Exploring Factors Influencing Changes in Incidence and Severity of Multisystem Inflammatory Syndrome in Children

Multisystem inflammatory syndrome (MIS-C) is a rare condition associated with COVID-19 affecting children, characterized by severe and aberrant systemic inflammation leading to nonspecific symptoms, such as gastrointestinal, cardiac, respiratory, hematological, and neurological disorders. In the last year, we have experienced a progressive reduction in the incidence and severity of MIS-C, reflecting the worldwide trend. Thus, starting from the overall trend in the disease in different continents, we reviewed the literature, hypothesizing the potential influencing factors contributing to the reduction in cases and the severity of MIS-C, particularly the vaccination campaign, the spread of different SARS-CoV-2 variants (VOCs), and the changes in human immunological response. The decrease in the severity of MIS-C and its incidence seem to be related to a combination of different factors rather than a single cause. Maturation of an immunological memory to SARS-CoV-2 over time, the implication of mutations of key amino acids of S protein in VOCs, and the overall immune response elicited by vaccination over the loss of neutralization of vaccines to VOCs seem to play an important role in this change

Nonlinear quantum model for atomic Josephson junctions with one and two bosonic species

We study atomic Josephson junctions (AJJs) with one and two bosonic species confined by a double-well potential. Proceeding from the second quantized Hamiltonian, we show that it is possible to describe the zero-temperature AJJs microscopic dynamics by means of extended Bose-Hubbard (EBH) models, which include usually-neglected nonlinear terms. Within the mean-field approximation, the Heisenberg equations derived from such two-mode models provide a description of AJJs macroscopic dynamics in terms of ordinary differential equations (ODEs). We discuss the possibility to distinguish the Rabi, Josephson, and Fock regimes, in terms of the macroscopic parameters which appear in the EBH Hamiltonians and, then, in the ODEs. We compare the predictions for the relative populations of the Bose gases atoms in the two wells obtained from the numerical solutions of the two-mode ODEs, with those deriving from the direct numerical integration of the Gross-Pitaevskii equations (GPEs). Our investigations shows that the nonlinear terms of the ODEs are crucial to achieve a good agreement between ODEs and GPEs approaches, and in particular to give quantitative predictions of the self-trapping regime.Comment: Accepted for the publication in J. Phys. B: At. Mol. Opt. Phy

Estimation of functional connectivity from electromagnetic signals and the amount of empirical data required

An increasing number of neuroimaging studies are concerned with the identification of interactions or statistical dependencies between brain areas. Dependencies between the activities of different brain regions can be quantified with functional connectivity measures such as the cross-correlation coefficient. An important factor limiting the accuracy of such measures is the amount of empirical data available. For event-related protocols, the amount of data also affects the temporal resolution of the analysis. We use analytical expressions to calculate the amount of empirical data needed to establish whether a certain level of dependency is significant when the time series are autocorrelated, as is the case for biological signals. These analytical results are then contrasted with estimates from simulations based on real data recorded with magnetoencephalography during a resting-state paradigm and during the presentation of visual stimuli. Results indicate that, for broadband signals, 50–100 s of data is required to detect a true underlying cross-correlations coefficient of 0.05. This corresponds to a resolution of a few hundred milliseconds for typical event-related recordings. The required time window increases for narrow band signals as frequency decreases. For instance, approximately 3 times as much data is necessary for signals in the alpha band. Important implications can be derived for the design and interpretation of experiments to characterize weak interactions, which are potentially important for brain processing

UGIJAR AND CANJAYAR NEOGENE BASINS (SE SPAIN): AN EXAMPLE OF STRIKE-SLIP BASIN EVOLUTION IN TRANSPRESSIVE REGIME

The present study has been carried out in the eastern part of the Alpujarran corridor (Betic Chain), an E-W trending basin, 80 km long, of Neogene-Quaternary age. In particular, the Ugijar and Canjayar basins (respectively named Basin 1 and Basin 2), controlled by an E-W trending left stepping right lateral strike­slip system, associated with NE-SW trending thrust faults, have been investigated. The stratigraphic sequence of the forementioned two basins, which can be up to 2000 m thick, is mainly due to tectonic subsidence and is here interpreted in terms of Sequence Stratigraphy. The age of the whole sequence, dated by means of planktonic foraminifera, is Late Serravallian-Pliocene

Quantum diffusion with disorder, noise and interaction

Disorder, noise and interaction play a crucial role in the transport properties of real systems, but they are typically hard to control and study both theoretically and experimentally, especially in the quantum case. Here we explore a paradigmatic problem, the diffusion of a wavepacket, by employing ultra-cold atoms in a disordered lattice with controlled noise and tunable interaction. The presence of disorder leads to Anderson localization, while both interaction and noise tend to suppress localization and restore transport, although with completely different mechanisms. When only noise or interaction are present we observe a diffusion dynamics that can be explained by existing microscopic models. When noise and interaction are combined, we observe instead a complex anomalous diffusion. By combining experimental measurements with numerical simulations, we show that such anomalous behavior can be modeled with a generalized diffusion equation, in which the noise- and interaction-induced diffusions enter in an additive manner. Our study reveals also a more complex interplay between the two diffusion mechanisms in regimes of strong interaction or narrowband noise.Comment: 11 pages, 10 figure

Localization from quantum interference in one-dimensional disordered potentials

We show that the tails of the asymptotic density distribution of a quantum wave packet that localizes in the the presence of random or quasiperiodic disorder can be described by the diagonal term of the projection over the eingenstates of the disordered potential. This is equivalent of assuming a phase randomization of the off-diagonal/interference terms. We demonstrate these results through numerical calculations of the dynamics of ultracold atoms in the one-dimensional speckle and quasiperiodic potentials used in the recent experiments that lead to the observation of Anderson localization for matter waves [Billy et al., Nature 453, 891 (2008); Roati et al., Nature 453, 895 (2008)]. For the quasiperiodic case, we also discuss the implications of using continuos or discrete models.Comment: 5 pages, 3 figures; minor changes, references update

Advantages of the lognormal approach to determining reference change values for N-terminal propeptide B-type natriuretic peptide

Serial measurement of NT-proBNP is performed routinely in the monitoring and assessment of the effectiveness of therapy in patients being treated for chronic heart failure (CHF). Intra-individual changes in NT-proBNP levels over time are compared typically to a reference change value (RCV) determined using either a standard [i.e., nested analysis of variance (nANOVA)] or a lognormal approach. The RCV defines the minimum percent change in serial analyte values that exceeds the percent change expected due to biological variation alone. Currently, there is no consensus on which approach (nANOVA or lognormal) to determining RCV is better. AIMS: Based on these considerations, we aimed to illustrate the impact of data transformation on the calculation of the biological variation of NT-proBNP and discuss the utility of logarithmic transformation in monitoring patients with heart failure. METHODS: 15 healthy subjects were enrolled after informed consent; 5 blood specimens were collected twice a week. Nested ANOVA from replicate analyses was applied to obtain components of biological variation, on the raw data and after data transformation. RESULTS: NT-proBNP distribution being highly skewed required data transformation. Natural log transformation yielded normalization. An example demonstrates that for untransformed values the RCV was overestimated for low concentrations of NT-proBNP and underestimated for higher concentrations. CONCLUSIONS: Log-transformed data are often used in the establishment of reference intervals for evaluating laboratory tests results in clinical practice, especially when the reference interval data are not Gaussian distributed. As log-normal approach is the best approach to determining RCV values we encourage its use assessing the clinical utility of NT-proBNP serial testing. We propose that the log-normal approach becomes the standard approach to determining RCV and replaces the use of nANOV

Rapid recognition of drug-resistance/sensitivity in leukemic cells by Fourier transform infrared microspectroscopy and unsupervised hierarchical cluster analysis.

We tested the ability of Fourier Transform (FT) InfraRed (IR) microspectroscopy (microFTIR) in combination with unsupervised Hierarchical Cluster Analysis (HCA) in identifying drug-resistance/sensitivity in leukemic cells exposed to tyrosine kinase inhibitors (TKIs). Experiments were carried out in a well-established mouse model of human Chronic Myelogenous Leukemia (CML). Mouse-derived pro-B Ba/F3 cells transfected with and stably expressing the human p210(BCR-ABL) drug-sensitive wild-type BCR-ABL or the V299L or T315I p210(BCR-ABL) drug-resistant BCR-ABL mutants were exposed to imatinib-mesylate (IMA) or dasatinib (DAS). MicroFTIR was carried out at the Diamond IR beamline MIRIAM where the mid-IR absorbance spectra of individual Ba/F3 cells were acquired using the high brilliance IR synchrotron radiation (SR) via aperture of 15 7 15 \u3bcm(2) in sizes. A conventional IR source (globar) was used to compare average spectra over 15 cells or more. IR signatures of drug actions were identified by supervised analyses in the spectra of TKI-sensitive cells. Unsupervised HCA applied to selected intervals of wavenumber allowed us to classify the IR patterns of viable (drug-resistant) and apoptotic (drug-sensitive) cells with an accuracy of >95%. The results from microFTIR + HCA analysis were cross-validated with those obtained via immunochemical methods, i.e. immunoblotting and flow cytometry (FC) that resulted directly and significantly correlated. We conclude that this combined microFTIR + HCA method potentially represents a rapid, convenient and robust screening approach to study the impact of drugs in leukemic cells as well as in peripheral blasts from patients in clinical trials with new anti-leukemic drugs