Cytokinin dynamics in xylem sap and leaves of fruiting and de-fruited sunflower hybrids of contrasting post-anthesis canopy senescence patterns during flowering and grain-filling

Plant and Soil - To determine whether xylem sap and leaf cytokinin levels were associated with live root length density (LRLD) and leaf senescence, these variables were measured in intact (control)...     

Carbon Sequestration of Caesalpinia platyloba S. Watt (Leguminosae) (Lott 1985) in the Tropical Deciduous Forest

Caesalpinia platyloba was evaluated as an alternative for the retention of atmospheric carbon and as a feasible and viable economic activity in terms of income for tropical deciduous forest (TDF) peasants in the carbon markets. A total of 110 trees of C. platyloba from plantations and a TDF in the Northwest of Mexico were sampled. Growth (increase in height, diameter, and volume curves) was adjusted to assess their growth. Growth of individuals (height, diameter at breast height [DBH], age, and tree crown cover) was recorded. The Schumacher model (H = β₀e^β₁•E-1), by means of the guided curve method, was used to adjust growth models. Information analysis was made through the non-linear procedure with the multivariate secant or false position (DUD) method using the SAS software. Growth and increase models revealed acceptable adjustments (pseudo R²>0.8). C. platyloba reaches >8m of height with 12cm in diameter and 550cm³ of volume, presenting the highest increase at 11 years considered as basal age. Highest significant density of wood was in good quality sites (0.80g•cm^-3), with a carbon content (average of 99.15tC•ha^-1) at the highest density of 2500 trees•ha^-1 (without thinning). Average incomes of US$483.33tC•ha^-1 are expected. The profitability values (NPW = US$81,646.65, IRR = 472%, and B/C = 0.82) for C. platyloba make its cultivation a viable and profitable activity, considering a management scheme of the income derived from wood selling and from carbon credits.     

Plasma Biomarkers Discriminate Clinical Forms of Multiple Sclerosis

Multiple sclerosis, the most common cause of neurological disability in young population after trauma, represents a significant public health burden. Current challenges associated with management of multiple sclerosis (MS) patients stem from the lack of biomarkers that might enable stratification of the different clinical forms of MS and thus prompt treatment for those patients with progressive MS, for whom there is currently no therapy available. In the present work we analyzed a set of thirty different plasma cytokines, chemokines and growth factors present in circulation of 129 MS patients with different clinical forms (relapsing remitting, secondary progressive and primary progressive MS) and 53 healthy controls, across two independent cohorts. The set of plasma analytes was quantified with Luminex xMAP technology and their predictive power regarding clinical outcome was evaluated both individually using ROC curves and in combination using logistic regression analysis. Our results from two independent cohorts of MS patients demonstrate that the divergent clinical and histology-based MS forms are associated with distinct profiles of circulating plasma protein biomarkers, with distinct signatures being composed of chemokines and growth/angiogenic factors. With this work, we propose that an evaluation of a set of 4 circulating biomarkers (HGF, Eotaxin/CCL11, EGF and MIP-1β/CCL4) in MS patients might serve as an effective tool in the diagnosis and more personalized therapeutic targeting of MS patients.     

Can transposable element copy number distribution parameters be estimated from natural populations of Drosophila melanogaster?

The copy frequency distribution of a transposable element family in a Drosophila melanogaster natural population is generally characterised by the values of the Charlesworths' model parameters α and β (Charlesworth & Charlesworth, 1983). The estimation of these parameters is made using the observed distribution of the occupied sites in a population sample. Several results have been interpreted as due either to the influence of stochastic factors or to deterministic factors (transposition, excision, selection…). The accuracy of this method was tested by estimations performed on samples from simulated populations. The results show that with the sample size usually used for natural population studies, the confidence intervals are too large to reasonably deduce either the element copy number distribution or the values of transposition and excision rate and selective coefficients.     

The "Alzheimer's disease signature": potential perspectives for novel biomarkers

Alzheimer's disease is a progressive and neurodegenerative disorder which involves multiple molecular mechanisms. Intense research during the last years has accumulated a large body of data and the search for sensitive and specific biomarkers has undergone a rapid evolution. However, the diagnosis remains problematic and the current tests do not accurately detect the process leading to neurodegeneration. Biomarkers discovery and validation are considered the key aspects to support clinical diagnosis and provide discriminatory power between different stages of the disorder. A considerable challenge is to integrate different types of data from new potent approach to reach a common interpretation and replicate the findings across studies and populations. Furthermore, long-term clinical follow-up and combined analysis of several biomarkers are among the most promising perspectives to diagnose and manage the disease. The present review will focus on the recent published data providing an updated overview of the main achievements in the genetic and biochemical research of the Alzheimer's disease. We also discuss the latest and most significant results that will help to define a specific disease signature whose validity might be clinically relevant for future AD diagnosis.     

Simulation of Y-chromosomal haplotype data

The non-recombining nature of the Y-chromosome determines the non-independence of alleles between loci. The evolution of short tandem repeat (STR) loci in the Y-chromosome is the result of different factors such as differential mutation rates, mutation modes, gene conversion, selection and demographic processes. The degree of correlation between loci is dependent on the magnitude of these processes. The simulation of data is a routine tool used for testing hypotheses in population and evolutionary studies. The most basic parameters hitherto used in lineage haplotype simulations are the allele frequency distributions and mutation rates, assuming either full independence or linkage between loci. In this study we introduce use of the Spearman correlation coefficient to estimate the degree of dependence between non-recombining loci. Then, both the interdependence between loci and the allele frequency distributions at multi-allelic loci are incorporated in an algorithm for simulating haplotypes. We illustrate the method using published and unpublished Y-chromosome STR data.     

Importance of the cultivation history for the response of Escherichia coli to oscillations in scale-down experiments

Bioprocess and Biosystems Engineering - Large-scale bioreactors are inhomogeneous systems, in which the fluid phase expresses concentration gradients. They depend on the mass transfer and fluid...