Vegetative growth response of beets and lettuce to stored human urine

ArticleIn this work, we present the experimental results of the effect of stored human urine (SHU) on the growth of beets (Beta vulgaris L) and lettuce (Lactuca sativaL). We apply different amounts of SHU according to the recommended dose of nitrogen, considering soil from farmland and vermiculite as substrates. The last allows us to determine with high precision the isolated effect of SHU over the vegetative development of beet plants, without considering other nutrients present in common soils. Experimental results demonstrate that the application of SHU has no significant effects on lettuce vegetative growth under our soil conditions. In contrast, SHU can be used successfully as a fertilizer of beets. The optimum dose was found at 120kgN ha-1and resulted in average dry weight of 125g. However, if the dose exceeds the optimum levels, the growth of the plant is inhibited. Beets fertilized with SHU does not pose any hygienic risk for human consumption. Our findings represent a promising alternative to propose expanding the use of SHU as fertilizer in medium-sized greenhouses and to provide benefits to families in rural areas, with little or no available water supplies

Selección de establecimientos escolares en el departamento de Caazapá aplicando programación matemática

Las decisiones en infraestructura educativa en el departamento de Caazapá, como en otras regiones del Paraguay, generan algunos inconvenientes. En particular, la distribución de alumnos respecto a los establecimientos escolares presenta cierta inconsistencia, esto se ve reflejado en sobrecostos por reparación o por mantener aulas/escuelas abiertas. Actualmente, existen 469 escuelas en este departamento, y en promedio se tiene 83 alumnos por escuela. Igualmente, se debe considerar que el 66% de las escuelas tienen menos de 25 alumnos, y se puede inferir que existe una subutilización de la infraestructura y de los costos operativos asociados. Un dato no menor, es que el 1% de las escuelas tiene en promedio más de 49 estudiantes por aula, muy por arriba del promedio en todo el departamento. El diseño de la red educativa es ineficiente, con una concentración de escuelas que excede las necesidades en determinadas zonas y es deficitaria en otras; esto tiene como consecuencia problemas de gestión de recursos y altos costos de inversión para mejorar y mantener las escuelas en distritos que no cuentan con el presupuesto suficiente. Es imperativa la aplicación de estrategias que estén orientadas a la optimización de los recursos disponibles. En este estudio, se identificó un modelo de programación lineal entera mixta (PLEM) existen-te en la literatura, para seleccionar establecimientos escolares a fin de minimizar los costos operativos, de inversión en infraestructura y de transporte. Se combinaron técnicas de investigación operativa con sistemas de información geográfica para analizar el problema e interpretar los resultados. Los resultados muestran oportunidades de mejora en el diseño de la red educativa en los 11 distritos del departamento de Caazapá, y es posible reducir los costos de inversión al consolidar la demanda en menos establecimientos de los que ya existen actualmente. En la selección y distribución de establecimientos escolares, propuesta como solución, se reduce al 50% el número de escuelas, disminuyendo también los costos de inversión y costos operativos. Por otra parte, será necesario incurrir en costos de transporte que representarán el 7% de los costos. Finalmente, con esta propuesta, se reduce el costo estimado para el diseño de la red de infraestructura del sistema educativo en el departamento de Caazapá en un 24% con respecto al costo actual.Sociedad Argentina de Informática e Investigación Operativ

Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge.

Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations. The results of the challenge suggest that methods selected by the 14 teams participating in the challenge can provide high correlations between estimated and ground-truth connectivity weights, in complex numerical environments. Additionally, the methods used by the participating teams were able to accurately identify the binary connectivity of the numerical dataset. However, specific false positive and false negative connections were consistently estimated across all methods. Although the challenge dataset doesn't capture the complexity of a real brain, it provided unique data with known macrostructure and microstructure ground-truth properties to facilitate the development of connectivity estimation methods

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ABSTRACT. The tumor necrosis factor-alpha (TNF-α) gene plays an important role in cell proliferation, differentiation, apoptosis, lipid metabolism, coagulation, insulin resistance, and endothelial function. Polymorphisms of TNF-α have been associated with cancer. We examined the role of the -308G>A polymorphism in this gene by comparing the genotypes of 294 healthy Mexican women with those of 465 Mexican women with breast cancer. The observed genotype frequencies for controls and breast cancer patients were 1 and 14% for AA, 13 and 21% for GA, and 86 and 65% for GG, respectively. We found that the odds ratio (OR) for AA genotype was 2.4, with a 95% confidence interval (95%CI) of 5.9-101.1 (P = 0.0001). The association was also evident when comparing the distribution of the AA-GA genotype in patients in the following categories: 1) premenopause and obesity I (OR = 3.5, 95%CI = 1.3-9.3, P = 0.008), 2) Her-2 neu and tumor stage I-II (OR = 2.5, 95%CI = 1.31-4.8, P = 0.004), 3) premenopause and tumor stage III-IV (OR = 1.7, 95%CI = 1.0-2.9, P = 0.034), 4) chemotherapy non-response and abnormal hematocrit (OR = 2.4, 95%CI = 1.2-4.8, P = 0.015), 5) body mass index and Her-2 neu and III-IV tumor stage (OR = 2.8, 95%CI = 1.2-6.6, P = 0.016), and 6) nodule metastasis and K-I67 (OR = 4.0, 95%CI = 1.01-15.7, P = 0.038). We concluded that the genotypes AA-GA of the -308G>A polymorphism in TNF-α significantly contribute to breast cancer susceptibility in the analyzed sample from the Mexican population

Identification of Plasmodium vivax Proteins with Potential Role in Invasion Using Sequence Redundancy Reduction and Profile Hidden Markov Models

BACKGROUND: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. RESULTS: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. CONCLUSIONS: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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Measurements of the νμ\nu_{\mu} and νˉμ\bar{\nu}_{\mu}-induced Coherent Charged Pion Production Cross Sections on 12C^{12}C by the T2K experiment

We report an updated measurement of the $\nu_{\mu}$-induced, and the first measurement of the $\bar{\nu}_{\mu}$-induced coherent charged pion production cross section on $^{12}C$ nuclei in the T2K experiment. This is measured in a restricted region of the final-state phase space for which $p_{\mu,\pi} > 0.2$ GeV, $\cos(\theta_{\mu}) > 0.8$ and $\cos(\theta_{\pi}) > 0.6$, and at a mean (anti)neutrino energy of 0.85 GeV using the T2K near detector. The measured $\nu_{\mu}$ CC coherent pion production flux-averaged cross section on $^{12}C$ is $(2.98 \pm 0.37 (stat.) \pm 0.31 (syst.) \substack{ +0.49 \\ -0.00 } \mathrm{ (Q^2\,model)}) \times 10^{-40}~\mathrm{cm}^{2}$. The new measurement of the $\bar{\nu}_{\mu}$-induced cross section on $^{12}{C}$ is $(3.05 \pm 0.71 (stat.) \pm 0.39 (syst.) \substack{ +0.74 \\ -0.00 } \mathrm{(Q^2\,model)}) \times 10^{-40}~\mathrm{cm}^{2}$. The results are compatible with both the NEUT 5.4.0 Berger-Sehgal (2009) and GENIE 2.8.0 Rein-Sehgal (2007) model predictions

Basin-wide variations in Amazon forest structure and function are mediated by both soils and climate

Forest structure and dynamics vary across the Amazon Basin in an east-west gradient coincident with variations in soil fertility and geology. This has resulted in the hypothesis that soil fertility may play an important role in explaining Basin-wide variations in forest biomass, growth and stem turnover rates. Soil samples were collected in a total of 59 different forest plots across the Amazon Basin and analysed for exchangeable cations, carbon, nitrogen and pH, with several phosphorus fractions of likely different plant availability also quantified. Physical properties were additionally examined and an index of soil physical quality developed. Bivariate relationships of soil and climatic properties with above-ground wood productivity, stand-level tree turnover rates, above-ground wood biomass and wood density were first examined with multivariate regression models then applied. Both forms of analysis were undertaken with and without considerations regarding the underlying spatial structure of the dataset. Despite the presence of autocorrelated spatial structures complicating many analyses, forest structure and dynamics were found to be strongly and quantitatively related to edaphic as well as climatic conditions. Basin-wide differences in stand-level turnover rates are mostly influenced by soil physical properties with variations in rates of coarse wood production mostly related to soil phosphorus status. Total soil P was a better predictor of wood production rates than any of the fractionated organic- or inorganic-P pools. This suggests that it is not only the immediately available P forms, but probably the entire soil phosphorus pool that is interacting with forest growth on longer timescales. A role for soil potassium in modulating Amazon forest dynamics through its effects on stand-level wood density was also detected. Taking this into account, otherwise enigmatic variations in stand-level biomass across the Basin were then accounted for through the interacting effects of soil physical and chemical properties with climate. A hypothesis of self-maintaining forest dynamic feedback mechanisms initiated by edaphic conditions is proposed. It is further suggested that this is a major factor determining endogenous disturbance levels, species composition, and forest productivity across the Amazon Basin. © 2012 Author(s). CC Attribution 3.0 License

Amazon tree dominance across forest strata

The forests of Amazonia are among the most biodiverse plant communities on Earth. Given the immediate threats posed by climate and land-use change, an improved understanding of how this extraordinary biodiversity is spatially organized is urgently required to develop effective conservation strategies. Most Amazonian tree species are extremely rare but a few are common across the region. Indeed, just 227 ‘hyperdominant’ species account for >50% of all individuals >10 cm diameter at 1.3 m in height. Yet, the degree to which the phenomenon of hyperdominance is sensitive to tree size, the extent to which the composition of dominant species changes with size class and how evolutionary history constrains tree hyperdominance, all remain unknown. Here, we use a large floristic dataset to show that, while hyperdominance is a universal phenomenon across forest strata, different species dominate the forest understory, midstory and canopy. We further find that, although species belonging to a range of phylogenetically dispersed lineages have become hyperdominant in small size classes, hyperdominants in large size classes are restricted to a few lineages. Our results demonstrate that it is essential to consider all forest strata to understand regional patterns of dominance and composition in Amazonia. More generally, through the lens of 654 hyperdominant species, we outline a tractable pathway for understanding the functioning of half of Amazonian forests across vertical strata and geographical locations