Search Results (1,217)

Bisphenol AF (BPAF) exposure is increasingly linked to metabolic disorders, yet the molecular initiating events (MIE) and key events (KE) leading to hepatic steatosis remain unclear. We constructed an adverse outcome pathway (AOP) to mechanistically connect BPAF-triggered macrophage–hepatocyte crosstalk to liver fat accumulation. Male C57BL/6 mice received daily oral gavage of 0, 0.5, 4, or 32 mg kg⁻¹ BPAF for 90 d, and Transwell co-cultures of RAW264.7 macrophages and AML12 hepatocytes were used for in vitro validation. Targeted metabolomics, western blotting, and lipid staining quantified succinate, pathway proteins, and steatosis. BPAF dose-dependently increased serum succinate (BMD = 6901.95 nM) and hepatic triglyceride (TG) (BMD = 874.26 nM). Cryo-EM docking revealed BPAF binding to SUCNR1 at 2.9 Å, disrupting the inactive-state conformation. In co-culture, BPAF-exposed macrophages released succinate that bound hepatocyte SUCNR1, suppressed Akt phosphorylation, and activated JNK. These KEs led to a 40% increase in lipid droplets and elevated TG, total cholesterol (TC), and free fatty acids (FFA) without liver weight gain. We propose the first AOP for BPAF-induced hepatic steatosis: BPAF–SUCNR1 binding (MIE) → macrophage succinate release (KE1) → SUCNR1-mediated Akt inhibition/JNK activation (KE2–4) → hepatic lipid accumulation (KE5) → steatosis (AO). These findings provide mechanistic insight for chemical risk assessment of BPAF and structurally related bisphenols. Full article

Background: Cryopreservation of hematopoietic stem cells (HSCs) at −80 °C using uncontrolled-rate freezing is frequently employed in resource-constrained settings, yet concerns remain regarding long-term viability and clinical efficacy. Reliable post-thaw assessment is essential to ensure graft quality and engraftment success. Methods: This single-center, retrospective study evaluated 72 cryopreserved stem cell products from 25 patients stored at −80 °C for a median of 868 days. Viability was assessed using both acridine orange (AO) staining and 7-AAD (7-aminoactinomycin D) flow cytometry at three time points: collection (T0), pre-infusion (T1), and delayed post-thaw evaluation (T2). Associations between viability loss, storage duration, and clinical engraftment outcomes were analyzed. Results: Median post-thaw viability remained high (94.8%) despite a moderate time-dependent decline (~1.02% per 100 days; R² = 0.283, p < 0.001). Mean viability loss at T2 was 9.2% (AO) and 6.6% (flow cytometry). AO demonstrated greater sensitivity to delayed degradation, with a significant difference between methods (p < 0.001). Engraftment kinetics were preserved in most patients, with neutrophil and platelet recovery primarily influenced by disease type rather than product integrity. Notably, storage duration and donor age were not significantly associated with engraftment outcomes or CD34⁺ cell dose. Conclusions: Long-term cryopreservation at −80 °C maintains HSC viability sufficient for durable engraftment, despite gradual decline. While transplant outcomes are primarily dictated by disease biology and remission status, AO staining provides enhanced sensitivity for detecting delayed cellular damage. Notably, our viability-loss model offers a practical framework for predicting product quality, potentially supporting graft selection and clinical decision-making in real-world, resource-constrained transplant settings. Full article

Background: Pilon fractures are severe distal tibia injuries from high-energy trauma, often involving joint and soft tissue damage. Despite surgical advances, long-term outcomes remain poor. This study compared quality of life and functional limitations after surgical treatment of pilon versus tibial shaft fractures using validated PROMs. Methods: This case–control study was conducted at a Level I Trauma Center. Between 2016 and 2019, 84 patients with lower leg fractures were included: 38 pilon and 46 tibial shaft fractures. Inclusion criteria were AO type 42 or 43 fractures and follow-up of ≥24 months; exclusion criteria were polytrauma (ISS > 15), ASA ≥ 3, and incomplete consent. Outcomes were assessed with SF-12, EQ-5D-5L, and VAS-FA. Data were collected 36–48 months postoperatively. Analyses included t-tests, chi-square tests, linear regression. Results: Patients with pilon fractures had significantly poorer physical quality of life than tibial shaft fractures (SF-12 physical: 39 vs. 42, p < 0.05). Mental quality of life showed no significant difference. EQ-5D-5L scores were lower in the pilon group (70% vs. 79%). VAS-FA indicated higher pain and reduced function (total: 64 vs. 76, p = 0.009). Rehabilitation duration correlated with improved VAS outcomes in pilon fractures (p = 0.008), while physiotherapy reduced pain in tibial shaft fractures (p = 0.030). Conclusions: Pilon fractures substantially impair physical quality of life and long-term function, while mental well-being remains unaffected. PROMs provide insights beyond radiological findings and should be integrated into follow-up. Further multicenter studies are required to validate these results and optimize rehabilitation strategies. Full article

Biomass burning in the Amazon region, especially during the dry season, generates aerosol dispersion events across the southern part of the continent, with impacts observable thousands of kilometers from the emission source. This study presents a long-range aerosol transport case from September 2024, in which smoke aerosols from forest fires in the central Amazon reached southeastern and southern Brazil, affecting the air quality in distant areas such as São Paulo and São Martinho. The event was simulated using the Weather Research and Forecasting model with Chemistry (WRF-Chem), configured with the MOZCART chemical mechanism, combined with MERRA-2 reanalysis data and by using the 3BEM biomass burning emission inventory. Satellite datasets from MODIS and MERRA-2 reanalysis were used to evaluate the model’s performance. The results indicate that the South American Low-Level Jet (SALLJ) played a key role in transporting carbonaceous aerosols over long distances. The model successfully captured the spatial and temporal evolution of the aerosol plume and its impacts, although it tended to underestimate aerosol optical depth (AOD) values compared with satellite observations. This study highlights the WRF-Chem’s capability to simulate extreme smoke transport events in South America and supports its potential application in forecasting and air quality assessments. Full article

Aerosols from natural and anthropogenic sources exert significant yet highly variable influences on the Earth’s radiative balance characterized by pronounced spatial and temporal heterogeneity. Accurate quantification of these effects is crucial for enhancing climate projections and informing effective mitigation strategies. In this study, we evaluated the performance of three widely used aerosol optical depth (AOD) datasets—MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2), MODIS Aqua, and MODIS Terra—by comparing them against ground-based AERONET observations from ten stations located within the dust belt region. Statistical assessments included coefficient of determination (R²), correlation coefficient (R), Index of Agreement (IOA), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Relative Mean Bias (RMB), and standard deviation (SD). The results indicate that MERRA-2 showed the highest agreement (R = 0.76), followed by MODIS Aqua (R = 0.75) and MODIS Terra (R = 0.73). Seasonal and annual AOD climatology maps revealed comparable spatial patterns across datasets, although MODIS Terra consistently reported slightly higher AOD values. These findings provide a robust assessment and reanalysis of satellite AOD products over arid regions, offering critical guidance for aerosol modeling, data assimilation, and climate impact studies. Full article

Busan’s major port is among the largest trading ports worldwide; however, it is also one of the ten most polluted ports globally. This study aims to assess the effectiveness of satellite-derived aerosol data for monitoring particulate matter levels in Busan. Aerosol optical depth (AOD) from the Visible Infrared Imaging Radiometer (VIIRS) Deep Blue product tends to be sparse near coastlines due to higher retrieval uncertainties. To increase the number of samples along the coastal area, we established optimized quality control criteria, resulting in more than three times the number of samples. The VIIRS AOD showed a positive correlation with surface particulate matter (PM_2.5) measurements (r = 0.42). The ratios of VIIRS AOD to surface PM_2.5 and PM₁₀ were higher in coastal areas, probably due to greater hygroscopic growth of particles. This connection can assist in estimating surface PM concentrations using satellite data. Both VIIRS AOD and surface PM concentrations exhibit a negative correlation with terrain elevation, primarily due to the locations of emission sources and altitude-dependent weather factors such as temperature and humidity. We expect that combining higher-resolution ancillary databases, including digital elevation maps and meteorology, with satellite-based AOD will enhance the detail of air quality evaluations in port cities. Full article

Acute Oak Decline (AOD) is a progressive disease affecting oaks across Europe and is increasingly recognised as a threat to the health of forests and urban trees. While the occurrence of this disease has been documented in forest ecosystems, its presence in urban landscapes is still poorly understood. In this study, the occurrence of AOD-associated bacteria (Brenneria goodwinii, Gibbsiella quercinecans, Rahnella victoriana, Lonsdalea quercina) was investigated in Quercus robur and Q. rubra growing in urban areas of Wrocław, Poland. Multiplex real-time PCR analyses confirmed the pathogens in 11 trees, with B. goodwinii being the most common species. Importantly, we provide the first confirmed detection of B. goodwinii in Q. rubra under urban conditions, possibly the first such detection in Europe. The results show the occurrence of AOD-associated pathogens in urban environments, suggesting that such habitats may provide favourable conditions for their occurrence. However, further investigations, including epidemiological and spatial analyses, are needed to clarify whether urban areas contribute to the persistence or spread of these pathogens. Beyond local documentation, our results emphasise the need to include urban ecosystems in AOD surveillance and highlight potential pathways for pathogen adaptation and spread in cities. This work provides new insights into the ecology of AOD in anthropogenically modified habitats and has direct implications for urban tree health monitoring, biodiversity conservation, and the development of integrated management strategies. Full article

Maintaining operational efficiency in distributed solar energy systems requires intelligent coordination of inspection tasks and workforce resources to handle diverse fault conditions. This study presents a bi-level multi-objective optimization framework that addresses two tightly coupled problems: dynamic job scheduling and skill-based team formation. The job scheduling component assigns geographically dispersed inspection tasks to mobile teams while minimizing multiple conflicting objectives, including travel distance, tardiness, and workload imbalance. Concurrently, the team formation component ensures that each team satisfies fault-specific skill requirements by optimizing team cohesion and compactness. To solve the bi-objective team formation problem, we propose HMOO-AOS, a hybrid algorithm integrating six metaheuristic operators under an NSGA-II framework with an Upper Confidence Bound-based Adaptive Operator Selection. Experiments on datasets of up to seven instances demonstrate statistically significant improvements ($p<0.05$) in solution quality, skill coverage, and computational efficiency compared to NSGA-II, NSGA-III, and MOEA/D variants, with computational complexity $\mathcal{O}\left(G·N·(M+logN)\right)$ (time complexity), $\mathcal{O}(N·L)$ (space complexity). A cloud-integrated system architecture is also proposed to contextualize the framework within real-world solar inspection operations, supporting real-time data integration, dynamic rescheduling, and mobile workforce coordination. These contributions provide scalable, practical tools for solar operators, maintenance planners, and energy system managers, establishing a robust and adaptive approach to intelligent inspection planning in renewable energy operations. Full article

We consider that the source sends packets to the receiver through a Ber/Geo/1/2 queue modeled status updating system, where the transmitted packets are subject to potential eavesdropping. Time is discretized into identical time slots. This paper studies the tradeoffs between the information freshness and transmission security of a system, where freshness is characterized by the age of information (AoI) metric and transmission security is represented by the proportion of obtained insecure packets over a long period of time. We assume that in a time slot, the source generates a new packet with probability p, and a packet arrives at the receiver with probability ${\gamma }_d$. With probability ${\gamma }_E$, a transmitted packet is eavesdropped. At the receiver, AoI is defined as the elapsed time since the generation instant of the latest obtained packet. A packet is defined to be insecure if it is obtained by the eavesdropper earlier than the receiver. To control the proportion of insecure packets obtained in the receiver, we propose using the probabilistic deletion/retaining scheme. More specifically, when a packet is eavesdropped before arriving at the receiver, this packet is deleted with probability $\delta$ or retained with probability $1-\delta$. Under this transmission policy, we derive the system’s average AoI which we call the average $\delta -$secure AoI, and investigate its relations with the insecure packet proportion, which is denoted as $\eta \left(\delta \right)$. The obtained formulas are then calculated in three special cases, including ${\gamma }_E=0$, ${\gamma }_E=1$, and $\delta =1$. We explain that these cases correspond to the average AoI of a basic status updating system with Ber/Geo/1/2 queue, packet with random geometric deadline in service process, and average age of secure information (AoSI), respectively. Numerical simulations of obtained results are provided. In particular, the tradeoffs between average $\delta -$secure AoI and $\eta \left(\delta \right)$ are analyzed in detail. We demonstrate that depending on the value of the eavesdropping probability ${\gamma }_E$, average $\delta -$secure AoI varies in different trends with $\eta \left(\delta \right)$, and in most cases the average $\delta -$secure AoI and $\eta \left(\delta \right)$ can be minimized simultaneously. Full article

Air pollution represents a critical environmental challenge in stressed riverine cities, particularly in regions experiencing rapid urbanization and inadequate emission management infrastructure. This study investigates the spatio-temporal dynamics of atmospheric pollution in Baghdad, Iraq, during 2012–2023, analyzing seven key pollutants (CO, CO₂, SO₂, SO₄, O₃, CH₄, and AOD) using NASA’s Giovanni platform coupled with Google Earth Engine analytics. Monthly time-series data were processed through advanced statistical techniques, including Seasonal Autoregressive Integrated Moving Average (SARIMA) modeling and correlation analysis with meteorological parameters, to identify temporal trends, seasonal variations, and driving mechanisms. The analysis revealed three distinct pollutant trajectory categories reflecting complex emission–atmosphere interactions. Carbon monoxide exhibited dramatic decline (60–70% reduction from 2021), attributed to COVID-19 pandemic restrictions and demonstrating rapid responsiveness to activity modifications. Conversely, greenhouse gases showed persistent accumulation, with CO₂ increasing from 400.5 to 417.5 ppm and CH₄ rising 5.9% over the study period, indicating insufficient mitigation efforts. Sulfur compounds and ozone displayed stable concentrations with pronounced seasonal oscillations (winter peaks 2–3 times summer levels), while aerosol optical depth showed high temporal variability linked to dust storm events. Spatial analysis identified pronounced urban–rural concentration gradients, with central Baghdad CO levels exceeding 0.40 ppm compared to peripheral regions below 0.20 ppm. Linear concentration patterns along transportation corridors and industrial zones confirmed anthropogenic source dominance. Correlation analysis revealed strong relationships between meteorological factors and pollutant concentrations (atmospheric pressure: r = 0.62–0.70 with NO₂), providing insights for integrated climate–air quality management strategies. The study demonstrates substantial contributions to Sustainable Development Goals across four dimensions (Environmental Health 30%, Sustainable Cities and Climate Action 25%, Economic Development 25%, and Institutional Development 20%) while providing transferable methodological frameworks for evidence-based policy interventions and environmental monitoring in similar stressed urban environments globally. Full article

Wildfires are a complex and underexplored aspect of the Earth system, significantly affecting climate, as they emit greenhouse gases and aerosols that alter the Earth’s radiative balance. This study utilizes the EC-Earth3 Earth System Model to investigate how interannual variability in biomass burning emissions influences variability in total aerosol optical depth (AOD), as well as carbon monoxide (CO) and ozone (O₃) tropospheric columns. We demonstrate that fluctuations in biomass burning emissions impact AOD, CO, and O₃ variability at regional and global scales, emphasizing the need for improved understanding of wildfires and their climate effects. Full article

Current mainstream remote sensing target detection algorithms mostly estimate the rotation angle of targets by designing different bounding box descriptions and loss functions. However, they fail to consider the symmetry–asymmetry duality anisotropy in the distribution of key features required for target localization. Moreover, the equivalent feature extraction mode of shared convolutional kernels may lead to difficulties in accurately predicting parameters with different attributes, thereby reducing the performance of the detector. In this paper, we propose the Feature Equalization and Hierarchical Decoupling Network (FEHD-Net), which comprises three core components: a Symmetry-Enhanced Parallel Interleaved Convolution Module (PICM), a Parameter Decoupling Module (PDM), and a Critical Feature Matching Loss Function (CFM-Loss). PICM captures diverse spatial features over long distances by integrating square convolution and multi-branch continuous orthogonal large kernel strip convolution sequences, thereby enhancing the network’s capability in processing long-distance spatial information. PDM decomposes feature maps with different properties and assigns them to different regression branches to estimate the parameters of the target’s rotating bounding box. Finally, to stabilize the training of anchors with different qualities that have captured the key features required for detection, CFM-Loss utilizes the intersection ratio between anchors and true value labels, as well as the uncertainty of convolutional regression during training, and designs an alignment criterion (symmetry-aware alignment) to evaluate the regression ability of different anchors. This enables the network to fine-tune the processing of templates with different qualities, achieving stable training of the network. A large number of experiments demonstrate that compared with existing methods, FEHD-Net can achieve state-of-the-art performance on DOTA, HRSC2016, and UCAS-AOD datasets. Full article

Background and Objectives: The study aims to evaluate the effects of regular physical activity on ocular structures by comparing eye anterior segment structures and retinal nerve fiber layer (RNFL) parameters between elite individual athletes and sedentary persons. Materials and Methods: This cross-sectional observational study included 75 participants (33 female and 42 male) aged 18–32 years. Participants consisted of 33 elite individual athletes (66 eyes) aged 18–32 years and 42 sedentary individuals (84 eyes) aged 18–28 years. The elite athlete group consisted of participants who had trained ≥ 3 times per week for the past 5 years and had competition experience in tennis (n = 11), badminton (n = 8), and short/middle distance running (n = 14). Sedentary participants had not engaged in regular physical activity for the last 2 years. Anterior segment structures were measured with ultrasound biomicroscopy (UBM), RNFL parameters were measured with spectral-domain optical coherence tomography (SD-OCT), and intraocular pressure (IOP) was measured with a non-contact pneumotonometer. Results: When the anterior segment parameters were compared, a significance was found in the group effect (p = 0.021, ${ƞ}_p^2$ = 0.036) in the TIA500 value, but the effects of side and gender were insignificant (p > 0.05). While the gender effect was found to be significant for the AOD500 (p = 0.030, ${ƞ}_p^2$ = 0.032) and ARA500 (p = 0.019, ${ƞ}_p^2$ = 0.038) variables, the group and side effects were statistically insignificant (p > 0.05). There was a significant difference in IOP values between sedentary individuals (15.82 ± 2.69) and athletes (14.61 ± 1.80) (p = 0.004, ${ƞ}_p^2$ = 0.057). There was a significant difference between the right (15.71 ± 2.70) and left (14.87 ± 2.02) sides (p = 0.027, ${ƞ}_p^2$ = 0.033). The effect of gender was not significant (p > 0.05). When the results were evaluated, a significant effect of the TEMPORAL side in RNFL parameters (p = 0.003, ${ƞ}_p^2$ = 0.058) was observed. Correlations were seen between the anterior segment and RNFL parameters in both groups (p < 0.05). Conclusions: Athletes exhibited lower IOP compared with sedentary individuals, with similar RNFL parameters but distinct correlation patterns with anterior segment structures. These findings suggest that ocular parameters should be evaluated in an integrated manner and that physical activity may support ocular health by contributing to IOP reduction and potentially slowing the progression of eye diseases. Full article

Remote sensing objects often exhibit significant scale variations, high aspect ratios, and diverse orientations. The anisotropic spatial distribution of such objects’ features leads to the conflict between feature representation and boundary regression caused by the coupling of different attribute parameters: previous detection methods based on square-kernel convolution lack the overall perception of large-scale or slender objects due to the limited receptive field; if the receptive field is simply expanded, although more context information can be captured to help object perception, a large amount of background noise will be introduced, resulting in inaccurate feature extraction of remote sensing objects. Additionally, the extracted features face issues of feature conflict and discontinuous loss during parameter regression. Existing methods often neglect the holistic optimization of these aspects. To address these challenges, this paper proposes SODE-Net as a systematic solution. Specifically, we first design a multi-scale fusion and spatially orthogonal convolution (MSSO) module in the backbone network. Its multiple shapes of receptive fields can naturally capture the long-range dependence of the object without introducing too much background noise, thereby extracting more accurate target features. Secondly, we design a multi-level decoupled detection head, which decouples target classification, bounding-box position regression and bounding-box angle regression into three subtasks, effectively avoiding the coupling problem in parameter regression. At the same time, the phase-continuous encoding module is used in the angle regression branch, which converts the periodic angle value into a continuous cosine value, thus ensuring the stability of the loss value. Extensive experiments demonstrate that, compared to existing detection networks, our method achieves superior performance on four widely used remote sensing object datasets: DOTAv1.0, HRSC2016, UCAS-AOD, and DIOR-R. Full article

In 2024, Brazil experienced record-breaking wildfire activity, underscoring the escalating influence of climate change. This study examines the long-range transport of wildfire-generated aerosol plumes to São Paulo, combining multi-platform observations to trace their origin and properties. During August and September—a period marked by intense fire outbreaks in Pará and Mato Grosso do Sul—lidar measurements performed at São Paulo detected pronounced aerosol plumes. To investigate their source and characteristics, we integrated data from the Earth Cloud Aerosol and Radiation Explorer (EarthCARE) satellite, HYSPLIT back-trajectory modeling, and ground-based AERONET and Raman lidar measurements. Aerosol properties were derived from aerosol optical depth (AOD), Ångström exponent, and lidar ratio (LR) retrievals. Back-trajectory analysis identified three transport pathways originating from active fire zones, with coinciding AOD values (0.7–1.1) and elevated LR (60–100 sr), indicative of dense smoke plumes. Compositional analysis revealed a significant black carbon component, implicating wildfires near Corumbá (Mato Grosso do Sul) and São Félix do Xingu (Pará) as probable emission sources. These findings highlight the efficacy of satellite-based lidar systems, such as Atmospheric Lidar (ATLID) onboard EarthCARE, in atmospheric monitoring, particularly in data-sparse regions where ground instrumentation is limited. Full article