Statistical methodology for the detection of small changes in distances by EXAFS: application to the antimalarial ruthenoquine.

Antimalarial compounds ruthenoquine and methylruthenoquine were studied by X-ray absorption spectroscopy both in solid state and in solution, in normal (aqueous or CH(2)Cl(2) solutions) and oxidative (aqueous solution with H(2)O(2), either equimolar or in large excess) conditions, to detect small changes in the coordination sphere of the ruthenium atom. Since changes in the EXAFS spectra of these compounds are quite subtle, a complete procedure was developed to assess the different sources of uncertainties in fitted structural parameters, including the use of multivariate statistic methods for simultaneous comparison of edge energy correction ΔE(0) and distances, which can take into account the very strong correlation between these two parameters. Factors limiting the precision of distance determination depend on the recording mode. In transmission mode, the main source of uncertainty is the data reduction process, whereas in fluorescence mode, experimental noise is the main source of variability in the fitted parameters. However, it was shown that the effects of data reduction are systematic and almost identical for all compounds; hence, they can be ignored when comparing distances. Consequently, for both fluorescence and transmission recorded spectra, experimental noise is the limiting factor for distance comparisons, which leads to the use of statistical methods for comparing distances. Univariate methods, focusing on the distance only, are shown to be less powerful in detecting changes in distances than bivariate methods making a simultaneous comparison of ΔE(0) and distances. This bivariate comparison can be done either by using the Hotelling's T(2) test or by using a graphical comparison of Monte Carlo simulation results. We have shown that using these methods allows for the detection of very subtle changes in distances. When applied to ruthenoquine compounds, it suggests that the implication of the nonbinding doublet of the aminoquine nitrogen in either protonation or methylation enhances the tilt of the two cyclopentadienyls. It also suggests that ruthenoquine and methylruthenoquine are, at least partially, oxidized in the presence of H(2)O(2), with a small decrease in the Ru-C bond length and increase in the edge energy.

Geriatric Nutritional Risk Index: a new index for evaluating at-risk elderly medical patients.

BACKGROUND: Patients at risk of malnutrition and related morbidity and mortality can be identified with the Nutritional Risk Index (NRI). However, this index remains limited for elderly patients because of difficulties in establishing their normal weight. OBJECTIVE: Therefore, we replaced the usual weight in this formula by ideal weight according to the Lorentz formula (WLo), creating a new index called the Geriatric Nutritional Risk Index (GNRI). DESIGN: First, a prospective study enrolled 181 hospitalized elderly patients. Nutritional status [albumin, prealbumin, and body mass index (BMI)] and GNRI were assessed. GNRI correlated with a severity score taking into account complications (bedsores or infections) and 6-mo mortality. Second, the GNRI was measured prospectively in 2474 patients admitted to a geriatric rehabilitation care unit over a 3-y period. RESULTS: The severity score correlated with albumin and GNRI but not with BMI or weight:WLo. Risk of mortality (odds ratio) and risk of complications were, respectively, 29 (95% CI: 5.2, 161.4) and 4.4 (95% CI: 1.3, 14.9) for major nutrition-related risk (GNRI: <82), 6.6 (95% CI: 1.3, 33.0), 4.9 (95% CI: 1.9, 12.5) for moderate nutrition-related risk (GNRI: 82 to <92), and 5.6 (95% CI: 1.2, 26.6) and 3.3 (95% CI: 1.4, 8.0) for a low nutrition-related risk (GNRI: 92 to < or =98). Accordingly, 12.2%, 31.4%, 29.4%, and 27.0% of the 2474 patients had major, moderate, low, and no nutrition-related risk, respectively. CONCLUSION: GNRI is a simple and accurate tool for predicting the risk of morbidity and mortality in hospitalized elderly patients and should be recorded systematically on admission.

Temperature and pH Dependence XAFS Study of Gd(DOTA)(-) and Gd(DTPA)(2)(-) Complexes: Solid State and Solution Structures.

We present an X-ray absorption spectroscopy study of the local structures of Gd(DTPA)(2)(-) and Gd(DOTA)(-) complexes in the crystalline state (at room and low temperatures) and in aqueous solutions exhibiting various pH values (0.15-7) at different temperatures (25-90 degrees C). Using X-ray absorption fine structure (XAFS) analysis procedures and ab initio multiple scattering calculations of XAFS spectra at the Gd L(3) edge, we reconstructed the Gd(3+) local environment, and compared it with existing structural models. From neutral pH to a value of 1.5, we found that the local environment and complex dynamics around the gadolinium ions were conserved up to 4.5 Å, and the structure agreed well with the known crystallographic data. In these solutions, the gadolinium ions in the complex Gd(DOTA)(-) are bonded to the four carboxylate oxygen atoms [R(Gd-O(av)) 2.38 Å, Debye-Waller (DW) factor 0.006 Å(2)], to the four nitrogen atoms [R(Gd-N(av)) 2.65 Å, DW factor 0.006 Å(2)] and to one water molecule [R(Gd-O(w)) 2.46 Å, DW factor 0.012 Å(2)]. Concerning the complex Gd(DTPA)(2)(-), the gadolinium ions are bonded to the five carbonyl oxygen atoms [R(Gd-O(av)) 2.39 Å, DW factor 0.007 Å(2)], to the three nitrogen atoms [R(Gd-N(av)) 2.64 Å, DW factor 0.006 Å(2)], and to one water molecule [R(Gd-O(w)) 2.47 Å, DW factor 0.018 Å(2)]. In the range of pH (0.15-1.5) for the Gd(DTPA)(2)(-) complexes, thanks to the pH strong dependence of the XAFS signals, we observed a progressive complex dissociation. On the other hand, the XAFS signals of Gd(DOTA)(-) complexes exhibited only a slight pH (1-1.5) dependence. Concerning both complexes, we noted just a slight temperature dependence.

Mathematical modeling in metal metabolism: overview and perspectives.

A review of mathematical modeling in metal metabolism is presented. Both endogenous and exogenous metals are considered. Four classes of methods are considered: Petri nets, multi-agent systems, determinist models based on differential equations and stochastic models. For each, a basic theoretical background is given, then examples of applications are given, detailed and commented. Advantages and disadvantages of each class of model are presented. A special attention is given to determinist differential equation models, since almost all models belong to this class.

Characterization of stabilized/solidified refinery oily sludge and incinerated refinery sludge with cement using XRD, SEM and EXAFS.

Solidification/stabilization (S/S) of refinery oily sludge and incinerated oily sludge (ash) with cement type I42.5 and II42.5 was investigated using, X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM) combined with Energy Dispersive Spectroscopy (EDS) and Extended X-ray Absorption Fine Structure (EXAFS). The results showed that delayed ettringite formation (DEF) and major cement hydration reactions occurred. XRD analysis of S/S oily sludge samples revealed cement-bearing solid phases, such as portlandite, calcite, C(3)S, C(2)S and C(4)AF. SEM analysis, confirmed ettringite at solidified oily sludge samples. Solidified ash samples contained ettringite substituted by chromates. However, solid phases found in solidified ash samples with I42.5 cement showed minor variation in type and structure compared to those observed in solidified ash samples with II42.5 cement. Fe K edge EXAFS analysis revealed the presence of iron oxides in both S/S wastes. The comparison between spectra of the S/S resulting materials and the ones of their original components, showed that the first sphere Fe-O distances were longer than in the pure iron oxide thereby providing evidence that the resulting materials were not simple mixtures, but products of a reaction that modified the local environment of iron.

About estimation of fitted parameters' statistical uncertainties in EXAFS. Critical approach on usual and Monte Carlo methods.

An important step in X-ray absorption spectroscopy (XAS) analysis is the fitting of a model to the experimental spectra, with a view to obtaining structural parameters. It is important to estimate the errors on these parameters, and three methods are used for this purpose. This article presents the conditions for applying these methods. It is shown that the usual equation Sigma = 2H(-1) is not applicable for fitting in R space or on filtered XAS data; a formula is established to treat these cases, and the equivalence between the usual formula and the brute-force method is evidenced. Lastly, the problem of the nonlinearity of the XAS models and a comparison with Monte Carlo methods are addressed.

X-ray absorption spectroscopy of low-molar-mass metallic complexes in pharmacy.

X-ray absorption spectroscopy provides valuable information on metallic speciation and so has a wide range of applications in bioinorganic systems. In this paper, low-molar-mass metallic complexes as used in pharmaceutical science are focused on. The results of structural studies on metal-based drugs applied as disease treatments, nutritional supplements or tools for diagnostic methods are presented. Then metal speciation (spatial and chemical distribution) in biological samples through micro-XANES imaging experiments are dealt with. Problems arising from the analysis of noisy data collected from these diluted samples are discussed.

A different approach to analyzing age-related HbA1c values in non-diabetic subjects.

Using appropriate statistical tests and taking into account the analytical performance of hemoglobin A1c (HbA1c) measurements, is it useful to establish HbA1c age-related values in non-diabetic subjects? Non-diabetic subjects (n=135, 72 women and 63 men) from the neuromuscular department of the Pitié-Salpétrière Hospital (Paris) were involved in our study. Subjects were divided into two groups related to age: 51 patients under 50 years old and 84 subjects aged 50 years or more. Fasting plasma glucose and HbA1c measurements were respectively performed by enzymatic assay using the hexokinase method and high-performance liquid chromatography based on the ion exchange methodology with high precision. We first checked the normality of HbA1c distribution using the Kolmogorov-Smirnov test. Then we compared mean HbA1c in the two age subgroups using the Student's t test. Mean HbA1c was significantly (p<0.0001) higher in the subgroup aged 50 years or more (mean HbA1c=5.2%) than in younger subjects (mean HbA1c=5.0%). Then plots were drawn to check the relationship between HbA1c and age. Under the hypothesis of linearity, determination coefficients (R2) were calculated. However, considering their low values, this hypothesis must be rejected and other factors than age must be retained to explain HbA1c variability.