A multivariate analysis of socio-demographic factors, water contact patterns and Schistosoma mansoni infection in an endemic area in Brazil

Associations between socio-demographic factors, water contact patterns and Schistosoma mansoni infection were investigated in 506 individuals (87% of inhabitants over 1 year of age) in an endemic area in Brazil (Divino), aiming at determining priorities for public health measures to prevent the infection. Those who eliminated S. mansoni eggs (n = 198) were compared to those without eggs in the stools (n = 308). The following explanatory variables were considered: age, sex, color, previous treatment with schistosomicide, place of birth, quality of the houses, water supply for the household, distance from houses to stream, and frequency and reasons for water contact. Factors found to be independently associated with the infection were age (10-19 and > 20 yrs old), and water contact for agricultural activities, fishing, and swimming or bathing (Adjusted relative odds = 5.0, 2.4, 3.2, 2.1 and 2.0, respectively). This suggests the need for public health measures to prevent the infection, emphasizing water contact for leisure and agricultural activities in this endemic area.

Brownian bridge and other path-dependent Gaussian processes vectorial simulation

The iterative simulation of the Brownian bridge is well known. In this article, we present a vectorial simulation alternative based on Gaussian processes for machine learning regression that is suitable for interpreted programming languages implementations. We extend the vectorial simulation of path-dependent trajectories to other Gaussian processes, namely, sequences of Brownian bridges, geometric Brownian motion, fractional Brownian motion, and Ornstein-Ulenbeck mean reversion process.

Optimization of River Water Quality Surveys by Multivariate Analysis of Physicochemical, Bacteriological and Ecotoxicological Data

This study aims to optimize the water quality monitoring of a polluted watercourse (Leça River, Portugal) through the principal component analysis (PCA) and cluster analysis (CA). These statistical methodologies were applied to physicochemical, bacteriological and ecotoxicological data (with the marine bacterium Vibrio fischeri and the green alga Chlorella vulgaris) obtained with the analysis of water samples monthly collected at seven monitoring sites and during five campaigns (February, May, June, August, and September 2006). The results of some variables were assigned to water quality classes according to national guidelines. Chemical and bacteriological quality data led to classify Leça River water quality as “bad” or “very bad”. PCA and CA identified monitoring sites with similar pollution pattern, giving to site 1 (located in the upstream stretch of the river) a distinct feature from all other sampling sites downstream. Ecotoxicity results corroborated this classification thus revealing differences in space and time. The present study includes not only physical, chemical and bacteriological but also ecotoxicological parameters, which broadens new perspectives in river water characterization. Moreover, the application of PCA and CA is very useful to optimize water quality monitoring networks, defining the minimum number of sites and their location. Thus, these tools can support appropriate management decisions.

A multivariate analysis of the relationship between work ability and S. japonicum infection in Dongting Lake Region, in China

A cross-sectional case-control study on the association between the reduced work ability and S. japonicum infection was carried out in a moderate endemic area for schistosomiasis japonica in the southern part of Dongting lake in China. A total of 120 cases with reduced work ability and 240 controls paired to the case by age, sex, occupation and without reduced work ability, participated in the study. The mean age for individuals was 37.6 years old (21-60), the ratio of male: female was 60:40, the prevalence of S. japonicum in the individuals was 28.3%. The results obtained in this study showed that the infection of S. japonicum in case and control groups was 49.2% (59/120) and 17.9% (43/240), respectively. Odds ratio for reduced work ability among those who had schistosomiasis was 4.34 (95%), confidence interval was 2.58-7.34, and among those who had S. japonicum infection (egg per gram > 100) was up to 12.67 (95%), confidence interval was 3.64-46.39. After odds ratio was adjusted by multiple logistic regression, it was confirmed that heavier intensity of S. japonicum infection and splenomegaly due to S. japonicum infection were the main risk factors for reduced work ability in the population studied.

In situ NIR spectroscopy monitoring of plasmid production processes effect of producing strain, medium composition and the cultivation strategy

BACKGROUNDWhile the pharmaceutical industry keeps an eye on plasmid DNA production for new generation gene therapies, real-time monitoring techniques for plasmid bioproduction are as yet unavailable. This work shows the possibility of in situ monitoring of plasmid production in Escherichia coli cultures using a near infrared (NIR) fiber optic probe. RESULTSPartial least squares (PLS) regression models based on the NIR spectra were developed for predicting bioprocess critical variables such as the concentrations of biomass, plasmid, carbon sources (glucose and glycerol) and acetate. In order to achieve robust models able to predict the performance of plasmid production processes, independently of the composition of the cultivation medium, cultivation strategy (batch versus fed-batch) and E. coli strain used, three strategies were adopted, using: (i) E. coliDH5 cultures conducted under different media compositions and culture strategies (batch and fed-batch); (ii) engineered E. coli strains, MG1655endArecApgi and MG1655endArecA, grown on the same medium and culture strategy; (iii) diverse E. coli strains, over batch and fed-batch cultivations and using different media compositions. PLS models showed high accuracy for predicting all variables in the three groups of cultures. CONCLUSIONNIR spectroscopy combined with PLS modeling provides a fast, inexpensive and contamination-free technique to accurately monitoring plasmid bioprocesses in real time, independently of the medium composition, cultivation strategy and the E. coli strain used.

Monitoring the ex-vivo expansion of human mesenchymal stem/stromal cells in xeno-free microcarrier-based reactor systems by MIR spectroscopy

Human mesenchymal stem/stromal cells (MSCs) have received considerable attention in the field of cell-based therapies due to their high differentiation potential and ability to modulate immune responses. However, since these cells can only be isolated in very low quantities, successful realization of these therapies requires MSCs ex-vivo expansion to achieve relevant cell doses. The metabolic activity is one of the parameters often monitored during MSCs cultivation by using expensive multi-analytical methods, some of them time-consuming. The present work evaluates the use of mid-infrared (MIR) spectroscopy, through rapid and economic high-throughput analyses associated to multivariate data analysis, to monitor three different MSCs cultivation runs conducted in spinner flasks, under xeno-free culture conditions, which differ in the type of microcarriers used and the culture feeding strategy applied. After evaluating diverse spectral preprocessing techniques, the optimized partial least square (PLS) regression models based on the MIR spectra to estimate the glucose, lactate and ammonia concentrations yielded high coefficients of determination (R2 ≥ 0.98, ≥0.98, and ≥0.94, respectively) and low prediction errors (RMSECV ≤ 4.7%, ≤4.4% and ≤5.7%, respectively). Besides PLS models valid for specific expansion protocols, a robust model simultaneously valid for the three processes was also built for predicting glucose, lactate and ammonia, yielding a R2 of 0.95, 0.97 and 0.86, and a RMSECV of 0.33, 0.57, and 0.09 mM, respectively. Therefore, MIR spectroscopy combined with multivariate data analysis represents a promising tool for both optimization and control of MSCs expansion processes.

Lysotypes and plasmidial profile of Salmonella Serovar Typhimurium isolated from children with enteric processes in the cities of Rio de Janeiro, RJ, and Salvador, BA - Brazil

The lysotypes, plasmidial profiles, and profiles of resistance to antimicrobial agents were determined in 111 Salmonella Typhimurium strains isolated from feces and blood of children treated in Rio de Janeiro and in Salvador. Six distinct lysotypes (19, 41, 97, 105, 120 and 193) were recognized, with a predominance of lysotype 193 (59.7%) in Rio de Janeiro and of phage type 105 (38.4) in Salvador. Approximately 86.7% of the lysotype 193 strains presented multiple resistance to more than six antimicrobial agents, whereas 93% of lysotype 105 strains were fully susceptible. More than 90% of the strains presented plasmids distributed into 36 different profiles in Rio de Janeiro and into 10 profiles in Salvador. A 40 MDa plasmid was the most frequent (47%) in the strains from Rio de Janeiro, whereas a 61 MDa plasmid predominated (14.5%) in Salvador. Combined analysis of plasmid profile and classification into lysotypes (especially those belonging to types 105 and 103, proved to be more discriminatory than the other methods applied).

Development of thermoresponsive (polysulfone/polyacrylonitrile) - based membranes for bioseparation processes

Mestrado integrado em Engenharia Química e Bioquímica

The impact of firm-promoted accreditation of prior learning processes on the worker-organization relationship

The process of Competences Recognition, Validation and Certification , also known as Accreditation of Prior Learning (APL), is an innovative means of attaining school certificates for individuals without an academic background. The main objective of this process is to validate what people have learned in informal contexts, in order to attribute academic certificates. With the increasing interest of the qualification of workers and governmental support, more and more Portuguese organizations promote this process within their facilities and their work hours. This study explores the relationship between the promotion of this Human Resource Development Programme and employee’s attitudes (Job Satisfaction and Organizational Commitment) and behaviours (Extra-role Organizational Citizenship Behaviours) towards the organization they work for. Results of a cross-sectional survey of Portuguese Industrial Workers (N=135) showed that statistical significant results are in the higher levels of Voice Behaviours (a dimension of Extra-role Organizational Citizenship Behaviour in the groups of workers who were involved or had graduated from the firm promoted APL process.

The removal of xenobiotic compounds from wastewater through the use of biological processes and advanced oxidation technologies

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Química e Bioquímica pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Assessment of groundwater contamination in an agricultural peri-urban area (NW Portugal): an integrated approach

The excessive use of pesticides and fertilisers in agriculture has generated a decrease in groundwater and surface water quality in many regions of the EU, constituting a hazard for human health and the environment. Besides, on-site sewage disposal is an important source of groundwater contamination in urban and peri-urban areas. The assessment of groundwater vulnerability to contamination is an important tool to fulfil the demands of EU Directives. The purpose of this study is to assess the groundwater vulnerability to contamination related mainly to agricultural activities in a peri-urban area (Vila do Conde, NW Portugal). The hydrogeological framework is characterised mainly by fissured granitic basement and sedimentary cover. Water samples were collected and analysed for temperature, pH, electrical conductivity, chloride, phosphate, nitrate and nitrite. An evaluation of groundwater vulnerability to contamination was applied (GOD-S, Pesticide DRASTIC-Fm, SINTACS and SI) and the potential nitrate contamination risk was assessed, both on a hydrogeological GIS-based mapping. A principal component analysis was performed to characterised patterns of relationship among groundwater contamination, vulnerability, and the hydrogeological setting assessed. Levels of nitrate above legislation limits were detected in 75 % of the samples analysed. Alluvia units showed the highest nitrate concentrations and also the highest vulnerability and risk. Nitrate contamination is a serious problem affecting groundwater, particularly shallow aquifers, especially due to agriculture activities, livestock and cesspools. GIS-based cartography provided an accurate way to improve knowledge on water circulation models and global functioning of local aquifer systems. Finally, this study highlights the adequacy of an integrated approach, combining hydrogeochemical data, vulnerability assessments and multivariate analysis, to understand groundwater processes in peri-urban areas.

The use of nanoparticles in soil and water remediation processes

Environmental nanoremediation of various contaminants has been reported in several recent studies. In this paper, the state of the art on the use of nanoparticles in soil and groundwater remediation processes is presented. There is a substantive body of evidence on the growing and successful application of nanoremediation for a diversity of soil and groundwater contamination contexts, particularly, for heavy metals, other inorganic contaminants, organic contaminants and emerging contaminants, as pharmaceutical and personal care products. This review confirms the competence of the use of nanoparticles in the remediation of contaminated media and the prevalent use of iron based nanoparticles.

Analyzing Multiple Outcomes: Is it Really Worth the use of Multivariate Linear Regression?

In health related research it is common to have multiple outcomes of interest in a single study. These outcomes are often analysed separately, ignoring the correlation between them. One would expect that a multivariate approach would be a more efficient alternative to individual analyses of each outcome. Surprisingly, this is not always the case. In this article we discuss different settings of linear models and compare the multivariate and univariate approaches. We show that for linear regression models, the estimates of the regression parameters associated with covariates that are shared across the outcomes are the same for the multivariate and univariate models while for outcome-specific covariates the multivariate model performs better in terms of efficiency.

Decision making processes based on innovation indicators: which implications for technology assessment?

Based on the report for “Project IV” unit of the PhD programme on Technology Assessment. This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Manuel Laranja (ISEG-UTL). Other members of the thesis committee are Stefan Kuhlmann (Twente University), Leonhard Hennen (Karlsruhe Institute of Technology-ITAS), Tiago Santos Pereira (Universidade de Coimbra/CES) and Cristina Sousa (FCT-UNL).