Algorithms and computational tools for metabolic flux analysis

PhD thesis in Biomedical Engineering

A critical evaluation of methods for the reconstruction of tissue-specific models

Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.

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 intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations 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.

BIOMedical search engine framework: lightweight and customized implementation of domain-specific biomedical search engines

The Smart Drug Search is publicly accessible at http://sing.ei.uvigo.es/sds/. The BIOMedical Search Engine Framework is freely available for non-commercial use at https://github.com/agjacome/biomsef

DESARROLLO DE APLICACIONES ESTADÍSTICAS PARA LA AGRICULTURA DE PRECISIÓN. STATISTICAL APPLICATIONS FOR PRECISION AGRICULTURE

A partir de las últimas décadas se ha impulsado el desarrollo y la utilización de los Sistemas de Información Geográficos (SIG) y los Sistemas de Posicionamiento Satelital (GPS) orientados a mejorar la eficiencia productiva de distintos sistemas de cultivos extensivos en términos agronómicos, económicos y ambientales. Estas nuevas tecnologías permiten medir variabilidad espacial de propiedades del sitio como conductividad eléctrica aparente y otros atributos del terreno así como el efecto de las mismas sobre la distribución espacial de los rendimientos. Luego, es posible aplicar el manejo sitio-específico en los lotes para mejorar la eficiencia en el uso de los insumos agroquímicos, la protección del medio ambiente y la sustentabilidad de la vida rural. En la actualidad, existe una oferta amplia de recursos tecnológicos propios de la agricultura de precisión para capturar variación espacial a través de los sitios dentro del terreno. El óptimo uso del gran volumen de datos derivado de maquinarias de agricultura de precisión depende fuertemente de las capacidades para explorar la información relativa a las complejas interacciones que subyacen los resultados productivos. La covariación espacial de las propiedades del sitio y el rendimiento de los cultivos ha sido estudiada a través de modelos geoestadísticos clásicos que se basan en la teoría de variables regionalizadas. Nuevos desarrollos de modelos estadísticos contemporáneos, entre los que se destacan los modelos lineales mixtos, constituyen herramientas prometedoras para el tratamiento de datos correlacionados espacialmente. Más aún, debido a la naturaleza multivariada de las múltiples variables registradas en cada sitio, las técnicas de análisis multivariado podrían aportar valiosa información para la visualización y explotación de datos georreferenciados. La comprensión de las bases agronómicas de las complejas interacciones que se producen a la escala de lotes en producción, es hoy posible con el uso de éstas nuevas tecnologías. Los objetivos del presente proyecto son: (l) desarrollar estrategias metodológicas basadas en la complementación de técnicas de análisis multivariados y geoestadísticas, para la clasificación de sitios intralotes y el estudio de interdependencias entre variables de sitio y rendimiento; (ll) proponer modelos mixtos alternativos, basados en funciones de correlación espacial de los términos de error que permitan explorar patrones de correlación espacial de los rendimientos intralotes y las propiedades del suelo en los sitios delimitados. From the last decades the use and development of Geographical Information Systems (GIS) and Satellite Positioning Systems (GPS) is highly promoted in cropping systems. Such technologies allow measuring spatial variability of site properties including electrical conductivity and others soil features as well as their impact on the spatial variability of yields. Therefore, site-specific management could be applied to improve the efficiency in the use of agrochemicals, the environmental protection, and the sustainability of the rural life. Currently, there is a wide offer of technological resources to capture spatial variation across sites within field. However, the optimum use of data coming from the precision agriculture machineries strongly depends on the capabilities to explore the information about the complex interactions underlying the productive outputs. The covariation between spatial soil properties and yields from georeferenced data has been treated in a graphical manner or with standard geostatistical approaches. New statistical modeling capabilities from the Mixed Linear Model framework are promising to deal with correlated data such those produced by the precision agriculture. Moreover, rescuing the multivariate nature of the multiple data collected at each site, several multivariate statistical approaches could be crucial tools for data analysis with georeferenced data. Understanding the basis of complex interactions at the scale of production field is now within reach the use of these new techniques. Our main objectives are: (1) to develop new statistical strategies, based on the complementarities of geostatistics and multivariate methods, useful to classify sites within field grown with grain crops and analyze the interrelationships of several soil and yield variables, (2) to propose mixed linear models to predict yield according spatial soil variability and to build contour maps to promote a more sustainable agriculture.

Epidemiology of multiple congenital anomalies in Europe: a EUROCAT population-based registry study.

BACKGROUND: This study describes the prevalence, associated anomalies, and demographic characteristics of cases of multiple congenital anomalies (MCA) in 19 population-based European registries (EUROCAT) covering 959,446 births in 2004 and 2010. METHODS: EUROCAT implemented a computer algorithm for classification of congenital anomaly cases followed by manual review of potential MCA cases by geneticists. MCA cases are defined as cases with two or more major anomalies of different organ systems, excluding sequences, chromosomal and monogenic syndromes. RESULTS: The combination of an epidemiological and clinical approach for classification of cases has improved the quality and accuracy of the MCA data. Total prevalence of MCA cases was 15.8 per 10,000 births. Fetal deaths and termination of pregnancy were significantly more frequent in MCA cases compared with isolated cases (p < 0.001) and MCA cases were more frequently prenatally diagnosed (p < 0.001). Live born infants with MCA were more often born preterm (p < 0.01) and with birth weight < 2500 grams (p < 0.01). Respiratory and ear, face, and neck anomalies were the most likely to occur with other anomalies (34% and 32%) and congenital heart defects and limb anomalies were the least likely to occur with other anomalies (13%) (p < 0.01). However, due to their high prevalence, congenital heart defects were present in half of all MCA cases. Among males with MCA, the frequency of genital anomalies was significantly greater than the frequency of genital anomalies among females with MCA (p < 0.001). CONCLUSION: Although rare, MCA cases are an important public health issue, because of their severity. The EUROCAT database of MCA cases will allow future investigation on the epidemiology of these conditions and related clinical and diagnostic problems.

Empirical studies in industrial location: an assessment of their methods and results

This paper surveys recent evidence on the determinants of (national and/or foreign) industrial location. We find that the basic analytical framework has remained essentially unaltered since the early contributions of the early 1980's while, in contrast, there have been significant advances in the quality of the data and, to a lesser extent, the econometric modelling. We also identify certain determinants (neoclassical and institutional factors) that tend to provide largely consistent results across the reviewed studies. In light of this evidence, we finally suggest future lines of research.

Effect of vitamin D on Epstein-Barr (EBV)-specific CD8+T cells in patients with early multiple sclerosis (MS)

Background: Infection with EBV and a lack in vitamin D may be important environmental triggers of MS. 1,25-(OH)2D3 mediates a shift of antigen presenting cells (APC) and CD4+ T cells to a less inflammatory profile. Although CD8+ T cells do express the vitamin D receptor, a direct effect of 1,25(OH)2D3 on these cells has not been demonstrated until now. Since CD8+ T cells are important immune mediators of the inflammatory response in MS, we examined whether vitamin D directly affects the CD8+ T cell response, and more specifically if it modulates the EBV-specific CD8+ T cell response. Material and Methods: To explore whether the vitamin D status may influence the pattern of the EBV-specific CD8+ T cell response, PBMC of 10 patients with early MS and 10 healthy controls (HC) were stimulated with a pool of immunodominant 8-10 mer peptide epitopes known to elicit CD8+ T cell responses. PBMC were stimulated with this EBV CD8 peptide pool, medium (negative control) or anti- CD3/anti-CD28 beads (positive control). The following assays were performed: ELISPOT to assess the secretion of IFN-gamma by T cells in general; cytometric beads array (CBA) and ELISA to determine whichcytokines were released by EBV-specific CD8+ T cells after six days of culture; and intracellular cytokine staining assay to determine by which subtype of T cells secreted given cytokines. To examine whether vitamin D could directly modulate CD8+ T cell immune responses, we depleted CD4+ T cells using negative selection. Results: We found that pre-treatment of vitamin D had an antiinflammatory action on both EBV-specific CD8+ T cells and on CD3/ CD28-stimulated T cells: secretion of pro-inflammatory cytokines (IFNgamma and TNF-alpha) was decreased, whereas secretion of antiinflammatory cytokines (IL-5 and TGF-beta) was increased. At baseline, CD8+ T cells of early MS patients showed a higher secretion of TNFalpha and lower secretion of IL-5. Addition of vitamin D did not restore the same levels of both cytokines as compared to HC. Vitamin D-pretreated CD8+T cells exhibited a decreased secretion of IFN-gamma and TNF-alpha, even after depletion of CD4+ T cells from culture. Conclusion: Vitamin D has a direct anti-inflammatory effect on CD8+ T cells independently from CD4+ T cells. CD8+ T cells of patients with earlyMS are less responsive to the inflammatory effect of vitamin D than HC, pointing toward an intrinsic dysregulation of CD8+ T cells. The modulation of EBV-specific CD8+T cells by vitaminDsuggests that there may be interplay between these twomajor environmental factors of MS. This study was supported by a grant from the Swiss National Foundation (PP00P3-124893), and by an unrestricted research grant from Bayer to RDP.

Statin use and peripheral blood progenitor cells mobilization in patients with multiple myeloma.

PURPOSE: Statins have beneficial effects in patients after myocardial infarction and at least part of the benefit results from mobilization of marrow endothelial progenitors to repopulate damaged myocardial tissues. This study examines if statins may have the same effect in mobilizing marrow progenitors to be harvested and subsequently used in high-dose chemotherapy with progenitor cell rescue in multiple myeloma. METHODS: From 2006 to 2012, 86 patients with multiple myeloma were mobilized with the use of G-CSF and were retrospectively analyzed. Patients with other malignancies or mobilized with the use of chemotherapy or with plerixafor were excluded. RESULTS: The median age of the patients was 60 years. 72 patients had received one line of chemotherapy and 14 patients two or more lines of chemotherapy. Twenty patients were taking statins at the time of the harvest while 66 patients were not. In the group of patients taking statins the success rate of first leukapheresis (obtaining the target number of 4 × 10(6) CD34+ cells/kg) was 85 % while in the group not taking statins this rate was 63.6 %. Despite the comparatively small number of patients this difference approached statistical significance (χ (2) = 0.07). CONCLUSION: This retrospective analysis of 86 patients shows for the first time a possible benefit of statins for peripheral blood progenitor cells mobilization in patients with multiple myeloma. Larger studies would be required to clarify the issue. If their effectiveness is confirmed, statins could be a safe and cheaper addition to chemotherapy and plerixafor for peripheral hematopoietic stem cell mobilization.

First use of multiple substances: Identification of meaningful patterns

Context: Understanding the process through which adolescents and young adults are trying legal and illegal substances is a crucial point for the development of tailored prevention and treatment programs. However, patterns of substance first use can be very complex when multiple substances are considered, requiring reduction into a few meaningful number of categories. Data: We used data from a survey on adolescent and young adult health conducted in 2002 in Switzerland. Answers from 2212 subjects aged 19 and 20 were included. The first consumption ever of 10 substances (tobacco, cannabis, medicine to get high, sniff (volatile substances, and inhalants), ecstasy, GHB, LSD, cocaine, methadone, and heroin) was considered for a grand total of 516 different patterns. Methods: In a first step, automatic clustering was used to decrease the number of patterns to 50. Then, two groups of substance use experts, three social field workers, and three toxicologists and health professionals, were asked to reduce them into a maximum of 10 meaningful categories. Results: Classifications obtained through our methodology are of practical interest by revealing associations invisible to purely automatic algorithms. The article includes a detailed analysis of both final classifications, and a discussion on the advantages and limitations of our approach.

How reliable is the monitoring of permanent vegetation plots? A test with multiple observers

Questions: A multiple plot design was developed for permanent vegetation plots. How reliable are the different methods used in this design and which changes can we measure? Location: Alpine meadows (2430 m a.s.l.) in the Swiss Alps. Methods: Four inventories were obtained from 40 m(2) plots: four subplots (0.4 m(2)) with a list of species, two 10m transects with the point method (50 points on each), one subplot (4 m2) with a list of species and visual cover estimates as a percentage and the complete plot (40 m(2)) with a list of species and visual estimates in classes. This design was tested by five to seven experienced botanists in three plots. Results: Whatever the sampling size, only 45-63% of the species were seen by all the observers. However, the majority of the overlooked species had cover < 0.1%. Pairs of observers overlooked 10-20% less species than single observers. The point method was the best method for cover estimate, but it took much longer than visual cover estimates, and 100 points allowed for the monitoring of only a very limited number of species. The visual estimate as a percentage was more precise than classes. Working in pairs did not improve the estimates, but one botanist repeating the survey is more reliable than a succession of different observers. Conclusion: Lists of species are insufficient for monitoring. It is necessary to add cover estimates to allow for subsequent interpretations in spite of the overlooked species. The choice of the method depends on the available resources: the point method is time consuming but gives precise data for a limited number of species, while visual estimates are quick but allow for recording only large changes in cover. Constant pairs of observers improve the reliability of the records.

Equilibrium Exchange Rate Determination and Multiple Structural Changes

The large appreciation and depreciation of the US dollar in the 1980s stimulated an important debate on the usefulness of unit root tests in the presence of structural breaks. In this paper, we propose a simple model to describe the evolution of the real exchange rate. We then propose a more general smooth transition (STR) function than has hitherto been employed, which is able to capture structural changes along the (long-run) equilibrium path, and show that this is consistent with our economic model. Our framework allows for a gradual adjustment between regimes and allows for under- and/or over-valued exchange rate adjustments. Using monthly and quarterly data for up to twenty OECD countries, we apply our methodology to investigate the univariate time series properties of CPI-based real exchange rates with both the U.S. dollar and German mark as the numeraire currencies. The empirical results show that, for more than half of the quarterly series, the evidence in favour of the stationarity of the real exchange rate was clearer in the sub-sample period post-1980.

99mTc-sestamibi imaging and bone marrow karyotyping in the assessment of multiple myeloma and MGUS

AIM: The first pathogenetic step in multiple myeloma is the emergence of a limited number of clonal plasma cells, clinically known as monoclonal gammopathy of undetermined significance (MGUS). Patients with MGUS do not have symptoms or end-organ damage but they do have a 1% annual risk of progression to multiple myeloma or related malignant disorders. With progression of MGUS to multiple myeloma, complex genetic events occur in the neoplastic plasma cell. Karyotyping and fluorescence in-situ hybridization (FISH) were shown to be of prognostic value in patients with multiple myeloma. Tc-sestamibi imaging reflects myeloma disease activity in bone marrow with very high sensitivity and specificity predicting disease evolution. This study was undertaken to evaluate the role of Tc-sestamibi imaging and cytogenetic analysis in prognosis prediction of MGUS and multiple myeloma. METHODS: We enrolled 30 consecutive patients with a confirmed diagnosis of multiple myeloma or MGUS. Bone marrow biopsy and biochemical staging according to the International Staging System (ISS) were performed in all cases. Karyotype analysis and FISH were performed in 11 of 12 patients with MGUS and in 17 of 18 patients with multiple myeloma having adequate metaphases. RESULTS: The karyotype was abnormal in four of 11 MGUS and in six of 17 multiple myeloma. Abnormalities of chromosome 13 were present in one case of MGUS and in six cases of multiple myeloma whereas the involvement of immunoglobulin was observed in one case of multiple myeloma. An abnormal FISH panel was found in four MGUS and nine multiple myeloma patients. All patients with MGUS showed a normal MIBI scan (score 0). Among patients with multiple myeloma only three, all with ISS stage I, showed a normal scan while a positive scan was obtained in others (score range, 1-7). The MIBI uptake was strongly related to the bone marrow plasma cell infiltration and to cytogenetic abnormalities. Particularly, a MIBI uptake score above 5 identified patients with poor prognosis encompassing all stage III multiple myeloma and three of seven stage II multiple myeloma. On the other hand all stage I and II patients having a MIBI score less than 5 showed a good prognosis. CONCLUSION: Both cytogenetic analysis and a MIBI scan add no relevant prognostic information to the ISS in patients with stage I and III multiple myeloma. The MIBI scan was of prognostic value in stage II multiple myeloma patients. Additionally, MIBI imaging may be useful to guide bone marrow biopsy in order to obtain adequate samples for cytogenetic analysis.

Vitamin D has a direct immunomodulatory effect on CD8+ T cells of patients with early multiple sclerosis and healthy control subjects.

Little is known on a putative effect of vitamin D on CD8+ T cells. Yet, these cells are involved in the immmunopathogenesis of MS. We assessed the cytokine profile of EBV-specific CD8+ T cells of 10 early MS patients and 10 healthy control subjects with or without 1,25(OH)(2)D(3) and found that, with 1,25(OH)(2)D(3), these cells secreted less IFN-γ and TNF-α and more IL-5 and TGF-β. CD4+ T cell depletion or even culture with CD8+ T cells only did not abolish the immunomodulatory effect of 1,25(OH)(2)D(3) on CD8+ T cells, suggesting that 1,25(OH)(2)D(3) can act directly on CD8+ T cells.

A Modulated Closed Form solution for Quantitative Susceptibility Mapping - A thorough evaluation and comparison to iterative methods based on edge prior knowledge.

The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.