Search Results (926)

Background/Objectives: Pharmacogenetic variability plays a crucial role in determining both the efficacy and toxicity of chemotherapy for gastrointestinal cancers. However, data on allele frequencies and their clinical relevance in Russian populations remain scarce. Methods: We conducted a prospective observational study of 412 patients with gastrointestinal malignancies between 2020 and 2023. Pharmacogenetic testing was performed prior to the initiation of chemotherapy using real-time allele-specific PCR and microarray hybridization technology. Polymorphisms in the DPYD, UGT1A1, CYP2C8, CYP3A5, GSTP1, ERCC1, XPC, CDA, MTHFR, TYMS, and SLC31A1 genes were analyzed. Results: The frequency of most variants was consistent with those reported in European populations, reflecting the ethnic proximity of the studied cohort. Several clinically relevant variants were identified: DPYD rs2297595 occurred more frequently than in European cohorts, and UGT1A1 rs8175347 was observed at a higher prevalence, underscoring the potential risk of irinotecan-related neutropenia and diarrhea. CYP2C8 rs10509681 was present at frequencies comparable to European populations and is associated with an increased risk of taxane-induced peripheral neuropathy. Other markers (GSTP1, ERCC1, CDA, SLC31A1, MTHFR, TYMS) demonstrated variable associations with chemotherapy efficacy and toxicity, consistent with findings from previous international studies. Conclusions: This study provides the first comprehensive description of pharmacogenetic polymorphisms in a Russian cohort of patients with gastrointestinal cancers. Our findings confirm the clinical importance of DPYD and UGT1A1 testing and highlight additional variants of potential interest. Full article

Diabetic nephropathy (DN) remains the leading cause of end-stage renal disease worldwide, with proximal tubular epithelial cells (PTECs) playing a central role in its pathogenesis. Under hyperglycemic conditions, PTECs drive a pathological triad of inflammation, apoptosis, and fibrosis. Recent advances reveal that these processes interact synergistically to form a self-perpetuating vicious cycle, rather than operating in isolation. This review systematically elucidates the molecular mechanisms underlying this crosstalk in PTECs. Hyperglycemia induces reactive oxygen species (ROS) overproduction, advanced glycation end products (AGEs) accumulation, and endoplasmic reticulum stress (ERS), which collectively activate key inflammatory pathways (NF-κB, NLRP3, cGAS-STING). The resulting inflammatory milieu triggers apoptosis via death receptor and mitochondrial pathways, while apoptotic cells release damage-associated molecular patterns (DAMPs) that further amplify inflammation. Concurrently, fibrogenic signaling (TGF-β1/Smad, Hippo-YAP/TAZ) promotes epithelial–mesenchymal transition (EMT) and extracellular matrix (ECM) deposition. Crucially, the resulting fibrotic microenvironment reciprocally exacerbates inflammation and apoptosis through mechanical stress and hypoxia. Quantitative data from preclinical and clinical studies are integrated to underscore the magnitude of these effects. Current therapeutic strategies are evolving toward multi-target interventions against this pathological network. We contrast the paradigm of monotargeted agents (e.g., Finerenone, SGLT2 inhibitors), which offer high specificity, with that of multi-targeted natural product-based formulations (e.g., Huangkui capsule, Astragaloside IV), which provide synergistic multi-pathway modulation. Emerging approaches (metabolic reprogramming, epigenetic regulation, mechanobiological signaling) hold promise for reversing fibrosis. Future directions include leveraging single-cell technologies to decipher PTEC heterogeneity and developing kidney-targeted drug delivery systems. We conclude that disrupting the inflammation–apoptosis–fibrosis vicious cycle in PTECs is central to developing next-generation therapies for DN. Full article

This study provides a comprehensive analysis of lemon peel (LP) combustion behaviour using combined physicochemical characterization and non-isothermal thermogravimetric kinetics. To achieve this, LP was characterized for its proximate and ultimate composition, with its structure analysed via FTIR, XRD, and SEM. Thermogravimetric analysis (TGA) was then performed at high heating rates (20–80 K min⁻¹) to investigate combustion stages, and kinetic and thermodynamic parameters were determined using six model-free and one model-fitting method. The results revealed a high heating value (23.02 MJ kg⁻¹) and high volatile matter (73.2 wt%), establishing LP’s significant energy potential. TGA displayed four distinct decomposition stages corresponding to dehydration, pectin/hemicellulose, cellulose, and lignin/char combustion. Kinetic analysis yielded activation energies that varied with conversion, peaking at approximately 304 kJ mol⁻¹, and a three-dimensional diffusion (D3) mechanism was identified as the rate-limiting step. In conclusion, while its high energy content and low nitrogen (1.26 wt%) and sulphur (0.20 wt%) content make LP an attractive low-emission biofuel, its viability is challenged by a high potassium concentration in the ash (34.8 wt% K₂O), posing a severe risk of slagging. This study provides the comprehensive combustion kinetic data for LP at high heating rates, which is essential for designing appropriate energy conversion technologies and ash management strategies. Full article

Edible insects represent an emerging and sustainable alternative in human nutrition, characterized by their high protein and fiber content, along with a lipid profile rich in unsaturated fatty acids. This study evaluated the technological feasibility and impact of incorporating Acheta domesticus powder (10% and 20% as a substitution of pork meat) into patties, assessing their proximate composition, physicochemical properties, texture profile (TPA), cooking characteristics, and sensory acceptance. Cricket powder (ADP) increased protein and fiber in the meat product, improved texture and reduced cooking losses. Reformulation with 20% substitution led to significant changes in composition, physicochemical properties, and texture and decreased sensory acceptance, while 10% substitution achieved higher sensory ratings with improved nutritional benefits. In conclusion, optimizing the color of these products is essential to enhance consumer acceptance and promote the development of novel formulations based on insect-derived alternative proteins. Full article

Small and medium-sized enterprises (SMEs) constitute the backbone of the EU economy, yet their uneven digital transformation raises challenges for competitiveness and territorial cohesion. This article examines the organizational and spatial aspects of SME digitalization across the European Union using Flash Eurobarometer 486 data and latent class analysis (LCA) combined with Bayesian multilevel multinomial regression. The results reveal four SME digitalization profiles—Digitally Conservative Backbone; Partially Digital and Upgrading; Digitally Advanced and Diversified; and Focused Digital Integrators—reflecting diverse adoption patterns of key technologies such as AI, big data and cloud computing. Digitalization is shaped by organizational factors (firm size, value chain integration, digital barriers) and territorial factors (urbanity, border proximity, national digital infrastructure as measured by the Digital Economy and Society Index, DESI). Contrary to linear modernization assumptions, digital adoption follows geographically embedded trajectories, with sectoral uptake occurring even in low-DESI or non-urban regions. These results challenge core–periphery models and highlight the significance of place-based innovation networks. The study contributes to modernization theory and regional innovation systems by showing that digital inequalities exist not only between countries but also within regions and among adoption profiles, emphasizing the need for nuanced, multi-level digital policy approaches across Europe. Full article

The aim of this retrospective clinical pilot study is to evaluate multiparametric ultrasound liver parenchyma assessments in the diagnosis of Osler’s disease, and to detect micro-shunts using SRCEUS with quantifications at the capillary level. Material/Method: All examinations were performed by an experienced examiner with a multi-frequency probe on a high-resolution matrix ultrasound device (SC 7-1U), convex probe (Mindray A 20), and were stored digitally in the PACS system. Vascular ultrasound was performed using colour-coded Doppler ultrasound (CCDS) and ultrasound microangiography (UMA). The recent M-Ref tool was utilised for the purpose of liver tissue characterisation, encompassing the domains of shear wave elastography, fat evaluation, and viscosity. Dynamic CEUS, HiFR CEUS, and SR CEUS were performed after the intravenous bolus injection of 1–2.4 mL of ultrasound contrast agent (SonoVue^®). Measurements of SR CEUS capillary changes were performed independently by PACS-stored digital cine loops up to 5 s. Results: In the context of angiomas or haemangiomas, the initial contrast enhancement of echogenic or almost echogenic foci within 25 s without late wash-out was observed in 5/10 cases. In the evaluation of microvasculature, the presence of capsule-proximal shunts in Osler’s disease was observed, resulting in the identification of increased numbers of dilated capillaries within both peripheral and central shunts. In the control group, general liver tissue changes (20 cases) were observed in instances of inflammation (3/20 cases), peripherally in 4/20 cases with micro-shunts in altered parenchyma. In the context of multiparametric ultrasound, 16 out of 30 cases exhibited elevated fibrosis values, with a maximum recorded as high as 1.7 m/s, and in 13 out of 30 cases, there was an increase in fat values up to 0.65 dB/cm/MHz, indicative of moderate steatosis. Additionally, in seven cases, there was an increase in viscosity values up to 2.7 Pa·s, suggesting reactive changes. Conclusions: Recent advancements in medical imaging technology, specifically SR CEUS contrast ultrasound imaging, have led to the development of novel diagnostic tools that facilitate the evaluation of tissue and haemodynamic changes, in addition to capillary alterations, associated with Osler’s disease. Full article

The precise analysis of protein interactions in their native cellular context and the sensitive quantification of protein abundance in biological fluids are both fundamental to understanding health and disease. Traditional methods for cellular imaging and biochemical quantification often face limitations in specificity, sensitivity, or the preservation of spatial information. The proximity ligation assay (PLA) is a versatile technological platform developed to overcome these challenges by converting protein recognition events into amplifiable DNA signals, thereby achieving exceptional sensitivity. This foundational principle has given rise to two major formats: in situ PLA (isPLA) and solution-phase PLA. In basic research, isPLA provides high-resolution visualization of protein–protein interactions (PPIs), post-translational modifications (PTMs), and subcellular architecture directly within fixed cells and tissues. In translational and clinical applications, solution-phase PLA enables the highly sensitive quantification of low-abundance biomarkers in liquid samples, which is critical for diagnostics and prognostics in fields such as oncology, neuroscience, and infectious diseases. This review discusses the foundational principles, development, and diverse applications of PLA platforms. We also highlight significant technological advancements, including the development of high-throughput formats, integration with advanced readouts, and the use of alternative affinity reagents. These innovations continue to transform PLA from a targeted validation method into a powerful and multifaceted platform for both fundamental systems biology and clinical diagnostics. Full article

Multi-unmanned aerial vehicle (UAV)-assisted communication is a critical technology for the low-altitude economy, supporting applications from logistics to emergency response. Semantic communication effectively enhances transmission efficiency and improves the communication performance of multi-UAV-assisted systems. Existing research on multi-UAV semantic communication networks predominantly assumes static ground devices, overlooking computation offloading and resource allocation challenges when ground devices are mobile. This overlooks the critical challenge of dynamically managing computation offloading and resources for mobile users, whose varying channel conditions and semantic compression needs directly impact system performance. To address this gap, this paper proposes a multi-UAV-assisted semantic communication model that novelly integrates user mobility with adaptive semantic compression, formulating a joint optimization problem for computation offloading and resource allocation. The objective is to minimize the maximum task processing latency through the joint optimization of UAV–device association, UAV trajectories, transmission power, task offloading ratios, and semantic compression depth. To solve this problem, we design a MAPPO-APSO algorithm integrating alternating iteration, multi-agent proximal policy optimization (MAPPO), and adaptive particle swarm optimization (APSO). Simulation results demonstrate that the proposed algorithm reduces the maximum task latency and system energy consumption by up to 20.7% and 16.1%, respectively, while maintaining transmission performance and outperforming benchmark approaches. Full article

Cold-ripened fish marinades, produced mainly from Atlantic herring, represent one of the major seafood products in Northern and Central Europe. Because the shelf-life of these mildly acidified, salty products rarely surpasses 4 weeks, more than half of the commercial lots contain the preservatives sodium benzoate (E211) and potassium sorbate (E202). However, the broader technological consequences of such additives remain poorly documented. This study evaluated the impact of 0.25 (w/w) benzoate + 0.10 g/100 g sorbate on the quality of industrial-scale marinades (200 kg fish; 7 d, 4 ± 1 °C). Physicochemical traits (mass loss, pH, proximate composition, salt content, colour, and texture), enzymatic indices of ripening (cathepsins, amino-peptidases, and TCA soluble nitrogen fractions), lipid oxidation, microbial growth, and sensory attributes were analyzed. Preservatives caused only marginal changes in pH and proximate composition (0.3–3.4% w/w differences) but markedly suppressed proteolysis. Free amino acid and peptide fractions in muscle decreased by 6.0% and 8.8%, in parallel to 45% and 22% reductions in leucine- and alanine-amino-peptidase activities in muscle. In the marinating brine, the levels of total nitrogen, peptides, and free amino acids were also lower in the samples with preservatives, confirming that sodium benzoate and potassium sorbate slowed down the enzymatic ripening of the marinades. Concomitantly, peroxide, p-anisidine, and TOTOXs increased by up to 9.4, 71.3, and 33.7%, respectively, indicating accelerated lipid oxidation despite the chelating capacity of benzoate/sorbate acids. Overall sensory acceptability declined slightly (−0.15 points on a five-point scale), mainly owing to chemical off-flavours and lower juiciness. Microbial counts remained <1.0 log CFU/g in the preservative batch versus 2.1 log in the control. Benzoate–sorbate combinations effectively stabilized the microbiota of marinated herring without appreciably altering basic physicochemical traits, but they retard enzymatic ripening, diminish antioxidant peptide pools, and thereby promote lipid oxidation—collectively lowering the nutritional value. The data supports a cautious, minimal-use approach to application of chemical preservatives in cold-ripened fish products. Full article

Information and communication technology (ICT) infrastructure can facilitate urban–rural integration. However, few studies have explored the role of virtual agglomeration in the mechanisms underlying this process, which can enable geographically dispersed market participants (both urban and rural) to achieve proximity in network space through digital connectivity provided by ICT. This study uses the PLS-SEM method to empirically analyzes the relationships among ICT infrastructure, virtual agglomeration, and urban–rural integration based on data obtained from 31 provincial-level regions in China from 2012 to 2022. The results indicate that: (1) ICT infrastructure can promote urban–rural integration. (2) Virtual agglomeration plays a significant mediating role in the relationship between ICT infrastructure and urban–rural integration. In relatively developed eastern China, virtual agglomeration fully mediates the impact of ICT infrastructure on urban–rural integration. (3) Other complementary infrastructures—including transport and education—have positive moderating effects on the process of virtual agglomeration facilitated by ICT. This study advances the understanding of ICT’s effects on regional development from the perspective of employing a new form of spatial agglomeration (i.e., virtual agglomeration). Meanwhile, this study indicates that in order to address the global challenge of urban–rural divide, it is necessary to strengthen the development of ICT infrastructure in remote rural areas, while developing complementary infrastructure such as transportation or education in alignment with regional characteristics. Full article

As Earth Pressure Balance (EPB) shield machine crossed with steep slopes beneath an existing highway in sandstone–mudstone alternating strata, case studies of changes in vertical displacement, settlement trough evolution, and tunnel stress induced by shield tunnel construction were investigated. The quality of synchronous grouting was evaluated using ground penetrating radar (GPR) technology. The results showed that highway settlement could be categorized into four stages: initial settlement, uplift, secondary settlement, and stabilization. The secondary settlement caused by shield tail detachment was significantly greater than the initial settlement induced by distant shield construction. The settlement trough evolved throughout construction; the maximum settlement point shifted from the tunnel centerline but it consistently remained within 3 m. During the early phase of shield tail detachment, the circumferential stress of shield tunnel changed rapidly. The circumferential stress was primarily compressive, tensile stress was observed at some monitoring points. The tensile stress at the monitoring points gradually transitioned to compressive stress. After the tunnel undercrossed, the circumferential stress gradually stabilized. The GPR detection revealed that in groundwater-rich strata, poor grouting quality areas were prone to appear at the tunnel crown, while grouting quality in other areas performed better. This engineering case can serve as a positive reference for similar EPB shield tunnels passing in close proximity beneath existing highways. Full article

Object detection is a critical technology for smart city development. As request volumes surge, inference is increasingly offloaded from centralized clouds to user-proximal edge sites to reduce latency and backhaul traffic. However, heterogeneous workloads, fluctuating bandwidth, and dynamic device capabilities make offloading and scheduling difficult to optimize in edge environments. Deep reinforcement learning (DRL) has proved effective for this problem, but in practice, it relies on manually engineered reward functions that must be redesigned whenever service objectives change. To address this limitation, we introduce an LLM-driven framework that retargets DRL policies for edge object detection directly through natural language instructions. By leveraging understanding of the text and encoding capabilities of large language models (LLMs), our system (i) interprets the current optimization objective; (ii) generates an executable, environment-compatible reward function code; and (iii) iteratively refines the reward via closed-loop simulation feedback. In simulations for a real-world dataset, policies trained with LLM-generated rewards adapt from prompts alone and outperform counterparts trained with expert-designed rewards, while eliminating manual reward engineering. Full article

Non-mechanical contact distance measurement solutions are becoming more and more necessary in various industries, including building monitoring, automotive, and aviation industries. Inductive proximity sensor (IPS) technology is becoming a more popular solution in the field of short distances. Because of its small size, dependability, and measurement capabilities, IPS is a good option. Separate circuits are used in the classical structures to generate the excitation signal for the sensor coil and measure the response signal. The response signal’s amplitude is typically measured. This article proposes an IPS model that uses frequency response as its basis for operation. A microcontroller and embedded technology are used to implement a small IPS structure. This includes the circuit for determining distance, as well as the signal generator used to excite the sensor coil. In essence, an LC circuit is employed, which at the unit step has a damped oscillatory response by nature. Periodically injecting energy into the LC circuit, however, causes it to enter a persistent oscillatory state. The full experimental model is implemented and presented in the article, illustrating how the distance can be measured with a 33 µm accuracy within the 10 mm range with the help of the nonlinear relationship between frequency and distance and the linear drift of frequency with temperature. Full article

Edge computing networks represent an emerging technological paradigm that enhances real-time responsiveness for mobile devices by reallocating computational resources from central servers to the network’s edge. This shift enables more efficient computing services for mobile devices. However, deploying computing services on inappropriate edge nodes can result in imbalanced resource utilization within edge computing networks, ultimately compromising service efficiency. Consequently, effectively leveraging the resources of edge computing devices while minimizing the energy consumption of terminal devices has become a critical issue in resource scheduling for edge computing. To tackle these challenges, this paper proposes a resource scheduling algorithm for edge computing networks based on multi-objective optimization. This approach utilizes the entropy weight method to assess both dynamic and static metrics of edge computing nodes, integrating them into a unified computing power metric for each node. This integration facilitates a better alignment between computing power and service demands. By modeling the resource scheduling problem in edge computing networks as a multi-objective Markov decision process (MOMDP), this study employs multi-objective reinforcement learning (MORL) and the proximal policy optimization (PPO) algorithm to concurrently optimize task transmission latency and energy consumption in dynamic environments. Finally, simulation experiments demonstrate that the proposed algorithm outperforms state-of-the-art scheduling algorithms in terms of latency, energy consumption, and overall reward. Additionally, it achieves an optimal hypervolume and Pareto front, effectively balancing the trade-off between task transmission latency and energy consumption in multi-objective optimization scenarios. Full article

Advances in sensor technology have significantly improved the efficiency and precision of agricultural spraying. Unmanned aerial vehicles (UAVs) are widely utilized for applying plant protection products (PPPs) and fertilizers, offering enhanced spatial control and operational flexibility. This study evaluated the performance of an autonomous UAV-based precision spraying system that applies variable rates based on zone levels defined in a prescription map. The system integrates real-time kinematic global navigation satellite system positioning with a proximity-triggered spray algorithm. Field experiments on a rice field were conducted to assess spray accuracy and fertilization efficacy with liquid fertilizer. Spray deposition patterns on water-sensitive paper showed that the graded strategy distinguished among zone levels, with the highest deposition in high-spray zones, moderate in medium zones, and minimal in no-spray zones. However, entry and exit deviations—used to measure system response delays—averaged 0.878 m and 0.955 m, respectively, indicating slight lags in spray activation and deactivation. Fertilization results showed that higher application levels significantly increased the grain-filling rate and thousand-grain weight (both p < 0.001), but had no significant effect on panicle number or grain count per panicle (p > 0.05). This suggests that increased fertilization primarily enhances grain development rather than overall plant structure. Overall, the system shows strong potential to optimize inputs and yields, though UAV path tracking errors and system response delays require further refinement to enhance spray uniformity and accuracy under real-world applications. Full article