An Experimental Model of Prostatic Inflammation for Drug Discovery

There is increasing evidence to support a significant role for chronic non-bacterial, prostatic inflammation in the development of human voiding dysfunction and prostate cancer. Their increased prevalence with age suggests that the decrease of testosterone concentration and/or the ratio of testosterone-to-estradiol in serum may have a role in their development. The main objective of this study was to explore prostatic inflammation and its relationship with voiding dysfunction and prostate carcinogenesis by developing an experimental model. A novel selective estrogen receptor modulator (SERM), fispemifene, was tested for the prevention and treatment of prostatic inflammation in this model. Combined treatment of adult Noble rats with testosterone and estradiol for 3 to 6 weeks induced gradually developing prostatic inflammation in the dorsolateral prostatic lobes. Inflammatory cells, mainly T-lymphocytes, were first seen around capillaries. Thereafter, the lymphocytes migrated into the stroma and into periglandular space. When the treatment time was extended to 13 weeks, the number of inflamed acini increased. Urodynamical recordings indicated voiding dysfunction. When the animals had an above normal testosterone and estradiol concentrations but still had a decreased testosterone-to-estradiol ratio in serum, they developed obstructive voiding. Furthermore, they developed precancerous lesions and prostate cancers in the ducts of the dorsolateral prostatic lobes. Interestingly, inflammatory infiltrates were observed adjacent to precancerous lesions but not in the adjacency of adenocarcinomas suggesting that inflammation has a role in the early stages of prostate carcinogenesis. Fispemifene, a novel SERM tested in this experimental model, showed anti-inflammatory action by attenuating the number of inflamed acini in the dorsolateral prostate. Fispemifene exhibited also antiestrogenic properties by decreasing expression of estrogen-induced biomarkers in the acinar epithelium. These findings suggest that SERMs could be considered as a new therapeutic possibility in the prevention and in the treatment of chronic prostatic inflammation

Statistical Methods for Conservation and Alignment Quality in Proteins

Construction of multiple sequence alignments is a fundamental task in Bioinformatics. Multiple sequence alignments are used as a prerequisite in many Bioinformatics methods, and subsequently the quality of such methods can be critically dependent on the quality of the alignment. However, automatic construction of a multiple sequence alignment for a set of remotely related sequences does not always provide biologically relevant alignments.Therefore, there is a need for an objective approach for evaluating the quality of automatically aligned sequences. The profile hidden Markov model is a powerful approach in comparative genomics. In the profile hidden Markov model, the symbol probabilities are estimated at each conserved alignment position. This can increase the dimension of parameter space and cause an overfitting problem. These two research problems are both related to conservation. We have developed statistical measures for quantifying the conservation of multiple sequence alignments. Two types of methods are considered, those identifying conserved residues in an alignment position, and those calculating positional conservation scores. The positional conservation score was exploited in a statistical prediction model for assessing the quality of multiple sequence alignments. The residue conservation score was used as part of the emission probability estimation method proposed for profile hidden Markov models. The results of the predicted alignment quality score highly correlated with the correct alignment quality scores, indicating that our method is reliable for assessing the quality of any multiple sequence alignment. The comparison of the emission probability estimation method with the maximum likelihood method showed that the number of estimated parameters in the model was dramatically decreased, while the same level of accuracy was maintained. To conclude, we have shown that conservation can be successfully used in the statistical model for alignment quality assessment and in the estimation of emission probabilities in the profile hidden Markov models.

Asymptotic analysis of stock price densities and implied volatilities in mixed stochastic models

In this paper, we obtain sharp asymptotic formulas with error estimates for the Mellin con- volution of functions de ned on (0;1), and use these formulas to characterize the asymptotic behavior of marginal distribution densities of stock price processes in mixed stochastic models. Special examples of mixed models are jump-di usion models and stochastic volatility models with jumps. We apply our general results to the Heston model with double exponential jumps, and make a detailed analysis of the asymptotic behavior of the stock price density, the call option pricing function, and the implied volatility in this model. We also obtain similar results for the Heston model with jumps distributed according to the NIG law.

Novel Robot Solutions for Carrying out Field Joint Welding and Machining in the Assembly of the Vacuum Vessel of ITER

It is necessary to use highly specialized robots in ITER (International Thermonuclear Experimental Reactor) both in the manufacturing and maintenance of the reactor due to a demanding environment. The sectors of the ITER vacuum vessel (VV) require more stringent tolerances than normally expected for the size of the structure involved. VV consists of nine sectors that are to be welded together. The vacuum vessel has a toroidal chamber structure. The task of the designed robot is to carry the welding apparatus along a path with a stringent tolerance during the assembly operation. In addition to the initial vacuum vessel assembly, after a limited running period, sectors need to be replaced for repair. Mechanisms with closed-loop kinematic chains are used in the design of robots in this work. One version is a purely parallel manipulator and another is a hybrid manipulator where the parallel and serial structures are combined. Traditional industrial robots that generally have the links actuated in series are inherently not very rigid and have poor dynamic performance in high speed and high dynamic loading conditions. Compared with open chain manipulators, parallel manipulators have high stiffness, high accuracy and a high force/torque capacity in a reduced workspace. Parallel manipulators have a mechanical architecture where all of the links are connected to the base and to the end-effector of the robot. The purpose of this thesis is to develop special parallel robots for the assembly, machining and repairing of the VV of the ITER. The process of the assembly and machining of the vacuum vessel needs a special robot. By studying the structure of the vacuum vessel, two novel parallel robots were designed and built; they have six and ten degrees of freedom driven by hydraulic cylinders and electrical servo motors. Kinematic models for the proposed robots were defined and two prototypes built. Experiments for machine cutting and laser welding with the 6-DOF robot were carried out. It was demonstrated that the parallel robots are capable of holding all necessary machining tools and welding end-effectors in all positions accurately and stably inside the vacuum vessel sector. The kinematic models appeared to be complex especially in the case of the 10-DOF robot because of its redundant structure. Multibody dynamics simulations were carried out, ensuring sufficient stiffness during the robot motion. The entire design and testing processes of the robots appeared to be complex tasks due to the high specialization of the manufacturing technology needed in the ITER reactor, while the results demonstrate the applicability of the proposed solutions quite well. The results offer not only devices but also a methodology for the assembly and repair of ITER by means of parallel robots.

From "being to the self" to "become to be": on development of autonomy construction in nursing students

Objective: To understand nursing student's self-consciousness and his/her autonomy in the discipline of fundamentals of professional care in the context of a liberating pedagogical proposal. Methodology. This qualitative, case-based research in the model of Ludke and André involved 14 students participating in the discipline. Data were collected by non-participatory observation and analysis of documents. Field observation was conducted from March to July 2010 and data were collected according to the proposal of Minayo: pre-analysis, exploration of material and treatment of results. Results. We constructed two thematic units of analysis: from "being to the self" and exercise of "become to be". Conclusion. When nursing students feel more liberty, they have the opportunity to substitute the scary prospect of learning something new material to something that motivates their curiosity and leads them to become more autonomous.

Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.

Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.

Description of epidemics of coffee rust with neural networks

The objective of this paper was to evaluate the potential of neural networks (NN) as an alternative method to the basic epidemiological approach to describe epidemics of coffee rust. The NN was developed from the intensities of coffee (Coffea arabica) rust along with the climatic variables collected in Lavras-MG between 13 February 1998 and 20 April 2001. The NN was built with climatic variables that were either selected in a stepwise regression analysis or by the Braincel® system, software for NN building. Fifty-nine networks and 26 regression models were tested. The best models were selected based on small values of the mean square deviation (MSD) and of the mean prediction error (MPE). For the regression models, the highest coefficients of determination (R²) were used. The best model developed with neural networks had an MSD of 4.36 and an MPE of 2.43%. This model used the variables of minimum temperature, production, relative humidity of the air, and irradiance 30 days before the evaluation of disease. The best regression model was developed from 29 selected climatic variables in the network. The summary statistics for this model were: MPE=6.58%, MSE=4.36, and R²=0.80. The elaborated neural networks from a time series also were evaluated to describe the epidemic. The incidence of coffee rust at four previous fortnights resulted in a model with MPE=4.72% and an MSD=3.95.

Investment risks in Russia: A Finnish perspective

Purpose of this study is to analyze the effect of Russia's economic environment changes in the total return indexes of Finnish companies. The research data consisted of Finnish publicly listed companies, which have made physical investments to Russia, and operating in the area. The study used six different variables to model the Russian operating environment. The data consists of total return indexes of Finnish companies. From those we calculated the monthly mean interval between timeline of 1 January 2000 to 31 December 2009. Sample period is divided into two different parts. Variables impact on companies' total return indices is tested by regression analysis. By F-test we tested significance of model and squared coefficient correlation told us how much model explains from changes. Goodness of the β-coefficient is tested in the model by t-test. The research results shows that the Russian operating environment, or changes in which the active Finnish companies in total return indices. On partial sample periods results were not so significant.

Hypoxia-associated biomarkers in rectal cancer treated by preoperative radiotherapy or chemoradiotherapy

Hypoksiaan liittyvät biologiset merkkiaineet leikkausta edeltävällä sädehoidolla tai kemosädehoidolla hoidetussa peräsuolisyövässä Peräsuolensyöpä on yleinen pahanlaatuinen kasvain. Leikkausta edeltävä sädehoito annetaan yleensä T3-T4-kasvaimille. Tutkimuksella pyrittiin selvittämään, voidaanko kasvaimen hapenpuutteeseen liittyvillä biologisilla merkkiaineilla arvioida peräsuolisyövän ennustetta leikkausta edeltävän sädehoidon tai kemosädehoidon jälkeen. Tällaisia merkkiaineita ovat hapenpuutteen vaikutuksesta aktivoituva HIF-1alfa hiilihappoanhydraasi IX (CA IX), sokerin kuljetukseen solussa osallistuva GLUT-1 sekä solun tukirankaproteiini ezrin. Tutkimukseen otettiin 178 potilasta, jotka olivat saaneet ennen leikkausta lyhyen (n=77) tai pitkän sädehoidon (n=10), pitkän sädehoidon ja solunsalpaajahoidon (n=37) tai ei mitään hoitoa (n=54). Lisäksi osalta leikkausta edeltävää sädehoitoa saaneelta potilaalta tutkittiin hoitoja edeltävät, diagnostiset näytteet (n=80). Tutkimuksessa käytettiin immunehistokemiallisia värjäysmenetelmiä. Kasvaimen regressiota (TRG) arvioitiin pitkän sädehoidon jälkeisistä näytteistä. Leikkausnäytteissä negatiivinen/heikko CA IX intensiteetti liittyi sekä pidempään tautispesifiseen (p=0.034) että tautivapaaseen elinaikaan (p=0.003) ja pitkän sädehoidon jälkeen HIF-1alfa-negatiivisuus pidempään tautispesifiseen (p=0.001) sekä negatiivinen/heikko GLUT-1 pidempään tautivapaaseen elinaikaan (p=0.066). Voimakas ezrin-ilmentymä diagnostisissa näytteissä liittyi lyhyempään tautivapaaseen ja tautispesifiseen (p=0.027 ja p=0.002) ennusteeseen. Monimuuttuja-analyysissä vahva CA IX intensiteetti leikkausnäytteissä ennusti itsenäisesti huonompaa tautivapaata ja tautispesifistä selviytymistä. Erinomainen TRG liittyi negatiiviseen/heikkoon CA IX- (p=0.057), ezrin- (p=0.012) ja GLUT-1 -ilmentymään (p=0.013) leikkausnäytteissä. Kun kaikki neljä merkkiainetta analysoitiin yhdessä monimuuttuja-analyysissä, CA IX intensiteetti leikkausnäytteissä ennusti itsenäisesti tautispesifistä elinaikaa. Voimakas CA IX-ilmentymä leikkausnäytteissä ja positiivinen HIF-1alfa- ja vahva GLUT-1-ilmentymä pitkän sädehoidon jälkeisissä leikkausnäytteissä sekä vahva ezrin-ilmentymä diagnostisissa näytteissä liittyivät epäsuotuisaan ennusteeseen. Monimuuttujaanalyysissä kohtalainen/voimakas CA IX intensiteetti leikkausnäytteissä ennusti itsenäisesti huonompaa tautivapaata ja tautispesifistä elinaikaa. CA IX on vahva biologinen merkkiaine peräsuolisyövässä.

From Fluid Dynamics to Human Psychology.What Drives Financial Markets Towards Extreme Events

For decades researchers have been trying to build models that would help understand price performance in financial markets and, therefore, to be able to forecast future prices. However, any econometric approaches have notoriously failed in predicting extreme events in markets. At the end of 20th century, market specialists started to admit that the reasons for economy meltdowns may originate as much in rational actions of traders as in human psychology. The latter forces have been described as trading biases, also known as animal spirits. This study aims at expressing in mathematical form some of the basic trading biases as well as the idea of market momentum and, therefore, reconstructing the dynamics of prices in financial markets. It is proposed through a novel family of models originating in population and fluid dynamics, applied to an electricity spot price time series. The main goal of this work is to investigate via numerical solutions how well theequations succeed in reproducing the real market time series properties, especially those that seemingly contradict standard assumptions of neoclassical economic theory, in particular the Efficient Market Hypothesis. The results show that the proposed model is able to generate price realizations that closely reproduce the behaviour and statistics of the original electricity spot price. That is achieved in all price levels, from small and medium-range variations to price spikes. The latter were generated from price dynamics and market momentum, without superimposing jump processes in the model. In the light of the presented results, it seems that the latest assumptions about human psychology and market momentum ruling market dynamics may be true. Therefore, other commodity markets should be analyzed with this model as well.

Modelling of combustion and sorbent reactions in three-dimensional flow environment of a circulating fluidized bed furnace

This thesis presents a three-dimensional, semi-empirical, steady state model for simulating the combustion, gasification, and formation of emissions in circulating fluidized bed (CFB) processes. In a large-scale CFB furnace, the local feeding of fuel, air, and other input materials, as well as the limited mixing rate of different reactants produce inhomogeneous process conditions. To simulate the real conditions, the furnace should be modelled three-dimensionally or the three-dimensional effects should be taken into account. The only available methods for simulating the large CFB furnaces three-dimensionally are semi-empirical models, which apply a relatively coarse calculation mesh and a combination of fundamental conservation equations, theoretical models and empirical correlations. The number of such models is extremely small. The main objective of this work was to achieve a model which can be applied to calculating industrial scale CFB boilers and which can simulate all the essential sub-phenomena: fluid dynamics, reactions, the attrition of particles, and heat transfer. The core of the work was to develop the model frame and the required sub-models for determining the combustion and sorbent reactions. The objective was reached, and the developed model was successfully used for studying various industrial scale CFB boilers combusting different types of fuel. The model for sorbent reactions, which includes the main reactions for calcitic limestones, was applied for studying the new possible phenomena occurring in the oxygen-fired combustion. The presented combustion and sorbent models and principles can be utilized in other model approaches as well, including other empirical and semi-empirical model approaches, and CFD based simulations. The main achievement is the overall model frame which can be utilized for the further development and testing of new sub-models and theories, and for concentrating the knowledge gathered from the experimental work carried out at bench scale, pilot scale and industrial scale apparatus, and from the computational work performed by other modelling methods.

Application of Computational Fluid Dynamics in Modeling Blood Flow in Human Thoracic Aorta

The aim of this study was to simulate blood flow in thoracic human aorta and understand the role of flow dynamics in the initialization and localization of atherosclerotic plaque in human thoracic aorta. The blood flow dynamics in idealized and realistic models of human thoracic aorta were numerically simulated in three idealized and two realistic thoracic aorta models. The idealized models of thoracic aorta were reconstructed with measurements available from literature, and the realistic models of thoracic aorta were constructed by image processing Computed Tomographic (CT) images. The CT images were made available by South Karelia Central Hospital in Lappeenranta. The reconstruction of thoracic aorta consisted of operations, such as contrast adjustment, image segmentations, and 3D surface rendering. Additional design operations were performed to make the aorta model compatible for the numerical method based computer code. The image processing and design operations were performed with specialized medical image processing software. Pulsatile pressure and velocity boundary conditions were deployed as inlet boundary conditions. The blood flow was assumed homogeneous and incompressible. The blood was assumed to be a Newtonian fluid. The simulations with idealized models of thoracic aorta were carried out with Finite Element Method based computer code, while the simulations with realistic models of thoracic aorta were carried out with Finite Volume Method based computer code. Simulations were carried out for four cardiac cycles. The distribution of flow, pressure and Wall Shear Stress (WSS) observed during the fourth cardiac cycle were extensively analyzed. The aim of carrying out the simulations with idealized model was to get an estimate of flow dynamics in a realistic aorta model. The motive behind the choice of three aorta models with distinct features was to understand the dependence of flow dynamics on aorta anatomy. Highly disturbed and nonuniform distribution of velocity and WSS was observed in aortic arch, near brachiocephalic, left common artery, and left subclavian artery. On the other hand, the WSS profiles at the roots of branches show significant differences with geometry variation of aorta and branches. The comparison of instantaneous WSS profiles revealed that the model with straight branching arteries had relatively lower WSS compared to that in the aorta model with curved branches. In addition to this, significant differences were observed in the spatial and temporal profiles of WSS, flow, and pressure. The study with idealized model was extended to study blood flow in thoracic aorta under the effects of hypertension and hypotension. One of the idealized aorta models was modified along with the boundary conditions to mimic the thoracic aorta under the effects of hypertension and hypotension. The results of simulations with realistic models extracted from CT scans demonstrated more realistic flow dynamics than that in the idealized models. During systole, the velocity in ascending aorta was skewed towards the outer wall of aortic arch. The flow develops secondary flow patterns as it moves downstream towards aortic arch. Unlike idealized models, the distribution of flow was nonplanar and heavily guided by the artery anatomy. Flow cavitation was observed in the aorta model which was imaged giving longer branches. This could not be properly observed in the model with imaging containing a shorter length for aortic branches. The flow circulation was also observed in the inner wall of the aortic arch. However, during the diastole, the flow profiles were almost flat and regular due the acceleration of flow at the inlet. The flow profiles were weakly turbulent during the flow reversal. The complex flow patterns caused a non-uniform distribution of WSS. High WSS was distributed at the junction of branches and aortic arch. Low WSS was distributed at the proximal part of the junction, while intermedium WSS was distributed in the distal part of the junction. The pulsatile nature of the inflow caused oscillating WSS at the branch entry region and inner curvature of aortic arch. Based on the WSS distribution in the realistic model, one of the aorta models was altered to induce artificial atherosclerotic plaque at the branch entry region and inner curvature of aortic arch. Atherosclerotic plaque causing 50% blockage of lumen was introduced in brachiocephalic artery, common carotid artery, left subclavian artery, and aortic arch. The aim of this part of the study was first to study the effect of stenosis on flow and WSS distribution, understand the effect of shape of atherosclerotic plaque on flow and WSS distribution, and finally to investigate the effect of lumen blockage severity on flow and WSS distributions. The results revealed that the distribution of WSS is significantly affected by plaque with mere 50% stenosis. The asymmetric shape of stenosis causes higher WSS in branching arteries than in the cases with symmetric plaque. The flow dynamics within thoracic aorta models has been extensively studied and reported here. The effects of pressure and arterial anatomy on the flow dynamic were investigated. The distribution of complex flow and WSS is correlated with the localization of atherosclerosis. With the available results we can conclude that the thoracic aorta, with complex anatomy is the most vulnerable artery for the localization and development of atherosclerosis. The flow dynamics and arterial anatomy play a role in the localization of atherosclerosis. The patient specific image based models can be used to diagnose the locations in the aorta vulnerable to the development of arterial diseases such as atherosclerosis.

Performance of UASB reactors in two stages under different HRT and OLR treating residual waters of swine farming

In this study it was evaluated the effects of hydraulic retention time (HRT) and Organic Loading Rate (OLR) on the performance of UASB (Upflow Anaerobic Sludge Blanket) reactors in two stages treating residual waters of swine farming. The system consisted of two UASB reactors in pilot scale, installed in series, with volumes of 908 and 188 L, for the first and second stages (R1 and R2), respectively. The HRT applied in the system of anaerobic treatment in two stages (R1 + R2) was of 19.3, 29.0 and 57.9 h. The OLR applied in the R1 ranged from 5.5 to 40.1 kg CODtotal (m³ d)-1. The average removal efficiencies of chemical oxygen demand (COD) and total suspended solids (TSS) ranged, respectively, from 66.3 to 88.2% and 62.5 to 89.3% in the R1, and from 85.5 to 95.5% and 76.4 to 96.1% in the system (R1 + R2). The volumetric production of methane in the system (R1 + R2) ranged from 0.295 to 0.721 m³CH4 (m³ reactor d)-1. It was found that the OLR applied were not limiting to obtain high efficiencies of CODtotal and TSS removal and methane production. The inclusion of the UASB reactor in the second stage contributed to increase the efficiencies of CODtotal and TSS removal, especially, when the treatment system was submitted to the lowest HRT and the highest OLR.

COD, TSS, nutrients and coliforms removals in UASB reactors in two stages treating swine wastewater

The performance of two upflow anaerobic sludge blanket (UASB) reactors was evaluated in pilot scale (908 and 188 L), installed in series (R1 and R2), fed with swine wastewater with TSS around 5 and 13 g L-1. The UASB reactors were submitted to HDT of 36 and 18 h with VOL of 5.5 to 34.4 g COD (L d)-1 in the R1 and HDT of 7.5 e 3.7 h with VOL from 5.1 to 45.2 g COD (L d)-1 in the R2. The average removal efficiencies of COD ranged from 55 to 85% in the R1 and from 43 to 57% in the R2, resulting in values from 82 to 93% in the UASB reactors in two stage. Methane concentrations in the biogas were 69 to 74% with specific production from 0.05 to 0.27 L CH4 (g removedCOD)-1 in the R1 and of 0.10 to 0.12 L CH4 (g removedCOD)-1 in the R2. The average removal efficiencies were 61 to 75% for totalP, 39 to 69% for KN, 82 to 93% for orgN and 20 to 94% for Fe, Zn, Cu and Mn. The amN concentration were not reduced indicating the need to post-treatment for effluent disposal into water bodies. There were reductions of total coliforms from 99.8123 to 99.9989% and of thermotolerant coliforms from 99.9725 to 99.9999%. The conditions imposed to the UASB reactors in two stage provided high conversions of removedCOD into methane (up to 77%) and reductions of organic an inorganic pollution loads from swine wastewater.