 65 and 74 years? A randomised controlled trial

The aim of this study was to determine the cost effectiveness of influenza vaccination for healthy people aged 65-74 years living in the UK. People without risk factors for influenza (chronic heart, lung or renal disease, diabetic, immuno-suppressed or those living in an institution) were identified from 20 general practitioner (GP) practices in Liverpool in September 1999. 729/5875 (12.4%) eligible individuals were recruited and randomised to receive either influenza vaccine or placebo (ratio 3: 1)! with all participants receiving 23-valent-pneumococcal polysaccharide vaccine unless already administered. The primary analysis was the frequency of influenza as recorded by a GP diagnosis of pneumonia or influenza like illness. In 2000, the UK vaccination policy was changed with influenza vaccine becoming available. for all people aged 65 years and over irrespective of risk. As a consequence of this policy change. the study had to be fundamentally restructured and only results obtained over a one rather than the originally planned two-year randomised controlled trial framework were used. Results from 1999/2000 demonstrated no significant difference between groups for the primary outcome (relative risk 0.8, 95%, CI 0.16-4.1). In addition. there were no deaths or hospitalisations for influenza associated respiratory illness in either group. The subsequent analysis. using both national and local sources of evidence, estimated the following cost effectiveness indicators: (1) incremental NHS cost per GP consultation avoided = pound2000; (2) incremental NHS cost per hospital admission avoided = pound61,000: (3) incremental NHS cost per death avoided = pound1.900.000 and (4) incremental NHS cost per QALY gained = pound304,000. The analysis suggested that influenza vaccination in this Population would not be cost effective. (C) 2004 Elsevier Ltd. All rights reserved.

A-optimality orthogonal forward regression algorithm using branch and bound

In this brief, we propose an orthogonal forward regression (OFR) algorithm based on the principles of the branch and bound (BB) and A-optimality experimental design. At each forward regression step, each candidate from a pool of candidate regressors, referred to as S, is evaluated in turn with three possible decisions: 1) one of these is selected and included into the model; 2) some of these remain in S for evaluation in the next forward regression step; and 3) the rest are permanently eliminated from S. Based on the BB principle in combination with an A-optimality composite cost function for model structure determination, a simple adaptive diagnostics test is proposed to determine the decision boundary between 2) and 3). As such the proposed algorithm can significantly reduce the computational cost in the A-optimality OFR algorithm. Numerical examples are used to demonstrate the effectiveness of the proposed algorithm.

Self-immolative linkers in polymeric delivery systems

There has been significant interest in the methodologies of controlled release for a diverse range of applications spanning drug delivery, biological and chemical sensors, and diagnostics. The advancement in novel substrate-polymer coupling moieties has led to the discovery of self-immolative linkers. This new class of linker has gained popularity in recent years in polymeric release technology as a result of stable bond formation between protecting and leaving groups, which becomes labile upon activation, leading to the rapid disassembly of the parent polymer. This ability has prompted numerous studies into the design and development of self-immolative linkers and the kinetics surrounding their disassembly. This review details the main concepts that underpin self-immolative linker technologies that feature in polymeric or dendritic conjugate systems and outlines the chemistries of amplified self-immolative elimination.

Persistent, symptomless, systemic, and seed-borne infection of lettuce by Botrytis cinerea

Experiments are presented which show that Botrytis cinerea, the cause of gray mould disease, is often present in symptomless lettuce plants as a systemic, endophytic, infection which may arise from seed. The fungus was isolated on selective media from surface sterilized sections of roots, stem pieces and leaf discs from symptomless plants grown in a conventional glasshouse and in a spore-free air-flow provided by an isolation propagator. The presence of B. cinerea was confirmed by immuno-labelling the tissues with the Botrytis-specific monoclonal antibody BC-12.CA4. As plants grew, infection spread from the roots to stems and leaves. Surface sterilization of seeds reduced the number of infected symptomless plants. Artificial infection of seedlings with dry conidia increased the rate of infection in some experiments. Selected isolates were genetically finger-printed using microsatellite loci. This confirmed systemic spread of the inoculating isolates but showed that other isolates were also present and that single plants hosted multiple isolates. This shows that B. cinerea commonly grows in lettuce plants as an endophyte, as has already been shown for Primula. If true for other hosts, the endophytic phase may be as important a component of the species population as the aggressive necrotrophic phase.