Search Results (64)

Moderate-resolution leaf area index (LAI) retrieval over heterogeneous landscapes is affected not only by unresolved subpixel composition in coarse-resolution predictors, but also by structural bias in supervisory labels aggregated from higher-resolution products. To address this issue, we developed a reference-guided two-stage workflow to improve LAI retrieval from the Visible Infrared Imaging Radiometer Suite (VIIRS). In the first stage, aggregated Sentinel-2 LAI was calibrated against Ground-Based Observations for Validation (GBOV) LP3 reference LAI using subpixel plant functional type (PFT) fractions and forest-sensitive hinge terms to generate corrected 500 m labels. In the second stage, a random-forest model was trained using VIIRS spectral reflectance, viewing geometry, vegetation indices, texture, and subpixel compositional variables. Model development was based on 2020–2021 data from 11 U.S. GBOV sites. Performance was evaluated by same-site temporal transfer to 2019 and 2022 and by strict leave-one-site-out (LOSO) validation. Label calibration improved agreement with GBOV from a coefficient of determination (R²) of 0.752 and a root mean square error (RMSE) of 1.110 to an R² of 0.908 and an RMSE of 0.676. Under LOSO validation, the final model achieved an R² of 0.901 with an RMSE of 0.703. On the 2019/2022 overlap subset shared by the final VIIRS retrieval, the official VNP product, and the GBOV reference, the final model achieved an R² of 0.905 and an RMSE of 0.609, compared with 0.755 and 0.978 for the official VNP product. These results show that reference-guided label correction, combined with explicit subpixel compositional information, can substantially improve VIIRS LAI retrieval over mixed pixels within the evaluated study domain. Full article

Background: Conventional transdermal drug delivery systems are often limited by poor skin permeability and low drug loading efficiency, necessitating the development of advanced delivery platforms. Objectives: This study aimed to develop and optimize photopolymerizable bioinks (PBs) for liquid crystal display (LCD)-based 3D printing of crosslinked hydrogel microneedles (cHMNs) to enhance transdermal delivery of estradiol valerate (E2V). Methods: A Box–Behnken design (BBD) was used to optimize the effects of Gantrez™ S-97, Jurymer™, and polyvinyl alcohol (PVA) on viscosity, exposure time, hardness, and elasticity, with strong predictive performance (R² = 0.9702–0.9907). Results: Estradiol valerate-loaded nanoparticles (E2V-NPs) were prepared via ionotropic gelation, exhibiting a particle size of 698.33 (0.78) nm, PDI of 0.50 (0.06), zeta potential of −39.09 (7.32) mV, and high encapsulation efficiency (86.87 (0.78)%). The optimized PBs enabled fabrication of uniform cHMNs (~800 µm height) with adequate mechanical strength (hardness 20.45 (1.23) N; elasticity 2.97 (0.49) MPa) and effective insertion capability. The E2V-NPs-loaded cHMNs exhibited sustained drug release over 12 days (~56.92 (4.27)%). Skin permeation studies showed a significantly enhanced flux (10.81 (4.55) µg/cm²/h) and cumulative permeation (12.94 (2.06) µg/cm²) compared to topical E2V-NPs and suspension, along with increased skin accumulation (38.55 (0.10) µg). Cytotoxicity studies confirmed that E2V and E2V-NPs were biocompatible (>80% viability), while PBs showed concentration-dependent cytotoxicity. Conclusions: Overall, this integrated platform combining design of experiment, nanoparticles, microneedles, and LCD 3D printing offered a promising strategy for enhancing transdermal drug delivery efficiency and reproducibility. Full article

Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) active fire products are widely used for global fire monitoring, but single-sensor records are limited by differences in observation geometry, spatial resolution, detection sensitivity, and swath coverage. To combine the long-term continuity of Aqua MODIS with the higher sensitivity of Suomi NPP VIIRS, this study developed a correction-before-fusion framework for MYD14 and VNP14IMG and generated a daily fused fire radiative power (FRP) dataset at the native MODIS footprint scale. MYD14 and VNP14IMG observations from 2012 to 2024 were processed using duplicate-detection correction, footprint-scale near-synchronous matching, area-based VIIRS cloud correction, and anomalous-sample screening. Cloud-corrected VIIRS FRP was then used as the reference to develop an empirical viewing zenith angle (VZA)-dependent correction model for MODIS FRP. Finally, VZA-corrected MODIS FRP and cloud-corrected VIIRS FRP were integrated using a quality-prioritized fusion strategy. The correction model achieved high fitting accuracy ($R^2\ge 98.18\%$) and reduced MODIS underestimation under large-VZA conditions. Compared with the original MODIS product, the fused product increased detected fire pixels by approximately 3.82-fold, improved spatial continuity, and reduced temporal data gaps. Landsat-based validation showed improved low-intensity fire detection while maintaining low commission error. This framework provides a harmonized long-term FRP dataset for fire monitoring, emission estimation, and fire-climate studies. Full article

Crop residue open burning is a major source of atmospheric pollutants that degrade regional air quality, enhance climate forcing, and threaten public health through emissions of particulate matter, greenhouse gases, and toxic species. In southern China, satellite-based emission estimates are often underestimated because frequent cloud cover and limited spatiotemporal resolution hinder the detection of agricultural fires. In this study, crop residue open burning emissions in Guangxi province from 2017 to 2023 were quantified using a statistical approach. The open burning proportion (OBP) was updated on an annual basis using the Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m active fire product (VNP14IMG), and recently reported emission factors (EF_S) were adopted to enhance estimation accuracy. Annual emissions of pollutants were then spatially distributed to 0.05° × 0.05° grid cells based on satellite-detected fire counts and land cover information. The results indicated the total emissions of black carbon (BC), organic carbon (OC), sulfur dioxide (SO₂), nitric oxide (NO_X), carbon monoxide (CO), carbon dioxide (CO₂), fine particles (PM_2.5), coarse particles (PM₁₀), ammonia (NH₃), methane (CH₄) and non-methane volatile organic compound (NMVOC) in Guangxi province during 2017–2023 were 58.90, 230.48, 37.90, 213.95, 4234.41, 108,775.48, 583.09, 667.70, 46.36, 322.74 and 710.20 Gg, respectively. Sugarcane residue burning was identified as the dominant contributor, accounting for 41.26–64.38% of total emissions, followed by rice (20.66–43.06%), corn (5.11–17.25%), and cassava (4.33–6.45%). Emissions exhibited clear interannual variability, declining from 2017 to 2020 under strict control measures and increasing again from 2021 to 2023 as enforcement weakened. Incorporating annually updated VIIRS-derived OBP_S into the statistical inventory improves the temporal representation and reliability of multi-year emission estimates for agricultural burning. Full article

Thermal contextual algorithms for 375 m VIIRS active fire detection can produce substantial commission errors over persistent non-wildfire heat sources (e.g., refineries, gas flares, and volcanoes), and globally fixed thresholds may be suboptimal under heterogeneous thermal backgrounds. We present a lightweight spatiotemporal prior layer that augments by applying prior-guided, pixel-level parameter switching during the discrimination stage. The layer combines: (i) a persistent non-wildfire thermal anomaly mask (PFM) derived from multi-year VNP14IMG recurrence and seasonality statistics on a 0.004° grid, and (ii) a short-term heat-source mask (SHM) based on nighttime VIIRS I4/I5 brightness temperature stability to capture newly emerged or rapidly intensifying static sources. Pixels flagged by either prior are processed with a stricter parameter set, while other pixels follow the baseline setting. We evaluate the method using a stratified validation dataset (N = 3435) spanning industrial/urban clusters, volcanic regions, forest/grassland wildfires, and fragmented crop residue burning, with validation supported by independent high-resolution imagery (Sentinel-2/Landsat) and external POI datasets. The framework markedly reduces false positives in high-interference zones (industrial/urban false positive rate from 88.6% to 22.7%; volcanic from 100.0% to 57.3%) while preserving high performance for forest/grassland wildfires (F1 ≈ 0.999). For fragmented residue burning, omission error decreases from 11.2% to 1.3%, improving detection completeness without an apparent increase in commission errors. Overall, the results suggest that integrating long- and short-term spatiotemporal priors via threshold switching can improve the robustness and interpretability of contextual VIIRS fire detection under complex thermal backgrounds in the evaluated scenarios. Full article

Urban protected areas are increasingly recognized as essential for human well-being, biodiversity conservation, and climate resilience; however, their role in post-industrial cities remains insufficiently understood. To address this gap, we examine Văcărești Nature Park (VNP) (IUCN Category V), a 183-hectare urban wetland in Bucharest, Romania, formed through spontaneous ecological restoration within a post-industrial landscape. Using a mixed-methods approach that integrates ecological assessment, participatory mapping, and public perception analysis, we evaluate the park’s ecosystem services (ES) and social dynamics. Cultural ES—particularly recreation, wildlife observation, and biodiversity appreciation—dominate public valuation, while regulating services such as microclimate regulation are less recognized and provisioning services remain marginal. This pattern highlights the importance of experiential and relational values in shaping how urban nature is perceived and used. Spatial analysis reveals intensive use of biodiverse interior zones and the avoidance of peripheral areas, primarily driven by infrastructure degradation and perceived safety risks. The resulting core–periphery differentiation points to an uneven distribution of ES benefits with direct implications for urban ecosystem governance and social inclusiveness. Overall use is predominantly passive, centered on immersion in natural settings rather than interactive or educational engagement. By demonstrating how participatory surveys combined with spatial mapping can reveal both ES demand and latent governance challenges, this study shows that spontaneously restored urban wetlands can function as high-value, multifunctional assets and provide generally applicable insights for adaptive management in rapidly changing cities. Full article

On 7 January 2025, an Mw7.1 earthquake struck Dingri County, Tibet, causing severe damage in a high-altitude, sparsely instrumented region where traditional damage assessment methods are limited. To address this, we developed an integrated "source simulation–nighttime light validation" framework. First, a kinematic source model (constrained by InSAR and teleseismic data) and the Unified Seismic Tomography models for continental China lithosphere 2.0 (USTClitho2.0) velocity model were used with the curved-grid finite difference method to simulate high-resolution ground motion and intensity fields. Second, NASA Black Marble (VNP46A2) nighttime light data, processed with the Block-Matching and 3D filtering (BM3D) algorithm, were analyzed to compute pixel-level radiance changes and township-level total nighttime light loss rates (TNLR). The results reveal a high spatial consistency between simulated high-intensity zones and areas of significant light loss. For instance, Mangpu Township, within a simulated high-intensity zone, exhibited a TNLR of 44.7%. This demonstrates that nighttime light remote sensing can effectively validate physical simulations in areas lacking dense seismic networks. Our framework provides a novel, complementary methodology for rapid and reliable post-earthquake damage assessment in high-mountain, data-sparse regions. Full article

Daily nighttime light (NTL) observations made by remote sensing satellites can monitor human activity at high temporal resolution, but are often constrained by residual physical disturbances. Even in standard products, such as NASA’s Black Marble VNP46A2, factors related to sensor viewing geometry, lunar illumination, atmospheric conditions, and seasonality can introduce noise into daily radiance retrievals. This study develops a locally adaptive framework to diagnose and correct residual disturbances in daily NTL data. By estimating location-specific regression models, we quantify the residual sensitivity of VNP46A2 radiance to multiple disturbance factors and selectively remove statistically significant components. The results show that the proposed approach effectively removes statistically significant residual disturbances from daily NTL data in the VNP46A2 product. An application for COVID-19 containment periods in China demonstrates the effectiveness of the proposed approach, where corrected daily NTL data exhibit enhanced temporal stability and improved interpretability. Further analysis based on event study approaches demonstrates that corrected daily NTL data enable the identification of short-run policy effects that are difficult to detect with lower-frequency indicators. Overall, this study enhances the suitability of daily NTL data for high-frequency socioeconomic applications and extends existing preprocessing approaches for daily NTL observations. Full article

Breast milk is a major source of probiotics, particularly lactic acid bacteria (LAB), which are known to regulate the intestinal microbial community and exert antibacterial effects. However, little is known about the preventive effects of feline milk-derived LAB against Salmonella infection in vivo. In this study, a strain of Pediococcus acidilactici (M22) was isolated from feline milk and evaluated for its protective potential in C57BL/6 mice challenged with Salmonella Typhimurium SL1344 (VNP20009). Following oral administration of M22, mice were infected with S. Typhimurium, and protective efficacy was assessed through body weight changes, bacterial loads in tissues, histopathological examination of the colon, oxidative stress markers, cytokine profiles, and 16S rRNA gene sequencing of cecal microbiota. The results showed that pretreatment with M22 significantly reduced bacterial loads in the liver, spleen, and cecum compared with controls. M22 administration enhanced antioxidant capacity, alleviated infection-induced inflammation, and preserved intestinal barrier integrity by restoring villus morphology and upregulating tight junction proteins (ZO-1 and occludin). Microbiota analysis further revealed that M22 enriched short-chain fatty acid-producing beneficial taxa (e.g., lactic acid bacteria) while suppressing pro-inflammatory genera. Collectively, these findings provide scientific evidence that feline milk-derived P. acidilactici M22 is a safe and effective probiotic candidate. By enhancing gut health and host resistance to infection, M22 offers a promising strategy to improve companion animal health, reduce reliance on antibiotics, and mitigate zoonotic transmission of pathogens. Full article

The fraction of absorbed photosynthetically active radiation (FAPAR) stands as a pivotal parameter within the Earth system, quantifying the energy exchange between vegetation and solar radiation. Accordingly, there is an urgent need for comprehensive validation studies to accurately quantify uncertainties and improve the reliability of FAPAR-based applications. This study validated five global FAPAR products, MOD15A2H, MYD15A2H, VNP15A2H, GEOV2, and GEOV3, over four boreal forest sites in North America. Qualitative quality flags (QQFs) and quantitative quality indicators (QQIs) of each product were analyzed. Time series high-resolution reference FAPAR maps were developed using the Harmonized Landsat and Sentinel-2 dataset. The reference FAPAR maps revealed a strong agreement with the in situ FAPAR from AmeriFlux (correlation coefficient (R) = 0.91; root mean square error (RMSE) = 0.06). The results revealed that global FAPAR products show similar uncertainties (RMSE: 0.16 ± 0.04) and moderate agreement with the reference FAPAR (R = 0.75 ± 0.10). On average, 34.47 ± 6.91% of the FAPAR data met the goal requirements of the Global Climate Observing System (GCOS), while 54.41 ± 6.89% met the threshold requirements of the GCOS. Deciduous forests perform better than evergreen forests, and the products tend to underestimate the reference data, especially for the beginning and end of growing seasons in evergreen forests. There are no obvious quality differences at different QQFs, and the relative QQI can be used to filter high-quality values. To enhance the regional applicability of global FAPAR products, further algorithm improvements and expanded validation efforts are essential. Full article

Virus-like nanoparticles (VNPs) based on Moloney murine leukemia virus represent a well-established platform for the expression of heterologous molecules such as cytokines, cytokine receptors, peptide MHC (pMHC) and major allergens, but their application for inducing protective anti-viral immunity has remained understudied as of yet. Here, we variably fused the wildtype SARS-CoV-2 spike, its receptor-binding domain (RBD) and nucleocapsid (NC) to the minimal CD16b-GPI anchor acceptor sequence for expression on the surface of VNP. Moreover, a CD16b-GPI-anchored single-chain version of IL-12 was tested for its adjuvanticity. VNPs expressing RBD::CD16b-GPI alone or in combination with IL-12::CD16b-GPI were used to immunize BALB/c mice intramuscularly and subsequently to investigate virus-specific humoral and cellular immune responses. CD16b-GPI-anchored viral molecules and IL-12-GPI were well-expressed on HEK-293T-producer cells and purified VNPs. After the immunization of mice with VNPs, RBD-specific antibodies were only induced with RBD-expressing VNPs, but not with empty control VNPs or VNPs solely expressing IL-12. Mice immunized with RBD VNPs produced RBD-specific IgM, IgG_2a and IgG₁ after the first immunization, whereas RBD-specific IgA only appeared after a booster immunization. Protein/peptide microarray and ELISA analyses confirmed exclusive IgG reactivity with folded but not unfolded RBD and showed no specific IgG reactivity with linear RBD peptides. Notably, booster injections gradually increased long-term IgG antibody avidity as measured by ELISA. Interestingly, the final immunization with RBD–Omicron VNPs mainly enhanced preexisting RBD Wuhan Hu-1-specific antibodies. Furthermore, the induced antibodies significantly neutralized SARS-CoV-2 and specifically enhanced cellular cytotoxicity (ADCC) against RBD protein-expressing target cells. In summary, VNPs expressing viral proteins, even in the absence of adjuvants, efficiently induce functional SARS-CoV-2-specific antibodies of all three major classes, making this technology very interesting for future vaccine development and boosting strategies with low reactogenicity. Full article

Intrinsic point defects in NpO₂ significantly impact its chemical properties, but their formation mechanisms are not fully understood. Using first-principles plane-wave pseudopotential methods, this study systematically investigates the formation processes of Schottky, Frenkel, and substitutional impurity defects under various oxygen environments. Results show that formation energies vary with valence states, oxygen environments, and Fermi energy, and reveal the presence of antisite defects. Schottky, Frenkel, and antisite defects are rare in oxygen-rich conditions, but new defect pairs emerge in anoxic environments, including Schottky defect {2V_Np³⁻: 3V_O²⁺}, Np-Frenkel defects {V_Np³⁻: Np_i³⁺} and {V_Np⁴⁺: Np_i⁴⁺}, and pairs {O_Np⁵⁺: Np_O⁵⁻} and {O_Np⁶⁺: Np_O⁶⁻}. These findings provide new perspectives for understanding the intrinsic point defects in NpO₂. Full article

Multi-angle remote sensing observations play an important role in the remote sensing of solar radiation absorbed by land surfaces. Currently, the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) teams have successively applied the Ross–Li kernel-driven bidirectional reflectance distribution function (BRDF) model to integrate multi-angle observations to produce long time series BRDF model parameter products (MCD43 and VNP43), which can be used for the inversion of various surface parameters and the angle correction of remote sensing data. Even though the MODIS and VIIRS BRDF products originate from sensors and algorithms with similar designs, the consistency between BRDF parameters for different sensors is still unknown, and this likely affects the consistency and accuracy of various downstream parameter inversions. In this study, we applied BRDF model parameter time-series data from the overlapping period of the MODIS and VIIRS services to systematically analyze the temporal and spatial differences between the BRDF parameters and derived indices of the two sensors from the site scale to the region scale in the red band and NIR band, respectively. Then, we analyzed the sensitivity of the BRDF parameters to variations in Normalized Difference Hotspot–Darkspot (NDHD) and examined the spatiotemporal distribution of zero-valued pixels in the BRDF parameter products generated by the constraint method in the Ross–Li model from both sensors, assessing their potential impact on NDHD derivation. The results confirm that among the three BRDF parameters, the isotropic scattering parameters of MODIS and VIIRS are more consistent, whereas the volumetric and geometric-optical scattering parameters are more sensitive and variable; this performance is more pronounced in the red band. The indices derived from the MODIS and VIIRS BRDF parameters were compared, revealing increasing discrepancies between the albedo and typical directional reflectance and the NDHD. The isotropic scattering parameter and the volumetric scattering parameter show responses that are very sensitive to increases in the equal interval of the NDHD, indicating that the differences between the MODIS and VIIRS products may strongly influence the consistency of NDHD estimation. In addition, both MODIS and VIIRS have a large proportion of zero-valued pixels (volumetric and geometric-optical parameter layers), whereas the spatiotemporal distribution of zero-valued pixels in VIIRS is more widespread. While the zero-valued pixels have a minor influence on reflectance and albedo estimation, such pixels should be considered with attention to the estimation accuracy of the vegetation angular index, which relies heavily on anisotropic characteristics, e.g., the NDHD. This study reveals the need in optimizing the Clumping Index (CI)-NDHD algorithm to produce VIIRS CI product and highlights the importance of considering BRDF product quality flags for users in their specific applications. The method used in this study also helps improve the theoretical framework for cross-sensor product consistency assessment and clarify the uncertainty in high-precision ecological monitoring and various remote sensing applications. Full article

The leaf area index (LAI) is a crucial parameter for climate change research, agricultural management, and ecosystem monitoring. Despite extensive use of remote sensing data to estimate the LAI, comprehensive evaluations of product consistency and uncertainty remain limited. This study evaluated the uncertainties of four LAI products—GLASS, MCD15A2H, VNP15A2H, and CLMS—across diverse land cover types in the Heihe River Basin through two triple collocation approaches, innovatively. Each approach, respectively, focused on achieving more precise temporal characteristics and spatial characteristics of product uncertainties. The results indicate that all products generally met the Global Climate Observing System’s precision requirement (±0.5) for most biomes during the growing season. When comparing monthly uncertainties within grid cells, GLASS demonstrates superior performance, particularly in grasslands and croplands, whereas CLMS exhibits a slightly weaker ability to represent the spatial distribution of the LAI, especially in regions with high LAI values. When time series data are used to analyze the seasonal uncertainties of the products, MCD15A2H and VNP15A2H show more pronounced distortions, indicating their limited capability in capturing the temporal dynamics of the LAI. Correlation analyses revealed strong product agreement in regions with a low LAI, but discrepancies increased during the growing season and in heterogeneous land covers like croplands. These findings provide critical insights into the reliability of LAI products, offering a robust reference for validating their performance and ensuring their alignment with user requirements across diverse applications. The study highlights the importance of addressing spatial and temporal variability in uncertainties to improve the practical utility of LAI datasets in ecological and climate-related research. Full article

Background/Objectives: Spironolactone (SP), an aldosterone inhibitor widely used to treat androgen-dependent disorders such as acne, hirsutism, and alopecia, has demonstrated therapeutic potential in both oral and topical formulations. However, SP’s low solubility and poor bioavailability in conventional formulations have driven the development of novel nanocarriers to enhance its efficacy. This review systematically examines recent advancements in SP-loaded nanocarriers, including lipid nanoparticles (LNPs), vesicular nanoparticles (VNPs), polymeric nanoparticles (PNPs), and nanofibers (NFs). Methods: A search strategy was developed, and the relevant literature was systematically searched using databases such as Scopus, PubMed, and Google Scholar. The review process, including screening, inclusion, and exclusion criteria, adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: A comprehensive analysis of 13 eligible research articles, corresponding to 15 studies, highlights key aspects such as encapsulation efficiency, stability, particle size, and in vitro and in vivo efficacy. Six studies focused on lipid nanoparticles (LNPs), including solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs), which were found to improve SP’s bioavailability and skin permeation. Another six studies investigated vesicular nanoparticles (VNPs), such as ethosomes and niosomes, demonstrating superior skin targeting and penetration capabilities. Two studies on polymeric nanoparticles (PNPs) showed effectiveness in delivering SP to hair follicles for the treatment of alopecia and acne. Additionally, one study on SP-loaded nanofibers indicated significant potential for topical rosacea therapy. Conclusions: SP-loaded nanocarrier systems represent promising advancements in targeted topical therapy. However, further clinical studies are required to optimize their safety, efficacy, and delivery mechanisms. Full article