RESUMEN
We investigated the spectrum of density fluctuations of a liquid crystal, CB7CB, in two different orientations by using high-resolution inelastic x-ray scattering. Our analysis, based on Bayesian principles, revealed that high-frequency collective excitations propagate through this mesoscale-ordered sample in a peculiar manner that lies somewhere between those observed in liquids and crystalline systems. Interestingly, when we probed longer length scales, a more pronounced solid-like response emerged. This was mainly characterized by anomalously sharp inelastic excitations and the onset of shear mode propagation. Comparison with previous x-ray diffraction results suggests a correlation between the observed behavior and the mesogen arrangement.
RESUMEN
Understanding how molecules engage in collective motions in a liquid where a network of bonds exists has both fundamental and applied relevance. On the one hand, it can elucidate the "ordering" role of long-range correlations and inspire new avenues to control such order to implement sound manipulation. Water represents an ideal investigation case to unfold these general aspects, and, across the decades, it has been the focus of thorough scrutiny. Despite this investigative effort, the spectrum of terahertz density fluctuations of water largely remains a puzzle for condensed matter physicists. To unravel it, we compare previous scattering measurements of water spectra with new ones on ice. Owing to the unique asset of Bayesian inference, we draw a more detailed portrayal of the phonon response of ice. The comparison with the one of liquid water challenges the current understanding of density fluctuations in water, or more in general, of any networked liquid.
RESUMEN
We used inelastic x-ray scattering methods to measure the terahertz spectrum of density fluctuations of ethanol in both liquid and solid phases. The results of a Bayesian inference-based lineshape analysis with a multiple excitation model and the comparison with a previous similar analysis on water indicate that the different structures induced by hydrogen bonds in ethanol and water have a profound influence on the respective dynamic responses, the latter being characterized by longer living and better resolved high-frequency acoustic excitations. In addition, we compare these findings with those obtained with an alternative approach based on the exponential expansion theory and ensuring sum rules fulfillment, demonstrating that the model's choice directly impacts the number of spectral modes detected.
RESUMEN
When the dynamics of liquids and disordered systems at mesoscopic level is investigated by means of inelastic scattering (e.g., neutron or x ray), spectra are often characterized by a poor definition of the excitation lines and spectroscopic features in general and one important issue is to establish how many of these lines need to be included in the modeling function and to estimate their parameters. Furthermore, when strongly damped excitations are present, commonly used and widespread fitting algorithms are particularly affected by the choice of initial values of the parameters. An inadequate choice may lead to an inefficient exploration of the parameter space, resulting in the algorithm getting stuck in a local minimum. In this paper, we present a Bayesian approach to the analysis of neutron Brillouin scattering data in which the number of excitation lines is treated as unknown and estimated along with the other model parameters. We propose a joint estimation procedure based on a reversible-jump Markov chain Monte Carlo algorithm, which efficiently explores the parameter space, producing a probabilistic measure to quantify the uncertainty on the number of excitation lines as well as reliable parameter estimates. The method proposed could turn out of great importance in extracting physical information from experimental data, especially when the detection of spectral features is complicated not only because of the properties of the sample, but also because of the limited instrumental resolution and count statistics. The approach is tested on generated data set and then applied to real experimental spectra of neutron Brillouin scattering from a liquid metal, previously analyzed in a more traditional way.
RESUMEN
Human 3beta-hydroxysteroid dehydrogenase/isomerase (3beta-HSD) is a key steroidogenic enzyme that catalyzes the first step in the conversion of circulating dehydroepiandrosterone (DHEA), pregnenolone or 17alpha-hydroxypregenolone to produce the appropriate, active steroid hormone(s): estradiol, testosterone, progesterone, aldosterone or cortisol respectively. Our mutagenesis studies have identified Tyr154 and Lys158 as catalytic residues for the 3beta-HSD reaction. Our three-dimensional homology model of 3beta-HSD shows that Tyr154 and Lys158 are oriented near the 3beta-hydroxyl group of the bound substrate steroid, and predicts that Ser123 or Ser124 completes a Tyr-Lys-Ser catalytic triad that operates in many other dehydrogenases. The S123A and S124A mutants of human type 1 3beta-hydroxysteroid dehydrogenase/isomerase (3beta-HSD1) were created by PCR-based mutagenesis, expressed in insect cells using baculovirus and purified to homogeneity. The S124A mutant exhibits no 3beta-HSD activity and has a K(m) value (83.6 microM) for the isomerase substrate that is threefold greater than that of wild-type 1 isomerase. In contrast, S123A has substantial 3beta-HSD activity (DHEA K(m)=11.2 microM; k(cat)=0.8 min(-1)) and utilizes isomerase substrate, 5-androstene-3,17-dione, with a K(m) value (27.6 microM) that is almost identical to wild-type. The K(m) value (4.3 microM) of S124A for NADH as an allosteric activator of isomerase is similar to that of the wild-type 1 enzyme, indicating that Ser124 is not involved in cofactor binding. S123A utilizes NAD as a cofactor for 3beta-HSD and NADH as the activator for isomerase with K(m) values that are similar to wild-type. The 3beta-HSD activities of S123A and wild-type 3beta-HSD increase by 2.7-fold when the pH is raised from 7.4 to the optimal pH 9.7, but S124A exhibits very low residual 3beta-HSD activity that is pH-independent. These kinetic analyses strongly suggest that the Ser124 residue completes the catalytic triad for the 3beta-HSD activity. Since there are 29 Ser residues in the primary structure of human 3beta-HSD1, our homology model of the catalytic domain has been validated by this accurate prediction. A role for Ser124 in the binding of the isomerase substrate, which is the 3beta-HSD product-steroid of the bifunctional enzyme protein, is also suggested. These observations further characterize the structure/function relationships of human 3beta-HSD and bring us closer to the goal of selectively inhibiting the type 1 enzyme in placenta to control the timing of labor or in hormone-sensitive breast tumors to slow their growth.