Sensitivity Analysis: An operational picture

Modelling is crucial to understand the behavior of environmental systems.Adeeper comprehension of a model can be aided by global sensitivity analysis.Variabilityascribed to model variables could have a stochastic (i.e., lack of knowledge) or an operational (i.e., possible design values) origin. Despite the possible different nature inthe variability,current global sensitivity analysis strategies do not distinguish the latter in their formal derivations/developments. We propose to disentangle the variability inthe operational and stochastic variables while assessing the model output sensitivity with respect to theformer. Two operational sensitivity indices are introduced thatserve to characterize the sensitivity of a model output of interest with respect to an operational variable in terms of (a) its average(with respect to the stochastic variables) intensity and (b)its degree of fluctuation (across the set of possible realizations of the stochastic variables), respectively. We exemplify our developments considering two scenarios. Results highlight the relevance of employing an operational global sensitivity analysis when the focus is on the influence of operational variables on model outpu

Stochastic inverse modeling of transient laboratory-scale three-dimensional two-phase core flooding scenarios

We develop a comprehensive and efficient workflow for a stochastic assessment of key parameters governing two-phase flow conditions associated with core-scale experiments. We rely on original and detailed datasets collected on a Berea sandstone sample. These capture the temporal evolution of pressure drop across the core and three-dimensional maps of phase saturations (determined via X-ray CT) in oil- and brine-displacement flooding scenarios characterized by diverse brine/oil viscosity contrasts. Such experiments are used as a test-bed for the proposed stochastic model calibration strategy. The latter is structured across three main steps: (i) a preliminary calibration, aimed at identifying a behavioral region of the model parameter space; (ii) a Global Sensitivity Analysis (GSA), geared towards identification of the relative importance of model parameters on observed model outputs and assessment of non-influential parameters to reduce dimensionality of the parameter space; and (iii) a stochastic inverse modeling procedure. The latter is based on a differential-evolution genetic algorithm to efficiently explore the reduced parameter space stemming from the GSA. It enables one to obtain a probabilistic description of the relevant model parameters through their frequency distributions conditional on the detailed type of information collected. Coupling GSA with a stochastic parameter estimation approach based on a genetic algorithm of the type we consider enables streamlining the procedure and effectively cope with the considerable computational efforts linked to the two-phase scenario considered. Results show a remarkable agreement with experimental data and imbue us with confidence on the potential of the approach to embed the type of rich datasets considered towards model parameter estimation fully including uncertainty

Acute kidney injury and acute kidney disease in high-dose cisplatin-treated head and neck cancer

Background: In locally advanced head and neck squamous cell carcinoma (LA-SCCHN) at least 200mg/m2 (standard dose 300 mg/m2) of cisplatin concomitant with radiotherapy represents the standard of care, both in postoperative and conservative settings. Nevertheless, high dose administration every 3 weeks is often replaced with low dose weekly cisplatin to avoid toxicities like kidney injury, though often failing to reach the therapeutic dose. Our aim was to investigate the incidence of renal impairment in the real-life setting, integrating high dose cisplatin with adequate supportive therapy, and to explore both Acute Kidney Injury (AKI) and Acute Kidney Disease (AKD), a recently described clinical renal syndrome that encompasses functional alterations of the kidney lasting fewer than 3 months. Methods: One hundred and nine consecutive patients affected by LA-SCCHN and treated with at least a cumulative dosage of 200 mg/m2 of cisplatin concomitant with radiotherapy were enrolled in this prospective observational study. Results: AKI was reported in 12.8% of patients, 50% of whom were stage 1 (KDIGO criteria), while 25.7% of the cohort developed AKD. Patients with baseline estimated Glomerular Filtration Rate (eGFR) < 90 ml/min showed a higher incidence of AKD (36.2% vs 17.7%). Hypertension, baseline eGFR, and therapy with Renin-angiotensin-aldosterone system inhibitors proved to be significant factors associated with both AKI and AKD. Conclusion: AKI and AKD are not rare complications of high-dose cisplatin, but an appropriate prevention strategy and accurate monitoring of patients during treatment could lead to a reduction of the burden of these conditions

EP-1349: Long term results of a phase I-II study of moderate hypofractionated IGRT in prostate cancer

Pregnant women diagnosed with gestational diabetes mellitus subjected to diet (GDMd) that do not reach normal glycaemia are passed to insulin therapy (GDMi). GDMd associates with increased human cationic amino acid transporter 1 (hCAT-1)-mediated transport of L-arginine and nitric oxide synthase (NOS) activity in foetoplacental vasculature, a phenomenon reversed by exogenous insulin. Whether insulin therapy results in reversal of the GDMd effect on the foetoplacental vasculature is unknown. We assayed whether insulin therapy normalizes GDMd-associated foetoplacental endothelial dysfunction. Primary cultures of human umbilical vein endothelial cells (HUVECs) from GDMi pregnancies were used to assay L-arginine transport kinetics, NOS activity, p44/42mapk and protein kinase B/Akt activation, and umbilical vein rings reactivity. HUVECs from GDMi or GDMd show increased hCAT-1 expression and maximal transport capacity, NOS activity, and eNOS, and p44/42mapk, but not Akt activator phosphorylation. Dilation in response to insulin or calcitonin-gene related peptide was impaired in umbilical vein rings from GDMi and GDMd pregnancies. Incubation of HUVECs in vitro with insulin (1 nmol/L) restored hCAT-1 and eNOS expression and activity, and eNOS and p44/42mapk activator phosphorylation. Thus, maternal insulin therapy does not seem to reverse GDMd-associated alterations in human foetoplacental vasculature.Fondo Nacional de Desarrollo Científico y Tecnológico Chileno 1150377 , 1150344 , 11150083Servicio de Salud de Medicina Oriente de Chile 1938–2016Marie Curie International Research 295185 - EULAMDIM

Phenotypical, Clinical, and Molecular Aspects of Adults and Children With Homozygous Familial Hypercholesterolemia in Iberoamerica

Fil: Alves, Ana Catarina. Instituto Nacional de Saúde Doutor Ricardo Jorge, Lisboa; Portugal.Fil: Alonso, Rodrigo. Center for Advanced Metabolic Medicine and Nutrition, Santiago; Chile.Fil: Diaz-Diaz, José Luís. Hospital Universitario A Coruña. Department of Internal Medicine; España.Fil: Medeiros, Ana Margarida. Instituto Nacional de Saúde Doutor Ricardo Jorge, Lisboa; Portugal.Fil: Jannes, Cinthia E. University of São Paulo. Medical School. Hospital São Paulo. Heart Institute (InCor); Brasil.Fil: Merchan, Alonso. Fundación Clinica SHAIO, Cardiología, Bogotá; Colombia.Fil: Vasques-Cardenas, Norma A. Universidad Autónoma de Guadalajara. Facultad de Medicina Zapopan; México.Fil: Cuevas, Ada. Center for Advanced Metabolic Medicine and Nutrition, Santiago; Chile.Fil: Chacra, Ana Paula. University of São Paulo. Medical School. Hospital São Paulo. Heart Institute (InCor); Brasil.Fil: Krieger, Jose E. University of São Paulo. Medical School. Hospital São Paulo. Heart Institute (InCor); Brasil.Fil: Arroyo, Raquel. Fundación Hipercolesterolemia Familiar, Madrid; España.Fil: Arrieta, Francisco. Hospital Ramón y Cajal. Departamento de Endocrinología, Madrid; España.Fil: Schreier, Laura. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Bioquímica Clínica, Laboratorio de Lípidos y Aterosclerosis; Argentina.Fil: Corral, Pablo. Universidad FASTA. Facultad de Medicina. Cátedra Farmacología e Investigación, Mar del Plata; Argentina.Fil: Bañares, Virginia. ANLIS Dr.C.G.Malbrán. Centro Nacional de Genética Médica. Departamento de Genética Experimental; Argentina.Fil: Araujo, Maria B. Hospital Garrahan. Servicio de Nutrición; Argentina.Fil: Bustos, Paula. Universidad de Concepción. Facultad de Farmacia; Chile.Fil: Asenjo, Sylvia. Universidad de Concepción. Facultad de Medicina; Chile.Fil: Stoll, Mario. Programa GENYCO, Laboratorio de Genética Molecular. Comisión Honoraria de Salud Cardiovascular, Montevideo; Uruguay.Fil: Dell'Oca, Nicolás. Programa GENYCO, Laboratorio de Genética Molecular. Comisión Honoraria de Salud Cardiovascular, Montevideo; Uruguay.Fil: Reyes, Maria. Fundación Cardiovascular de Colombia. Cardiología; Bogotá.Fil: Ressia, Andrés. Fundación Cardiovascular de Colombia. Cardiología; Bogotá.Fil: Campo, Rafael. Instituto Mexicano del Seguro Social. Centro de Investigación Biomédica del Occidente, Guadalajara; México.Fil: Magaña-Torres, Maria T. Instituto Nacional de Ciencias Médicas y Nutrición. Unidad de Investigación de Enfermedades Metabólicas; México.Fil: Metha, Roopa. Instituto Nacional de Ciencias Médicas y Nutrición. Unidad de Investigación de Enfermedades Metabólicas; México.Fil: Aguilar-Salinas, Carlos A. Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán. Departamento de Endocrinología y Metabolismo. Secretaría de la Defensa Nacional. Unidad de Especialidades Médicas. Servicio de Endocrinología; México.Fil: Ceballos-Macias, José J. Pontificia Universidad Javerina. Facultad de Medicina. Departamento de Medicina Interna, Bogotá; Colombia.Fil: Ruiz Morales, Álvaro J. Pontificia Universidad Javerina. Facultad de Medicina. Departamento de Medicina Interna, Bogotá; Colombia.Fil: Mata, Pedro. Fundación Hipercolesterolemia Familiar, Madrid; España.Fil: Bourbon, Mafalda. Instituto Nacional de Saúde Doutor Ricardo Jorge, Lisboa; Portugal.Fil: Santos, Raul D. University of São Paulo. Medical School. Hospital São Paulo. Heart Institute (InCor); Brasil.OBJECTIVE: Characterize homozygous familial hypercholesterolemia (HoFH) individuals from Iberoamerica. APPROACH AND RESULTS: In a cross-sectional retrospective evaluation 134 individuals with a HoFH phenotype, 71 adults (age 39.3±15.8 years, 38.0% males), and 63 children (age 8.8±4.0 years, 50.8% males) were studied. Genetic characterization was available in 129 (96%). The majority (91%) were true homozygotes (true HoFH, n=79, 43.0% children, 46.8% males) or compound heterozygotes (compound heterozygous familial hypercholesterolemia, n=39, 51.3% children, 46.2% males) with putative pathogenic variants in the LDLR. True HoFH due to LDLR variants had higher total (P=0.015) and LDL (low-density lipoprotein)-cholesterol (P=0.008) compared with compound heterozygous familial hypercholesterolemia. Children with true HoFH (n=34) tended to be diagnosed earlier (P=0.051) and had a greater frequency of xanthomas (P=0.016) than those with compound heterozygous familial hypercholesterolemia (n=20). Previous major cardiovascular events were present in 25 (48%) of 52 children (missing information in 2 cases), and in 43 (67%) of 64 adults with LDLR variants. Children who are true HoFH had higher frequency of major cardiovascular events (P=0.02), coronary heart (P=0.013), and aortic/supra-aortic valve diseases (P=0.022) than compound heterozygous familial hypercholesterolemia. In adults, no differences were observed in major cardiovascular events according to type of LDLR variant. From 118 subjects with LDLR variants, 76 (64%) had 2 likely pathogenic or pathogenic variants. In 89 subjects with 2 LDLR variants, those with at least one null allele were younger (P=0.003) and had a greater frequency of major cardiovascular events (P=0.038) occurring at an earlier age (P=0.001). CONCLUSIONS: There was a high frequency of cardiovascular disease even in children. Phenotype and cardiovascular complications were heterogeneous and associated with the type of molecular defect

Interpretation of multi-scale permeability data through an information theory perspective

We employ elements of information theory to quantify (i) the information content related to data collected at given measurement scales within the same porous medium domain and (ii) the relationships among information contents of datasets associated with differing scales. We focus on gas permeability data collected over Berea Sandstone and Topopah Spring Tuff blocks, considering four measurement scales. We quantify the way information is shared across these scales through (i) the Shannon entropy of the data associated with each support scale, (ii) mutual information shared between data taken at increasing support scales, and (iii) multivariate mutual information shared within triplets of datasets, each associated with a given scale. We also assess the level of uniqueness, redundancy and synergy (rendering, i.e., information partitioning) of information content that the data associated with the intermediate and largest scales provide with respect to the information embedded in the data collected at the smallest support scale in a triplet

Characterization of flow through random media via Karhunen–Loève expansion: an information theory perspective

We leverage on information theory to assess the fidelity of approximated numerical stochastic groundwater flow simulations. We consider flow in saturated heterogeneous porous media, where the Karhunen–Loève (KL) expansion is used to express the hydraulic conductivity as a spatially correlated random field. We quantify the impact of the KL expansion truncation on the uncertainty associated with punctual values of hydraulic conductivity and flow velocity. In particular, we compare the statistical dependence between variables by considering (a) linear correlation metrics (Pearson coefficient of correlation) and (b) metrics capable of accounting for nonlinear dependence (coefficient of uncertainty based on mutual information). We test the selected metrics by analyzing the relationship between hydraulic conductivity fields generated via Monte Carlo sampling with different levels of truncation of the KL expansion and the corresponding fluid velocity fields, obtained through the numerical solution of Darcy’s flow. Our analysis shows that employing linear correlation metrics leads to a general overestimation of the correlation level and information theory based indicators are valuable tools to assess the impact of the KL truncation on the output velocity values. We then analyze the impact of the number of retained modes on the spatial organization of the velocity field. Results indicates that (i) as the number of modes decrease the spatial correlations of the velocity field increases; (ii) linear indicators of spatial correlation are again larger than their nonlinear counterparts

Global Sensitivity Analysis for Multiple Interpretive Models With Uncertain Parameters

We propose a set of new indices to assist global sensitivity analysis in the presence of data allowing for interpretations based on a collection of diverse models whose parameters could be affected by uncertainty. Our global sensitivity analysis metrics enable us to assess the sensitivity of various features (as rendered through statistical moments) of the probability density function of a quantity of interest with respect to imperfect knowledge of (i) the interpretive model employed to characterize the system behavior and (ii) the ensuing model parameters. We exemplify our methodology for the case of heavy metal sorption onto soil, for which we consider three broadly used (equilibrium isotherm) models. Our analyses consider (a) an unconstrained case, i.e., when no data are available to constrain parameter uncertainty and to evaluate the (relative) plausibility of each considered model, and (b) a constrained case, i.e., when the analysis is constrained against experimental observations. Our moment-based indices are structured according to two key components: (a) a model-choice contribution, associated with the possibility of analyzing the system of interest by taking advantage of multiple model conceptualizations (or mathematical renderings); and (b) a parameter-choice contribution, related to the uncertainty in the parameters of a selected model. Our results indicate that a given parameter can be associated with diverse degrees of importance, depending on the considered statistical moment of the target model output. The influence on the latter of parameter and model uncertainty evolves as a function of the available level of information about the modeled system behavior