947 resultados para Bacterial foraging algorithm


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A prospective study of fungal and bacterial flora of burn wounds was carried out from February 2004 to February 2005 at the Burns Unit of Hospital Regional da Asa Norte, Brasília, Brazil. During the period of the study, 203 patients were treated at the Burns Unit. Wound swab cultures were assessed at weekly intervals for four weeks. Three hundred and fifty four sampling procedures (surface swabs) were performed from the burn wounds. The study revealed that bacterial colonization reached 86.6% within the first week. Although the gram-negative organisms, as a group, were more predominant, Staphylococcus aureus (28.4%) was the most prevalent organism in the first week. It was however surpassed by Pseudomonas aeruginosa form third week onwards. For S. aureus and P. aeruginosa vancomycin and polymyxin were found to be the most effective drugs. Most of the isolates showed high level resistance to antimicrobial agents. Fungi were found to colonize the burn wound late during the second week postburn, with a peak incidence during the third and fourth weeks. Species identification of fungi revealed that Candida tropicalis was the most predominant, followed by Candida parapsilosis. It is crucial for every burn institution to determine the specific pattern of burn wound microbial colonization, the time-related changes in the dominant flora, and the antimicrobial sensitivity profiles. This would enable early treatment of imminent septic episodes with proper empirical systemic antibiotics, without waiting for culture results, thus improving the overall infection-related morbidity and mortality.

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Toxicity of chemical pollutants in aquatic environments is often addressed by assays that inquire reproductive inhibition of test microorganisms, such as algae or bacteria. Those tests, however, assess growth of populations as a whole via macroscopic methods such as culture turbidity or colony-forming units. Here we use flow cytometry to interrogate the fate of individual cells in low-density populations of the bacterium Pseudomonas fluorescens SV3 exposed or not under oligotrophic conditions to a number of common pollutants, some of which derive from oil contamination. Cells were stained at regular time intervals during the exposure assay with fluorescent dyes that detect membrane injury (i.e., live-dead assay). Reduction of population growth rates was observed upon toxicant insult and depended on the type of toxicant. Modeling and cell staining indicate that population growth rate decrease is a combined effect of an increased number of injured cells that may or may not multiply, and live cells dividing at normal growth rates. The oligotrophic assay concept presented here could be a useful complement for existing biomarker assays in compliance with new regulations on chemical effect studies or, more specifically, for judging recovery after exposure to fluctuating toxicant conditions.

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Emerging resistance phenotypes and antimicrobial resistance rates among pathogens recovered from community-acquired urinary tract infections (CA-UTI) is an increasing problem in specific regions, limiting therapeutic options. As part of the SENTRY Antimicrobial Surveillance Program, a total of 611 isolates were collected in 2003 from patients with CA-UTI presenting at Latin American medical centers. Each strain was tested in a central laboratory using Clinical Laboratory Standard Institute (CLSI) broth microdilution methods with appropriate controls. Escherichia coli was the leading pathogen (66%), followed by Klebsiella spp. (7%), Proteus mirabilis (6.4%), Enterococcus spp. (5.6%), and Pseudomonas aeruginosa (4.6%). Surprisingly high resistance rates were recorded for E. coli against first-line orally administered agents for CA-UTI, such as ampicillin (53.6%), TMP/SMX (40.4%), ciprofloxacin (21.6%), and gatifloxacin (17.1%). Decreased susceptibility rates to TMP/SMX and ciprofloxacin were also documented for Klebsiella spp. (79.1 and 81.4%, respectively), and P. mirabilis (71.8 and 84.6%, respectively). For Enterococcus spp., susceptibility rates to ampicillin, chloramphenicol, ciprofloxacin, and vancomycin were 88.2, 85.3, 55.9, and 97.1%, respectively. High-level resistance to gentamicin was detected in 24% of Enterococcus spp. Bacteria isolated from patients with CA-UTI in Latin America showed limited susceptibility to orally administered antimicrobials, especially for TMP/SMX and fluoroquinolones. Our results highlight the need for developing specific CA-UTI guidelines in geographic regions where elevated resistance to new and old compounds may influence prescribing decisions.

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Chronic exposure to food of low quality may exert conflicting selection pressures on foraging behaviour. On the one hand, more active search behaviour may allow the animal to find patches with slightly better, or more, food; on the other hand, such active foraging is energetically costly, and thus may be opposed by selection for energetic efficiency. Here, we test these alternative hypotheses in Drosophila larvae. We show that populations which experimentally evolved improved tolerance to larval chronic malnutrition have shorter foraging path length than unselected control populations. A behavioural polymorphism in foraging path length (the rover-sitter polymorphism) exists in nature and is attributed to the foraging locus (for). We show that a sitter strain (for(s2)) survives better on the poor food than the rover strain (for(R)), confirming that the sitter foraging strategy is advantageous under malnutrition. Larvae of the selected and control populations did not differ in global for expression. However, a quantitative complementation test suggests that the for locus may have contributed to the adaptation to poor food in one of the selected populations, either through a change in for allele frequencies, or by interacting epistatically with alleles at other loci. Irrespective of its genetic basis, our results provide two independent lines of evidence that sitter-like foraging behaviour is favoured under chronic larval malnutrition.

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To provide a novel resource for analysis of the genome of Biomphalaria glabrata, members of the international Biomphalaria glabrata Genome Initiative (biology.unm.edu/biomphalaria-genome.html), working with the Arizona Genomics Institute (AGI) and supported by the National Human Genome Research Institute (NHGRI), produced a high quality bacterial artificial chromosome (BAC) library. The BB02 strain B. glabrata, a field isolate (Belo Horizonte, Minas Gerais, Brasil) that is susceptible to several strains of Schistosoma mansoni, was selfed for two generations to reduce haplotype diversity in the offspring. High molecular weight DNA was isolated from ovotestes of 40 snails, partially digested with HindIII, and ligated into pAGIBAC1 vector. The resulting B. glabrata BAC library (BG_BBa) consists of 61824 clones (136.3 kb average insert size) and provides 9.05 × coverage of the 931 Mb genome. Probing with single/low copy number genes from B. glabrata and fingerprinting of selected BAC clones indicated that the BAC library sufficiently represents the gene complement. BAC end sequence data (514 reads, 299860 nt) indicated that the genome of B. glabrata contains ~ 63% AT, and disclosed several novel genes, transposable elements, and groups of high frequency sequence elements. This BG_BBa BAC library, available from AGI at cost to the research community, gains in relevance because BB02 strain B. glabrata is targeted whole genome sequencing by NHGRI.

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Population-based data on sexually transmitted infections (STI), bacterial vaginosis (BV), and candidiasis reflect the epidemiological situation more accurately than studies performed in specific populations, but such data are scarce. To determine the prevalence of STI, BV, and candidiasis among women of reproductive age from a resource-poor community in Northeast Brazil, a population-based cross sectional study was undertaken. All women from seven hamlets and the centre of Pacoti municipality in the state of Ceará, aged 12 to 49 years, were invited to participate. The women were asked about socio-demographic characteristics and genital symptoms, and thereafter examined gynaecologically. Laboratory testing included polymerase chain reaction (PCR) for human papillomavirus (HPV), ligase chain reaction (LCR) for Chlamydia trachomatis and Neisseria gonorrhoeae, ELISA for human immunodeficiency virus (HIV), venereal disease research laboratory (VDRL) and fluorescent treponema antibody absorption test (FTA-ABS) for syphilis, and analysis of wet mounts, gram stains and Pap smears for trichomoniasis, candidiasis, and BV. Only women who had initiated sexual life were included in the analysis (n = 592). The prevalences of STI were: HPV 11.7% (95% confidence interval: 9.3-14.7), chlamydia 4.5% (3.0-6.6), trichomoniasis 4.1% (2.7-6.1), gonorrhoea 1.2% (0.5-2.6), syphilis 0.2% (0.0-1.1), and HIV 0%. The prevalence of BV and candidiasis was 20% (16.9-23.6) and 12.5% (10.0-15.5), respectively. The most common gynaecological complaint was lower abdominal pain. STI are common in women in rural Brazil and represent an important health threat in view of the HIV pandemic.

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A luminescent bacterial biosensor was used to quantify bioavailable arsenic in artificial groundwater. Its light production above the background emission was proportional to the arsenite concentration in the toxicologically relevant range of 0 to 0.5 mu M. Effects of the inorganic solutes phosphate, Fe(II) and silicate on the biosensor signal were studied. Phosphate at a concentration of 0.25 g L-1 phosphate slightly stimulated the light emission, but much less than toxicologically relevant concentrations of the much stronger inducer arsenite. No effect of phosphate was oberved in the presence of arsenite. Freshly prepared sodium silicate solution at a concentration of 10 g L-1 Si reduced the arsenite-induced light production by roughly 37%, which can be explained by transient polymerization leading to sequestration of some arsenic. After three days of incubation, silicate did not have this effect anymore, probably because depolymerization occurred. In the presence of 0.4 g L-1 Fe(II), the arsenite-induced light emission was reduced by up to 90%, probably due to iron oxidation followed by arsenite adsorption on the less soluble Fe(III) possibly along with some oxidation to the stronger adsorbing As(V). Addition of 100 mu M EDTA was capable of releasing all arsenic from the precipitate and to transform it into the biologically measurable, dissolved state. The biosensor also proved valuable for monitoring the effectiveness of an arsenic removal procedure based on water filtration through a mixture of sand and iron granules.

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Most patients with acute suppurative meningitis are otherwise healthy individuals with regard to immune mechanisms against invasive bacterial disease. This medical emergency is among the most dramatic and potentially ravaging diseases that affect humans, particularly young children. The illness often strikes suddenly, and can either result in death or leave the survivors with significant neurological dysfunctions. The demonstration of a bacterial aetiology is necessary for decisions regarding treatment and prophylaxis. Conventional bacteriological methods frequently fail to identify an agent, as a result of administration of antibiotics or delayed lumbar punctures. We investigated the major aetiologic sources of unspecified bacterial meningitis cases (G00.9, ISCD-10) by polymerase chain reaction (PCR)-based identification of Neisseria meningitidis (crgA), Streptococcus pneumoniae (ply) and Haemophilus influenzae (bexA) in cerebrospinal fluid samples. The multiplex PCR detected N. meningitidis in 92%, S. pneumoniae in 4% and H. influenzae in 1% of the 192 clinical samples assayed; 3% were negative for all three DNA targets. Bacterial DNA detection was found to be a valuable adjunct to enhance bacterial meningitis surveillance when the yield of specimens by culture is reduced. The implementation of PCR assays as a diagnostic procedure in Public Health Laboratories is perceived to be a significant advance in the investigation of bacterial meningitis.

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Genetically engineered bioreporters are an excellent complement to traditional methods of chemical analysis. The application of fluorescence flow cytometry to detection of bioreporter response enables rapid and efficient characterization of bacterial bioreporter population response on a single-cell basis. In the present study, intrapopulation response variability was used to obtain higher analytical sensitivity and precision. We have analyzed flow cytometric data for an arsenic-sensitive bacterial bioreporter using an artificial neural network-based adaptive clustering approach (a single-layer perceptron model). Results for this approach are far superior to other methods that we have applied to this fluorescent bioreporter (e.g., the arsenic detection limit is 0.01 microM, substantially lower than for other detection methods/algorithms). The approach is highly efficient computationally and can be implemented on a real-time basis, thus having potential for future development of high-throughput screening applications.

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Abstract: Traditionally, pollution risk assessment is based on the measurement of a pollutant's total concentration in a sample. The toxicity of a given pollutant in the environment, however, is tightly linked to its bioavailability, which may differ significantly from the total amount. Physico-chemical and biological parameters strongly influence pollutant fate in terms of leaching, sequestration and biodegradation. Bacterial sensorreporters, which consist of living micro-organisms genetically engineered to produce specific output in response to target chemicals, offer an interesting alternative to monitoring approaches. Bacterial sensor-reporters detect bioavailable and/or bioaccessible compound fractions in samples. Currently, a variety of environmental pollutants can be targeted by specific biosensor-reporters. Although most of such strains are still confined to the lab, several recent reports have demonstrated utility of bacterial sensing-reporting in the field, with method detection limits in the nanomolar range. This review illustrates the general design principles for bacterial sensor-reporters, presents an overview of the existing biosensor-reporter strains with emphasis on organic compound detection. A specific focus throughout is on the concepts of bioavailability and bioaccessibility, and how bacteria-based sensing-reporting systems can help to improve our basic understanding of the different processes at work.

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The multiscale finite volume (MsFV) method has been developed to efficiently solve large heterogeneous problems (elliptic or parabolic); it is usually employed for pressure equations and delivers conservative flux fields to be used in transport problems. The method essentially relies on the hypothesis that the (fine-scale) problem can be reasonably described by a set of local solutions coupled by a conservative global (coarse-scale) problem. In most cases, the boundary conditions assigned for the local problems are satisfactory and the approximate conservative fluxes provided by the method are accurate. In numerically challenging cases, however, a more accurate localization is required to obtain a good approximation of the fine-scale solution. In this paper we develop a procedure to iteratively improve the boundary conditions of the local problems. The algorithm relies on the data structure of the MsFV method and employs a Krylov-subspace projection method to obtain an unconditionally stable scheme and accelerate convergence. Two variants are considered: in the first, only the MsFV operator is used; in the second, the MsFV operator is combined in a two-step method with an operator derived from the problem solved to construct the conservative flux field. The resulting iterative MsFV algorithms allow arbitrary reduction of the solution error without compromising the construction of a conservative flux field, which is guaranteed at any iteration. Since it converges to the exact solution, the method can be regarded as a linear solver. In this context, the schemes proposed here can be viewed as preconditioned versions of the Generalized Minimal Residual method (GMRES), with a very peculiar characteristic that the residual on the coarse grid is zero at any iteration (thus conservative fluxes can be obtained).

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This paper proposes a parallel architecture for estimation of the motion of an underwater robot. It is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. In a motion estimation algorithm, correspondences between two images have to be solved at the low level. In the underwater imaging, normalised correlation can be a solution in the presence of non-uniform illumination. Due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. Taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed

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In computer graphics, global illumination algorithms take into account not only the light that comes directly from the sources, but also the light interreflections. This kind of algorithms produce very realistic images, but at a high computational cost, especially when dealing with complex environments. Parallel computation has been successfully applied to such algorithms in order to make it possible to compute highly-realistic images in a reasonable time. We introduce here a speculation-based parallel solution for a global illumination algorithm in the context of radiosity, in which we have taken advantage of the hierarchical nature of such an algorithm

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Enteroinvasive Escherichia coli (EIEC) and Shigellaspp cause bacillary dysentery in humans by invading and multiplying within epithelial cells of the colonic mucosa. Although EIEC and Shigellashare many genetic and biochemical similarities, the illness caused by Shigellais more severe. Thus, genomic and structure-function molecular studies on the biological interactions of these invasive enterobacteria with eukaryotic cells have focused on Shigella rather than EIEC. Here we comparatively studied the interactions of EIEC and of Shigella flexneriwith cultured J774 macrophage-like cells. We evaluated several phenotypes: (i) bacterial escape from macrophages after phagocytosis, (ii) macrophage death induced by EIEC and S. flexneri, (iii) macrophage cytokine expression in response to infection and (iv) expression of plasmidial (pINV) virulence genes. The results showed thatS. flexneri caused macrophage killing earlier and more intensely than EIEC. Both pathogens induced significant macrophage production of TNF, IL-1 and IL-10 after 7 h of infection. Transcription levels of the gene invasion plasmid antigen-C were lower in EIEC than in S. flexneri throughout the course of the infection; this could explain the diminished virulence of EIEC compared to S. flexneri.

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Diffusion tensor magnetic resonance imaging, which measures directional information of water diffusion in the brain, has emerged as a powerful tool for human brain studies. In this paper, we introduce a new Monte Carlo-based fiber tracking approach to estimate brain connectivity. One of the main characteristics of this approach is that all parameters of the algorithm are automatically determined at each point using the entropy of the eigenvalues of the diffusion tensor. Experimental results show the good performance of the proposed approach