An epidemiologic study of early biologic effects of benzene in Chinese workers.

Benzene is a recognized hematotoxin and leukemogen, but its mechanisms of action in humans are still uncertain. To provide insight into these processes, we carried out a cross-sectional study of 44 healthy workers currently exposed to benzene (median 8-hr time-weighted average; 31 ppm), and unexposed controls in Shanghai, China. Here we provide an overview of the study results on peripheral blood cells levels and somatic cell mutation frequency measured by the glycophorin A (GPA) gene loss assay and report on peripheral cytokine levels. All peripheral blood cells levels (i.e., total white blood cells, absolute lymphocyte count, platelets, red blood cells, and hemoglobin) were decreased among exposed workers compared to controls, with the exception of the red blood cell mean corpuscular volume, which was higher among exposed subjects. In contrast, peripheral cytokine levels (interleukin-3, interleukin-6, erythropoietin, granulocyte colony-stimulating factor, tissue necrosis factor-alpha) in a subset of the most highly exposed workers (n = 11) were similar to values in controls (n = 11), suggesting that benzene does not affect these growth factor levels in peripheral blood. The GPA assay measures stem cell or precursor erythroid cell mutations expressed in peripheral red blood cells of MN heterozygous subjects, identifying NN variants, which result from loss of the GPA M allele and duplication of the N allele, and N phi variants, which arise from gene inactivation. The NN (but not N phi) GPA variant cell frequency was elevated in the exposed workers compared with controls (mean +/- SD, 13.9 +/- 8.4 mutants per million cells versus 7.4 +/- 5.2 per million cells, (respectively; p = 0.0002), suggesting that benzene produces gene-duplicating but not gene-inactivating mutations at the GPA locus in bone marrow cells of exposed humans. These findings, combined with ongoing analyses of benzene macromolecular adducts and chromosomal aberrations, will provide an opportunity to comprehensively evaluate a wide range of early biologic effects associated with benzene exposure in humans

The running coupling of 8 flavors and 3 colors

We compute the renormalized running coupling of SU(3) gauge theory coupled to N_f = 8 flavors of massless fundamental Dirac fermions. The recently proposed finite volume gradient flow scheme is used. The calculations are performed at several lattice spacings allowing for a controlled continuum extrapolation. The results for the discrete beta-function show that it is monotonic without any sign of a fixed point in the range of couplings we cover. As a cross check the continuum results are compared with the well-known perturbative continuum beta-function for small values of the renormalized coupling and perfect agreement is found.Comment: 15 pages, 17 figures, published versio

3D Protein structure prediction with genetic tabu search algorithm

Abstract Background Protein structure prediction (PSP) has important applications in different fields, such as drug design, disease prediction, and so on. In protein structure prediction, there are two important issues. The first one is the design of the structure model and the second one is the design of the optimization technology. Because of the complexity of the realistic protein structure, the structure model adopted in this paper is a simplified model, which is called off-lattice AB model. After the structure model is assumed, optimization technology is needed for searching the best conformation of a protein sequence based on the assumed structure model. However, PSP is an NP-hard problem even if the simplest model is assumed. Thus, many algorithms have been developed to solve the global optimization problem. In this paper, a hybrid algorithm, which combines genetic algorithm (GA) and tabu search (TS) algorithm, is developed to complete this task. Results In order to develop an efficient optimization algorithm, several improved strategies are developed for the proposed genetic tabu search algorithm. The combined use of these strategies can improve the efficiency of the algorithm. In these strategies, tabu search introduced into the crossover and mutation operators can improve the local search capability, the adoption of variable population size strategy can maintain the diversity of the population, and the ranking selection strategy can improve the possibility of an individual with low energy value entering into next generation. Experiments are performed with Fibonacci sequences and real protein sequences. Experimental results show that the lowest energy obtained by the proposed GATS algorithm is lower than that obtained by previous methods. Conclusions The hybrid algorithm has the advantages from both genetic algorithm and tabu search algorithm. It makes use of the advantage of multiple search points in genetic algorithm, and can overcome poor hill-climbing capability in the conventional genetic algorithm by using the flexible memory functions of TS. Compared with some previous algorithms, GATS algorithm has better performance in global optimization and can predict 3D protein structure more effectively

Accelerated search for biomolecular network models to interpret high-throughput experimental data

<p>Abstract</p> <p>Background</p> <p>The functions of human cells are carried out by biomolecular networks, which include proteins, genes, and regulatory sites within DNA that encode and control protein expression. Models of biomolecular network structure and dynamics can be inferred from high-throughput measurements of gene and protein expression. We build on our previously developed fuzzy logic method for bridging quantitative and qualitative biological data to address the challenges of noisy, low resolution high-throughput measurements, i.e., from gene expression microarrays. We employ an evolutionary search algorithm to accelerate the search for hypothetical fuzzy biomolecular network models consistent with a biological data set. We also develop a method to estimate the probability of a potential network model fitting a set of data by chance. The resulting metric provides an estimate of both model quality and dataset quality, identifying data that are too noisy to identify meaningful correlations between the measured variables.</p> <p>Results</p> <p>Optimal parameters for the evolutionary search were identified based on artificial data, and the algorithm showed scalable and consistent performance for as many as 150 variables. The method was tested on previously published human cell cycle gene expression microarray data sets. The evolutionary search method was found to converge to the results of exhaustive search. The randomized evolutionary search was able to converge on a set of similar best-fitting network models on different training data sets after 30 generations running 30 models per generation. Consistent results were found regardless of which of the published data sets were used to train or verify the quantitative predictions of the best-fitting models for cell cycle gene dynamics.</p> <p>Conclusion</p> <p>Our results demonstrate the capability of scalable evolutionary search for fuzzy network models to address the problem of inferring models based on complex, noisy biomolecular data sets. This approach yields multiple alternative models that are consistent with the data, yielding a constrained set of hypotheses that can be used to optimally design subsequent experiments.</p

Evaluation of non-inferiority of intradermal versus adjuvanted seasonal influenza vaccine using two serological techniques: a randomised comparative study

<p>Abstract</p> <p>Background</p> <p>Although seasonal influenza vaccine is effective in the elderly, immune responses to vaccination are lower in the elderly than in younger adults. Strategies to optimise responses to vaccination in the elderly include using an adjuvanted vaccine or using an intradermal vaccination route. The immunogenicity of an intradermal seasonal influenza vaccine was compared with that of an adjuvanted vaccine in the elderly.</p> <p>Methods</p> <p>Elderly volunteers (age ≥ 65 years) were randomised to receive a single dose of trivalent seasonal influenza vaccine: either a split-virion vaccine containing 15 μg haemagglutinin [HA]/strain/0.1-ml dose administered intradermally, or a subunit vaccine (15 μg HA/strain/0.5-ml dose) adjuvanted with MF59C.1 and administered intramuscularly. Blood samples were taken before and 21 ± 3 days post-vaccination. Anti-HA antibody titres were assessed using haemagglutination inhibition (HI) and single radial haemolysis (SRH) methods. We aimed to show that the intradermal vaccine was non-inferior to the adjuvanted vaccine.</p> <p>Results</p> <p>A total of 795 participants were enrolled (intradermal vaccine n = 398; adjuvanted vaccine n = 397). Non-inferiority of the intradermal vaccine was demonstrated for the A/H1N1 and B strains, but not for the A/H3N2 strain (upper bound of the 95% CI = 1.53) using the HI method, and for all three strains by the SRH method. A <it>post-hoc </it>analysis of covariance to adjust for baseline antibody titres demonstrated the non-inferiority of the intradermal vaccine by HI and SRH methods for all three strains. Both vaccines were, in general, well tolerated; the incidence of injection-site reactions was higher for the intradermal (70.1%) than the adjuvanted vaccine (33.8%) but these reactions were mild and of short duration.</p> <p>Conclusions</p> <p>The immunogenicity and safety of the intradermal seasonal influenza vaccine in the elderly was comparable with that of the adjuvanted vaccine. Intradermal vaccination to target the immune properties of the skin appears to be an appropriate strategy to address the challenge of declining immune responses in the elderly.</p> <p>Trial registration</p> <p>ClinicalTrials.gov: NCT00554333.</p

A systematic review of psychosocial interventions for family carers of palliative care patients

<p>Abstract</p> <p>Background</p> <p>Being a family carer to a patient nearing the end of their life is a challenging and confronting experience. Studies show that caregiving can have negative consequences on the health of family carers including fatigue, sleep problems, depression, anxiety and burnout. One of the goals of palliative care is to provide psychosocial support to patients and families facing terminal illness. A systematic review of interventions for family carers of cancer and palliative care patients conducted at the start of this millennium demonstrated that there was a dearth of rigorous inquiry on this topic and consequently limited knowledge regarding the types of interventions likely to be effective in meeting the complex needs of family carers. We wanted to discern whether or not the evidence base to support family carers has improved. Furthermore, undertaking this review was acknowledged as one of the priorities for the International Palliative Care Family Carer Research Collaboration <url>http://www.centreforpallcare.org</url>.</p> <p>Methods</p> <p>A systematic review was undertaken in order to identify developments in family carer support that have occurred over the last decade. The focus of the review was on interventions that targeted improvements in the psychosocial support of family carers of palliative care patients. Studies were graded to assess their quality.</p> <p>Results</p> <p>A total of fourteen studies met the inclusion criteria. The focus of interventions included psycho-education, psychosocial support, carer coping, symptom management, sleep promotion and family meetings. Five studies were randomised controlled trials, three of which met the criteria for the highest quality evidence. There were two prospective studies, five pre-test/post-test projects and two qualitative studies.</p> <p>Conclusions</p> <p>The systematic review identified a slight increase in the quality and quantity of psychosocial interventions conducted for family carers in the last decade. More rigorous intervention research is required in order to meet the supportive care needs of family carers of palliative care patients.</p

Identification of gene co-regulatory modules and associated cis-elements involved in degenerative heart disease

<p>Abstract</p> <p>Background</p> <p>Cardiomyopathies, degenerative diseases of cardiac muscle, are among the leading causes of death in the developed world. Microarray studies of cardiomyopathies have identified up to several hundred genes that significantly alter their expression patterns as the disease progresses. However, the regulatory mechanisms driving these changes, in particular the networks of transcription factors involved, remain poorly understood. Our goals are (A) to identify modules of co-regulated genes that undergo similar changes in expression in various types of cardiomyopathies, and (B) to reveal the specific pattern of transcription factor binding sites, <it>cis</it>-elements, in the proximal promoter region of genes comprising such modules.</p> <p>Methods</p> <p>We analyzed 149 microarray samples from human hypertrophic and dilated cardiomyopathies of various etiologies. Hierarchical clustering and Gene Ontology annotations were applied to identify modules enriched in genes with highly correlated expression and a similar physiological function. To discover motifs that may underly changes in expression, we used the promoter regions for genes in three of the most interesting modules as input to motif discovery algorithms. The resulting motifs were used to construct a probabilistic model predictive of changes in expression across different cardiomyopathies.</p> <p>Results</p> <p>We found that three modules with the highest degree of functional enrichment contain genes involved in myocardial contraction (n = 9), energy generation (n = 20), or protein translation (n = 20). Using motif discovery tools revealed that genes in the contractile module were found to contain a TATA-box followed by a CACC-box, and are depleted in other GC-rich motifs; whereas genes in the translation module contain a pyrimidine-rich initiator, Elk-1, SP-1, and a novel motif with a GCGC core. Using a naïve Bayes classifier revealed that patterns of motifs are statistically predictive of expression patterns, with odds ratios of 2.7 (contractile), 1.9 (energy generation), and 5.5 (protein translation).</p> <p>Conclusion</p> <p>We identified patterns comprised of putative <it>cis</it>-regulatory motifs enriched in the upstream promoter sequence of genes that undergo similar changes in expression secondary to cardiomyopathies of various etiologies. Our analysis is a first step towards understanding transcription factor networks that are active in regulating gene expression during degenerative heart disease.</p