A Pragmatic Smoothing Method for Improving the Quality of the Results in Atomic Spectroscopy.

A new smoothing method for improvement on the quantification of spectral signals, which requires the previous knowledge of the functions that should be quantified, is presented. These functions are used as weighted coefficients in the proposed smoothing algorithm. This method is extremely effective in reducing the scatter of signals obtained by the multichannel analyzer and it could be applied in atomic and nuclear spectroscopies, preferably to these techniques where net counts are a linear function of the acquisition time, like total reflection X-ray fluorescence, micro X-ray fluorescence, etc. If this algorithm is properly applied, it does not distort the form or the intensity of the signal, so it is well suited for use in all kinds of spectroscopic techniques. However, it should not be applied to data obtained from systems depending on time, e.g., control sciences, time series, sound analysis, etc. We applied this method over simulated data and real experimental measurements. As with all smoothing techniques, the proposed method improves the precision of the results, but when it was applied to computer-simulated spectra, we found a systematic enhancement on the accuracy of the results. We still do not have an answer for this apparent paradox. We also have to evaluate, in spectral analysis, the improvement produced by this smoothing procedure over detection and quantification limits. When this algorithm is applied over experimental results, it is mandatory that the sought characteristic functions, required for this weighted smoothing method, should be obtained from a system with strong stability. If the sought signals are not perfectly clean, this method should be applied with care.

Mammalian agmatinases constitute unusual members in the family of Mn2+-dependent ureahydrolases.

Agmatine (1-amino-4-guanidinobutane) plays an important role in a range of metabolic functions, in particular in the brain. Agmatinases (AGMs) are enzymes capable of converting agmatine to the polyamine putrescine and urea. AGMs belong to the family of Mn2+-dependent ureahydrolases. However, no AGM from a mammalian source has yet been extracted in catalytically active form. While in human AGM the six amino acid ligands that coordinate the two Mn2+ ions in the active site are conserved, four mutations are observed in the murine enzyme. Here, we demonstrate that similar to its human counterpart murine AGM does not appear to have in vitro catalytic activity, independent of the presence of Mn2+. However, in presence of agmatine both enzymes are very efficient in promoting cell growth of a yeast strain that is deficient in polyamine biosynthesis (Saccharomyces cerevisiae strain TRY104Δspe1). Furthermore, mutations among the putative Mn2+ binding residues had no effect on the ability of murine AGM to promote growth of the yeast culture. It thus appears that mammalian AGMs form a distinct group within the family of ureahydrolases that (i) either fold in a manner distinct from other members in this family, or (ii) require accessory proteins to bind Mn2+ in a mechanism related to that observed for the Ni2+-dependent urease.

A procedure for the improvement in the determination of a TXRF spectrometer sensitivity curve.

A simple procedure is proposed to determine the total reflection X-ray fluorescence (TXRF) spectrometer sensitivity curve; this procedure provides better accuracy and exactitude than the standard established method. It uses individual pure substances instead of the use of vendor-certified values of reference calibration standards, which are expensive and lack any method to check their quality. This method avoids problems like uncertainties in the determination of the sensitivity curve according to different standards. It also avoids the need for validation studies between different techniques, in order to assure the quality of their TXRF results.