Search Results (205)

Serum gamma-glutamyltransferase (GGT) is a biomarker for cardiovascular disease, but the role of its encoding gene family in ischemic stroke (IS) is unknown. This pilot study of 1288 individuals (600 cases and 688 controls) investigated GGT1, GGT5, GGT6, and GGT7 polymorphisms using the MassARRAY-4 system. Conventional single-variant, haplotype, and diplotype analyses were complemented by Model-Based Multifactor Dimensionality Reduction (MB-MDR) with stability assessment and model prioritization. Conventional analysis identified female-specific associations for three GGT5 variants (rs8140505, rs2275984, and rs2267073; P_perm < 0.05). A common GGT5 haplotype was protective in females (P_perm = 0.02). Diplotype analysis revealed joint effects of GGT genotypes on IS risk in females (FDR < 0.05). MB-MDR uncovered complex higher-order interactions (P_perm < 0.0001): in women, 12 models represented second-order interactions between smoking and individual GGT variants. In men, 8 models centered on GGT1 rs5751909 spanning second- to fourth-order interactions with alcohol, smoking, and other GGT family members. All prioritized models passed FDR correction (q < 0.05) and achieved higher weighted composite scores. eQTL data linked these variants to regulatory networks controlling glutathione metabolism, oxidative stress, and inflammation. This study supports a novel hypothesis on the combined involvement of GGT gene family polymorphisms and pro-oxidant environmental factors in ischemic stroke predisposition, demonstrating that disease risk is shaped by sex-specific gene–environment interactions. The pronounced sexual dimorphism highlights the need for sex-specific personalized approaches: smoking cessation may be particularly impactful in women carrying GGT5 risk variants, while alcohol moderation could be prioritized in men with GGT1 risk variants. Full article

In various sectors of the petrochemical and metallurgical industries, significant volumes of waste in the form of highly stable water–hydrocarbon emulsions are generated and stored. The presence of an aqueous phase limits their further use. To utilize this waste and obtain valuable commercial products, a thermomechanical dewatering method based on the evaporation of the aqueous phase under turbulent emulsion flow conditions has been proposed and tested. However, the dynamics of aqueous phase evaporation and vapor phase formation within this method remain poorly understood. This understanding is crucial, as it directly influences the optimal selection of necessary auxiliary equipment. To address this gap, the dynamics of vapor formation during the boiling off of the aqueous phase from highly stable water–hydrocarbon emulsions in a batch thermomechanical dewatering reactor were simulated. To identify general patterns, the gradual evaporation process was calculated as a set of multiple single-effect evaporation steps with a two-degree increment. Initially, modeling results showed that to obtain a commercial product with a water content of less than 1%, temperatures must be maintained at up to 150 °C. This finding was in complete agreement with experimental data, thereby confirming the accuracy of the calculations. Subsequently, extreme vaporization rates were identified, which significantly (1.7–9 times) exceeded the average vapor formation rates in a batch reactor. Maximum vapor formation rates were observed in the temperature range of 100–120 °C. Furthermore, increasing the feedstock water content above 10% was found to significantly prolong the processing time and elevate the maximum vapor formation rate. The patterns presented in this article facilitate the optimization of operating modes for commercial thermomechanical dewatering units, enable the informed selection of necessary auxiliary equipment, and help maintain both the safety and efficiency of the industrial process. Full article

Neuroimplants represent an emerging medical technology, offering new therapeutic approaches for severe neurological and psychiatric disorders. One of the key limitations to long-term neuroimplant performance is the foreign body response elicited by intracortical implantation. Among the contributing cell types, astrocytes play a central role in glial scar formation around the implant, which can compromise device functionality. Immunofluorescence of glial fibrillary acidic protein (GFAP) provides a well-established marker of astrogliosis (neuroinflammation), yet quantitative and reproducible assessment of astrocyte morphology remains challenging due to the complexity and variability of image analysis approaches. Here, we aimed to quantitatively assess implantation-induced astrogliosis and to determine how classifier training strategy influences segmentation outcomes and morphometric measurements. We present a machine learning-assisted pipeline based on the LabKit plugin in Fiji for segmentation and morphometric analysis of GFAP-positive astrocytes in peri-implant scar versus distant cortical regions. Using this approach, we demonstrate an increase in GFAP expression, cell area, and astrocytic process length as well as the redistribution of GFAP signal along astrocytic processes within scar regions. We show that different classifier training strategies produce systematically distinct segmentation outcomes, with rule-compliant annotation improving agreement with manually defined ground truth. These findings highlight the critical role of annotation strategy in shallow learning-based segmentation and provide a practical framework for improving reproducibility of astrocyte morphometry in studies of neuroinflammation and neuroimplant biocompatibility. Full article

Vast quantities of liquid hydrocarbon and oil-containing wastes are generated and accumulate annually. Dewatering such sludges presents a significant technological challenge due to the high content of emulsified and chemically bound water. Consequently, the development of integrated approaches, particularly thermomechanical methods, have emerged as a promising strategy. These methods aim to disrupt the emulsion stability and enhance water evaporation efficiency. This study provides a theoretical basis for stabilizing the evaporation of the aqueous phase through mechanical agitation within boiling emulsions. A quantitative mathematical model is developed to identify critical conditions that prevent explosive boiling. Under intensive mixing, water globule diameters decrease by 80–85% within the first 5 s, while their settling time exceeds the dispersion time by hundreds of times—effectively inhibiting the accumulation of a critical aqueous-phase mass. Energy analysis reveals that, at a superheat temperature of 110 °C, the maximum permissible droplet diameter is approximately 0.5 mm; at 150 °C, it must not exceed 0.25 mm to avoid explosive boiling. To ensure safe operation, mixer rotational speeds of at least 100–200 rpm are required, with higher speeds (>200 rpm) necessary near 150 °C. The mechanical agitation modes proposed herein enable controlled, non-explosive evaporation of water from complex emulsions. Collectively, these findings lay a theoretical foundation for the industrial-scale deployment of thermomechanical dewatering technologies—offering a safer, more efficient pathway for managing challenging sludge streams. Full article

The inadequate biosafety of MRI contrast agents (CAs) remains a challenging issue. Both increasing the magnetic relaxivity of CAs and targeting them through conjugation with folates are promising approaches to addressing this issue. Silica nanoparticles (SNs) with Mn²⁺ ions specifically localized in the outer layer were selected as the target for further surface modification for the covalent attachment of folates. It was shown that when Mn-containing SNs are conjugated with folates via preliminary amino modification of the surface silanol groups, the folate-conjugated SNs suffer from colloidal instability. Thus, precoating Mn-containing SNs with unfolded BSA exposes surface amino groups that successfully conjugate with folates without loss of colloidal stability. Partial washout of surface-localized Mn²⁺ follows folate conjugation of Mn-containing SNs, although residual Mn²⁺ ions provide r₁₍₂₎ relaxivities of 62.1 (160.4) mM⁻¹s⁻¹ at 0.47 T. Full article

The formation of a unified innovation space is a key challenge for deepening Eurasian integration. This study aims to develop the concept of asymmetric complementarity by investigating how the structural asymmetry between the NIS of Russia and Kazakhstan can be transformed from a source of imbalance into a basis for strategic synergy. Based on a mixed methodology that includes quantitative analysis of data from the Global Innovation Index (GII) 2025, SWOT analysis, and scenario modeling, two divergent models were identified. Russia’s NIS is defined as “compensatory disbalanced” (strong human capital with weak institutions), while Kazakhstan’s NIS is defined as “institutionally focused with knowledge deficit” (relatively developed institutions with critically low R&D investment). The theoretical contribution of this work lies in developing the concept of asymmetric complementarity, which demonstrates that the identified structural differences create a foundation for synergistic cooperation. The practical conclusions are aimed at transitioning from rule harmonization to network capability integration, including the creation of distributed excellence centers, the development of “soft” type supranational infrastructure, and the implementation of the “innovative accounting” principle. Full article

Copper-based catalysts have emerged as promising materials for electrochemical carbon dioxide reduction reactions, owing to copper’s unique ability to facilitate multi-electron transfer processes and produce valuable products such as methanol and ethanol. In this study, novel trisferrocenyltrithiophosphite–copper(I) bromide composites with Cu-to-ligand molar ratios of 1:1 and 2:1 were synthesized and evaluated for their catalytic performance. The composites were characterized by a combination of techniques, including powder X-ray diffraction (PXRD), linear sweep voltammetry (LSV), potentiostatic testing, chromatographic analysis, scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). Electrochemical measurements demonstrated significant current enhancements in the presence of CO₂, highlighting the composites’ catalytic activity. Potentiostatic tests revealed excellent stability, with only a 9% decline in current density over 5 h of electrolysis. Product analysis via gas chromatography indicated the formation of methanol for the 1:1 composite and ethanol for the 2:1 composite with Faradaic efficiencies of 5.79% and 9.26%, respectively. While absolute efficiencies remain modest due to competitive hydrogen evolution, these results demonstrate a tunable catalytic performance based on the Cu-to-ligand ratio. SEM and XPS studies further supported the formation of active catalytic centers and changes in the oxidation states of copper during CO₂ reduction. PXRD analysis confirmed the retention of structural integrity for both composites before and after catalytic testing. Full article

The increasing number of Base Stations (BSs) and connected devices, coupled with their mobility, poses significant challenges and makes mobility management even more pressing. Therefore, advanced handover (HO) management technologies are required to address this issue. This paper focuses on the ping-pong HO problem. To address this issue, we propose an algorithm using Reinforcement Learning (RL) based on the Double Deep Q-Network (DDQN). The novelty of our approach is to assign specialized RL agents to users based on their mobility patterns. The use of specialized RL agents simplifies the learning process. The effectiveness of the proposed algorithm is demonstrated in tests on the ns-3 platform due to its ability to replicate real-world scenarios. To compare the results of the proposed approach, the baseline handover algorithm based on Events A2 and A4 is used. The results show that the proposed approach reduces the number of HO by more than four times on average, resulting in a more stable data rate and increasing it up to two times in the best case. Full article

Background. The aim of this study was to develop a predictive model of anticancer drug therapy toxicity in patients with gastric cancer. Methods. The retrospective study included 100 patients with stage II–IV gastric cancer who underwent 4 chemotherapy cycles. Initial significant toxicity factors included age, gender, height, body mass, body mass index, disease stage, skeletal muscle index (SMI), as well as plasma levels of trace elements (copper, zinc, selenium, manganese) and thyroid-stimulating hormone, cancer histology type and treatment regimen. The CTCAE v5.0 scale was employed to assess the severity of adverse events. Statistical analysis and building of mathematical neural network models were carried out in SPSS Statistics (v19.0). Results. Lower SMI values were associated with higher rates of toxicity-related complications of anticancer drug therapy (p < 0.05): leukopenia, hypoproteinemia, nausea, vomiting, cardiovascular events. Anemia, thrombocytopenia, hepatic cytolysis syndrome, nausea, diarrhea, constipation and stomatitis showed a weaker correlation with SMI. An increase in TSH was associated with higher rates of thrombocytopenia, nausea and vomiting. A decrease in Cu/Zn in plasma correlated with the severity of leukopenia and diarrhea, whereas Se/Mn showed an inverse correlation with the severity of anemia. Conclusions. Sarcopenia, abnormal thyroid status and imbalances in copper, zinc, selenium and manganese in blood plasma of patients with gastric cancer may be used as predictors of increased toxicity of anticancer drug therapy. Full article

Microplastic pollution of ecosystems is considered a modern problem. Freshwater ecosystems, despite the interest shown in their study, remain poorly understood. Lake Baikal (Russia) is one of the least studied freshwater ecosystems in this regard. This large lake is distinguished from others by its high level of biodiversity and clean drinking water. The aim of this study is a multi-matrix investigation of microplastic pollution in one of the lake’s bay. The following matrices are used: surface water, water column, sediment, macrophytes, macroinvertebrates, and fish, as well as ice and snow during the winter. The results show that certain locations exhibit high concentrations of microplastic particles. In some cases, this was due to the properties or characteristics of these locations (littoral zones near the water’s edge, macrophytes with mucus sheaths, ice and snow (potentially, the near-surface water layer after ice melt)), while in others, it was due to localized pollution (pier and ship mooring areas). An analysis of the polymer types of the detected microplastic particles reveals the presence of both common (polypropylene, polyethylene terephthalate, polystyrene, polyethylene, polyvinyl chloride) and rare (polyvinyl alcohol and alkyd resin). Moreover, in some locations, the latter two polymers predominate, a phenomenon rarely observed in other studies. Further research was recommended to focus on the chronic effects of microplastic particles on organisms associated with areas of elevated particle concentrations. Full article

Gold nanoparticles (AuNPs) are promising for biomedical applications, but their synthesis often requires toxic reagents. “Green” methods utilizing biopolymers offer a sustainable alternative. This study presents a novel synthesis of stable gold nanoparticles using a disulfide-crosslinked derivative of alginic acid (AA–S–S–AA) as both a reducing agent and stabilizer. The S–S-cross-linked alginate was synthesized with a degree of substitution of ~4.2% and reacted with HAuCl₄ in water at room temperature for just 10 min to give stable and polysaccharide in situ modified gold nanoparticles (AA-AuNPs). The resulting AA-AuNPs were characterized by a surface plasmon resonance peak at 539 nm and exhibited good colloidal stability over 14 days. Electron microscopy revealed spherical nanoparticles with a bimodal size distribution (10 nm and 75–100 nm) and a visible polysaccharide shell (5–9 nm), confirming effective stabilization. X-ray photoelectron spectroscopy confirmed the presence of metallic gold (Au⁰) and Au¹⁺. NMR analysis indicated the oxidation of disulfide groups to sulfonic acid during synthesis. The nanoparticles demonstrated a high negative zeta-potential of −53.9 mV, attributable to the polyanionic alginate corona, ensuring strong electrostatic stabilization. This work establishes sulfur-modified alginic acid as an efficient platform for the rapid synthesis of stable, hybrid nanoparticles for potential use in catalysis and biomedicine. Full article

Ionomers are promising materials because ionic interactions and their reversible clustering provide sensitivity to stimuli and facilitate energy dissipation, polymer miscibility, and ion transport. The existence of a wide variety of interacting ionic groups and their associated macromolecular structures provides the basis for considering the supramolecular organization of ionic polymeric materials as a factor determining the emergence of specific properties. The main structural elements of ionomers are ionic clusters, and the properties of ionomers are determined by their sizes and size distribution. Ionomers are attractive for use in composites, actuators, coatings, dyed textiles, adhesives, shape-memory and self-healing materials, water purification membranes, and ion-exchange membranes for fuel cells and batteries. This paper presents a review of the macromolecular structure and supramolecular organization of ionomers and their properties, depending on the basis of their ionic functionalization. The ionic functions of ionomers are determined primarily by the type of ion (cations or anions) that serves as the basis for their functionalization. Ionomers containing both anionic and cationic pendant ions are considered, with attention given to the influence of the nature of the counterions used on the properties of ionomers. Full article

Glucocorticoids (GCs) represent effective anti-cancer drugs for the treatment of hematological malignancies, but their clinical use is limited due to their multiple adverse effects. Selective glucocorticoid receptor agonists/modulators (SEGRAMs) modify glucocorticoid receptor (GR) function, shifting it towards therapeutically important transrepression and, therefore, could be safer alternative to GCs. Here we report on the biological activity of four novel glucocorticoid receptor (GR) ligands, derivatives of synephrine, a natural-origin molecule. We demonstrated the affinity of synephrine derivatives in silico and in vitro by molecular dynamics simulation and radioligand binding assay, correspondingly. Further, we tested the induction of apoptosis in cultured cells and cytotoxic effects in primary lymphoblasts from patients with acute lymphoblastic leukemia. Therapeutically important GR transrepression was evaluated by luciferase reporter assay and Q-PCR of transrepression marker genes, while GR transactivation associated with side effects was evaluated by Q-PCR analysis and by the level of GR phosphorylation at Ser211. Anti-cancer effects of the leader compound, 1-[4-(benzyloxy)phenyl]-2-(hexylamino)ethanol (10S-E2), were studied using a murine transplantable lymphoma P388 model. The potential of 10S-E2 to prevent the development of atrophic complication was evaluated using a murine model of glucocorticoid-induced osteoporosis. All studied synephrine derivatives demonstrated high GR affinity, with the IC₅₀ value of the most active derivative 10S-E2 being 0.56 µM; the effects on GR function were cell-type-specific. The leader compound, 10S-E2, revealed SEGRAM properties in vitro and demonstrated anti-cancer effects in vivo, inhibiting tumor growth by more than 60%. Although the anti-cancer effect of 10S-E2 was less pronounced than that of the reference drug dexamethasone, non-atrophogenic properties of 10S-E2 make this molecule an attractive candidate for long-term GR-associated therapies. Full article

Pipeline insulation is critical for energy-efficient building heating systems, as moisture ingress significantly degrades thermal performance and increases energy losses. This study experimentally evaluated how quality characteristics of mineral wool affect the thermal performance of pipe insulations (wired mats) at temperatures ranging from 20 °C to 85 °C with moisture content up to 12% by weight. Thermal conductivity measurements were performed on two representative samples using the “guarded hot pipe” and direct water injections. Thermal conductivity measurements confirmed the expected increase with rising temperature and moisture content for both samples. In a dry state, quality parameters have practically no effect on the thermal conductivity (0.036–0.041 W∙m⁻¹·K⁻¹). In a low-temperature regime, the inferior quality sample (Sample A) at a maximum moisture content of 12% exhibited thermal conductivity of 0.042 W∙m⁻¹·K⁻¹, and the sample with the best hydrophobic treatment (Sample B) had a thermal conductivity of 0.050 W∙m⁻¹·K⁻¹. At an elevated temperature at a moisture content of 12%, Sample A and Sample B had thermal conductivity of 0.077 W∙m⁻¹·K⁻¹, and 0.109 W∙m⁻¹·K⁻¹, respectively. The results suggest that highly hydrophobic materials are advantageous only in high-temperature applications where rapid moisture removal occurs after short-term ingress, providing critical data for optimizing insulation selection and improving energy conservation in heating networks. Full article

Gold nanoparticles (AuNPs) are of significant interest due to their unique properties and applications in biomedicine. While hyaluronic acid (HA) has been used to modify pre-formed AuNPs, its thiolated derivative (HA−SH) has been less explored for the direct synthesis and stabilization of AuNPs. This study investigates the use of thiolated hyaluronic acid as a key component in the synthesis of AuNPs. A series of HA-AuNPs (HA-AuNP1-4) were synthesized by reacting HA-SH with HAuCl₄ at different mass ratios. The resulting nanoparticles were characterized using UV-Vis spectroscopy, scanning/transmission electron microscopy (SEM/STEM), X-ray photoelectron spectroscopy (XPS), photon cross-correlation spectroscopy (PCCS), and zeta potential measurements. The chemical transformations of the thiol ligand were studied using NMR spectroscopy. The morphologies and sizes of AuNPs depended on the HA-SH-to-HAuCl₄ ratio, ranging from icosahedral and triangular particles (≥146 nm) to quasi-spherical particles with a bimodal distribution (6–7 nm and 45–60 nm). XPS confirmed the presence of metallic gold (Au⁰) and a Au−S bond, while NMR and XPS revealed the partial oxidation of thiol groups to sulfonic acid. Zeta potential measurements showed that lower HAuCl₄ concentrations resulted in higher negative charge (up to −41.5 mV), enhancing colloidal stability. This work demonstrates a versatile approach to the synthesis of hyaluronic acid-based gold nanomaterials with tunable properties for potential biomedical applications. Full article