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Trifluoroacetic acid (TFA) is commonly used as mobile phase additive to improve retention and peak shape characteristics in hydrophilic interaction liquid chromatography (HILIC) of intact proteins. However, when using electrospray ionization-mass spectrometry (ESI-MS) detection, TFA may cause ionization suppression and adduct formation, leading to reduced analyte sensitivity. To address this, we describe a membrane-based microfluidic chip with multiple parallel channels for the selective post-column removal of TFA anions from HILIC. An anion-exchange membrane was used to physically separate the column effluent from a stripper flow solution comprising acetonitrile, formic acid, and propionic acid. The exchange of ions allowed the post-column removal of TFA used during HILIC separation of model proteins. The multichannel design of the device allows the use of flow rates of 0.2 mL/min without the need for a flow splitter, using mobile phases containing 0.1% TFA (13 mM). Separation selectivity and efficiency were maintained (with minor band broadening effects) while increasing the signal intensity and peak areas by improving ionization and reducing TFA adduct formation.

We study the evolution of a 2D vortex layer at high Reynolds number. Vortex layer flows are characterized by intense vorticity concentrated around a curve. In addition to their intrinsic interest, vortex layers are relevant configurations because they are regularizations of vortex sheets. In this paper, we consider vortex layers whose thickness is proportional to the square-root of the viscosity. We investigate the typical roll-up process, showing that crucial phases in the initial flow evolution are the formation of stagnation points and recirculation regions. Stretching and folding characterizes the following stage of the dynamics, and we relate these events to the growth of the palinstrophy. The formation of an inner vorticity core, with vorticity intensity growing to infinity for larger Reynolds number, is the final phase of the dynamics. We display the inner core's self-similar structure, with the scale factor depending on the Reynolds number. We reveal the presence of complex singularities in the solutions of Navier–Stokes equations; these singularities approach the real axis with increasing Reynolds number. The comparison between these singularities and the Birkhoff–Rott singularity seems to suggest that vortex layers, in the limit $Re\\rightarrow \\infty$, behave differently from vortex sheets.

In this paper we derive a reaction-diffusion-chemotaxis model for the dynamics of multiple sclerosis. We focus on the early inflammatory phase of the disease characterized by activated local microglia, with the recruitment of a systemically activated immune response, and by oligodendrocyte apoptosis. The model consists of three equations describing the evolution of macrophages, cytokine and apoptotic oligodendrocytes. The main driving mechanism is the chemotactic motion of macrophages in response to a chemical gradient provided by the cytokines. Our model generalizes the system proposed by Calvez and Khonsari (Math Comput Model 47(7–8):726–742, 2008 ) and Khonsari and Calvez (PLos ONE 2(1):e150, 2007 ) to describe Baló’s sclerosis, a rare and aggressive form of multiple sclerosis. We use a combination of analytical and numerical approaches to show the formation of different demyelinating patterns. In particular, a Turing instability analysis demonstrates the existence of a threshold value for the chemotactic coefficient above which stationary structures develop. In the case of subcritical transition to the patterned state, the numerical investigations performed on a 1-dimensional domain show the existence, far from the bifurcation, of complex spatio-temporal dynamics coexisting with the Turing pattern. On a 2-dimensional domain the proposed model supports the emergence of different demyelination patterns: localized areas of apoptotic oligodendrocytes, which closely fit existing MRI findings on the active MS lesion during acute relapses; concentric rings, typical of Baló’s sclerosis; small clusters of activated microglia in absence of oligodendrocytes apoptosis, observed in the pathology of preactive lesions.

In this paper, we undertake an analysis of the eigenstates of two non-self-adjoint operators q^ and p^ similar, in a suitable sense, to the self-adjoint position and momentum operators q^0 and p^0 usually adopted in ordinary quantum mechanics. In particular, we discuss conditions for these eigenstates to be biorthogonal distributions, and we discuss a few of their properties. We illustrate our results with two examples, one in which the similarity map between the self-adjoint and the non-self-adjoint is bounded, with bounded inverse, and the other in which this is not true. We also briefly propose an alternative strategy to deal with q^ and p^, based on the so-called quasi *-algebras.

Current approaches to study glycosylation of polyclonal human immunoglobulins G (IgG) usually imply protein digestion or glycan release. While these approaches allow in-depth characterization, they also result in a loss of valuable information regarding certain subclasses, allotypes and co-occuring post-translational modifications (PTMs). Unfortunately, the high variability of polyclonal IgGs makes their intact mass spectrometry (MS) analysis extremely challenging. We propose here a middle-up strategy for the analysis of the intact fragment crystallizable (Fc) region of human plasma IgGs, with the aim of acquiring integrated information of the -glycosylation and other PTMs of subclasses and allotypes. Human plasma IgG was isolated using Fc-specific beads followed by an on-bead C 2 domain digestion with the enzyme IdeS. The obtained mixture of Fc subunits was analyzed by capillary electrophoresis (CE) and hydrophilic interaction liquid chromatography (HILIC) hyphenated with MS. CE-MS provided separation of different IgG-subclasses and allotypes, while HILIC-MS allowed resolution of the different glycoforms and their oxidized variants. The orthogonality of these techniques was key to reliably assign Fc allotypes. Five individual donors were analyzed using this approach. Heterozygosis was observed in all the analyzed donors resulting in a total of 12 allotypes identified. The assignments were further confirmed using recombinant monoclonal IgG allotypes as standards. While the glycosylation patterns were similar within allotypes of the same subclass, clear differences were observed between IgG subclasses and donors, highlighting the relevance of the proposed approach. In a single analysis, glycosylation levels specific for each allotype, relative abundances of subclasses and information on co-occurring modifications are obtained. This middle-up method represents an important step toward a comprehensive analysis of immunoglobulin G-Fc variants.

Effective pain management is crucial for patient care, impacting comfort, recovery, and overall well-being. Traditional subjective pain assessment methods can be challenging, particularly in specific patient populations. This research explores an alternative approach using computer vision (CV) to detect pain through facial expressions. The study implements the YOLOv8 real-time object detection model to analyze facial expressions indicative of pain. Given four pain datasets, a dataset of pain-expressing faces was compiled, and each image was carefully labeled based on the presence of pain-associated Action Units (AUs). The labeling distinguished between two classes: pain and no pain. The pain category included specific AUs (AU4, AU6, AU7, AU9, AU10, and AU43) following the Prkachin and Solomon Pain Intensity (PSPI) scoring method. Images showing these AUs with a PSPI score above 2 were labeled as expressing pain. The manual labeling process utilized an open-source tool, makesense.ai, to ensure precise annotation. The dataset was then split into training and testing subsets, each containing a mix of pain and no-pain images. The YOLOv8 model underwent iterative training over 10 epochs. The model's performance was validated using precision, recall, and mean Average Precision (mAP) metrics, and F1 score. When considering all classes collectively, our model attained a mAP of 0.893 at a threshold of 0.5. The precision for \"pain\" and \"nopain\" detection was 0.868 and 0.919, respectively. F1 scores for the classes \"pain\", \"nopain\", and \"all classes\" reached a peak value of 0.80. Finally, the model was tested on the Delaware dataset and in a real-world scenario. Despite limitations, this study highlights the promise of using real-time computer vision models for pain detection, with potential applications in clinical settings. Future research will focus on evaluating the model's generalizability across diverse clinical scenarios and its integration into clinical workflows to improve patient care.

Current measurements of the cosmic ray spectra have reached unprecedented accuracy thanks to the new generation of experiments, and in particular the AMS-02 mission. At the same time, significant progress has been made in the propagation models of galactic cosmic rays. Nevertheless, the current knowledge on spallation cross sections is very poor, impeding a more precise estimation of the diffusion coefficient. In this work we show a new Markov-Chain Monte Carlo algorithm able to derive the propagation parameters from the flux ratios of light secondary cosmic rays (Li, Be, B) to C and O and a new procedure able to combine the flux of these secondary cosmic rays in order to get rid of the uncertainties associated to their production cross sections. Then, we show that the antiproton spectrum inferred from this diffusion model match experimental data much better than with earlier analyses, discarding the excess of data previously explained as a possible signature of antiproton production from dark matter.

Numerical solutions of the laminar Prandtl boundary-layer and Navier–Stokes equations are considered for the case of the two-dimensional uniform flow past an impulsively-started circular cylinder. The various viscous–inviscid interactions that occur during the unsteady separation process are investigated by applying complex singularity analysis to the wall shear and streamwise velocity component of the two solutions. This is carried out using two different methodologies, namely a singularity-tracking method and the Padé approximation. It is shown how the van Dommelen and Shen singularity that occurs in solutions of the Prandtl boundary-layer equations evolves in the complex plane before leading to a separation singularity in finite time. Navier–Stokes solutions, computed at different Reynolds numbers in the range $10^3 \\leq Re \\leq 10^5$ , are characterized by the presence of various complex singularities that can be related to different physical interactions acting over multiple spatial scales. The first interaction developing in the separation process is large-scale interaction that is visible for all the Reynolds numbers considered, and it signals the first relevant differences between the Prandtl and Navier–Stokes solutions. For $Re\\geq O(10^4)$ , a small-scale interaction follows the large-scale interaction. The onset of these interactions is related to the characteristic changes of the streamwise pressure gradient on the circular cylinder. Even if these interactions physically differ from that prescribed by the Prandtl solution, and they set a possible limit on the comparison of Prandtl solutions with Navier–Stokes solutions, it is shown how the asymptotic validity of boundary-layer theory is strongly supported by the results that have been obtained through the complex singularity analysis.

The astrophysical community is currently focusing its efforts in the development of a new generation of gamma-ray telescopes to detect low-energy photons in the MeV-GeV energy range, operating both in the Compton and pair conversion regimes. The reconstruction of the incident photons energy and direction is not straightforward, as the range of secondary particles produced by photon interactions is usually short. We propose a detector consisting of a tracker system based on scintillating fibers and of a Compton-pair imaging calorimeter made of CsI(Na) crystals coupled to wavelength shifting (WLS) fibers read out by Silicon Photomultiplier (SiPM) arrays. We have developed a dedicated simulation code to study the performance of this detector. The simulation takes into account the optical photon production and propagation inside the fibers and is used to optimize the fiber geometrical and optical properties and the design of the readout system.

Gamma-ray spectroscopy and gamma-ray imaging are two complementary techniques used for the localization and the identification of radioactive sources containing gamma-ray emitting radioisotopes. The radioactivity monitoring is focused on the detection of both artificial and environmental radioactive sources like Naturally Occurring Radioactive Materials (NORM). This kind of contamination becomes dangerous when the detection of the unwanted substances exhibits a concentration significantly above the environmental radioactive background radiation levels. For this purpose, we have developed, tested and shown a High Efficiency fast-Response GAmma (HERGA) detector useful for the identification of radionuclides and for gamma-ray imaging. A first version of the gamma detector prototype was composed of 16 CsI(Tl) scintillating crystals of 3x3x10 cm3 size, arranged in 4x4 matrix coupled with standard Photomultiplier tubes (PMTs). An image reconstruction of a radioactive gamma emitter source is possible using the coded mask technique, in which a 7x7 mask, made of Plastic and Tungsten tiles, is placed in front of the detector and a pattern recognition algorithm based on classical statistical methods (Kolmogorov Smirnov) is used to reconstruct the source position. The measurements carried out showed a point spread function (PSF) of a few mrad for pointlike sources. The Minimum Detectable Activity (MDA) was also determined in the case of pointlike radioactive sources. In this contribution we will present an update of the HERGA detector prototype in which Silicon Photomultipliers (SiPMs) are used in place of the PMTs. SiPMs provide similar or even better performance compared to the standard PMT sand provide benefits in terms of lower power consumption and reduced cost and compactness. The advantages of the SiPM technology are also characterized by the robustness of the photosensor that makes the new prototype compact, portable, ideal for in-situ and real-time. We will show a comparison between the results obtained with the newest SiPM read-out technology with respect to those obtained with the PMT one, in terms of energy and spatial resolution. The imaging performance is also in phase of testing in order to localize extended radioactive sources such as for example NORM samples or to detect inaccessible or hidden nuclear waste.