Temporal relationships of a pulse of prolactin (PRL) to a pulse of a metabolite of PGF2 alpha in mares

Hourly blood samples were collected from 10 mares during 24 h of each of the preluteolytic, luteolytic, and postluteolytic periods. The autocorrelation function of the R program was used to detect pulse rhythmicity, and the intra-assay CV was used to locate and characterize pulses of prolactin (PRL) and a metabolite of prostaglandin F2 alpha (PGFM). Rhythmicity of PRL and PGFM concentrations was detected in 67% and 89% of mares, respectively. Combined for the three periods (no difference among periods), the PRL pulses were 5.2 +/- 0.4 h (mean +/- SEM) at the base, 7.5 +/- 1.5 h between nadirs of adjacent pulses, and 12.3 +/- 1.5 h from peak to peak. The peaks of PRL pulses were greater (P < 0.05) during the luteolytic period (46 +/- 14 ng/mL) and postluteolytic period (52 15 ng/mL) than during the preluteolytic period (17 3 ng/mL). Concentrations of PRL during hours of a PGFM pulse were different (P < 0.003) within the luteolytic period and postluteolytic period and were greatest at the PGFM peak; PRL concentrations during a PGFM pulse were not different during the preluteolytic period. The frequency of the peak of PRL and PGFM pulses occurring at the same hour (synchrony) was greater for the luteolytic period (65%, P < 0.01) and postluteolytic period (50%, P < 0.001) than for the preluteolytic period (17%). This is the first report in mares on characterization and rhythmicity of PRL pulses, synchrony between PRL and PGFM pulses, and greater PRL activity during the luteolytic and postluteolytic periods than during the preluteolytic period. (C) 2012 Elsevier Inc. All rights reserved.

Sensitivity, specificity and predictive values of linear and nonlinear indices of heart rate variability in stable angina patients

Abstract Background Decreased heart rate variability (HRV) is related to higher morbidity and mortality. In this study we evaluated the linear and nonlinear indices of the HRV in stable angina patients submitted to coronary angiography. Methods We studied 77 unselected patients for elective coronary angiography, which were divided into two groups: coronary artery disease (CAD) and non-CAD groups. For analysis of HRV indices, HRV was recorded beat by beat with the volunteers in the supine position for 40 minutes. We analyzed the linear indices in the time (SDNN [standard deviation of normal to normal], NN50 [total number of adjacent RR intervals with a difference of duration greater than 50ms] and RMSSD [root-mean square of differences]) and frequency domains ultra-low frequency (ULF) ≤ 0,003 Hz, very low frequency (VLF) 0,003 – 0,04 Hz, low frequency (LF) (0.04–0.15 Hz), and high frequency (HF) (0.15–0.40 Hz) as well as the ratio between LF and HF components (LF/HF). In relation to the nonlinear indices we evaluated SD1, SD2, SD1/SD2, approximate entropy (−ApEn), α1, α2, Lyapunov Exponent, Hurst Exponent, autocorrelation and dimension correlation. The definition of the cutoff point of the variables for predictive tests was obtained by the Receiver Operating Characteristic curve (ROC). The area under the ROC curve was calculated by the extended trapezoidal rule, assuming as relevant areas under the curve ≥ 0.650. Results Coronary arterial disease patients presented reduced values of SDNN, RMSSD, NN50, HF, SD1, SD2 and -ApEn. HF ≤ 66 ms2, RMSSD ≤ 23.9 ms, ApEn ≤−0.296 and NN50 ≤ 16 presented the best discriminatory power for the presence of significant coronary obstruction. Conclusion We suggest the use of Heart Rate Variability Analysis in linear and nonlinear domains, for prognostic purposes in patients with stable angina pectoris, in view of their overall impairment.

Indagine delle proprietà statistiche di serie temporali di posizione applicata al caso della stazione permanente GPS della base Mario Zucchelli in Terra Vittoria (Antartide)

Da ormai sette anni la stazione permanente GPS di Baia Terranova acquisisce dati giornalieri che opportunamente elaborati consentono di contribuire alla comprensione della dinamica antartica e a verificare se modelli globali di natura geofisica siano aderenti all’area di interesse della stazione GPS permanente. Da ricerche bibliografiche condotte si è dedotto che una serie GPS presenta molteplici possibili perturbazioni principalmente dovute a errori nella modellizzazione di alcuni dati ancillari necessari al processamento. Non solo, da alcune analisi svolte, è emerso come tali serie temporali ricavate da rilievi geodetici, siano afflitte da differenti tipologie di rumore che possono alterare, se non opportunamente considerate, i parametri di interesse per le interpretazioni geofisiche del dato. Il lavoro di tesi consiste nel comprendere in che misura tali errori, possano incidere sui parametri dinamici che caratterizzano il moto della stazione permanente, facendo particolare riferimento alla velocità del punto sul quale la stazione è installata e sugli eventuali segnali periodici che possono essere individuati.

Monte Carlo simulations of Potts glasses

A complete understanding of the glass transition isstill a challenging problem. Some researchers attributeit to the (hypothetical) occurrence of a static phasetransition, others emphasize the dynamical transitionof mode coupling-theory from an ergodic to a non ergodicstate. A class of disordered spin models has been foundwhich unifies both scenarios. One of these models isthe p-state infinite range Potts glass with p>4, whichexhibits in the thermodynamic limit both a dynamicalphase transition at a temperature T_D, and a static oneat T_0 < T_D. In this model every spins interacts withall the others, irrespective of distance. Interactionsare taken from a Gaussian distribution.In order to understand better its behavior forfinite number N of spins and the approach to thethermodynamic limit, we have performed extensive MonteCarlo simulations of the p=10 Potts glass up to N=2560.The time-dependent spin-autocorrelation function C(t)shows strong finite size effects and it does not showa plateau even for temperatures around the dynamicalcritical temperature T_D. We show that the N-andT-dependence of the relaxation time for T > T_D can beunderstood by means of a dynamical finite size scalingAnsatz.The behavior in the spin glass phase down to atemperature T=0.7 (about 60% of the transitiontemperature) is studied. Well equilibratedconfigurations are obtained with the paralleltempering method, which is also useful for properlyestablishing static properties, such as the orderparameter distribution function P(q). Evidence is givenfor the compatibility with a one step replica symmetrybreaking scenario. The study of the cumulants of theorder parameter does not permit a reliable estimation ofthe static transition temperature. The autocorrelationfunction at low T exhibits a two-step decay, and ascaling behavior typical of supercooled liquids, thetime-temperature superposition principle, is observed. Inthis region the dynamics is governed by Arrheniusrelaxations, with barriers growing like N^{1/2}.We analyzed the single spin dynamics down to temperaturesmuch lower than the dynamical transition temperature. We found strong dynamical heterogeneities, which explainthe non-exponential character of the spin autocorrelationfunction. The spins seem to relax according to dynamicalclusters. The model in three dimensions tends to acquireferromagnetic order for equal concentration of ferro-and antiferromagnetic bonds. The ordering has differentcharacteristics from the pure ferromagnet. The spinglass susceptibility behaves like chi_{SG} proportionalto 1/T in the region where a spin glass is predicted toexist in mean-field. Also the analysis of the cumulantsis consistent with the absence of spin glass orderingat finite temperature. The dynamics shows multi-scalerelaxations if a bimodal distribution of bonds isused. We propose to understand it with a model based onthe local spin configuration. This is consistent with theabsence of plateaus if Gaussian interactions are used.

Confocal microscopy applied to the study of single entity fluorescence and light scattering

A sample scanning confocal optical microscope (SCOM) was designed and constructed in order to perform local measurements of fluorescence, light scattering and Raman scattering. This instrument allows to measure time resolved fluorescence, Raman scattering and light scattering from the same diffraction limited spot. Fluorescence from single molecules and light scattering from metallic nanoparticles can be studied. First, the electric field distribution in the focus of the SCOM was modelled. This enables the design of illumination modes for different purposes, such as the determination of the three-dimensional orientation of single chromophores. Second, a method for the calculation of the de-excitation rates of a chromophore was presented. This permits to compare different detection schemes and experimental geometries in order to optimize the collection of fluorescence photons. Both methods were combined to calculate the SCOM fluorescence signal of a chromophore in a general layered system. The fluorescence excitation and emission of single molecules through a thin gold film was investigated experimentally and modelled. It was demonstrated that, due to the mediation of surface plasmons, single molecule fluorescence near a thin gold film can be excited and detected with an epi-illumination scheme through the film. Single molecule fluorescence as close as 15nm to the gold film was studied in this manner. The fluorescence dynamics (fluorescence blinking and excited state lifetime) of single molecules was studied in the presence and in the absence of a nearby gold film in order to investigate the influence of the metal on the electronic transition rates. The trace-histogram and the autocorrelation methods for the analysis of single molecule fluorescence blinking were presented and compared via the analysis of Monte-Carlo simulated data. The nearby gold influences the total decay rate in agreement to theory. The gold presence produced no influence on the ISC rate from the excited state to the triplet but increased by a factor of 2 the transition rate from the triplet to the singlet ground state. The photoluminescence blinking of Zn0.42Cd0.58Se QDs on glass and ITO substrates was investigated experimentally as a function of the excitation power (P) and modelled via Monte-Carlo simulations. At low P, it was observed that the probability of a certain on- or off-time follows a negative power-law with exponent near to 1.6. As P increased, the on-time fraction reduced on both substrates whereas the off-times did not change. A weak residual memory effect between consecutive on-times and consecutive off-times was observed but not between an on-time and the adjacent off-time. All of this suggests the presence of two independent mechanisms governing the lifetimes of the on- and off-states. The simulated data showed Poisson-distributed off- and on-intensities, demonstrating that the observed non-Poissonian on-intensity distribution of the QDs is not a product of the underlying power-law probability and that the blinking of QDs occurs between a non-emitting off-state and a distribution of emitting on-states with different intensities. All the experimentally observed photo-induced effects could be accounted for by introducing a characteristic lifetime tPI of the on-state in the simulations. The QDs on glass presented a tPI proportional to P-1 suggesting the presence of a one-photon process. Light scattering images and spectra of colloidal and C-shaped gold nano-particles were acquired. The minimum size of a metallic scatterer detectable with the SCOM lies around 20 nm.

Influence of pollination and seed dispersal on the genetic population structure of two Commiphora species in Madagascar and South Africa

Pollination and seed dispersal are important ecological processes for the regeneration of plant populations and both vectors for gene exchange between plant populations. For my thesis, I studied the pollination ecology of the South African tree Commiphora harveyi (Burseraceae) and compared it with C. guillauminii from Madagascar. Both species have low visitation rates and a low number of pollinating insect species, resulting in a low fruit set. While their pollination ecology is very similar, they differ in their seed dispersal with a low seed dispersal rate in the Malagasy and a high seed dispersal rate in the South African species. This should be reflected in a stronger genetic differentiation among populations in the Malagasy than in the South African species. My results, based on AFLP markers, contradict these expectations, the overall differentiation was lower in the Malagasy (FST = 0.05) than in the South African species (FST = 0.16). However, at a smaller spatial scale (below 3 km), the Malagasy species was genetically more strongly differentiated than the South African species, which was reflected by the high inter-population variance within the sample site (C. guillauminii: 72.2 - 85.5 %; C. harveyi: 8.4 - 14.5 %). This strong differentiation could arise from limited gene flow, which was confirmed by spatial autocorrelation analyses. The shape of the autocorrelogram suggested that gene exchange between individuals occurred only up to 3 km in the Malagasy species, whereas up to 30 km in the South African species. These results on the genetic structure correspond to the expectations based on seed dispersal data. Thus, seed dispersal seems to be a key factor for the genetic structure in plant populations on a local scale.

Influence of habitat and climate change on European bird communities

Die Fragmentierung von Waldgebieten, der Verlust geeigneter Habitate, die Invasion exotischer Arten und globale Klimaveränderung haben auf Artengemeinschaften erhebliche Auswirkungen. Vögel dienen in vielen Fällen als Indikatorarten für Umweltveränderungen und, besonders, für Veränderungen im Zusammenhang mit globaler Erwärmung. In meiner Arbeit habe ich zuerst einen Literaturüberblick über die Auswirkungen globaler Klimaveränderung auf die Verbreitungsgebiete, den Artenreichtum und die Zusammensetzung von Vogelgemeinschaften dargestellt. Zahlreiche Untersuchungen zeigen, daß die Grenzen der Verbreitungsgebiete der meisten Vogelarten mit klimatischen Faktoren korrelieren. Verschiebungen der Verbreitungsgebiete in nördliche Richtung oder in höhere Regionen im Gebirge konnten bereits für viele temperate Vogelarten beobachtet werden. Weiterhin wurde ein zunehmender Artenreichtum besonders in nördlichen Breiten und in höheren Lagen für viele temperate Vogelgemeinschaften vorhergesagt. In trockenen Gebieten ist dagegen mit einer Abnahme des Artenreichtums zu rechnen. Im zweiten Teil meiner Arbeit habe ich untersucht, ob beobachtete Veränderungen in der Zusammensetzung europäischer Vogelgemeinschaften tatsächlich durch aktuelle Klimaveränderungen beeinflußt werden. Das Zugverhalten der Arten war dabei ein Schwerpunkt der Untersuchung, weil zu erwarten war, daß Vogelarten mit verschiedenem Zugverhalten unterschiedlich auf Klimaveränderungen reagieren. Ich habe ein Regressionsmodell genutzt, welches die räumliche Beziehung zwischen dem Anteil von Langstreckenziehern, Kurzstreckenziehern und Standvögeln in europäischen Vogelgemeinschaften und verschiedenen Klimavariablen beschreibt. Für 21 Gebiete in Europa habe ich Daten über beobachtete Veränderungen in der Struktur der Vogelgemeinschaften und isochrone Klimaveränderungen zusammengetragen. Mit Hilfe dieser Klimaveränderungen und dem räumlichen Regressionsmodell konnte ich berechnen, welche Veränderungen in den Vogelgemeinschaften aufgrund der veränderten Klimabedingungen zu erwarten wären und sie mit beobachteten Veränderungen vergleichen. Beobachtete und berechnete Veränderungen korrelierten signifikant miteinander. Die beobachteten Veränderungen konnten nicht durch räumliche Autokorrelationseffekte oder durch alternative Faktoren, wie z.B. Veränderungen in der Landnutzung, erklärt werden. Im dritten Teil der Arbeit untersuchte ich für eine mitteleuropäische Vogelgemeinschaft welchen Einfluß Habitatveränderungen, die Invasion exotischer Arten und die Klimaveränderung auf Veränderungen der Häufigkeit und Verbreitungsgröße der 159 Vogelarten am Bodensee zwischen 1980-1981 und 2000-2002 hatten. Dabei konnte gezeigt werden, daß Veränderungen in der regionalen Abundanz sowohl durch Habitatveränderungen als auch durch Klimavänderungen hervorgerufen wurden. Exotische Arten schienen in dieser Zeit keinen bedeutenden Einfluß zu haben. Besonders bei Agrarlandarten, Arten mit nördlicheren Verbreitungsgebieten und bei Langstreckenziehern konnten signifikante Abnahmen in der Abundanz beobachtet werden. Vor allem die anhaltenden negativen Bestandsveränderungen bei Langstreckenziehern und die in den letzten zehn Jahren aufgetretenen Abnahmen nördlicher verbreiteter Vogelarten deuten darauf hin, daß die Klimaveränderung aktuell als der größte Einfluß für Vögel in Europa angesehen werden muß. Insgesamt zeigen die Ergebnisse dieser Arbeit, daß sich der anhaltende Druck auf die Umwelt in erster Linie durch Habitat- und Klimaveränderungen manifestiert.

On the Efficiency of the Benchmarks Used in the Asset Management

In this work we studied the efficiency of the benchmarks used in the asset management industry. In chapter 2 we analyzed the efficiency of the benchmark used for the government bond markets. We found that for the Emerging Market Bonds an equally weighted index for the country weights is probably the more suited because guarantees maximum diversification of country risk but for the Eurozone government bond market we found a GDP weighted index is better because the most important matter is to avoid a higher weight for highly indebted countries. In chapter 3 we analyzed the efficiency of a Derivatives Index to invest in the European corporate bond market instead of a Cash Index. We can state that the two indexes are similar in terms of returns, but that the Derivatives Index is less risky because it has a lower volatility, has values of skewness and kurtosis closer to those of a normal distribution and is a more liquid instrument, as the autocorrelation is not significant. In chapter 4 it is analyzed the impact of fallen angels on the corporate bond portfolios. Our analysis investigated the impact of the month-end rebalancing of the ML Emu Non Financial Corporate Index for the exit of downgraded bond (the event). We can conclude a flexible approach to the month-end rebalancing is better in order to avoid a loss of valued due to the benchmark construction rules. In chapter 5 we did a comparison between the equally weighted and capitalization weighted method for the European equity market. The benefit which results from reweighting the portfolio into equal weights can be attributed to the fact that EW portfolios implicitly follow a contrarian investment strategy, because they mechanically rebalance away from stocks that increase in price.

Econometrics of default risk

This thesis is the result of a project aimed at the study of a crucial topic in finance: default risk, whose measurement and modelling have achieved increasing relevance in recent years. We investigate the main issues related to the default phenomenon, under both a methodological and empirical perspective. The topics of default predictability and correlation are treated with a constant attention to the modelling solutions and reviewing critically the literature. From the methodological point of view, our analysis results in the proposal of a new class of models, called Poisson Autoregression with Exogenous Covariates (PARX). The PARX models, including both autoregressive end exogenous components, are able to capture the dynamics of default count time series, characterized by persistence of shocks and slowly decaying autocorrelation. Application of different PARX models to the monthly default counts of US industrial firms in the period 1982-2011 allows an empirical insight of the defaults dynamics and supports the identification of the main default predictors at an aggregate level.

Variability of lung function predicts loss of asthma control following withdrawal of inhaled corticosteroid treatment

BACKGROUND One aspect of a multidimensional approach to understanding asthma as a complex dynamic disease is to study how lung function varies with time. Variability measures of lung function have been shown to predict response to beta(2)-agonist treatment. An investigation was conducted to determine whether mean, coefficient of variation (CV) or autocorrelation, a measure of short-term memory, of peak expiratory flow (PEF) could predict loss of asthma control following withdrawal of regular inhaled corticosteroid (ICS) treatment, using data from a previous study. METHODS 87 adult patients with mild to moderate asthma who had been taking ICS at a constant dose for at least 6 months were monitored for 2-4 weeks. ICS was then withdrawn and monitoring continued until loss of control occurred as per predefined criteria. Twice-daily PEF was recorded during monitoring. Associations between loss of control and mean, CV and autocorrelation of morning PEF within 2 weeks pre- and post-ICS withdrawal were assessed using Cox regression analysis. Predictive utility was assessed using receiver operator characteristics. RESULTS 53 out of 87 patients had sufficient PEF data over the required analysis period. The mean (389 vs 370 l/min, p<0.0001) and CV (4.5% vs 5.6%, p=0.007) but not autocorrelation of PEF changed significantly from prewithdrawal to postwithdrawal in subjects who subsequently lost control, and were unaltered in those who did not. These changes were related to time to loss of control. CV was the most consistent predictor, with similar sensitivity and sensitivity to exhaled nitric oxide. CONCLUSION A simple, easy to obtain variability measure of daily lung function such as the CV may predict loss of asthma control within the first 2 weeks of ICS withdrawal.

A Method for Detecting Population Genetic Structure in Diverse, High Gene-Flow Species

Detecting small amounts of genetic subdivision across geographic space remains a persistent challenge. Often a failure to detect genetic structure is mistaken for evidence of panmixia, when more powerful statistical tests may uncover evidence for subtle geographic differentiation. Such slight subdivision can be demographically and evolutionarily important as well as being critical for management decisions. We introduce here a method, called spatial analysis of shared alleles (SAShA), that detects geographically restricted alleles by comparing the spatial arrangement of allelic co-occurrences with the expectation under panmixia. The approach is allele-based and spatially explicit, eliminating the loss of statistical power that can occur with user-defined populations and statistical averaging within populations. Using simulated data sets generated under a stepping-stone model of gene flow, we show that this method outperforms spatial autocorrelation (SA) and UST under common real-world conditions: at relatively high migration rates when diversity is moderate or high, especially when sampling is poor. We then use this method to show clear differences in the genetic patterns of 2 nearshore Pacific mollusks, Tegula funebralis (5 Chlorostoma funebralis) and Katharina tunicata, whose overall patterns of within-species differentiation are similar according to traditional population genetics analyses. SAShA meaningfully complements UST/FST, SA, and other existing geographic genetic analyses and is especially appropriate for evaluating species with high gene flow and subtle genetic differentiation.

A Novel Method for the Homogenization of Daily Temperature Series and Its Relevance for Climate Change Analysis

Instrumental daily series of temperature are often affected by inhomogeneities. Several methods are available for their correction at monthly and annual scales, whereas few exist for daily data. Here, an improved version of the higher-order moments (HOM) method, the higher-order moments for autocorrelated data (HOMAD), is proposed. HOMAD addresses the main weaknesses of HOM, namely, data autocorrelation and the subjective choice of regression parameters. Simulated series are used for the comparison of both methodologies. The results highlight and reveal that HOMAD outperforms HOM for small samples. Additionally, three daily temperature time series from stations in the eastern Mediterranean are used to show the impact of homogenization procedures on trend estimation and the assessment of extremes. HOMAD provides an improved correction of daily temperature time series and further supports the use of corrected daily temperature time series prior to climate change assessment.

A Nonstationary Negative Binomial Time Series with Time-Dependent Covariates: Enterococcus Counts in Boston Harbor

Boston Harbor has had a history of poor water quality, including contamination by enteric pathogens. We conduct a statistical analysis of data collected by the Massachusetts Water Resources Authority (MWRA) between 1996 and 2002 to evaluate the effects of court-mandated improvements in sewage treatment. Motivated by the ineffectiveness of standard Poisson mixture models and their zero-inflated counterparts, we propose a new negative binomial model for time series of Enterococcus counts in Boston Harbor, where nonstationarity and autocorrelation are modeled using a nonparametric smooth function of time in the predictor. Without further restrictions, this function is not identifiable in the presence of time-dependent covariates; consequently we use a basis orthogonal to the space spanned by the covariates and use penalized quasi-likelihood (PQL) for estimation. We conclude that Enterococcus counts were greatly reduced near the Nut Island Treatment Plant (NITP) outfalls following the transfer of wastewaters from NITP to the Deer Island Treatment Plant (DITP) and that the transfer of wastewaters from Boston Harbor to the offshore diffusers in Massachusetts Bay reduced the Enterococcus counts near the DITP outfalls.

On Time Series Analysis of Public Health and Biomedical Data

A time series is a sequence of observations made over time. Examples in public health include daily ozone concentrations, weekly admissions to an emergency department or annual expenditures on health care in the United States. Time series models are used to describe the dependence of the response at each time on predictor variables including covariates and possibly previous values in the series. Time series methods are necessary to account for the correlation among repeated responses over time. This paper gives an overview of time series ideas and methods used in public health research.

Direct MR arthrography at 1.5 and 3.0 T: signal dependence on gadolinium and iodine concentrations--phantom study

PURPOSE: To prospectively quantify in vitro the influence of gadopentetate dimeglumine and ioversol on the magnetic resonance (MR) imaging signal observed with a variety of musculoskeletal pulse sequences to predict optimum gadolinium concentrations for direct MR arthrography at 1.5 and 3.0 T. MATERIALS AND METHODS: In an in vitro study, T1 and T2 relaxation times of three dilution series of gadopentetate dimeglumine (concentration, 0-20.0 mmol gadolinium per liter) at ioversol concentrations with iodine concentration of 0, 236.4, and 1182 mmol iodine per liter (corresponding to 0, 30, and 150 mg of iodine per milliliter) were measured at 1.5 and 3.0 T. The relaxation rate dependence on concentrations of gadolinium and iodine was analytically modeled, and continuous profiles of signal versus gadolinium concentration were calculated for 10 pulse sequences used in current musculoskeletal imaging. After fitting to experimental discrete profiles, maximum signal-to-noise ratio (SNR), gadolinium concentration with maximum SNR, and range of gadolinium concentration with 90% of maximum SNR were derived. The overall influence of field strength and iodine concentration on these parameters was assessed by using t tests. The deviation of simulated from experimental signal-response profiles was assessed with the autocorrelation of the residuals. RESULTS: The model reproduced relaxation rates of 0.37-38.24 sec(-1), with a mean error of 4.5%. Calculated SNR profiles matched the discrete experimental profiles, with autocorrelation of the residuals divided by the mean of less than 5.0. Admixture of ioversol consistently reduced T1 and T2, narrowed optimum gadolinium concentration ranges (P = .004-.006), and reduced maximum SNR (P < .001 to not significant). Optimum gadolinium concentration was 0.7-3.4 mmol/L at both field strengths. At 3.0 T, maximum SNR was up to 75% higher than at 1.5 T. CONCLUSION: Admixture of ioversol to gadopentetate dimeglumine solutions results in a consistent additional relaxation enhancement, which can be analytically modeled to allow a near-quantitative a priori optimized match of contrast media concentrations and imaging protocol for a broad variety of pulse sequences.