A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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Molecular weight distribution of interacting proteins calculated by multiple regression analysis from sedimentation equilibrium data: An interpretation of α s1-κ-casein interaction

Multiple regression analysis in four series with exponentially spaced molecular weight scales shifted by a factor of 2 1 4 between series was applied to sedimentation equilibrium data for determination of the molecular weight distribution of synthesized model systems consisting of up to three components which represented heterogeneous associating systems. Negative weight fractions of the components which were frequently encountered during multiple regression analysis were forced to zero by successively eliminating from the regression matrix the corresponding molecular weights in order of the magnitude of negative t values. The simplex optimization technique in conjunction with a prohibit-trespassing routine was used to maximize F values obtained from multiple regression analysis in search of the best fit values of component molecular weights. The quantitative information relating molecular weights and relative concentrations obtained by simplex optimization supplemented the regression matrix for calculation of the molecular weight distribution to improve the resolution of the molecular weight distribution patterns. This multiple regression method when carried out in conjunction with the simplex optimization provided a better fit to the data than the linear programming method of Scholte. When applied to mixtures of three standard proteins, the simplex optimization routine yielded values of molecular weights and relative concentrations of the component proteins which were in good agreement with the known values of the original mixtures. The molecular weight distribution calculated from sedimentation equilibrium data of α s1-κ-casein mixtures using a uv scanner indicated that κ-casein readily dissociated to an oligomer, probably up to trimer, and interacted with the monomer or dimer of α s1-casein forming a complex of approximately 400,000 molecular weight. This dissociation of κ-casein was promoted in the presence of ovalbumin, a nonmilk protein. © 1979.link_to_subscribed_fulltex

Rapid method for the determination of moisture content in biodiesel using FTIR spectroscopy

A new, rapid, and direct method was developed for the determination of moisture content in biodiesel produced from various types of oils using Fourier transform infrared (FTIR) spectroscopy with an attenuated total reflectance (ATR) element. Samples of biodiesels used in this study were produced using sludge palm oil (SPO). The calibration set was prepared by spiking double-distilled water into dried biodiesel samples in ratios (w/w) between 0 and 10% moisture. Absorbance values from the wavelength regions 3,700–3,075 and 1,700–1,500 cm-1, and the partial least square (PLS) regression method were used to derive a FTIR spectroscopic calibration model for moisture content in biodiesel samples. The coefficient of determinations (R2) for the models was computed by comparing the results obtained from FTIR spectroscopy against the values of the moisture concentrations (%) determined using the American Oil Chemists’ Society (AOCS) oven method Ca 2d-25. Same comparison was done using International Union of Pure and Applied Chemistry (IUPAC) distillation method 2.602. R2 was 0.9793 and 0.9700 using AOCS and IUPAC methods, respectively. The standard error (SE) of calibration was 1.84. The calibration model was cross validated within the same set of samples, and the standard deviation (SD) of the difference for repeatability (SDDr) and accuracy (SDDa) of the FTIR method was determined. With its speed and ease of data manipulation, FTIR spectroscopy is a useful alternative method to other methods for rapid and routine determination of moisture content in biodiesel for quality control