Biomaterials for cartilage tissue engineering under mechanical stimulus

Tese de Doutoramento em Ciências (Especialidade de Física)

Type 2 diabetes-related variants influence the risk of developing multiple myeloma: results from the IMMEnSE consortium

Type 2 diabetes (T2D) has been suggested to be a risk factor for multiple myeloma (MM), but the relationship between the two traits is still not well understood. The aims of this study were to evaluate whether 58 genome-wide-association-studies (GWAS)-identified common variants for T2D influence the risk of developing MM and to determine whether predictive models built with these variants might help to predict the disease risk. We conducted a case–control study including 1420 MM patients and 1858 controls ascertained through the International Multiple Myeloma (IMMEnSE) consortium. Subjects carrying the KCNQ1rs2237892T allele or the CDKN2A-2Brs2383208G/G, IGF1rs35767T/T and MADDrs7944584T/T genotypes had a significantly increased risk of MM (odds ratio (OR)=1.32–2.13) whereas those carrying the KCNJ11rs5215C, KCNJ11rs5219T and THADArs7578597C alleles or the FTOrs8050136A/A and LTArs1041981C/C genotypes showed a significantly decreased risk of developing the disease (OR=0.76–0.85). Interestingly, a prediction model including those T2D-related variants associated with the risk of MM showed a significantly improved discriminatory ability to predict the disease when compared to a model without genetic information (area under the curve (AUC)=0.645 vs AUC=0.629; P=4.05×10-06). A gender-stratified analysis also revealed a significant gender effect modification for ADAM30rs2641348 and NOTCH2rs10923931 variants (Pinteraction=0.001 and 0.0004, respectively). Men carrying the ADAM30rs2641348C and NOTCH2rs10923931T alleles had a significantly decreased risk of MM whereas an opposite but not significant effect was observed in women (ORM=0.71 and ORM=0.66 vs ORW=1.22 and ORW=1.15, respectively). These results suggest that TD2-related variants may influence the risk of developing MM and their genotyping might help to improve MM risk prediction models.

Estimativa dos parâmetros de compactação de solos usando técnicas de data mining

Dissertação de mestrado integrado em Engenharia Civil

Optimisation of a surface mount technology process using a SnAgCu lead-free alloy

The impending introduction of lead-free solder in the manufacture of electrical and electronic products has presented the electronics industry with many challenges. European manufacturers must transfer from a tin-lead process to a lead-free process by July 2006 as a result of the publication of two directives from the European Parliament. Tin-lead solders have been used for mechanical and electrical connections on printed circuit boards for over fifty years and considerable process knowledge has been accumulated. Extensive literature reviews were conducted on the topic and as a result it was found there are many implications to be considered with the introduction of lead-free solder. One particular question that requires answering is; can lead-free solder be used in existing manufacturing processes? The purpose of this research is to conduct a comparative study of a tin-lead solder and a lead-free solder in two key surface mount technology (SMT) processes. The two SMT processes in question were the stencil printing process and the reflow soldering process. Unreplicated fractional factorial experimental designs were used to carry out the studies. The quality of paste deposition in terms of height and volume were the characteristics of interest in the stencil printing process. The quality of solder joints produced in the reflow soldering experiment was assessed using x-ray and cross sectional analysis. This provided qualitative data that was then uniquely scored and weighted using a method developed during the research. Nested experimental design techniques were then used to analyse the resulting quantitative data. Predictive models were developed that allowed for the optimisation of both processes. Results from both experiments show that solder joints of comparable quality to those produced using tin-lead solder can be produced using lead-free solder in current SMT processes.

On the Sources of Uncertainty in Exchange Rate Predictability

We analyse the role of time-variation in coefficients and other sources of uncertainty in exchange rate forecasting regressions. Our techniques incorporate the notion that the relevant set of predictors and their corresponding weights, change over time. We find that predictive models which allow for sudden rather than smooth, changes in coefficients significantly beat the random walk benchmark in out-of-sample forecasting exercise. Using innovative variance decomposition scheme, we identify uncertainty in coefficients' estimation and uncertainty about the precise degree of coefficients' variability, as the main factors hindering models' forecasting performance. The uncertainty regarding the choice of the predictor is small.

In silico prediction of human carboxylesterase-1 (hCES1) metabolism combining docking analyses and MD simulations.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted in developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas little has been done to predict the hydrolytic activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES1. The study involves both docking analyses of known substrates to develop predictive models, and molecular dynamics (MD) simulations to reveal the in situ behavior of substrates and products, with particular attention being paid to the influence of their ionization state. The results emphasize some crucial properties of the hCES1 catalytic cavity, confirming that as a trend with several exceptions, hCES1 prefers substrates with relatively smaller and somewhat polar alkyl/aryl groups and larger hydrophobic acyl moieties. The docking results underline the usefulness of the hydrophobic interaction score proposed here, which allows a robust prediction of hCES1 catalysis, while the MD simulations show the different behavior of substrates and products in the enzyme cavity, suggesting in particular that basic substrates interact with the enzyme in their unprotonated form.

Predicting reptile distributions at the mesoscale: relation to climate and topography

Aim To explore the respective power of climate and topography to predict the distribution of reptiles in Switzerland, hence at a mesoscale level. A more detailed knowledge of these relationships, in combination with maps of the potential distribution derived from the models, is a valuable contribution to the design of conservation strategies. Location All of Switzerland. Methods Generalized linear models are used to derive predictive habitat distribution models from eco-geographical predictors in a geographical information system, using species data from a field survey conducted between 1980 and 1999. Results The maximum amount of deviance explained by climatic models is 65%, and 50% by topographical models. Low values were obtained with both sets of predictors for three species that are widely distributed in all parts of the country (Anguis fragilis , Coronella austriaca , and Natrix natrix), a result that suggests that including other important predictors, such as resources, should improve the models in further studies. With respect to topographical predictors, low values were also obtained for two species where we anticipated a strong response to aspect and slope, Podarcis muralis and Vipera aspis . Main conclusions Overall, both models and maps derived from climatic predictors more closely match the actual reptile distributions than those based on topography. These results suggest that the distributional limits of reptile species with a restricted range in Switzerland are largely set by climatic, predominantly temperature-related, factors.

Will climate change drive alien invasive plants into areas of high protection value? An improved model-based regional assessment to prioritise the management of invasions.

Species distribution models (SDMs) studies suggest that, without control measures, the distribution of many alien invasive plant species (AIS) will increase under climate and land-use changes. Due to limited resources and large areas colonised by invaders, management and monitoring resources must be prioritised. Choices depend on the conservation value of the invaded areas and can be guided by SDM predictions. Here, we use a hierarchical SDM framework, complemented by connectivity analysis of AIS distributions, to evaluate current and future conflicts between AIS and high conservation value areas. We illustrate the framework with three Australian wattle (Acacia) species and patterns of conservation value in Northern Portugal. Results show that protected areas will likely suffer higher pressure from all three Acacia species under future climatic conditions. Due to this higher predicted conflict in protected areas, management might be prioritised for Acacia dealbata and Acacia melanoxylon. Connectivity of AIS suitable areas inside protected areas is currently lower than across the full study area, but this would change under future environmental conditions. Coupled SDM and connectivity analysis can support resource prioritisation for anticipation and monitoring of AIS impacts. However, further tests of this framework over a wide range of regions and organisms are still required before wide application.

Prediction of postpartum depression using multilayer perceptrons and pruning.

OBJECTIVE. The main goal of this paper is to obtain a classification model based on feed-forward multilayer perceptrons in order to improve postpartum depression prediction during the 32 weeks after childbirth with a high sensitivity and specificity and to develop a tool to be integrated in a decision support system for clinicians. MATERIALS AND METHODS. Multilayer perceptrons were trained on data from 1397 women who had just given birth, from seven Spanish general hospitals, including clinical, environmental and genetic variables. A prospective cohort study was made just after delivery, at 8 weeks and at 32 weeks after delivery. The models were evaluated with the geometric mean of accuracies using a hold-out strategy. RESULTS. Multilayer perceptrons showed good performance (high sensitivity and specificity) as predictive models for postpartum depression. CONCLUSIONS. The use of these models in a decision support system can be clinically evaluated in future work. The analysis of the models by pruning leads to a qualitative interpretation of the influence of each variable in the interest of clinical protocols.

Diaspore traits discriminate good from weak colonisers on high elevation summits

The richness of plant species in Swiss alpine-nival summits increased during the climate warming of the 20th century. Thirty-seven summits (2797-3418 m a.s.l.) with both old (~1900-1920) and recent (~2000) plant inventories were used to test whether biological species traits can explain the observed rates of summit colonisation. Species were classified into two groups: good colonisers (colonising five or more summits) and weak colonisers (fewer than five new summits). We compared species traits related to growth, reproduction and dispersal between these two groups and between the good colonisers and a group of high alpine grassland species. The observed colonisation pattern was subsequently compared to a simulated random colonisation pattern. The distribution of new species on the summits was not random, and 16 species exhibited a colonisation rate higher than expected by chance. Taraxacum alpinum aggr. and Cardamine resedifolia were the best colonisers. Results showed that diaspore traits enhancing long-distance dispersal were more frequent among good colonisers than among weak colonisers. Good colonisers were mostly characterised by pappi or narrow wings on their diaspores. Both groups were able to grow on soils more bare and rocky than species from the alpine grasslands. All other biological traits that we considered were similar among the three alpine species groups. These results are important for improving predictive models of species distribution under climate change

Síntesi i propietats de vidres metàl•lics massissos i materials nanocomposites basats en Fe per aplicacions com a materials magnètics tous

Estudi realitzat a partir d’una estada a l’ Institut für Komplexe Materialien, Leibniz-Institut für Festkörper- und Werkstoffforschung Dresden, entre 2010 i 2011. S'ha explorat l'efecte de les condicions i influència dels elements d'aleació en la capacitat de formació de vidre, l'estructura i les propietats tèrmiques i magnètiques de vidres metàl•lics massissos i materials nanocristal•lins en base Fe. La producció d'aquests materials en forma de cintes de unes 20 micres de gruix ha estat àmpliament estudiada i s'ha vist que presenten unes propietats excel•lents com a materials magnètics tous. El propòsit general d'aquest projecte era l'obtenció de composicions òptimes amb alta capacitat de formar vidre i amb excel•lents propietats magnètiques com a materials magnètics tous combinat amb bones propietats mecàniques. El projecte prenia com a punt de partida l'aliatge [FeCoBSi]96Nb4 ja que és el que presenta millor capacitat de formar vidre i presenta una alta imantació de saturació i baix camp coercitiu. S'ha fet un estudi dels factors fonamentals que intervenen en la formació de l'estat vitri. La composició abans esmentada ha estat variada amb l'addició d'altres elements per estudiar com afecten aquests nous elements a les propietats, la formació de vidre i l'estructura dels aliatges resultants amb l'objectiu de millorar-ne les propietats magnètiques i la capacitat de formació de vidre. Entre altres s'ha usat el Zr, Mo, Y i el Gd per millorar la formació de vidre; i el Co i el Ni per millorar les propietats magnètiques a alta temperatura. S'han estudiat les relacions entre la capacitat de formació de vidre i la seva estabilitat tèrmica, la resistència a la cristal•lització i la estructura de l'aliatge resultant després del procés de solidificació. Per aquest estudi s'han determinat els mecanismes que controlen la transformació i la seva cinètica així com les fases que es formen durant el tractament tèrmic permetent la formulació de models predictius.

The InterPro protein families database: the classification resource after 15 years.

The InterPro database (http://www.ebi.ac.uk/interpro/) is a freely available resource that can be used to classify sequences into protein families and to predict the presence of important domains and sites. Central to the InterPro database are predictive models, known as signatures, from a range of different protein family databases that have different biological focuses and use different methodological approaches to classify protein families and domains. InterPro integrates these signatures, capitalizing on the respective strengths of the individual databases, to produce a powerful protein classification resource. Here, we report on the status of InterPro as it enters its 15th year of operation, and give an overview of new developments with the database and its associated Web interfaces and software. In particular, the new domain architecture search tool is described and the process of mapping of Gene Ontology terms to InterPro is outlined. We also discuss the challenges faced by the resource given the explosive growth in sequence data in recent years. InterPro (version 48.0) contains 36 766 member database signatures integrated into 26 238 InterPro entries, an increase of over 3993 entries (5081 signatures), since 2012.

Predictability of drug expenditures: An application using morbidity data

The growth of pharmaceutical expenditure and its prediction is a major concern for policy makers and health care managers. This paper explores different predictive models to estimate future drug expenses, using demographic and morbidity individual information from an integrated healthcare delivery organization in Catalonia for years 2002 and 2003. The morbidity information consists of codified health encounters grouped through the Clinical Risk Groups (CRGs). We estimate pharmaceutical costs using several model specifications, and CRGs as risk adjusters, providing an alternative way of obtaining high predictive power comparable to other estimations of drug expenditures in the literature. These results have clear implications for the use of risk adjustment and CRGs in setting the premiums for pharmaceutical benefits.

Biomass estimation of Triplectides egleri Sattler (Trichoptera, Leptoceridae) in a stream at Ducke Reserve, Central Amazonia

ABSTRACT Biomass is a fundamental measure for understanding the structure and functioning (e.g. fluxes of energy and nutrients in the food chain) of aquatic ecosystems. We aim to provide predictive models to estimate the biomass of Triplectides egleri Sattler, 1963, in a stream in Central Amazonia, based on body and case dimensions. We used body length, head-capsule width, interocular distance and case length and width to derive biomass estimations. Linear, exponential and power regression models were used to assess the relationship between biomass and body or case dimensions. All regression models used in the biomass estimation of T. egleri were significant. The best fit between biomass and body or case dimensions was obtained using the power model, followed by the exponential and linear models. Body length provided the best estimate of biomass. However, the dimensions of sclerotized structures (interocular distance and head-capsule width) also provided good biomass predictions, and may be useful in estimating biomass of preserved and/or damaged material. Case width was the dimension of the case that provided the best estimate of biomass. Despite the low relation, case width may be useful in studies that require low stress on individuals.

A Novel Volume-Age-KPS (VAK) Glioblastoma Classification Identifies a Prognostic Cognate microRNA-Gene Signature.

BACKGROUND: Several studies have established Glioblastoma Multiforme (GBM) prognostic and predictive models based on age and Karnofsky Performance Status (KPS), while very few studies evaluated the prognostic and predictive significance of preoperative MR-imaging. However, to date, there is no simple preoperative GBM classification that also correlates with a highly prognostic genomic signature. Thus, we present for the first time a biologically relevant, and clinically applicable tumor Volume, patient Age, and KPS (VAK) GBM classification that can easily and non-invasively be determined upon patient admission. METHODS: We quantitatively analyzed the volumes of 78 GBM patient MRIs present in The Cancer Imaging Archive (TCIA) corresponding to patients in The Cancer Genome Atlas (TCGA) with VAK annotation. The variables were then combined using a simple 3-point scoring system to form the VAK classification. A validation set (N = 64) from both the TCGA and Rembrandt databases was used to confirm the classification. Transcription factor and genomic correlations were performed using the gene pattern suite and Ingenuity Pathway Analysis. RESULTS: VAK-A and VAK-B classes showed significant median survival differences in discovery (P = 0.007) and validation sets (P = 0.008). VAK-A is significantly associated with P53 activation, while VAK-B shows significant P53 inhibition. Furthermore, a molecular gene signature comprised of a total of 25 genes and microRNAs was significantly associated with the classes and predicted survival in an independent validation set (P = 0.001). A favorable MGMT promoter methylation status resulted in a 10.5 months additional survival benefit for VAK-A compared to VAK-B patients. CONCLUSIONS: The non-invasively determined VAK classification with its implication of VAK-specific molecular regulatory networks, can serve as a very robust initial prognostic tool, clinical trial selection criteria, and important step toward the refinement of genomics-based personalized therapy for GBM patients.