Search Results (4,058)

Background/Objectives: Paclitaxel (PTX) is widely used in the treatment of a variety of solid tumours due to its broad-spectrum anti-tumour activity, but its use in brain gliomas is limited by insufficient blood–brain tumour barrier (BBTB) penetration and systemic toxicity. The aim of this study was to develop a Solutol HS-15-based micellar nanoparticle (PSM) to enhance the brain glioma targeting of PTX and reduce toxicity. Methods: PSMs were prepared by solvent injection and characterised for particle size, encapsulation rate, haemolysis rate and in vitro release properties. A C6 in situ glioma mouse model was used to assess the brain targeting and anti-tumour effects of the PSM by in vivo imaging, tissue homogenate fluorescence analysis and bioluminescence monitoring. Meanwhile, its safety was evaluated by weight monitoring, serum biochemical indexes and histopathological analysis. Results: The particle size of PSMs was 13.45 ± 0.70 nm, with an encapsulation rate of 96.39%, and it demonstrated excellent cellular uptake. In tumour-bearing mice, PSMs significantly enhanced brain tumour targeting with a brain drug concentration 5.94 times higher than that of free PTX. Compared with Taxol, PSMs significantly inhibited tumour growth (terminal luminescence intensity <1 × 10⁶ p/s/cm²/Sr) and did not cause significant liver or kidney toxicity or body weight loss. Conclusions: PSMs achieve an efficient accumulation of brain gliomas through passive targeting and EPR effects while significantly reducing the systemic toxicity of PTX. Its simple preparation process and excellent therapeutic efficacy support its use as a potential clinically translational candidate for glioma treatment. Full article

Semi-supervised object detection (SSOD) in remote sensing is challenged by the accumulation of pseudo-label errors in complex scenes with dense objects and high intra-class variability. While teacher–student frameworks enable learning from unlabeled data, erroneous pseudo-labels such as false positives and missed detections can be reinforced over time, which degrades model performance. To address this issue, we propose the Error-Mitigation Teacher (EMT), a unified framework designed to suppress error propagation during SSOD training. EMT consists of three lightweight modules. First, the Adaptive Pseudo-Label Filtering (APLF) module removes noisy pseudo boxes via a second-stage RCNN and adjusts class-specific thresholds through dynamic confidence filtering. Second, the Confidence-Based Loss Reweighting (CBLR) module reweights training loss by evaluating the teacher model’s ability to reconstruct its own pseudo-labels, using the resulting loss as an indicator of label reliability. Third, the Enhanced Supervised Learning (ESL) module improves class-level balance by adjusting supervised loss weights according to pseudo-label statistics. EMT demonstrates consistent performance gains over representative state-of-the-art SSOD methods on DOTA, DIOR, and SSDD datasets. Notably, EMT achieves a 2.9% absolute mAP₅₀ improvement on DIOR using only 10% of labeled data, without incurring additional inference cost. These results highlight EMT’s effectiveness in improving SSOD for remote sensing. Full article

Existing Simultaneous Localization and Mapping (SLAM) algorithms provide precise local pose estimation and real-time scene reconstruction, widely applied in autonomous navigation for land vehicles. However, the odometry of SLAM algorithms exhibits localization drift and error divergence over long-distance operations due to the lack of inherent global constraints. In this paper, we propose a real-time geo-localization method for land vehicles, which only relies on a LiDAR-inertial-visual SLAM (LIV-SLAM) and a referenced image. The proposed method enables long-distance navigation without requiring GPS or loop closure, while eliminating accumulated localization errors. To achieve this, the local map constructed by SLAM is real-timely projected onto a downward-view image, and a highly efficient cross modal matching algorithm is proposed to estimate the global position by aligning the projected local image to a geo-referenced satellite image. The cross-modal algorithm leverages dense texture orientation features, ensuring robustness against cross-modal distortion and local scene changes, and supports efficient correlation in the frequency domain for real-time performance. We also propose a novel adaptive Kalman filter (AKF) to integrate the global position provided by the cross-modal matching and the pose estimated by LIV-SLAM. The proposed AKF is designed to effectively handle observation delays and asynchronous updates while simultaneously rejecting the impact of erroneous matches through an Observation-Aware Gain Scaling (OAGS) mechanism. We verify the proposed algorithm through R³LIVE and NCLT datasets, demonstrating superior computational efficiency, reliability, and accuracy compared to existing methods. Full article

A nanoparticle formulation was generated from distiller dried grains with solubles (DDGS), and its effect on the production of anthraquinones (AQs) was evaluated on Rubia tinctorum hairy roots. The DDGS material was washed with water and ethyl acetate to remove mainly the soluble organic/inorganic molecules and reduce the fat content, respectively, followed by an alkaline treatment to remove the polysaccharides. The resulting alkaline solutions were then lyophilized and redispersed in deionized water to generate a monodispersed nanoparticulate formulation (DDGS-NP) with a hydrodynamic diameter and zeta potential of 227 ± 42 nm and −53 ± 7 mV, respectively. The formulation demonstrated good colloidal stability over time, and sterilized DDGS-NPs maintained comparable physicochemical properties. The nanoparticles were enriched in protein fractions, unsaturated fatty acids, and orthophosphate anion components from DDGS, as determined by solid-state Nuclear Magnetic Resonance (NMR), X-ray photoelectron spectroscopy (XPS), organic elemental analysis (OEA), and inductively coupled plasma optical emission spectrometry (ICP-OES) techniques. The DDGS-NPs were tested at different concentrations on Rubia tinctorum hairy roots, in comparison to or in combination with methyl jasmonate (MeJ), for their capacity to induce the production of AQs. All DDGS-NP concentrations increased the production of specific AQs to 7.7 (100 mg L⁻¹), 7.8 (200 mg L⁻¹), and 9.3 µmol/gFW (500 mg L⁻¹), with an extracellular AQ accumulation of 18 µM for the highest DDGS-NP concentration, in comparison with the control hairy roots (~2 µM AQ). The plant growth was not affected at any of the tested nanoparticle concentrations. Interestingly, the combination of DDGS-NPs and MeJ resulted in the highest extracellular AQ accumulation in R. tinctorum root cultures. Full article

Aftershocks are inevitable phenomena following a mainshock, especially after a major earthquake. However, the cumulative damage caused by aftershocks and its impact on structural performance evaluation has only recently received significant attention. This study explores the effects of mainshock–aftershock (MS–AS) sequences, including multiple consecutive aftershocks, acting on 3D steel moment-resisting frame structures. Following nonlinear time history analysis, several fundamental variables such as residual interstory drift, maximum displacement, plastic hinge formation, and base shear are evaluated to examine cumulative damage. In this context, the findings depicted in terms of aftershocks play a significant role in exacerbating plastic deformations and damage accumulation in steel moment frames. Subsequently, to mitigate cumulative damage on steel moment frames, retrofitting strategies were implemented. Retrofitting strategies effectively reduce cumulative damage and improve seismic resilience under multiple earthquake events. This research highlights the limitations of single-event seismic assessments and the need to incorporate sequential earthquake effects in design and retrofit practices. Furthermore, it provides new insights into mitigating further damage by retrofitting existing structures under multiple earthquakes. Full article

Federated learning (FL) enables multiple participants to collaboratively train models while efficiently mitigating the issue of data silos. However, large-scale heterogeneous data distributions result in inconsistent client objectives and catastrophic forgetting, leading to model bias and slow convergence. To address the challenges under non-independent and identically distributed (non-IID) data, we propose DPAO-PFL, a Dynamic Parameter-Aware Optimization framework that leverages continual learning principles to improve Personalized Federated Learning under non-IID conditions. We decomposed the parameters into two components: local personalized parameters tailored to client characteristics, and global shared parameters that capture the accumulated marginal effects of parameter updates over historical rounds. Specifically, we leverage the Fisher information matrix to estimate parameter importance online, integrate the path sensitivity scores within a time-series sliding window to construct a dynamic regularization term, and adaptively adjust the constraint strength to mitigate the conflict overall tasks. We evaluate the effectiveness of DPAO-PFL through extensive experiments on several benchmarks under IID and non-IID data distributions. Comprehensive experimental results indicate that DPAO-PFL outperforms baselines with improvements from $5.41\%$ to $30.42\%$ in average classification accuracy. By decoupling model parameters and incorporating an adaptive regularization mechanism, DPAO-PFL effectively balances generalization and personalization. Furthermore, DPAO-PFL exhibits superior performance in convergence and collaborative optimization compared to state-of-the-art FL methods. Full article

Leeches hold significant medical and pharmaceutical value for antithrombotic treatments, yet their genetic diversity patterns remain poorly understood. We performed population genetic analyses on seven Hirudinaria manillensis populations from southern China using mitochondrial protein-coding genes (MitPCGs). Complete sequences of all 13 MitPCGs were obtained from 74 individuals. Haplotype diversity exhibited a logarithmic relationship with the gene length (R² = 0.858, p < 0.001), while nucleotide diversity showed a near-perfect alternating low-high pattern (Z = 2.938, p = 0.003). Concatenated sequence analyses indicated high haplotype diversity (>0.5) and low nucleotide diversity (<0.005) across all populations, suggesting a historical bottleneck followed by rapid expansion and mutation accumulation. The haplotype network, haplotype phylogenetics, and genetic structure analyses revealed moderate genetic differentiation across populations, dividing them into three clades: a basal Yunnan population (YNHH), sub-basal Guangxi populations (GXGG, GXLZ, and GXYL), and distal Guangdong/Hainan populations (GDMM, GDZJ, and HNDA). Analysis of historical population demography revealed five phases from ancient to recent times (P1–5): growth, prolonged stability, rapid decline, rapid growth, and secondary decline. These phases correlate strongly with past climatic events, demonstrating that glacial–interglacial cycles profoundly impacted the leech’s effective population size. This study provides a key scientific basis for H. manillensis resource conservation and utilization. Full article

Even for the strongest human being, maintaining an elevated arm position for an extended duration represents a significant challenge, as fatigue inevitably accumulates over time. The physical strain is further intensified when the individual is engaged in repetitive tasks, particularly those involving the use of tools or heavy equipment. Such activities increase the probability of developing muscle fatigue or injuries due to overuse or improper posture. Over time, this can result in the development of chronic conditions, which may impair the individual’s ability to perform tasks effectively and potentially lead to long-term physical impairment. Exoskeletons play a transformative role by reducing the perceived load on the muscles and providing mechanical support, mitigating the risk of injuries and alleviating the physical burden associated with strenuous activities. In addition to injury prevention, these devices also promise to facilitate the rehabilitation of individuals who have sustained musculoskeletal injuries. This document examines the various types of exoskeletons, investigating their design, functionality, and applications. The objective of this study is to present a comprehensive understanding of the current state of these devices, highlighting advancements in the field and evaluating their real-world impact. Furthermore, it analyzes the crucial insights obtained by other researchers, and by summarizing these findings, this work aims to contribute to the ongoing efforts to enhance exoskeleton performance and expand their accessibility across different sectors, including agriculture, healthcare, industrial work, and beyond. Full article

Objectives: Non-cystic fibrosis bronchiectasis (BE) is a chronic airway disease with increasing prevalence, reduced quality of life, and increased mortality. Inhaled corticosteroids (ICS) are used in BE despite limited evidence of effect on lung function parameters. ICS may increase the risk of Staphylococcus aureus (S. aureus) infections in patients with BE, but this is unexplored. We examined the association between ICS use prior to BE diagnosis at different doses and the risk of S. aureus isolation in patients with BE. Methods: We conducted a national register-based cohort study including Danish patients with a BE diagnosis code between 2001 and 2018 with a 1-year follow-up time from the date of diagnosis. ICS exposure was categorized based on accumulated prescriptions redeemed 365 days before BE diagnosis and divided into none, low, moderate, or high use based on clinically relevant doses. A cause-specific Cox proportional hazards regression model was used to estimate the risk of S. aureus isolation. A sensitivity analysis, an inverse probability of treatment weighted model (IPTW), was performed. Results: A total of 5093 patients were included in this study. S. aureus was isolated in 156 patients (3.1%). High-dose ICS was associated with an increased risk of S. aureus isolation, HR 3.81 (95% CI 2.51; 5.79). No association for low or moderate use was found, low-dose HR 1.22 (95% CI 0.77; 1.93), and moderate-dose HR 1.24 (95% CI 0.72; 2.16). IPTW analysis yielded similar results. Conclusions: High-dose ICS use in patients with BE was associated with an increased risk of S. aureus isolation. ICS should be used cautiously in patients with BE. Full article

The aim of the article is to highlight the increasing environmental burden on aquatic ecosystems in Slovakia due to continuous pollution from municipal, industrial and agricultural sources. Laboratory analyses have shown alarming exceedance of the limit values of contaminants, with nitrate nitrogen (NO₃⁻) reaching 5.8 mg/L compared to the set limit of 2.5 mg/L and phosphorus concentrations exceeding the permissible values by a factor of five, thereby escalating the risk of eutrophication and loss of ecological stability of the aquatic ecosystem. The accumulation of heavy metals is also a problem—lead (Pb) concentrations reach up to 9.7 μg/L, which exceeds the safe limit by a factor of ten. Despite the measures implemented, such as scum barriers, there is continuous contamination of the aquatic environment, with illegal waste dumps and uncontrolled runoff of agrochemicals playing a significant role. The research results underline the critical need for a more effective environmental policy and more rigorous monitoring of toxic substances in real time. These findings highlight not only the urgency of more effective environmental policy and stricter real-time monitoring of toxic substances, but also the necessity of integrating environmental logistics into the design of sustainable solutions. Logistical approaches including the optimization of waste collection, coordination of stakeholders and creation of infrastructural conditions can significantly contribute to reducing environmental burdens and ensure the continuity of environmental management in ecologically sensitive areas. Full article

High concentrations of vicine and convicine (v-c) in faba beans can trigger favism in susceptible humans, posing a significant barrier to the broader adoption of faba beans as a food source. While plant breeding and various post-harvest processing methods have been adopted to reduce v-c levels, there is limited understanding of how agronomic practices may assist in reducing v-c levels. This study investigated the effect of sowing time (TOS), soil type, and genotype on v-c levels in faba beans. Twelve faba bean genotypes were evaluated across multiple field sites by applying two sowing times and two diverse soil types. The v-c content was quantified using established chromatographic techniques. Genotypes were identified as the most major factor affecting v-c levels, with significant variation observed in mean vicine and convicine contents. Sowing time also had a significant impact (p < 0.01), with lower v-c levels observed in TOS 1 compared to TOS 2. This reduction may be due to a longer plant development period and extended seed desiccation in TOS 1. Soil conditions, likely linked to nutritional factors, significantly influenced vicine concentrations (p < 0.05) but did not influence convicine levels (p > 0.05). These findings highlight the importance of agronomy practices, such as optimal sowing time, soil nutrition, and moisture management, in minimizing v-c levels; the most effective strategy remains the development of low v-c genotypes combined with farming practices that naturally suppress v-c accumulation. Full article

Temperature is the most critical factor in fish preservation. Superchilled storage represents a novel technology that effectively retards quality deterioration in aquatic products. This study investigated the flavor variation patterns and deterioration mechanisms in 16 northern pike (Esox lucius) samples during superchilled storage (−3 °C) based on analysis using gas chromatography-ion mobility spectrometry (GC-IMS) and ultra-performance liquid chromatography–quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS). The results indicate that GC-MS analysis identified 25 key volatile flavor compounds. These comprised seven ketones, thirteen alcohols, aldehydes including 2-methylbutanal, esters such as 2-heptyl acetate and methyl butyrate, as well as nitrogen-containing compounds, exemplified by pyrazines and indole. Non-targeted metabolomics further revealed four pivotal metabolic pathways, glycerophospholipid metabolism, purine metabolism, the pentose phosphate pathway, and arginine biosynthesis. These metabolic pathways were found to regulate flavor changes through modulation of lipid oxidation, nucleotide degradation, and amino acid metabolism. Notably, the arginine biosynthesis pathway exhibited significant correlations with the development of characteristic cold-storage off-flavors, mediated by glutamate accumulation and fumarate depletion. This investigation provided a theoretical foundation for optimizing preservation strategies in cold-water fish species at the molecular level. Full article

Intracerebral hemorrhage (ICH), a severe stroke subtype common in the elderly, often results in high morbidity and mortality, with limited treatment options for long-term recovery. While glial scar formation is increasingly recognized as key to central nervous system (CNS) repair, its role and characteristics in the aging brain post-ICH remain unclear. This study investigated glial scar formation after ICH (100 μL autologous blood injected into the right basal ganglia model) in aged Fischer 344 rats and assessed the effects of deferoxamine (DFX) treatment. Histological and immunohistochemical analyses were conducted on days 7, 28, and 60 post-ICH using cell-specific and iron-related markers, with DFX administered at 100 mg/kg daily for 14 days in separate groups. Over time, the lesion core showed increased hemosiderin accumulation and astrogliosis. By day 60, the area of astrogliosis corresponded to an area with persistent neuronal loss (DARPP-32-negative). Glial composition shifted from microglia dominance on day 28 to astrocyte predominance by day 60. DFX treatment reduced iron deposition, astrogliosis, and DARPP-32-negative regions while enhancing oligodendrocyte presence. Iron-related markers (HO-1, ferritin, Perls’ staining) and PDGFRβ-positive fibrotic cells were concentrated in the scar core. These findings provide novel insights into scar formation after ICH in aged rats and suggest DFX as a potential therapy to improve outcomes in elderly stroke patients. Full article

Blood is a widely used sample for diagnosing diseases such as malaria and diabetes. While diagnostic techniques have advanced, sample preparation remains labor-intensive, requiring steps like mixing and centrifugation. Microfluidic technologies have automated parts of this process, including cell lysis, yet challenges persist. Electrical lysis offers a chemical-free, continuous approach, but lysing small cells like red blood cells requires high electric fields, which can damage electrodes and cause system failures. Here, we present a microfluidic device utilizing ion concentration polarization (ICP) for rapid blood cell lysis at 75 V. Fluorescence imaging confirmed the formation of an ion depletion region near the Nafion^® nanochannel membrane, where the electric field was concentrated across the entire microchannel width. This phenomenon enabled the efficient trapping and lysis of blood cells under these conditions. Continuous blood injection achieved a lysis time of 0.3 s with an efficiency exceeding 99.4%. Moreover, lysed cell contents accumulated near the Nafion membrane, forming a concentrated lysate. This approach eliminates the need for high-voltage circuits or chemical reagents, offering a simple yet effective method for blood cell lysis. The proposed device is expected to advance lab-on-a-chip and point-of-care diagnostics by enabling rapid and continuous sample processing. Full article

The air quality within urban public transport is a critical determinant of passenger health. In the crowded and poorly ventilated cabins of Almaty’s metro, buses, and trolleybuses, concentrations of CO₂ and PM_2.5 often accumulate, elevating the risk of respiratory and cardiovascular diseases. This study investigates the air quality along three of the city’s busiest transport corridors, analyzing how the concentrations of CO₂, PM_2.5, and PM₁₀, as well as the temperature and relative humidity, fluctuate with the passenger density and time of day. Continuous measurements were collected using the Tynys mobile IoT device, which was bench-calibrated against a commercial reference sensor. Several machine learning models (logistic regression, decision tree, XGBoost, and random forest) were trained on synchronized environmental and occupancy data, with the XGBoost model achieving the highest predictive accuracy at 91.25%. Our analysis confirms that passenger occupancy is the primary driver of in-cabin pollution and that these machine learning models effectively capture the nonlinear relationships among environmental variables. Since the surveyed routes serve Almaty’s most densely populated districts, improving the ventilation on these lines is of immediate importance to public health. Furthermore, the high-temporal-resolution data revealed short-term pollution spikes that correspond with peak ridership, advancing the current understanding of exposure risks in transit. These findings highlight the urgent need to combine real-time monitoring with ventilation upgrades. They also demonstrate the practical value of using low-cost IoT technologies and data-driven analytics to safeguard public health in urban mobility systems. Full article