Machine-learning model selection and parameter estimation from kinetic data of complex first-order reaction systems.

Dealing with a system of first-order reactions is a recurrent issue in chemometrics, especially in the analysis of data obtained by spectroscopic methods applied on complex biological systems. We argue that global multiexponential fitting, the still common way to solve such problems, has serious weaknesses compared to contemporary methods of sparse modeling. Combining the advantages of group lasso and elastic net-the statistical methods proven to be very powerful in other areas-we created an optimization problem tunable from very sparse to very dense distribution over a large pre-defined grid of time constants, fitting both simulated and experimental multiwavelength spectroscopic data with high computational efficiency. We found that the optimal values of the tuning hyperparameters can be selected by a machine-learning algorithm based on a Bayesian optimization procedure, utilizing widely used or novel versions of cross-validation. The derived algorithm accurately recovered the true sparse kinetic parameters of an extremely complex simulated model of the bacteriorhodopsin photocycle, as well as the wide peak of hypothetical distributed kinetics in the presence of different noise levels. It also performed well in the analysis of the ultrafast experimental fluorescence kinetics data detected on the coenzyme FAD in a very wide logarithmic time window. We conclude that the primary application of the presented algorithms-implemented in available software-covers a wide area of studies on light-induced physical, chemical, and biological processes carried out with different spectroscopic methods. The demand for this kind of analysis is expected to soar due to the emerging ultrafast multidimensional infrared and electronic spectroscopic techniques that provide very large and complex datasets. In addition, simulations based on our methods could help in designing the technical parameters of future experiments for the verification of particular hypothetical models.

Niosomes decorated with dual ligands targeting brain endothelial transporters increase cargo penetration across the blood-brain barrier.

Nanoparticles targeting transporters of the blood-brain barrier (BBB) are promising candidates to increase the brain penetration of biopharmacons. Solute carriers (SLC) are expressed at high levels in brain endothelial cells and show a specific pattern at the BBB. The aim of our study was to test glutathione and ligands of SLC transporters as single or dual BBB targeting molecules for nanovesicles. High mRNA expression levels for hexose and neutral amino acid transporting SLCs were found in isolated rat brain microvessels and our rat primary cell based co-culture BBB model. Niosomes were derivatized with glutathione and SLC ligands glucopyranose and alanine. Serum albumin complexed with Evans blue (67 kDa), which has a very low BBB penetration, was selected as a cargo. The presence of targeting ligands on niosomes, especially dual labeling, increased the uptake of the cargo molecule in cultured brain endothelial cells. This cellular uptake was temperature dependent and could be decreased with a metabolic inhibitor and endocytosis blockers filipin and cytochalasin D. Making the negative surface charge of brain endothelial cells more positive with a cationic lipid or digesting the glycocalyx with neuraminidase elevated the uptake of the cargo after treatment with targeted nanocarriers. Treatment with niosomes increased plasma membrane fluidity, suggesting the fusion of nanovesicles with endothelial cell membranes. Targeting ligands elevated the permeability of the cargo across the BBB in the culture model and in mice, and dual-ligand decoration of niosomes was more effective than single ligand labeling. Our data indicate that dual labeling with ligands of multiple SLC transporters can potentially be exploited for BBB targeting of nanoparticles.

Improvement of infrared single-photon detectors absorptance by integrated plasmonic structures.

Plasmonic structures open novel avenues in photodetector development. Optimized illumination configurations are reported to improve p-polarized light absorptance in superconducting-nanowire single-photon detectors (SNSPDs) comprising short- and long-periodic niobium-nitride (NbN) stripe-patterns. In OC-SNSPDs consisting of ~quarter-wavelength dielectric layer closed by a gold reflector the highest absorptance is attainable at perpendicular incidence onto NbN patterns in P-orientation due to E-field concentration at the bottom of nano-cavities. In NCAI-SNSPDs integrated with nano-cavity-arrays consisting of vertical and horizontal gold segments off-axis illumination in S-orientation results in polar-angle-independent perfect absorptance via collective resonances in short-periodic design, while in long-periodic NCAI-SNSPDs grating-coupled surface waves promote EM-field transportation to the NbN stripes and result in local absorptance maxima. In NCDAI-SNSPDs integrated with nano-cavity-deflector-array consisting of longer vertical gold segments large absorptance maxima appear in 3p-periodic designs due to E-field enhancement via grating-coupled surface waves synchronized with the NbN stripes in S-orientation, which enable to compensate fill-factor-related retrogression.

Effect of pH on stability and plasmonic properties of cysteine-functionalized silver nanoparticle dispersion.

Citrate-stabilized spherical silver nanoparticles (Ag NPs) with d=8.25±1.25 nm diameter were prepared and functionalized with L-cysteine (Cys) in aqueous dispersion. The nanosilver-cysteine interactions have been investigated by Raman and (1)H NMR spectroscopy. The effect of pH on stability of biofunctionalized Ag NPs was investigated. The cysteine-capped nanosilver dispersions remain stable at higher pH (pH>7), while the degree of aggregation increased as the pH decreased. Below pH ~7, the characteristic surface plasmon band of bare silver nanoparticles was back-shifted from λ(measured)(bareAgNP)=391 nm to λ(measured)(1)=387-391 nm, while the presence of a new band at λ(measured)(2)=550-600 nm was also observed depending on pH. Finite element method (FEM) was applied to numerically compute the absorption spectra of aqueous dispersions containing bare and cysteine-functionalized Ag NPs at different pH. Both the dynamic light scattering (DLS) measurements, Zeta potential values and the transmission electron microscopic (TEM) images confirmed our supposition. Namely, electrostatic interaction arose between the deprotonated carboxylate (COO(-)) and protonated amino groups (NH(3)(+)) of the amino acid resulting in cross-linking network of the Ag NPs between pH ~3 and 7. If the pH is measurable lower than ~3, parallel with the protonation of citrate and L-cysteine molecules the connection of the particles via l-cysteine is partly decomposed resulting in decrease of second plasmon band intensity.

Numerical method to optimize the polar-azimuthal orientation of infrared superconducting-nanowire single-photon detectors.

A finite-element method for calculating the illumination-dependence of absorption in three-dimensional nanostructures is presented based on the radio frequency module of the Comsol Multiphysics software package (Comsol AB). This method is capable of numerically determining the optical response and near-field distribution of subwavelength periodic structures as a function of illumination orientations specified by polar angle, φ, and azimuthal angle, γ. The method was applied to determine the illumination-angle-dependent absorptance in cavity-based superconducting-nanowire single-photon detector (SNSPD) designs. Niobium-nitride stripes based on dimensions of conventional SNSPDs and integrated with ~ quarter-wavelength hydrogen-silsesquioxane-filled nano-optical cavity and covered by a thin gold film acting as a reflector were illuminated from below by p-polarized light in this study. The numerical results were compared to results from complementary transfer-matrix-method calculations on composite layers made of analogous film-stacks. This comparison helped to uncover the optical phenomena contributing to the appearance of extrema in the optical response. This paper presents an approach to optimizing the absorptance of different sensing and detecting devices via simultaneous numerical optimization of the polar and azimuthal illumination angles.

Detection and isolation of cell-derived microparticles are compromised by protein complexes resulting from shared biophysical parameters.

Numerous diseases, recently reported to associate with elevated microvesicle/microparticle (MP) counts, have also long been known to be characterized by accelerated immune complex (IC) formation. The goal of this study was to investigate the potential overlap between parameters of protein complexes (eg, ICs or avidin-biotin complexes) and MPs, which might perturb detection and/or isolation of MPs. In this work, after comprehensive characterization of MPs by electron microscopy, atomic force microscopy, dynamic light-scattering analysis, and flow cytometry, for the first time, we drive attention to the fact that protein complexes, especially insoluble ICs, overlap in biophysical properties (size, light scattering, and sedimentation) with MPs. This, in turn, affects MP quantification by flow cytometry and purification by differential centrifugation, especially in diseases in which IC formation is common, including not only autoimmune diseases, but also hematologic disorders, infections, and cancer. These data may necessitate reevaluation of certain published data on patient-derived MPs and contribute to correct the clinical laboratory assessment of the presence and biologic functions of MPs in health and disease.

Protection of the blood-brain barrier by pentosan against amyloid-ß-induced toxicity.

Endothelial cells of brain capillaries forming the blood-brain barrier play an important role in the pathogenesis and therapy of Alzheimer's disease. Amyloid-ß (Aß) peptides are key pathological elements in the development of the disease. A blood-brain barrier model, based on primary rat brain endothelial cells was used in which the barrier properties were induced by glial cells. The effects of amyloid peptides have been tested on cell viability and barrier functions. Aß showed toxic effects on primary rat brain endothelial cells measured by MTT dye conversion and the lactate dehydrogenase release. Morphologically cytoplasmic vacuolization, disruption of the structure of cytoplasmic organelles and tight junctions could be observed in brain endothelial cells. Treatment with Aß1-42 decreased the electrical resistance, and increased the permeability of brain endothelial cell monolayers for both fluorescein and albumin. Serum amyloid P component which stabilizes Aß fibrils in cortical amyloid plaques and cerebrovascular amyloid deposits significantly potentiated the barrier-weakening effect of Aß1-42. Sulfated polysaccharide pentosan could decrease the toxic effects of Aß peptides in brain endothelial cells. It could also significantly protect the barrier integrity of monolayers from damaging actions of peptides. Pentosan modified the size, and significantly decreased the number of amyloid aggregates demonstrated by atomic force microscopy. The present data further support the toxic effects of amyloid peptides on brain endothelial cells, and can contribute to the development of molecules protecting the blood-brain barrier in Alzheimer's disease.