Genome-scale metabolic network reconstruction of Polaromonas sp. strain JS666: analysis of cDCE degradation rates and design of experiments for bioremediation improvement

Release of chloroethene compounds into the environment often results in groundwater contamination, which puts people at risk of exposure by drinking contaminated water. cDCE (cis-1,2-dichloroethene) accumulation on subsurface environments is a common environmental problem due to stagnation and partial degradation of other precursor chloroethene species. Polaromonas sp. strain JS666 apparently requires no exotic growth factors to be used as a bioaugmentation agent for aerobic cDCE degradation. Although being the only suitable microorganism found capable of such, further studies are needed for improving the intrinsic bioremediation rates and fully comprehend the metabolic processes involved. In order to do so, a metabolic model, iJS666, was reconstructed from genome annotation and available bibliographic data. FVA (Flux Variability Analysis) and FBA (Flux Balance Analysis) techniques were used to satisfactory validate the predictive capabilities of the iJS666 model. The iJS666 model was able to predict biomass growth for different previously tested conditions, allowed to design key experiments which should be done for further model improvement and, also, produced viable predictions for the use of biostimulant metabolites in the cDCE biodegradation.

Molecular analysis of methicillin-resistant Staphylococcus aureus dissemination among healthcare professionals and/or HIV patients from a tertiary hospital

Abstract INTRODUCTION: Methicillin-resistant Staphylococcus aureus (MRSA) is a nosocomial pathogen in community settings. MRSA colonized individuals may contribute to its dissemination; the risk of MRSA infection is increased in human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS) patients, although the prevalence of colonization in this group is not well established. The present study addressed this issue by characterizing MRSA isolates from HIV/AIDS patients and their healthcare providers (HCPs) to determine whether transmission occurred between these two populations. METHODS: A total of 24 MRSA isolates from HIV-infected patients and five from HCPs were collected between August 2011 and May 2013. Susceptibility to currently available antimicrobials was determined. Epidemiological typing was carried out by pulsed-field gel electrophoresis, multilocus sequence typing, and Staphylococcus cassette chromosome (SCCmec) typing. The presence of heterogeneous vancomycin-intermediate Staphylococcus aureus (hVISA) and heterogeneous daptomycin-resistant Staphylococcus aureus (hDRSA) was confirmed by population analysis profile. Isolates characterized in this study were also compared to isolates from 2009 obtained from patients at the same hospital. RESULTS: A variety of lineages were found among patients, including ST5-SCCmecII and ST30-SCCmecIV. Two isolates were Panton-Valentine leukocidin-positive, and hVISA and hDRSA were detected. MRSA isolates from two HCPs were not related to those from HIV/AIDS patients, but clustered with archived MRSA from 2009 with no known relationship to the current study population. CONCLUSIONS: ST105-SCCmecII clones that colonized professionals in 2011 and 2012 were already circulating among patients in 2009, but there is no evidence that these clones spread to or between HIV/AIDS patients up to the 7th day of their hospitalization.

Healthcare- Associated infections: An analysis of costs in a Portuguese Hospital

Hospital-acquired infections (HAIs) delay healing, prolong Hospital stay, and increase both Hospital costs and risk of death. This study aims to estimate the extra length of stay and mortality rate attributable to each of the following HAIs: wound infection (WI); bloodstream infection (BSI); urinary infections (UI); and Hospital-acquired pneumonia (HAP). The study population consisted of patients discharged in CHLC in 2014. Data was collected to identify demographic information, surgical operations, development of HAIs and its outputs. The study used regressions and a matched strategy to compare cases (infected) and controls (uninfected). The matching criteria were: age, sex, week and type of admission, number of admissions, major diagnostic category and type of discharge. When compared to matched controls, cases with HAI had a higher mortality rate and greater length of stay. WI related to hip or knee surgery, increased mortality rate by 27.27% and the length of stay by 74.97 days. WI due to colorectal surgery caused an extra mortality rate of 10.69% and an excess length of stay of 20.23 days. BSI increased Hospital stay by 28.80 days and mortality rate by 32.27%. UI caused an average additional length of stay of 19.66 days and risk of death of 12.85%. HAP resulted in an extra Hospital stay of 25.06 days and mortality rate of 24.71%. This study confirms the results of the previous literature that patients experiencing HAIs incur in an excess of mortality rates and Hospital stay, and, overall, it presents worse results comparing with other countries.

Development of benchmarks for operating costs and resources consumption to be used in healthcare building sustainability assessment methods

Since the last decade of the twentieth century, the healthcare industry is paying attention to the environmental impact of their buildings and therefore new regulations, policy goals and Buildings Sustainability Assessment (HBSA) methods are being developed and implemented. At the present, healthcare is one of the most regulated industries and it is also one of the largest consumers of energy per net floor area. To assess the sustainability of healthcare buildings it is necessary to establish a set of benchmarks related with their life-cycle performance. They are both essential to rate the sustainability of a project and to support designers and other stakeholders in the process of designing and operating a sustainable building, by allowing the comparison to be made between a project and the conventional and best market practices. This research is focused on the methodology to set the benchmarks for resources consumption, waste production, operation costs and potential environmental impacts related to the operational phase of healthcare buildings. It aims at contributing to the reduction of the subjectivity found in the definition of the benchmarks used in Building Sustainability Assessment (BSA) methods, and it is applied in the Portuguese context. These benchmarks will be used in the development of a Portuguese HBSA method.

Towards effective control of P2P traffic aggregates in network infrastructures

Nowadays, many P2P applications proliferate in the Internet. The attractiveness of many of these systems relies on the collaborative approach used to exchange large resources without the dependence and associated constraints of centralized approaches where a single server is responsible to handle all the requests from the clients. As consequence, some P2P systems are also interesting and cost-effective approaches to be adopted by content-providers and other Internet players. However, there are several coexistence problems between P2P applications and In- ternet Service Providers (ISPs) due to the unforeseeable behavior of P2P traffic aggregates in ISP infrastructures. In this context, this work proposes a collaborative P2P/ISP system able to underpin the development of novel Traffic Engi- neering (TE) mechanisms contributing for a better coexistence between P2P applications and ISPs. Using the devised system, two TE methods are described being able to estimate and control the impact of P2P traffic aggregates on the ISP network links. One of the TE methods allows that ISP administrators are able to foresee the expected impact that a given P2P swarm will have in the underlying network infrastructure. The other TE method enables the definition of ISP friendly P2P topologies, where specific network links are protected from P2P traffic. As result, the proposed system and associated mechanisms will contribute for improved ISP resource management tasks and to foster the deployment of innovative ISP-friendly systems.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational in- telligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two il- lustrative Traffic Engineering methods are described, allowing to attain routing con- figurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Modeling microbes: New methods for integrated metabolic and regulatory network reconstruction

PhD Thesis in Bioengineering

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Thrombophilia screening: An artificial neural network approach

Thrombotic disorders have severe consequences for the patients and for the society in general, being one of the main causes of death. These facts reveal that it is extremely important to be preventive; being aware of how probable is to have that kind of syndrome. Indeed, this work will focus on the development of a decision support system that will cater for an individual risk evaluation with respect to the surge of thrombotic complaints. The Knowledge Representation and Reasoning procedures used will be based on an extension to the Logic Programming language, allowing the handling of incomplete and/or default data. The computational framework in place will be centered on Artificial Neural Networks.

A hybrid MAC Scheme to improve the transmission performance in body sensor networks

Wireless body sensor networks (WBSNs) constitute a key technology for closing the loop between patients and healthcare providers, as WBSNs provide sensing ability, as well as mobility and portability, essential characteristics for wide acceptance of wireless healthcare technology. However, one important and difficult aspect of WBSNs is to provide data transmissions with quality of service, among other factors due to the antennas being small size and placed close to the body. Such transmissions cannot be fully provided without the assumption of a MAC protocol that solves the problems of the medium sharing. A vast number of MAC protocols conceived for wireless networks are based on random or scheduled schemes. This paper studies firstly the suitability of two MAC protocols, one using CSMA and the other TDMA, to transmit directly to the base station the signals collected continuously from multiple sensor nodes placed on the human body. Tests in a real scenario show that the beaconed TDMA MAC protocol presents an average packet loss ratio lower than CSMA. However, the average packet loss ratio is above 1.0 %. To improve this performance, which is of vital importance in areas such as e-health and ambient assisted living, a hybrid TDMA/CSMA scheme is proposed and tested in a real scenario with two WBSNs and four sensor nodes per WBSN. An average packet loss ratio lower than 0.2 % was obtained with the hybrid scheme. To achieve this significant improvement, the hybrid scheme uses a lightweight algorithm to control dynamically the start of the superframes. Scalability and traffic rate variation tests show that this strategy allows approximately ten WBSNs operating simultaneously without significant performance degradation.

Spousal support and satisfaction with healthcare services as moderators between psychological morbidity and adherence to diet in Type 2 Diabetes patients

Objectives: This study analyzed the moderating role of partners’ support and satisfaction with healthcare services in the relationship between psychological morbidity and adherence to diet in patients with type 2 diabetes (T2DM). Methods: Participants were 387 recently diagnosed T2DM patients that answered the following instruments: Revised Summary of Diabetes Self- Care Activities Measure, Hospital Anxiety and Depression Scales, Multidimensional Diabetes Questionnaire and Patient Satisfaction Questionnaire. Results: Partners’ positive and negative support moderated the relationship between psychological morbidity and adherence to diet. Satisfaction with healthcare services also moderated the relationship between psychological morbidity and adherence to diet. Conclusions: Intervention programs to promote adherence to diet in patients with type 2 diabetes should focus on partners’ support and patient satisfaction with healthcare services.

Differential activation of the default mode network in jet lagged individuals

Long-term exposure to transmeridian flights has been shown to impact cognitive functioning. Nevertheless, the immediate effects of jet lag in the activation of specific brain networks have not been investigated. We analyzed the impact of short-term jet lag on the activation of the default mode network (DMN). A group of individuals who were on a transmeridian flight and a control group went through a functional magnetic resonance imaging acquisition. Statistical analysis was performed to test for differences in the DMN activation between groups. Participants from the jet lag group presented decreased activation in the anterior nodes of the DMN, specifically in bilateral medial prefrontal and anterior cingulate cortex. No areas of increased activation were observed for the jet lag group. These results may be suggestive of a negative impact of jet lag on important cognitive functions such as introspection, emotional regulation and decision making in a few days after individuals arrive at their destination.

A network approach to brain aging through multimodal neuroimaging

Tese de Doutoramento em Ciências da Saúde.

Evolution of the gene regulatory network controlling flower dorsoventral asymmetry

Tese de Doutoramento em Biologia de Plantas.

A modular traffic sampling architecture for flexible network measurements

Dissertação de Mestrado (Programa Doutoral em Informática)