Chemo-enzymatic saccharification strategy of microalgae chlorella sorokiniana

Biofuel production using microalgae attracted much attention because it can be cultured using CO2 and sunlight. With high carbohydrate content, microalgae have the potential to be used as a fermentation feedstock for bioethanol production. In present work, chemo-enzymatic saccharification of Chlorella sorokiniana microalgae were investigated. Chemical hydrolysis of the biomass followed by enzymatic hydrolysis and was also evaluated the effect of combining the two enzymes and the sequential addition. The effect of α-amylase concentrations was analyzed in ranged between 50 and 8000 U/g of biomass and for amyloglucosidase between 90 and 600 U/g of biomass. The higher concentrations showed the highest conversion of reducing sugars. The α-amylase concentration 8000 U/g of biomass presented a conversion of 43.06 ± 2.92% (w/w), while amyloglucosidase with 600 U/g of biomass obtained 76.57 ± 6.42% (w/w). The combination of two enzymes simultaneously was more efficient than the sequential addition for low enzyme concentrations (α-amylase 50 U/g and amyloglucosidase 90 U/g) with a total reducing sugar of 22.78 ± 3.06 and 16.92 ± 2.06% (w/w), respectively. On the other hand, using the higher enzymes concentrations, no difference was observed between the two addition strategies, 58.9 ± 3.55 and 57.05 ± 2.33% (w/w) for the sequential and simultaneous, respectively. Both strategies didn’t present advantage, since the amyloglucosidase enzyme alone produced slightly higher results. Even thought, the obtained results showed successfully performed saccharification of microalgal biomass and clearly point to microalgae use for saccharification and subsequent bioethanol production.Part of this work has been supported by European governments (INTERREG VA-POCTEP- 2014-2020; 0055_ALGARED_PLUS_5_E) and the Portuguese Science Foundation (FCT) through the grant UID/MAR/00350/2013 to the CIMA of the University of Algarve.info:eu-repo/semantics/publishedVersio

GABAA-Mediated Inhibition Modulates Stimulus-Specific Adaptation in the Inferior Colliculus

The ability to detect novel sounds in a complex acoustic context is crucial for survival. Neurons from midbrain through cortical levels adapt to repetitive stimuli, while maintaining responsiveness to rare stimuli, a phenomenon called stimulus-specific adaptation (SSA). The site of origin and mechanism of SSA are currently unknown. We used microiontophoretic application of gabazine to examine the role of GABAA-mediated inhibition in SSA in the inferior colliculus, the midbrain center for auditory processing. We found that gabazine slowed down the process of adaptation to high probability stimuli but did not abolish it, with response magnitude and latency still depending on the probability of the stimulus. Blocking GABAA receptors increased the firing rate to high and low probability stimuli, but did not completely equalize the responses. Together, these findings suggest that GABAA-mediated inhibition acts as a gain control mechanism that enhances SSA by modifying the responsiveness of the neuron

Effect of family relatedness on characteristics of estimated IBD probabilities in relation to precision of QTL estimates

<p>Abstract</p> <p>Background</p> <p>A random QTL effects model uses a function of probabilities that two alleles in the same or in different animals at a particular genomic position are identical by descent (IBD). Estimates of such IBD probabilities and therefore, modeling and estimating QTL variances, depend on marker polymorphism, strength of linkage and linkage disequilibrium of markers and QTL, and the relatedness of animals in the pedigree. The effect of relatedness of animals in a pedigree on IBD probabilities and their characteristics was examined in a simulation study.</p> <p>Results</p> <p>The study based on nine multi-generational family structures, similar to a pedigree structure of a real dairy population, distinguished by an increased level of inbreeding from zero to 28% across the studied population. Highest inbreeding level in the pedigree, connected with highest relatedness, was accompanied by highest IBD probabilities of two alleles at the same locus, and by lower relative variation coefficients. Profiles of correlation coefficients of IBD probabilities along the marked chromosomal segment with those at the true QTL position were steepest when the inbreeding coefficient in the pedigree was highest. Precision of estimated QTL location increased with increasing inbreeding and pedigree relatedness. A method to assess the optimum level of inbreeding for QTL detection is proposed, depending on population parameters.</p> <p>Conclusions</p> <p>An increased overall relationship in a QTL mapping design has positive effects on precision of QTL position estimates. But the relationship of inbreeding level and the capacity for QTL detection depending on the recombination rate of QTL and adjacent informative marker is not linear.</p

Three-point correlators for giant magnons

Three-point correlation functions in the strong-coupling regime of the AdS/CFT correspondence can be analyzed within a semiclassical approximation when two of the vertex operators correspond to heavy string states having large quantum numbers while the third vertex corresponds to a light state with fixed charges. We consider the case where the heavy string states are chosen to be giant magnon solitons with either a single or two different angular momenta, for various different choices of light string states.Comment: 15 pages. Latex. v2: Misprints corrected. Published versio

Isoforms of U1-70k control subunit dynamics in the human spliceosomal U1 snRNP

Most human protein-encoding genes contain multiple exons that are spliced together, frequently in alternative arrangements, by the spliceosome. It is established that U1 snRNP is an essential component of the spliceosome, in human consisting of RNA and ten proteins, several of which are post- translationally modified and exist as multiple isoforms. Unresolved and challenging to investigate are the effects of these post translational modifications on the dynamics, interactions and stability of the particle. Using mass spectrometry we investigate the composition and dynamics of the native human U1 snRNP and compare native and recombinant complexes to isolate the effects of various subunits and isoforms on the overall stability. Our data reveal differential incorporation of four protein isoforms and dynamic interactions of subunits U1-A, U1-C and Sm-B/B’. Results also show that unstructured post- ranslationally modified C-terminal tails are responsible for the dynamics of Sm-B/B’ and U1-C and that their interactions with the Sm core are controlled by binding to different U1-70k isoforms and their phosphorylation status in vivo. These results therefore provide the important functional link between proteomics and structure as well as insight into the dynamic quaternary structure of the native U1 snRNP important for its function.This work was funded by: BBSRC (OVM), BBSRC and EPSRC (HH and NM), EU Prospects (HH), European Science Foundation (NM), the Royal Society (CVR), and fellowship from JSPS and HFSP (YM and DAPK respectively)

Pattern Recognition in a Bimodal Aquifer Using the Normal-Score Ensemble Kalman Filter

The ensemble Kalman filter (EnKF) is now widely used in diverse disciplines to estimate model parameters and update model states by integrating observed data. The EnKF is known to perform optimally only for multi-Gaussian distributed states and parameters. A new approach, the normal-score EnKF (NS-EnKF), has been recently proposed to handle complex aquifers with non-Gaussian distributed parameters. In this work, we aim at investigating the capacity of the NS-EnKF to identify patterns in the spatial distribution of the model parameters (hydraulic conductivities) by assimilating dynamic observations in the absence of direct measurements of the parameters themselves. In some situations, hydraulic conductivity measurements (hard data) may not be available, which requires the estimation of conductivities from indirect observations, such as piezometric heads. We show how the NS-EnKF is capable of retrieving the bimodal nature of a synthetic aquifer solely from piezometric head data. 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Effect of Biodiversity Changes in Disease Risk: Exploring Disease Emergence in a Plant-Virus System

The effect of biodiversity on the ability of parasites to infect their host and cause disease (i.e. disease risk) is a major question in pathology, which is central to understand the emergence of infectious diseases, and to develop strategies for their management. Two hypotheses, which can be considered as extremes of a continuum, relate biodiversity to disease risk: One states that biodiversity is positively correlated with disease risk (Amplification Effect), and the second predicts a negative correlation between biodiversity and disease risk (Dilution Effect). Which of them applies better to different host-parasite systems is still a source of debate, due to limited experimental or empirical data. This is especially the case for viral diseases of plants. To address this subject, we have monitored for three years the prevalence of several viruses, and virus-associated symptoms, in populations of wild pepper (chiltepin) under different levels of human management. For each population, we also measured the habitat species diversity, host plant genetic diversity and host plant density. Results indicate that disease and infection risk increased with the level of human management, which was associated with decreased species diversity and host genetic diversity, and with increased host plant density. Importantly, species diversity of the habitat was the primary predictor of disease risk for wild chiltepin populations. This changed in managed populations where host genetic diversity was the primary predictor. Host density was generally a poorer predictor of disease and infection risk. These results support the dilution effect hypothesis, and underline the relevance of different ecological factors in determining disease/infection risk in host plant populations under different levels of anthropic influence. These results are relevant for managing plant diseases and for establishing conservation policies for endangered plant species

Maintaining extensivity in evolutionary multiplex networks

In this paper, we explore the role of network topology on maintaining the extensive property of entropy. We study analytically and numerically how the topology contributes to maintaining extensivity of entropy in multiplex networks, i.e. networks of subnetworks (layers), by means of the sum of the positive Lyapunov exponents, HKS, a quantity related to entropy. We show that extensivity relies not only on the interplay between the coupling strengths of the dynamics associated to the intra (short-range) and inter (long-range) interactions, but also on the sum of the intra-degrees of the nodes of the layers. For the analytically treated networks of size N, among several other results, we show that if the sum of the intra-degrees (and the sum of inter-degrees) scales as N?+1, ? > 0, extensivity can be maintained if the intra-coupling (and the inter-coupling) strength scales as N??, when evolution is driven by the maximisation of HKS. We then verify our analytical results by performing numerical simulations in multiplex networks formed by electrically and chemically coupled neurons

A straightforward multiallelic significance test for the Hardy-Weinberg equilibrium law

Much forensic inference based upon DNA evidence is made assuming Hardy-Weinberg Equilibrium (HWE) for the genetic loci being used. Several statistical tests to detect and measure deviation from HWE have been devised, and their limitations become more obvious when testing for deviation within multiallelic DNA loci. The most popular methods-Chi-square and Likelihood-ratio tests-are based on asymptotic results and cannot guarantee a good performance in the presence of low frequency genotypes. Since the parameter space dimension increases at a quadratic rate on the number of alleles, some authors suggest applying sequential methods, where the multiallelic case is reformulated as a sequence of “biallelic” tests. However, in this approach it is not obvious how to assess the general evidence of the original hypothesis; nor is it clear how to establish the significance level for its acceptance/rejection. In this work, we introduce a straightforward method for the multiallelic HWE test, which overcomes the aforementioned issues of sequential methods. The core theory for the proposed method is given by the Full Bayesian Significance Test (FBST), an intuitive Bayesian approach which does not assign positive probabilities to zero measure sets when testing sharp hypotheses. We compare FBST performance to Chi-square, Likelihood-ratio and Markov chain tests, in three numerical experiments. The results suggest that FBST is a robust and high performance method for the HWE test, even in the presence of several alleles and small sample sizes