The Role of Nanoanalytics in the Development of Organic-Inorganic Nanohybrids—Seeing Nanomaterials as They Are

The functional properties of organic-inorganic (O-I) hybrids can be easily tuned by combining system components and parameters, making this class of novel nanomaterials a crucial element in various application fields. Unfortunately, the manufacturing of organic-inorganic nanohybrids still suffers from mechanical instability and insufficient synthesis reproducibility. The control of the composition and structure of nanosurfaces themselves is a specific analytical challenge and plays an important role in the future reproducibility of hybrid nanomaterials surface properties and response. Therefore, appropriate and sufficient analytical methodologies and technical guidance for control of their synthesis, characterization and standardization of the final product quality at the nanoscale level should be established. In this review, we summarize and compare the analytical merit of the modern analytical methods, viz. Fourier transform infrared spectroscopy (FTIR), RAMAN spectroscopy, surface plasmon resonance (SPR) and several mass spectrometry (MS)-based techniques, that is, inductively coupled plasma mass spectrometry (ICP-MS), single particle ICP-MS (sp-ICP-MS), laser ablation coupled ICP-MS (LA-ICP-MS), time-of-flight secondary ion mass spectrometry (TOF-SIMS), liquid chromatography mass spectrometry (LC-MS) utilized for characterization of O-I nanohybrids. Special attention is given to laser desorption ionization mass spectrometry (LDI-MS) as a reliable nanoanalytical platform for characterization of O-I hybrid nanomaterials, their quality, design verification and validation

The Comparison of Methods for IndividualTreatment Effect Detection

Today, treatment effect estimation at the individual level isa vital problem in many areas of science and business. For example, inmarketing, estimates of the treatment effect are used to select the mostefficient promo-mechanics; in medicine, individual treatment effects areused to determine the optimal dose of medication for each patient and soon. At the same time, the question on choosing the best method, i.e., themethod that ensures the smallest predictive error (for instance, RMSE)or the highest total (average) value of the effect, remains open. Accord-ingly, in this paper we compare the effectiveness of machine learningmethods for estimation of individual treatment effects. The comparisonis performed on the Criteo Uplift Modeling Dataset. In this paper weshow that the combination of the Logistic Regression method and theDifference Score method as well as Uplift Random Forest method pro-vide the best correctness of Individual Treatment Effect prediction onthe top 30% observations of the test dataset

The Comparison of Methods for IndividualTreatment Effect Detection

Today, treatment effect estimation at the individual level isa vital problem in many areas of science and business. For example, inmarketing, estimates of the treatment effect are used to select the mostefficient promo-mechanics; in medicine, individual treatment effects areused to determine the optimal dose of medication for each patient and soon. At the same time, the question on choosing the best method, i.e., themethod that ensures the smallest predictive error (for instance, RMSE)or the highest total (average) value of the effect, remains open. Accord-ingly, in this paper we compare the effectiveness of machine learningmethods for estimation of individual treatment effects. The comparisonis performed on the Criteo Uplift Modeling Dataset. In this paper weshow that the combination of the Logistic Regression method and theDifference Score method as well as Uplift Random Forest method pro-vide the best correctness of Individual Treatment Effect prediction onthe top 30% observations of the test dataset

Application of Organic-Inorganic Hybrids in Chemical Analysis, Bio- and Environmental Monitoring

Organic-inorganic hybrids (OIH) are considered to be a powerful platform for applications in many research and industrial fields. This review highlights the application of OIH for chemical analysis, biosensors, and environmental monitoring. A methodology toward metrological traceability measurement and standardization of OIH and demonstration of the role of mathematical modeling in biosensor design are also presented. The importance of the development of novel types of OIH for biosensing applications is highlighted. Finally, current trends in nanometrology and nanobiosensors are presented

Protective Role of Mytilus edulis Hydrolysate in Lipopolysaccharide-Galactosamine Acute Liver Injury

Acute liver injury in its terminal phase trigger systemic inflammatory response syndrome with multiple organ failure. An uncontrolled inflammatory reaction is difficult to treat and contributes to high mortality. Therefore, to solve this problem a search for new therapeutic approaches remains urgent. This study aimed to explore the protective effects of M. edulis hydrolysate (N2-01) against Lipopolysaccharide-D-Galactosamine (LPS/D-GalN)-induced murine acute liver injure and the underlying mechanisms. N2-01 analysis, using Liquid Chromatography Mass Spectrometry (LCMS) metabolomic and proteomic platforms, confirmed composition, molecular-weight distribution, and high reproducibility between M. edulis hydrolysate manufactured batches. N2-01 efficiently protected mice against LPS/D-GalN-induced acute liver injury. The most prominent result (100% survival rate) was obtained by the constant subcutaneous administration of small doses of the drug. N2-01 decreased Vascular Cell Adhesion Molecule-1 (VCAM-1) expression from 4.648 ± 0.445 to 1.503 ± 0.091 Mean Fluorescence Intensity (MFI) and Interleukin-6 (IL-6) production in activated Human Umbilical Vein Endothelial Cells (HUVECs) from 7.473 ± 0.666 to 2.980 ± 0.130 ng/ml in vitro. The drug increased Nitric Oxide (NO) production by HUVECs from 27.203 ± 2.890 to 69.200 ± 4.716 MFI but significantly decreased inducible Nitric Oxide Synthase (iNOS) expression from 24.030 ± 2.776 to 15.300 ± 1.290 MFI and NO production by murine peritoneal lavage cells from 6.777 ± 0.373 µm to 2.175 ± 0.279 µm. The capability of the preparation to enhance the endothelium barrier function and to reduce vascular permeability was confirmed in Electrical Cell-substrate Impedance Sensor (ECIS) test in vitro and Miles assay in vivo. These results suggest N2-01 as a promising agent for treating a wide range of conditions associated with uncontrolled inflammation and endothelial dysfunction