Biocontrol strain Pseudomonas fluorescens CHA0 and its genetically modified derivative with enhanced biocontrol capability exert comparable effects on the structure of a Sinorhizobium meliloti population in a gnotobiotic system

The impact of biocontrol strain Pseudomonas fluorescens CHA0 and of its genetically modified, antibiotic-overproducing derivative CHA0/pME3424 on a reconstructed population of the plant-beneficial Sinorhizobium meliloti bacteria was assessed in gnotobiotic systems. In sterile soil, the final density of the reconstructed S. meliloti population decreased by more than one order of magnitude in the presence of either of the Pseudomonas strains when compared to a control without addition of P. fluorescens. Moreover, there was a change in the proportion of each individual S. meliloti strain within the population. Plant tests also revealed changes in the nodulating S. meliloti population in the presence of strains CHA0 or CHA0/pME3424. In both treatments one S. meliloti strain, f43, was significantly reduced in its root nodule occupancy. Analysis of alfalfa yields showed a slight but statistically significant increase in shoot dry weight when strain CHA0 was added to the reconstructed S. meliloti population whereas no such effect was observed with CHA0/pME3424.

Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.

Are oxygen uptake kinetics modified when using a respiratory snorkel?

PURPOSE: The aim of this study was to compare VO2 kinetics during constant power cycle exercise measured using a conventional facemask (CM) or a respiratory snorkel (RS) designed for breath-by-breath analysis in swimming. METHODS: VO2 kinetics parameters-obtained using CM or RS, in randomized counterbalanced order-were compared in 10 trained triathletes performing two submaximal heavy-intensity cycling square-wave transitions. These VO2 kinetics parameters (ie, time delay: td1, td2; time constant: τ1, τ2; amplitude: A1, A2, for the primary phase and slow component, respectively) were modeled using a double exponential function. In the case of the RS data, this model incorporated an individually determined snorkel delay (ISD). RESULTS: Only td1 (8.9 ± 3.0 vs 13.8 ± 1.8 s, P < .01) differed between CM and RS, whereas all other parameters were not different (τ1 = 24.7 ± 7.6 vs 21.1 ± 6.3 s; A1 = 39.4 ± 5.3 vs 36.8 ± 5.1 mL x min(-1) x kg(-1); td2 = 107.5 ± 87.4 vs 183.5 ± 75.9 s; A2' (relevant slow component amplitude) = 2.6 ± 2.4 vs 3.1 ± 2.6 mL x min(-1) x kg(-1) for CM and RS, respectively). CONCLUSIONS: Although there can be a small mixture of breaths allowed by the volume of the snorkel in the transition to exercise, this does not appear to significantly influence the results. Therefore, given the use of an ISD, the RS is a valid instrument for the determination of VO2 kinetics within submaximal exercise.

CYP3A5 and ABCB1 genes influence blood pressure and response to treatment, and their effect is modified by salt.

The permeability-glycoprotein efflux-transporter encoded by the multidrug resistance 1 (ABCB1) gene and the cytochromes P450 3A4/5 encoded by the CYP3A4/5 genes are known to interact in the transport and metabolism of many drugs. Recent data have shown that the CYP3A5 genotypes influence blood pressure and that permeability-glycoprotein activity might influence the activity of the renin-angiotensin system. Hence, these 2 genes may contribute to blood pressure regulation in humans. We analyzed the association of variants of the ABCB1 and CYP3A5 genes with ambulatory blood pressure, plasma renin activity, plasma aldosterone, endogenous lithium clearance, and blood pressure response to treatment in 72 families (373 individuals; 55% women; mean age: 46 years) of East African descent. The ABCB1 and CYP3A5 genes interact with urinary sodium excretion in their effect on ambulatory blood pressure (daytime systolic: P=0.05; nighttime systolic and diastolic: P<0.01), suggesting a gene-gene-environment interaction. The combined action of these genes is also associated with postproximal tubular sodium reabsorption, plasma renin activity, plasma aldosterone, and with an altered blood pressure response to the angiotensin-converting enzyme inhibitor lisinopril (P<0.05). This is the first reported association of the ABCB1 gene with blood pressure in humans and demonstration that genes encoding for proteins metabolizing and transporting drugs and endogenous substrates contribute to blood pressure regulation.

Sexual protection behavior in HIV-positive gay men: testing a modified information-motivation-behavioral skills model.

This study on determinants of sexual protection behavior among HIV-positive gay men used the empirically tested information-motivation-behavioral skills (IMB) model. HIV-specific variables were added to the model to determine factors decisive for condom use with steady and casual partners. Data were collected using an anonymous, standardized self-administered questionnaire. Study participants were recruited at HIV outpatient clinics associated with the Eurosupport Study Group and the Swiss HIV Cohort Study. To identify factors associated with condom use, backward elimination regression analyses were performed. Overall, 838 HIV-infected gay men from 14 European countries were included in this analysis. About 53% of them reported at least one sexual contact with a steady partner; 62.5% had sex with a casual partner during the last 6 months. Forty-three percent always used condoms with steady partners and 44% with casual partners. High self-efficacy and subjective norms in favor of condom-use were associated with increased condom use with casual and steady partners, whereas feeling depressed was associated with decreased condom use with casual partners. Condoms were used less often with HIV-positive partners. Self-efficacy as an important behavioral skill to perform protection behavior was influenced by lower perceived vulnerability, higher subjective norms, and more positive safer sex attitudes. The IMB-model constructs appeared to be valid; however, not all the model predictors could be determined as hypothesized. Besides the original IMB constructs, HIV-specific variables, including sexual partners' serostatus and mental health, explained condom use. Such factors should be considered in clinical interventions to promote "positive prevention."

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Comparison of fundus autofluorescence images acquired by the confocal scanning laser ophthalmoscope (488 nm excitation) and the modified Topcon fundus camera (580 nm excitation).

To compare autofluorescence (AF) images obtained with the confocal scanning laser ophthalmoscope (using the Heidelberg retina angiograph; HRA) and the modified Topcon fundus camera, in a routine clinical setting. A prospective comparative study conducted at the Jules-Gonin Eye Hospital. Fifty-six patients from the medical retina clinic. All patients had complete ophthalmic slit-lamp and fundus examinations, colour and red-free fundus photography, AF imaging with both instruments, and fluorescein angiography. Cataract and fixation were graded clinically. AF patterns were analyzed for healthy and pathological features. Differences of image noise were analyzed by cataract grading and fixation. A total of 105 eyes were included. AF patterns discovered by the retina angiograph and the fundus camera images, respectively, were a dark optic disc in 72 % versus 15 %, a dark fovea in 92 % versus 4 %, sub- and intraretinal fluid visible as hyperautofluorescence on HRA images only, lipid exudates visible as hypoautofluorescence on HRA images only. The same autofluorescent pattern was found on both images for geographic atrophy, retinal pigment changes, drusen and haemorrhage. Image noise was significantly associated with the degree of cataract and/or poor fixation, favouring the fundus camera. Images acquired by the fundus camera before and after fluorescein angiography were identical. Fundus AF images differ according to the technical differences of the instruments used. Knowledge of these differences is important not only for correctly interpreting images, but also for selecting the most appropriate instrument for the clinical situation.

Evaluation of organ-specific peripheral doses after 2-dimensional, 3-dimensional and hybrid intensity modulated radiation therapy for breast cancer based on Monte Carlo and convolution/superposition algorithms: implications for secondary cancer risk assessment.

To make a comprehensive evaluation of organ-specific out-of-field doses using Monte Carlo (MC) simulations for different breast cancer irradiation techniques and to compare results with a commercial treatment planning system (TPS). Three breast radiotherapy techniques using 6MV tangential photon beams were compared: (a) 2DRT (open rectangular fields), (b) 3DCRT (conformal wedged fields), and (c) hybrid IMRT (open conformal+modulated fields). Over 35 organs were contoured in a whole-body CT scan and organ-specific dose distributions were determined with MC and the TPS. Large differences in out-of-field doses were observed between MC and TPS calculations, even for organs close to the target volume such as the heart, the lungs and the contralateral breast (up to 70% difference). MC simulations showed that a large fraction of the out-of-field dose comes from the out-of-field head scatter fluence (>40%) which is not adequately modeled by the TPS. Based on MC simulations, the 3DCRT technique using external wedges yielded significantly higher doses (up to a factor 4-5 in the pelvis) than the 2DRT and the hybrid IMRT techniques which yielded similar out-of-field doses. In sharp contrast to popular belief, the IMRT technique investigated here does not increase the out-of-field dose compared to conventional techniques and may offer the most optimal plan. The 3DCRT technique with external wedges yields the largest out-of-field doses. For accurate out-of-field dose assessment, a commercial TPS should not be used, even for organs near the target volume (contralateral breast, lungs, heart).

Improved Innate and Adaptive Immunostimulation by Genetically Modified HIV-1 Protein Expressing NYVAC Vectors.

Attenuated poxviruses are safe and capable of expressing foreign antigens. Poxviruses are applied in veterinary vaccination and explored as candidate vaccines for humans. However, poxviruses express multiple genes encoding proteins that interfere with components of the innate and adaptive immune response. This manuscript describes two strategies aimed to improve the immunogenicity of the highly attenuated, host-range restricted poxvirus NYVAC: deletion of the viral gene encoding type-I interferon-binding protein and development of attenuated replication-competent NYVAC. We evaluated these newly generated NYVAC mutants, encoding HIV-1 env, gag, pol and nef, for their ability to stimulate HIV-specific CD8 T-cell responses in vitro from blood mononuclear cells of HIV-infected subjects. The new vectors were evaluated and compared to the parental NYVAC vector in dendritic cells (DCs), RNA expression arrays, HIV gag expression and cross-presentation assays in vitro. Deletion of type-I interferon-binding protein enhanced expression of interferon and interferon-induced genes in DCs, and increased maturation of infected DCs. Restoration of replication competence induced activation of pathways involving antigen processing and presentation. Also, replication-competent NYVAC showed increased Gag expression in infected cells, permitting enhanced cross-presentation to HIV-specific CD8 T cells and proliferation of HIV-specific memory CD8 T-cells in vitro. The recombinant NYVAC combining both modifications induced interferon-induced genes and genes involved in antigen processing and presentation, as well as increased Gag expression. This combined replication-competent NYVAC is a promising candidate for the next generation of HIV vaccines.

Enhanced production of indole-3-acetic acid by a genetically modified strain of Pseudomonas fluorescens CHA0 affects root growth of cucumber but does not improve protection of the plant against Pythium root rot

The biocontrol strain CHA0 of Pseudomonas fluorescens produces small amounts of indole-3-acetic acid via the tryptophan side chain oxidase and the tryptophan transaminase pathways. A recombinant plasmid (pME3468) expressing the tryptophan monooxygenase pathway was introduced into strain CHA0; this resulted in elevated synthesis of indole-3-acetic acid in vitro, especially after addition of -tryptophan. In natural soil, strain CHA0/pME3468 increased fresh root weight of cucumber by 17-36%, compared to the effect of strain CHA0; root colonization was about 106 cells per g of root. However, both strains gave similar protection of cucumber against Pythium ultimum. In autoclaved soil, at 6×107 cells per g of root, strain CHA0 stimulated growth of roots and shoots, whereas strain CHA0/pME3468 caused root stunting and strong reduction of plant weight. These results are in agreement with the known effects of exogenous indole-3-acetic acid on plant roots and suggest that in the system examined, indole-3-acetic acid does not contribute to the biocontrol properties of strain CHA0.

New perspectives in the use of ink evidence in forensic science: Part II. Development and testing of mathematical algorithms for the automatic comparison of ink samples analysed by HPTLC

In the first part of this research, three stages were stated for a program to increase the information extracted from ink evidence and maximise its usefulness to the criminal and civil justice system. These stages are (a) develop a standard methodology for analysing ink samples by high-performance thin layer chromatography (HPTLC) in reproducible way, when ink samples are analysed at different time, locations and by different examiners; (b) compare automatically and objectively ink samples; and (c) define and evaluate theoretical framework for the use of ink evidence in forensic context. This report focuses on the second of the three stages. Using the calibration and acquisition process described in the previous report, mathematical algorithms are proposed to automatically and objectively compare ink samples. The performances of these algorithms are systematically studied for various chemical and forensic conditions using standard performance tests commonly used in biometrics studies. The results show that different algorithms are best suited for different tasks. Finally, this report demonstrates how modern analytical and computer technology can be used in the field of ink examination and how tools developed and successfully applied in other fields of forensic science can help maximising its impact within the field of questioned documents.