Adubação mineral com cobalto e molibdênio na cultura da soja

Altas produtividades de soja requerem grandes quantidades de nitrogênio, que podem ser obtidas principalmente, a partir da fixação simbiótica. No entanto, há possibilidade da eficiência desse processo biológico ser prejudicada pela deficiência de micronutrientes, especialmente de cobalto e molibdênio. Nesse contexto, objetivou-se com o presente trabalho avaliar a eficiência agronômica e a forma de aplicação de adubação mineral com cobalto e molibdênio na cultura da soja. Para tanto, a cultivar CD-206 foi submetida a diferentes tratamentos que consistiram da combinação entre aplicação de Co e Mo via tratamento de sementes e adubação foliar. As características agronômicas avaliadas foram o número de nódulos, massa seca da parte aérea, massa seca de raiz, número de vagens, número de grãos, massa de mil grãos e produção de grãos. A aplicação de molibdênio e cobalto via sementes e/ ou adubação foliar no estádio V4 (terceira folha trifoliolada completamente desenvolvida, quarto nó) promoveram incrementos significativos no rendimento da cultura. Respostas positivas ao cobalto e molibdênio também foram observadas no número de nódulos, vagens e grãos, com aumentos de até 240 kg ha-1 no rendimento da cultura. Os parâmetros agronômicos avaliados foram afetados positivamente pela aplicação de Co e Mo, principalmente quanto aplicado tanto via semente como foliar (TS + V4), inclusive para a produtividade de grãos. A forma de aplicação não foi significativamente distinta, ou seja, tanto a aplicação via semente como via foliar foram eficientes no fornecimento destes nutrientes para a cultura da soja.

Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.

Genes involved in thoracic exoskeleton formation during the pupal-to-adult molt in a social insect model, Apis mellifera

Background: The insect exoskeleton provides shape, waterproofing, and locomotion via attached somatic muscles. The exoskeleton is renewed during molting, a process regulated by ecdysteroid hormones. The holometabolous pupa transforms into an adult during the imaginal molt, when the epidermis synthe3sizes the definitive exoskeleton that then differentiates progressively. An important issue in insect development concerns how the exoskeletal regions are constructed to provide their morphological, physiological and mechanical functions. We used whole-genome oligonucleotide microarrays to screen for genes involved in exoskeletal formation in the honeybee thoracic dorsum. Our analysis included three sampling times during the pupal-to-adult molt, i.e., before, during and after the ecdysteroid-induced apolysis that triggers synthesis of the adult exoskeleton. Results: Gene ontology annotation based on orthologous relationships with Drosophila melanogaster genes placed the honeybee differentially expressed genes (DEGs) into distinct categories of Biological Process and Molecular Function, depending on developmental time, revealing the functional elements required for adult exoskeleton formation. Of the 1,253 unique DEGs, 547 were upregulated in the thoracic dorsum after apolysis, suggesting induction by the ecdysteroid pulse. The upregulated gene set included 20 of the 47 cuticular protein (CP) genes that were previously identified in the honeybee genome, and three novel putative CP genes that do not belong to a known CP family. In situ hybridization showed that two of the novel genes were abundantly expressed in the epidermis during adult exoskeleton formation, strongly implicating them as genuine CP genes. Conserved sequence motifs identified the CP genes as members of the CPR, Tweedle, Apidermin, CPF, CPLCP1 and Analogous-to-Peritrophins families. Furthermore, 28 of the 36 muscle-related DEGs were upregulated during the de novo formation of striated fibers attached to the exoskeleton. A search for cis-regulatory motifs in the 5′-untranslated region of the DEGs revealed potential binding sites for known transcription factors. Construction of a regulatory network showed that various upregulated CP- and muscle-related genes (15 and 21 genes, respectively) share common elements, suggesting co-regulation during thoracic exoskeleton formation. Conclusions: These findings help reveal molecular aspects of rigid thoracic exoskeleton formation during the ecdysteroid-coordinated pupal-to-adult molt in the honeybee.

Biological evaluation of the bone healing process after application of two potentially osteogenic proteins: an animal experimental model

doi: 10.1111/j.1741-2358.2011.00526.x Biological evaluation of the bone healing process after application of two potentially osteogenic proteins: an animal experimental model Objective: The aim of this work was to analyse qualitatively and quantitatively the newly formed bone after insertion of rhBMP-2 and protein extracted from Hevea brasiliensis (P-1), associated or not with a carrier in critical bone defects created in Wistar rat calvarial bone, using histological and histomorphometrical analyses. Materials and methods: Eighty-four male Wistar rats were used, divided into two groups, according to the period of time until the sacrifice (2 and 6 weeks). Each one of these groups was subdivided into six groups with seven animals each, according to the treatments: (1) 5 mu g of pure rhBMP-2, (2) 5 mu g of rhBMP-2/monoolein gel, (3) pure monoolein gel, (4) 5 mu g of pure P-1, (5) 5 mu g of P-1/monoolein gel and (6) critical bone defect controls. The animals were euthanised and the calvarial bone tissue removed for histological and histomorphometrical analyses. Result and conclusion: The results showed an improvement in the bone healing process using the rhBMP-2 protein, associated or not with a material carrier in relation to the other groups, and this process demonstrated to be time dependent.

Assessing the gain of biological data integration in gene networks inference

Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

Discriminating Different Classes of Biological Networks by Analyzing the Graphs Spectra Distribution

The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e. g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed.

Effects of extrusion, lipid concentration and purity on physico-chemical and biological properties of cationic liposomes for gene vaccine applications

We developed cationic liposomes containing DNA through a conventional process involving steps of (i) preformation of liposomes, (ii) extrusion, (iii) drying and rehydration and (iv) DNA complexation. Owing to its high prophylactic potentiality against tuberculosis, which had already been demonstrated in preclinical assays, we introduced modifications into the conventional process towards getting a simpler and more economical process for further scale-up. Elimination of the extrusion step, increasing the lipid concentration (from 16 to 64 mM) of the preformed liposomes and using good manufacturing practice bulk lipids (96-98% purity) instead of analytical grade purity lipids (99.9-100%) were the modifications studied. The differences in the physico-chemical properties, such as average diameter, zeta potential, melting point and morphology of the liposomes prepared through the modified process, were not as significant for the biological properties, such as DNA loading on the cationic liposomes, and effective immune response in mice after immunisation as the control liposomes prepared through the conventional process. Beneficially, the modified process increased productivity by 22% and reduced the cost of raw material by 75%.

EX-SITU BIOREMEDIATION OF BRAZILIAN SOIL CONTAMINATED WITH PLASTICIZERS PROCESS WASTES

The aim of this research was to evaluate the bioremediation of a soil contaminated with wastes from a plasticizers industry, located in Sao Paulo, Brazil. A 100-kg soil sample containing alcohols, adipates and phthalates was treated in an aerobic slurry-phase reactor using indigenous and acclimated microorganisms from the sludge of a wastewater treatment plant of the plasticizers industry (11gVSS kg(-1) dry soil), during 120 days. The soil pH and temperature were not corrected during bioremediation; soil humidity was corrected weekly to maintain 40%. The biodegradation of the pollutants followed first-order kinetics; the removal efficiencies were above 61% and, among the analyzed plasticizers, adipate was removed to below the detection limit. Biological molecular analysis during bioremediation revealed a significant change in the dominant populations initially present in the reactor.

Silicon(IV) phthalocyanine-loaded-nanoparticles for application in photodynamic process

The aim of this study was to evaluate the potential application of biodegradable nanoparticles containing a photosensitizer in photodynamic therapy. The poly (D,L lactic-co-glycolic acid) nanoparticles were studied by steady-state techniques, time-resolved fluorescence, and laser flash photolysis. The external morphology of the nanoparticles was established by scanning electron microscopy, and the biological activity was evaluated by in vitro cell culture by 3-(4,5 dimethylthiazol-2,5 biphenyl) tetrazolium bromide assay. The particles were spherical in shape exhibiting a 435 nm diameter with a low tendency to aggregate. The loading efficiency was 77%. The phthalocyanine-loaded-nanoparticles maintained their photophysical behavior after encapsulation. The cellular viability was determined, obtaining 70% of cellular death. All the performed physical-chemical, photophysical, and photobiological measurements indicated that the phthalocyanine-loaded-nanoparticles are a promising drug delivery system for photodynamic therapy and photoprocesses. (C) 2012 Laser Institute of America.

The promoter of filamentation (POF1) protein from Saccharomyces cerevisiae is an ATPase involved in the protein quality control process

Background: The gene YCL047C, which has been renamed promoter of filamentation gene (POF1), has recently been described as a cell component involved in yeast filamentous growth. The objective of this work is to understand the molecular and biological function of this gene. Results: Here, we report that the protein encoded by the POF1 gene, Pof1p, is an ATPase that may be part of the Saccharomyces cerevisiae protein quality control pathway. According to the results, Δpof1 cells showed increased sensitivity to hydrogen peroxide, tert-butyl hydroperoxide, heat shock and protein unfolding agents, such as dithiothreitol and tunicamycin. Besides, the overexpression of POF1 suppressed the sensitivity of Δpct1, a strain that lacks a gene that encodes a phosphocholine cytidylyltransferase, to heat shock. In vitro analysis showed, however, that the purified Pof1p enzyme had no cytidylyltransferase activity but does have ATPase activity, with catalytic efficiency comparable to other ATPases involved in endoplasmic reticulum-associated degradation of proteins (ERAD). Supporting these findings, co-immunoprecipitation experiments showed a physical interaction between Pof1p and Ubc7p (an ubiquitin conjugating enzyme) in vivo. Conclusions: Taken together, the results strongly suggest that the biological function of Pof1p is related to the regulation of protein degradation.

Ex-situ bioremediation of Brazilian soil contaminated with plasticizers process wastes

The aim of this research was to evaluate the bioremediation of a soil contaminated with wastes from a plasticizers industry, located in São Paulo, Brazil. A 100-kg soil sample containing alcohols, adipates and phthalates was treated in an aerobic slurry-phase reactor using indigenous and acclimated microorganisms from the sludge of a wastewater treatment plant of the plasticizers industry (11gVSS kg-1 dry soil), during 120 days. The soil pH and temperature were not corrected during bioremediation; soil humidity was corrected weekly to maintain 40%. The biodegradation of the pollutants followed first-order kinetics; the removal efficiencies were above 61% and, among the analyzed plasticizers, adipate was removed to below the detection limit. Biological molecular analysis during bioremediation revealed a significant change in the dominant populations initially present in the reactor.

Biological evolution of replicator systems: towards a quantitative approach

The aim of this work is to study the features of a simple replicator chemical model of the relation between kinetic stability and entropy production under the action of external perturbations. We quantitatively explore the different paths leading to evolution in a toy model where two independent replicators compete for the same substrate. To do that, the same scenario described originally by Pross (J Phys Org Chem 17:312–316, 2004) is revised and new criteria to define the kinetic stability are proposed. Our results suggest that fast replicator populations are continually favored by the effects of strong stochastic environmental fluctuations capable to determine the global population, the former assumed to be the only acting evolution force. We demonstrate that the process is continually driven by strong perturbations only, and that population crashes may be useful proxies for these catastrophic environmental fluctuations. As expected, such behavior is particularly enhanced under very large scale perturbations, suggesting a likely dynamical footprint in the recovery patterns of new species after mass extinction events in the Earth’s geological past. Furthermore, the hypothesis that natural selection always favors the faster processes may give theoretical support to different studies that claim the applicability of maximum principles like the Maximum Metabolic Flux (MMF) or Maximum Entropy Productions Principle (MEPP), seen as the main goal of biological evolution.