Fourier Self-Deconvolution Analysis of β-Sheet Contents in the Amide I Region of Hemoglobin Aqueous Solutions under Exposure to 900 MHz Microwaves and Bioprotective Effectiveness of Sugar and Salt Solutions

Spectroscopic Fourier self-deconvolution analysis was used to investigate β-sheet features in the secondary structure of hemoglobin under mobile phone microwaves at 900 MHz. To this end, four samples of hemoglobin in bidistilled water, sucrose, trehalose, and sodium chloride aqueous solutions were exposed for up to 4 hr to 900 MHz microwaves at an average H-field intensity of 42 mA/m. Quantitative spectral analyses highlighted significant increases in β-sheet contents in the Amide I region of hemoglobin samples in bidistilled water solution, but no appreciable change was observed in hemoglobin samples in sucrose, trehalose, and sodium chloride solutions. These results led us to conclude that mobile phone microwaves can denaturate hemoglobin in bidistilled water solution whereas sucrose, trehalose, and sodium chloride solutions produce a protective effect against microwaves, preserving the protein from unfolding.     

Astrophysical Black Holes as Natural Laboratories for Fundamental Physics and Strong-Field Gravity

Astrophysical tests of general relativity belong to two categories: 1) “internal”, i.e. consistency tests within the theory (for example, tests that astrophysical black holes are indeed described by the Kerr solution and its perturbations), or 2) “external”, i.e. tests of the many proposed extensions of the theory. I review some ways in which astrophysical black holes can be used as natural laboratories for both “internal” and “external” tests of general relativity. The examples provided here (ringdown tests of the black hole “no-hair” theorem, bosonic superradiant instabilities in rotating black holes and gravitational-wave tests of massive scalar-tensor theories) are shamelessly biased towards recent research by myself and my collaborators. Hopefully this colloquial introduction aimed mainly at astrophysicists will convince skeptics (if there are any) that space-based detectors will be crucial to study fundamental physics through gravitational-wave observations.     

The Beneficial Role of Random Strategies in Social and Financial Systems

In this paper we focus on the beneficial role of random strategies in social sciences by means of simple mathematical and computational models. We briefly review recent results obtained by two of us in previous contributions for the case of the Peter principle and the efficiency of a Parliament. Then, we develop a new application of random strategies to the case of financial trading and discuss in detail our findings about forecasts of markets dynamics.     

Global sensitivity measures from given data

Simulation models support managers in the solution of complex problems. International agencies recommend uncertainty and global sensitivity methods as best practice in the audit, validation and application of scientific codes. However, numerical complexity, especially in the presence of a high number of factors, induces analysts to employ less informative but numerically cheaper methods. This work introduces a design for estimating global sensitivity indices from given data (including simulation input–output data), at the minimum computational cost. We address the problem starting with a statistic based on the L¹-norm. A formal definition of the estimators is provided and corresponding consistency theorems are proved. The determination of confidence intervals through a bias-reducing bootstrap estimator is investigated. The strategy is applied in the identification of the key drivers of uncertainty for the complex computer code developed at the National Aeronautics and Space Administration (NASA) assessing the risk of lunar space missions. We also introduce a symmetry result that enables the estimation of global sensitivity measures to datasets produced outside a conventional input–output functional framework.     

Re-weighted random series path integral simulations of molecular clusters: Applications to lithium solvated by a mixed Stockmayer cluster

Nuclear quantum effects in finite temperature simulations of molecular clusters are determined by taking advantage of a recently developed method based on the Feynman Path Integral. The structural and thermodynamic properties, including the nuclear quantum effects are determined for three Stockmayer clusters. The ionic system contain a lithium ion solvated by six strong dipoles and 12 weaker ones. The presence of the ion in the mixed Stockmayer cluster drastically enhances the fluxional nature of the less polar components which occupy the second solvation layer, whereas the neutral counterpart has the effect of reducing it. The nuclear quantum effects are significant at room temperature and above for the solvated ionic system. These are attributable to two factors: (a) the lightness of the lithium ion and (b) the stiffness of the ion-dipole interactions. At 300 K, the difference between the fully converged quantum and the classical heat capacities is about 1.3 K_B for the ionic cluster. This difference is about 10 SDs obtained from 95% confidence estimates of the statistical fluctuations. Cubic convergence is confirmed for temperatures as low as 50 K by regression analysis. The nuclear quantum effects do not change the peak melting temperature of the cluster.     

Individual‐Molecule Perspective Analysis of Chemical Reaction Networks: The Case of a Light‐Driven Supramolecular Pump

The first study in which stochastic simulations of a two‐component molecular machine are performed in the mass‐action regime is presented. This system is an autonomous molecular pump consisting of a photoactive axle that creates a directed flow of rings through it by exploiting light energy away from equilibrium. The investigation demonstrates that the pump can operate in two regimes, both experimentally accessible, in which light‐driven steps can be rate‐determining or not. The number of photons exploited by an individual molecular pump, as well as the precision of cycling and the overall efficiency, critically rely on the operating regime of the machine. This approach provides useful information not only to guide the chemical design of a self‐assembling molecular device with desired features, but also to elucidate the effect of the environment on its performance, thus facilitating its experimental investigation.     

The experimental design approach to the optimization of a simple quick easy cheap effective rugged and safe method for the analysis of phytoestrogens in complex soy‐based food

The present paper deals with the multivariate optimization of an extraction‐purification strategy for the determination of phytoestrogens (daidzein, genistein, coumestrol, formononetin, and biochanin A) in soy‐based meat substitutes by high performance liquid chromatography with tandem mass spectrometry. For a reliable quantitation of these new concerning compounds in such a complex matrix, recovery and matrix effect must be carefully evaluated. Therefore, two sequential experimental designs were used to optimize the sample‐pretreatment of soy‐based burgers: the chosen technique was the quick, easy, cheap, effective, rugged and safe methodology, which does not require any particular facility or instrumentation. Thanks to the first screening design (Plackett‐Burman), the significant factors influencing the studied responses were identified and further investigated through a response surface design (Box‐Behnken). The optimal values of the variables (volume of extraction solvent mix/sample mass ratio and two clean‐up sorbents) led to quantitative recoveries (97–104%) and low ion suppression (matrix effect 60–93%) for all analytes. This optimized method was characterized by low detection limits (0.2–1.5 ng/g) and excellent intraday precision (RSD 2–4%). It was applied to the determination of the considered compounds in several soy‐burgers from the Italian market, detecting low ng/g levels (up to 40 ng/g) of coumestrol, formononetin, and biochanin A, and high concentrations (7.9–78 µg/g) of genistein and daidzein.     

Parton distributions and new physics searches: the Drell–Yan forward–backward asymmetry as a case study

We present the first unquenched lattice-QCD calculation of the form factors for the decay \(B\rightarrow D^*\ell \nu \) at nonzero recoil. Our analysis includes 15 MILC ensembles with \(N_f=2+1\) flavors of asqtad sea quarks, with a strange quark mass close to its physical mass. The lattice spacings range from \(a\approx 0.15\) fm down to 0.045 fm, while the ratio between the light- and the strange-quark masses ranges from 0.05 to 0.4. The valence b and c quarks are treated using the Wilson-clover action with the Fermilab interpretation, whereas the light sector employs asqtad staggered fermions. We extrapolate our results to the physical point in the continuum limit using rooted staggered heavy-light meson chiral perturbation theory. Then we apply a model-independent parametrization to extend the form factors to the full kinematic range. With this parametrization we perform a joint lattice-QCD/experiment fit using several experimental datasets to determine the CKM matrix element \(|V_{cb}|\). We obtain \(\left| V_{cb}\right| = (38.40 \pm 0.68_{\text {th}} \pm 0.34_{\text {exp}} \pm 0.18_{\text {EM}})\times 10^{-3}\). The first error is theoretical, the second comes from experiment and the last one includes electromagnetic and electroweak uncertainties, with an overall \(\chi ^2\text {/dof} = 126/84\), which illustrates the tensions between the experimental data sets, and between theory and experiment. This result is in agreement with previous exclusive determinations, but the tension with the inclusive determination remains. Finally, we integrate the differential decay rate obtained solely from lattice data to predict \(R(D^*) = 0.265 \pm 0.013\), which confirms the current tension between theory and experiment.

     

Direct flow injection profiling of acyl glycerols from food products using isopropanol as solvent

This work proposes a novel method for the direct flow injection profiling of acylglycerols in edible oils and fats without preliminary extraction and consequent reconstitution in the injection solvent. The work exploits the outstanding performance of high‐resolution mass spectrometry to target unique elemental compositions even in the most complex matrices. The performance of isopropanol as the unique solvent for both the solubilization and analysis of acylglycerols was investigated in comparison with other classical methods involving preliminary extractions, sample recovery, and analysis. The calibrations of two triglyceride standards (triolein and trilinolenin) were successfully performed in presence and absence of oil matrix. As final application, the effects on the acylglycerol fraction of a heat treatment on three different fat samples (extra virgin olive oil, lard oil, and fat from dry cured ham—speck) were monitored. The proposed method is therefore suitable for a rapid evaluation of acylglycerol fractions in food lipid samples.     

Stability conditions in families

Publications mathématiques de l'IHÉS - We develop a theory of Bridgeland stability conditions and moduli spaces of semistable objects for a family of varieties. Our approach is based...