Metabolic engineering of beta-oxidation in Penicillium chrysogenum for improved semi-synthetic cephalosporin biosynthesis

Industrial production of semi-synthetic cephalosporins by Penicillium chrysogenum requires supplementation of the growth media with the side-chain precursor adipic acid. In glucose-limited chemostat cultures of P. chrysogenum, up to 88% of the consumed adipic acid was not recovered in cephalosporinrelated products, but used as an additional carbon and energy source for growth. This low efficiency of side-chain precursor incorporation provides an economic incentive for studying and engineering the metabolism of adipic acid in P. cluysogenum. Chemostat-based transcriptome analysis in the presence and absence of adipic acid confirmed that adipic acid metabolism in this fungus occurs via beta-oxidation. A set of 52 adipate-responsive genes included six putative genes for acyl-CoA oxidases and dehydrogenases, enzymes responsible for the first step of beta-oxidation. Subcellular localization of the differentially expressed acyl-CoA oxidases and dehydrogenases revealed that the oxidases were exclusively targeted to peroxisomes, while the dehydrogenases were found either in peroxisomes or in mitochondria. Deletion of the genes encoding the peroxisomal acyl-CoA oxidase Pc20g01800 and the mitochondrial acyl-CoA dehydrogenase Pc20g07920 resulted in a 1.6- and 3.7-fold increase in the production of the semi-synthetic cephalosporin intermediate adipoyl-6-APA, respectively. The deletion strains also showed reduced adipate consumption compared to the reference strain, indicating that engineering of the first step of beta-oxidation successfully redirected a larger fraction of adipic acid towards cephalosporin biosynthesis. (C) 2012 Elsevier Inc. All rights reserved.

GEDI: a user-friendly toolbox for analysis of large-scale gene expression data

Abstract Background Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, and software implementations that require advanced computer programming skills. Researchers from other areas may experience difficulties when they attempting to use those methods in their research. Here we present an user-friendly toolbox which allows large-scale gene expression analysis to be carried out by biomedical researchers with limited programming skills. Results Here, we introduce an user-friendly toolbox called GEDI (Gene Expression Data Interpreter), an extensible, open-source, and freely-available tool that we believe will be useful to a wide range of laboratories, and to researchers with no background in Mathematics and Computer Science, allowing them to analyze their own data by applying both classical and advanced approaches developed and recently published by Fujita et al. Conclusion GEDI is an integrated user-friendly viewer that combines the state of the art SVR, DVAR and SVAR algorithms, previously developed by us. It facilitates the application of SVR, DVAR and SVAR, further than the mathematical formulas present in the corresponding publications, and allows one to better understand the results by means of available visualizations. Both running the statistical methods and visualizing the results are carried out within the graphical user interface, rendering these algorithms accessible to the broad community of researchers in Molecular Biology.

Longitudinal familial analysis of blood pressure involving parametric (co)variance functions

Abstract Background For analyzing longitudinal familial data we adopted a log-linear form to incorporate heterogeneity in genetic variance components over the time, and additionally a serial correlation term in the genetic effects at different levels of ages. Due to the availability of multiple measures on the same individual, we permitted environmental correlations that may change across time. Results Systolic blood pressure from family members from the first and second cohort was used in the current analysis. Measures of subjects receiving hypertension treatment were set as censored values and they were corrected. An initial check of the variance and covariance functions proposed for analyzing longitudinal familial data, using empirical semi-variogram plots, indicated that the observed trait dispersion pattern follows the assumptions adopted. Conclusion The corrections for censored phenotypes based on ordinary linear models may be an appropriate simple model to correct the data, ensuring that the original variability in the data was retained. In addition, empirical semi-variogram plots are useful for diagnosis of the (co)variance model adopted.

Suicide rates and income in São Paulo and Brazil: a temporal and spatial epidemiologic analysis from 1996 to 2008

Abstract Background In a classical study, Durkheim noted a direct relation between suicide rates and wealth in the XIX century France. Since that time, several studies have verified this relationship. It is known that suicide rates are associated with income, although the direction of this association varies worldwide. Brazil presents a heterogeneous distribution of income and suicide across its territory; however, evaluation for an association between these variables has shown mixed results. We aimed to evaluate the relationship between suicide rates and income in Brazil, State of São Paulo (SP), and City of SP, considering geographical area and temporal trends. Methods Data were extracted from the National and State official statistics departments. Three socioeconomic areas were considered according to income, from the wealthiest (area 1) to the poorest (area 3). We also considered three regions: country-wide (27 Brazilian States and 558 Brazilian micro-regions), state-wide (645 counties of SP State), and city-wide (96 districts of SP city). Relative risks (RR) were calculated among areas 1, 2, and 3 for all regions, in a cross-sectional approach. Then, we used Joinpoint analysis to explore the temporal trends of suicide rates and SaTScan to investigate geographical clusters of high/low suicide rates across the territory. Results Suicide rates in Brazil, the State of SP, and the city of SP were 6.2, 6.6, and 5.4 per 100,000, respectively. Taking suicide rates of the poorest area (3) as reference, the RR for the wealthiest area was 1.64, 0.88, and 1.65 for Brazil, State of SP, and city of SP, respectively (p for trend <0.05 for all analyses). Spatial cluster of high suicide rates were identified at Brazilian southern (RR = 2.37), state of SP western (RR = 1.32), and city of SP central (RR = 1.65) regions. A direct association between income and suicide were found for Brazil (OR = 2.59) and the city of SP (OR = 1.07), and an inverse association for the state of SP (OR = 0.49). Conclusions Temporospatial analyses revealed higher suicide rates in wealthier areas in Brazil and the city of SP and in poorer areas in the State of SP. We further discuss the role of socioeconomic characteristics for explaining these discrepancies and the importance of our findings in public health policies. Similar studies in other Brazilian States and developing countries are warranted.

Morphometric analysis of the placenta in the New World mouse Necromys lasiurus (Rodentia, Cricetidae): a comparison of placental development in cricetids and murids

Background: Stereology is an established method to extrapolate three-dimensional quantities from two-dimensional images. It was applied to placentation in the mouse, but not yet for other rodents. Herein, we provide the first study on quantitative placental development in a sigmodontine rodent species with relatively similar gestational time. Placental structure was also compared to the mouse, in order to evaluate similarities and differences in developmental patterns at the end of gestation. Methods: Fetal and placental tissues of Necromys lasiurus were collected and weighed at 3 different stages of gestation (early, mid and late gestation) for placental stereology. The total and relative volumes of placenta and of its main layers were investigated. Volume fractions of labyrinth components were quantified by the One Stop method in 31 placentae collected from different individuals, using the Mercator® software. Data generated at the end of gestation from N. lasiurus placentae were compared to those of Mus musculus domesticus obtained at the same stage. Results: A significant increase in the total absolute volumes of the placenta and its main layers occurred from early to mid-gestation, followed by a reduction near term, with the labyrinth layer becoming the most prominent area. Moreover, at the end of gestation, the total volume of the mouse placenta was significantly increased compared to that of N. lasiurus although the proportions of the labyrinth layer and junctional zones were similar. Analysis of the volume fractions of the components in the labyrinth indicated a significant increase in fetal vessels and sinusoidal giant cells, a decrease in labyrinthine trophoblast whereas the proportion of maternal blood space remained stable in the course of gestation. On the other hand, in the mouse, volume fractions of fetal vessels and sinusoidal giant cells decreased whereas the volume fraction of labyrinthine trophoblast increased compared to N. lasiurus placenta. Conclusions: Placental development differed between N. lasiurus and M. musculus domesticus. In particular, the low placental efficiency in N. lasiurus seemed to induce morphological optimization of fetomaternal exchanges. In conclusion, despite similar structural aspects of placentation in these species, the quantitative dynamics showed important differences.

Hydro-physical characterization of soils under tropical semi-deciduous forest

The study of the hydro-physical behavior in soils using toposequences is of great importance for better understanding the soil, water and vegetation relationships. This study aims to assess the hydro-physical and morphological characterization of soil from a toposequence in Galia, state of São Paulo, Brazil). The plot covers an area of 10.24 ha (320 × 320 m), located in a semi-deciduous seasonal forest. Based on ultra-detailed soil and topographic maps of the area, a representative transect from the soil in the plot was chosen. Five profiles were opened for the morphological description of the soil horizons, and hydro-physical and micromorphological analyses were performed to characterize the soil. Arenic Haplustult, Arenic Haplustalf and Aquertic Haplustalf were the soil types observed in the plot. The superficial horizons had lower density and greater hydraulic conductivity, porosity and water retention in lower tensions than the deeper horizons. In the sub-superficial horizons, greater water retention at higher tensions and lower hydraulic conductivity were observed, due to structure type and greater clay content. The differences observed in the water retention curves between the sandy E and the clay B horizons were mainly due to the size distribution, shape and type of soil pores.

Contribution to assessing the stiffness reduction of structural elements in the global stability analysis of precast concrete multi-storey buildings

This study deals with the reduction of the stiffness in precast concrete structural elements of multi-storey buildings to analyze global stability. Having reviewed the technical literature, this paper present indications of stiffness reduction in different codes, standards, and recommendations and compare these to the values found in the present study. The structural model analyzed in this study was constructed with finite elements using ANSYS® software. Physical Non-Linearity (PNL) was considered in relation to the diagrams M x N x 1/r, and Geometric Non-Linearity (GNL) was calculated following the Newton-Raphson method. Using a typical precast concrete structure with multiple floors and a semi-rigid beam-to-column connection, expressions for a stiffness reduction coefficient are presented. The main conclusions of the study are as follows: the reduction coefficients obtained from the diagram M x N x 1/r differ from standards that use a simplified consideration of PNL; the stiffness reduction coefficient for columns in the arrangements analyzed were approximately 0.5 to 0.6; and the variation of values found for stiffness reduction coefficient in concrete beams, which were subjected to the effects of creep with linear coefficients from 0 to 3, ranged from 0.45 to 0.2 for positive bending moments and 0.3 to 0.2 for negative bending moments.

A semi-supervised classification technique based on interacting forces

Semi-supervised learning is a classification paradigm in which just a few labeled instances are available for the training process. To overcome this small amount of initial label information, the information provided by the unlabeled instances is also considered. In this paper, we propose a nature-inspired semi-supervised learning technique based on attraction forces. Instances are represented as points in a k-dimensional space, and the movement of data points is modeled as a dynamical system. As the system runs, data items with the same label cooperate with each other, and data items with different labels compete among them to attract unlabeled points by applying a specific force function. In this way, all unlabeled data items can be classified when the system reaches its stable state. Stability analysis for the proposed dynamical system is performed and some heuristics are proposed for parameter setting. Simulation results show that the proposed technique achieves good classification results on artificial data sets and is comparable to well-known semi-supervised techniques using benchmark data sets.

Quantitative analysis of photodynamic therapy effects in rat mammary tumor vascular density using image-pro plus software

Photodynamic therapy (PDT) is a treatment modality that has advanced rapidly in recent years. It causes tissue and vascular damage with the interaction of a photosensitizing agent (PS), light of a proper wavelength, and molecular oxygen. Evaluation of vessel damage usually relies on histopathology evaluation. Results are often qualitative or at best semi-quantitative based on a subjective system. The aim of this study was to evaluate, using CD31 immunohistochem- istry and image analysis software, the vascular damage after PDT in a well-established rodent model of chemically induced mammary tumor. Fourteen Sprague-Dawley rats received a single dose of 7,12-dimethylbenz(a)anthraxcene (80 mg/kg by gavage), treatment efficacy was evaluated by comparing the vascular density of tumors after treatment with Photogem® as a PS, intraperitoneally, followed by interstitial fiber optic lighting, from a diode laser, at 200 mW/cm and light dose of 100 J/cm directed against his tumor (7 animals), with a control group (6 animals, no PDT). The animals were euthanized 30 hours after the lighting and mammary tumors were removed and samples from each lesion were formalin-fixed. Immunostained blood vessels were quantified by Image Pro-Plus version 7.0. The control group had an average of 3368.6 ± 4027.1 pixels per picture and the treated group had an average of 779 ± 1242.6 pixels per area (P < 0.01), indicating that PDT caused a significant decrease in vascular density of mammary tumors. The combined immu- nohistochemistry using CD31, with selection of representative areas by a trained pathology, followed by quantification of staining using Image Pro-Plus version 7.0 system was a practical and robust methodology for vessel damage evalua- tion, which probably could be used to assess other antiangiogenic treatments.

Texture analysis by multi-resolution fractal descriptors

This work proposes a novel texture descriptor based on fractal theory. The method is based on the Bouligand- Minkowski descriptors. We decompose the original image recursively into four equal parts. In each recursion step, we estimate the average and the deviation of the Bouligand-Minkowski descriptors computed over each part. Thus, we extract entropy features from both average and deviation. The proposed descriptors are provided by concatenating such measures. The method is tested in a classification experiment under well known datasets, that is, Brodatz and Vistex. The results demonstrate that the novel technique achieves better results than classical and state-of-the-art texture descriptors, such as Local Binary Patterns, Gabor-wavelets and co-occurrence matrix.

Dry spell mitigation to upgrade semi-arid rainfed agriculture : Water harvesting and soil nutrient management for smallholder maize cultivation in Machakos, Kenya

Improvements in on-farm water and soil fertility management through water harvesting may prove key to up-grade smallholder farming systems in dry sub-humid and semi-arid sub-Sahara Africa (SSA). The currently experienced yield levels are usually less than 1 t ha-1, i.e., 3-5 times lower than potential levels obtained by commercial farmers and researchers for similar agro-hydrological conditions. The low yield levels are ascribed to the poor crop water availability due to variable rainfall, losses in on-farm water balance and inherently low soil nutrient levels. To meet an increased food demand with less use of water and land in the region, requires farming systems that provide more yields per water unit and/or land area in the future. This thesis presents the results of a project on water harvesting system aiming to upgrade currently practised water management for maize (Zea mays, L.) in semi-arid SSA. The objectives were to a) quantify dry spell occurrence and potential impact in currently practised small-holder grain production systems, b) test agro-hydrological viability and compare maize yields in an on-farm experiment using combinations supplemental irrigation (SI) and fertilizers for maize, and c) estimate long-term changes in water balance and grain yields of a system with SI compared to farmers currently practised in-situ water harvesting. Water balance changes and crop growth were simulated in a 20-year perspective with models MAIZE1&2. Dry spell analyses showed that potentially yield-limiting dry spells occur at least 75% of seasons for 2 locations in semi-arid East Africa during a 20-year period. Dry spell occurrence was more frequent for crop cultivated on soil with low water-holding capacity than on high water-holding capacity. The analysis indicated large on-farm water losses as deep percolation and run-off during seasons despite seasonal crop water deficits. An on-farm experiment was set up during 1998-2001 in Machakos district, semi-arid Kenya. Surface run-off was collected and stored in a 300m3 earth dam. Gravity-fed supplemental irrigation was carried out to a maize field downstream of the dam. Combinations of no irrigation (NI), SI and 3 levels of N fertilizers (0, 30, 80 kg N ha-1) were applied. Over 5 seasons with rainfall ranging from 200 to 550 mm, the crop with SI and low nitrogen fertilizer gave 40% higher yields (**) than the farmers’ conventional in-situ water harvesting system. Adding only SI or only low nitrogen did not result in significantly different yields. Accounting for actual ability of a storage system and SI to mitigate dry spells, it was estimated that a farmer would make economic returns (after deduction of household consumption) between year 2-7 after investment in dam construction depending on dam sealant and labour cost used. Simulating maize growth and site water balance in a system of maize with SI increased annual grain yield with 35 % as a result of timely applications of SI. Field water balance changes in actual evapotranspiration (ETa) and deep percolation were insignificant with SI, although the absolute amount of ETa increased with 30 mm y-1 for crop with SI compared to NI. The dam water balance showed 30% productive outtake as SI of harvested water. Large losses due to seepage and spill-flow occurred from the dam. Water productivity (WP, of ETa) for maize with SI was on average 1 796 m3 per ton grain, and for maize without SI 2 254 m3 per ton grain, i.e, a decerase of WP with 25%. The water harvesting system for supplemental irrigation of maize was shown to be both biophysically and economically viable. However, adoption by farmers will depend on other factors, including investment capacity, know-how and legislative possibilities. Viability of increased water harvesting implementation in a catchment scale needs to be assessed so that other down-stream uses of water remains uncompromised.

Numerical Model for the Dynamic Analysis of Pile Foundations

Programa de doctorado: Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería Instituto Universitario (SIANI)

The use of image analysis systems for the assesment of zooplankton physiological rates and carbon fluxes

Trabajo realizado por: Garijo, J. C., Hernández León, S.

Non-Markovian stochastic processes and their applications: from anomalous diffusion to time series analysis

This work provides a forward step in the study and comprehension of the relationships between stochastic processes and a certain class of integral-partial differential equation, which can be used in order to model anomalous diffusion and transport in statistical physics. In the first part, we brought the reader through the fundamental notions of probability and stochastic processes, stochastic integration and stochastic differential equations as well. In particular, within the study of H-sssi processes, we focused on fractional Brownian motion (fBm) and its discrete-time increment process, the fractional Gaussian noise (fGn), which provide examples of non-Markovian Gaussian processes. The fGn, together with stationary FARIMA processes, is widely used in the modeling and estimation of long-memory, or long-range dependence (LRD). Time series manifesting long-range dependence, are often observed in nature especially in physics, meteorology, climatology, but also in hydrology, geophysics, economy and many others. We deepely studied LRD, giving many real data examples, providing statistical analysis and introducing parametric methods of estimation. Then, we introduced the theory of fractional integrals and derivatives, which indeed turns out to be very appropriate for studying and modeling systems with long-memory properties. After having introduced the basics concepts, we provided many examples and applications. For instance, we investigated the relaxation equation with distributed order time-fractional derivatives, which describes models characterized by a strong memory component and can be used to model relaxation in complex systems, which deviates from the classical exponential Debye pattern. Then, we focused in the study of generalizations of the standard diffusion equation, by passing through the preliminary study of the fractional forward drift equation. Such generalizations have been obtained by using fractional integrals and derivatives of distributed orders. In order to find a connection between the anomalous diffusion described by these equations and the long-range dependence, we introduced and studied the generalized grey Brownian motion (ggBm), which is actually a parametric class of H-sssi processes, which have indeed marginal probability density function evolving in time according to a partial integro-differential equation of fractional type. The ggBm is of course Non-Markovian. All around the work, we have remarked many times that, starting from a master equation of a probability density function f(x,t), it is always possible to define an equivalence class of stochastic processes with the same marginal density function f(x,t). All these processes provide suitable stochastic models for the starting equation. Studying the ggBm, we just focused on a subclass made up of processes with stationary increments. The ggBm has been defined canonically in the so called grey noise space. However, we have been able to provide a characterization notwithstanding the underline probability space. We also pointed out that that the generalized grey Brownian motion is a direct generalization of a Gaussian process and in particular it generalizes Brownain motion and fractional Brownain motion as well. Finally, we introduced and analyzed a more general class of diffusion type equations related to certain non-Markovian stochastic processes. We started from the forward drift equation, which have been made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation has been interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time-evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the same memory kernel K(t). We developed several applications and derived the exact solutions. Moreover, we considered different stochastic models for the given equations, providing path simulations.

Pattern recognition analysis on heavy ion reaction data

One of the problems in the analysis of nucleus-nucleus collisions is to get information on the value of the impact parameter b. This work consists in the application of pattern recognition techniques aimed at associating values of b to groups of events. To this end, a support vec- tor machine (SVM) classifier is adopted to analyze multifragmentation reactions. This method allows to backtracing the values of b through a particular multidimensional analysis. The SVM classification con- sists of two main phase. In the first one, known as training phase, the classifier learns to discriminate the events that are generated by two different model:Classical Molecular Dynamics (CMD) and Heavy- Ion Phase-Space Exploration (HIPSE) for the reaction: 58Ni +48 Ca at 25 AMeV. To check the classification of events in the second one, known as test phase, what has been learned is tested on new events generated by the same models. These new results have been com- pared to the ones obtained through others techniques of backtracing the impact parameter. Our tests show that, following this approach, the central collisions and peripheral collisions, for the CMD events, are always better classified with respect to the classification by the others techniques of backtracing. We have finally performed the SVM classification on the experimental data measured by NUCL-EX col- laboration with CHIMERA apparatus for the previous reaction.