Search Results (456)

Background/Objectives: Virus-like particles (VLPs) represent an attractive platform for delivering vaccine formulations, combining a high biosafety profile with a potent immune-stimulatory ability. VLPs are non-infectious, non-replicating, self-assembling nanostructures that can be exploited to efficiently expose membrane-tethered glycoproteins such as the SARS-CoV-2 Spike (S) protein, the main target of approved preventive vaccines. Here, we describe the development and preclinical validation of Simian Immunodeficiency Virus (SIV)-based GFP-labeled VLPs displaying S from the B.1.617.2 (Delta) variant (VLP/S-Delta) for inducing persistent anti-SARS-CoV-2 neutralizing antibodies (nAbs) and S-specific T cell responses in mice. Methods: SIV-derived VLP/S-Delta were produced by co-transfecting a plasmid expressing SIVGag-GFP, required for VLP assembly and quantification by flow virometry, a plasmid encoding the Delta S protein deleted in the cytoplasmic tail (CT), to improve membrane binding, and a VSV.G-expressing plasmid, to enhance VLP uptake. Recovered VLPs were titrated by flow virometry and characterized in vitro by transmission electron microscopy (TEM) and confocal microscopy (CLSM). BALB/c mice were immunized intramuscularly with VLP/S-Delta following a prime–boost regimen, and humoral and cellular immune responses were assessed. Results: VLP/S-Delta were efficiently pseudotyped with CT-truncated S-Delta. After BALB/c priming, VLP/S-Delta elicited both specific anti-RBD IgGs and anti-Delta nAbs that significantly increased after the boost and were maintained over time. The prime–boost vaccination induced similar levels of cross-nAbs against the ancestral Wuhan-Hu-1 strain as well as cross-nAbs against Omicron BA.1, BA.2 and BA.4/5 VoCs, albeit at lower levels. Moreover, immunization with VLP/S-Delta induced S-specific IFNγ-producing T cells. Conclusions: These data suggest that SIV-based VLPs are an appropriate delivery system for the elicitation of efficient and sustained humoral and cellular immunity in mice, paving the way for further improvements in the immunogen design to enhance the quality and breadth of immune responses against different viral glycoproteins. Full article

Background/Objectives: The SARS-CoV-2’s high mutations and replication rates contribute to its high infectivity and resistance to current vaccinations and treatments. The primary cause of resistance to most current treatments aligns within the coding regions for the spike S protein of SARS-CoV-2 that has mutated. As a potential novel immunotherapy, we generated a novel fusion protein composed of a soluble ACE2 (sACE2) linked to llama-derived anti-CD16 that targets different variants of spike proteins and enhances natural killer cells to target infected cells. Methods: Here, we generated a novel sACE2-AntiCD16VHH fusion protein using a Gly4Ser linker, synthesized and cloned into the pLVX-EF1alpha-IRES-Puro vector, and further expressed in ExpiCHO-S cells and purified using Ni⁺NTA chromatography. Results: The fusion protein significantly blocked SARS-CoV-2 alpha, beta, delta, gamma, and omicron S-proteins binding and activating angiotensin-converting enzyme receptor-2 (ACE2) on ACE2-expressing RAW-Blue macrophage cells and the secretion of several key inflammatory cytokines, G-CSF, MIP-1A, and MCP-1, implicated in the cytokine release storm (CRS). The sACE2-Anti-CD16VHH fusion protein also bridged NK cells to ACE2-expressing human lung carcinoma A549 cells and significantly activated NK-dependent cytotoxicity. Conclusions: The findings show that a VHH directed against CD16 could be an excellent candidate to be linked to soluble ACE2 to generate a bi-specific molecule (sACE2-AntiCD16VHH) suitable for bridging effector cells and infected target cells to inhibit SARS-CoV-2 variant spike proteins binding to the ACE2 receptor in the RAW-Blue cell line and pro-inflammatory cytokines and to activate natural killer cell cytotoxicity. Full article

Diagnosing ozone (O₃) formation sensitivity using tropospheric observations of O₃ and its precursors is important for formulating O₃ pollution control strategies. Photochemical reactions producing O₃ occur at the earth’s surface and in the elevated layers, indicating the importance of diagnosing O₃ formation sensitivity at different layers. Synchronous measurements of tropospheric O₃ and its precursors nitrogen dioxide (NO₂) and formaldehyde (HCHO) were performed in urban Hefei to diagnose O₃ formation sensitivity at different atmospheric layers using multi-axis differential optical absorption spectroscopy observations. The retrieved surface NO₂ and O₃ were validated with in situ measurements (correlation coefficients (R) = 0.81 and 0.80), and the retrieved NO₂ and HCHO vertical column densities (VCDs) were consistent with TROPOMI results (R = 0.81 and 0.77). The regime transitions of O₃ formation sensitivity at different layers were derived using HCHO/NO₂ ratios and O₃ profiles, with contributions of VOC-limited, VOC-NO_x-limited, and NO_x-limited regimes of 74.19%, 7.33%, and 18.48%, respectively. In addition, the surface O₃ formation sensitivity between HCHO/NO₂ ratios and O₃ (or increased O₃, ΔO₃) had similar regime transitions of 2.21–2.46 and 2.39–2.71, respectively. Moreover, the O₃ formation sensitivity of the lower planetary boundary layer on polluted and non-polluted days was analyzed. On non-polluted days, the contributions of the VOC-limited regime were predominant in the lower planetary boundary layer, whereas those of the NO_x-limited regime were predominant in the elevated layers during polluted days. These results will help us understand the evolution of O₃ formation sensitivity and formulate O₃ mitigation strategies in the Yangtze River Delta region. Full article

This paper presents a novel methodology to generate Digital Elevation Models (DEMs) in flat areas, incorporating river channels from relatively coarse initial data. The technique primarily utilizes filtered dense point clouds derived from SfM-MVS (Structure from Motion-Multi-View Stereo) photogrammetry of available crewed aerial imagery datasets. The methodology operates under the assumption that the aerial survey was carried out during low-flow or drought conditions so that the dry (or almost dry) riverbed is detected, although in an imprecise way. Direct interpolation of the detected elevation points yields unacceptable river channel bottom profiles (often exhibiting unrealistic artifacts) and even distorts the floodplain. In our Fluvial Domain Method, channel bottoms are represented like “highways”, perhaps overlooking their (unknown) detailed morphology but gaining in general topographic consistency. For instance, we observed an 11.7% discrepancy in the river channel long profile (with respect to the measured cross-sections) and a 0.38 m RMSE in the floodplain (with respect to the GNSS-RTK measurements). Unlike conventional methods that utilize active sensors (satellite and airborne LiDAR) or classic topographic surveys—each with precision, cost, or labor limitations—the proposed approach offers a more accessible, cost-effective, and flexible solution that is particularly well suited to cases with scarce base information and financial resources. However, the method’s performance is inherently limited by the quality of input data and the simplification of complex channel morphologies; it is most suitable for cases where high-resolution geomorphological detail is not critical or where direct data acquisition is not feasible. The resulting DEM, incorporating a generalized channel representation, is well suited for flood hazard modeling. A case study of the Ranchería river delta in the Northern Colombian Caribbean demonstrates the methodology. Full article

The pastoral areas of Ethiopia are facing a recurrent drought crisis that significantly affects the availability of water resources for communities dependent on livestock. Despite the urgent need for effective drought early warning systems, Ethiopia’s pastoral areas have limited capacities to monitor variations in the intensity–duration–frequency of droughts. This study intends to drive drought intensity–duration–frequency (IDF) curves that account for climate-model uncertainty and spatial variability, with the goal of enhancing water resources management in Borana, Ethiopia. To achieve this, the study employed quantile delta mapping to bias-correct outputs from five climate models. A novel multi-model ensemble approach, known as spatiotemporal reliability ensemble averaging, was utilized to combine climate-model outputs, exploiting the strengths of each model while discounting their weaknesses. The Standardized Precipitation Evaporation Index (SPEI) was used to quantify meteorological (3-month SPEI), agricultural (6-month SPEI), and hydrological (12-month SPEI) droughts. Overall, the analysis of historical (1990–2014) and projected (2025–2049, 2050–2074, and 2075–2099) periods revealed that climate change significantly exacerbates drought conditions across all three systems, with changes in drought being more pronounced than changes in mean precipitation. A prevailing rise in droughts’ IDF features is linked to an anticipated decline in precipitation and an increase in temperature. From the derived drought IDF curves, projections for 2025–2049 and 2050–2074 indicate a significant rise in hydrological drought occurrences, while the historical and 2075–2099 periods demonstrate greater vulnerability in meteorological and agricultural systems. While the frequency of hydrological droughts is projected to decrease between 2075 and 2099 as their duration increases, the periods from 2025 to 2049 and from 2050 to 2074 are expected to experience more intense hydrological droughts. Generally, the findings underscore the critical need for timely interventions to mitigate the vulnerabilities associated with drought, particularly in areas like Borana that depend heavily on water resources availability. Full article

In the presented work, design conditions for breakwaters were derived from offshore climate reanalysis data (ERA5), which were downscaled to the nearshore by two numerical approaches, i.e., SwanOne and Delft3D, for different average and extreme wave and weather conditions. Model validation was performed using in situ measurements. The advantages and disadvantages of both numerical approaches were investigated. Both models showed sufficient accuracy according to measurements in the field, where SwanOne offers a simple and fast calculation method, while Delft3D provides a more complete representation, not only of waves but also current dynamics. However, it requires a much broader amount of input parameters and more complex boundary conditions. Then, SwanOne was applicable to calculate nearshore wave characteristics based on the input parameters extracted from the statistical analysis of long-term ERA5 data. Based on this process, design wave heights and periods at the nearshore were determined for 10- to 100-year return periods. For breakwater design on the west coast of the Mekong Delta, maximum wave heights in a range of 1.1 m to 1.3 m at a distance of 100 m to 300 m could be determined for a return period of 20 years, corresponding to water depths of 2.33 m and 2.88 m, respectively. Full article

Cardarine (C₂₁H₁₈F₃NO₃S₂), better known by the popular name of GW501516, is a peroxisome proliferator-activated receptor delta (PPR-δ) agonist that presents potential use in the approach of cardiovascular diseases and metabolic disorders, dyslipidemia, and insulin resistance. The capability of cardarine to exhibit new solid forms by recrystallization from a broad class of solvents was explored. A total of four new solid forms were obtained: a new polymorph of cardarine (C₂₁H₁₈F₃NO₃S₂), the cardarine: 4,4′-bipyridine cocrystal (C₂₁H₁₈F₃NO₃S₂·0.5C₁₀H₈N₂), the cardarine methanol solvate (C₂₁H₁₈F₃NO₃S₂·CH₃OH), and the cardarine dimethylformamide solvate (C₂₁H₁₈F₃NO₃S₂·C₃H₇NO). Moreover, two derivatives of cardarine were obtained, in the form of the mono-oxidized cardarine structure (C₂₁H₁₈F₃NO₄S₂) and the dioxidized cardarine structure (C₂₁H₁₈F₃NO₅S₂). The formation process was proven by the determination of their crystal structures using single crystal X-ray diffraction and followed by their lattice energies evaluation. Further investigations have been conducted by powder X-ray diffraction, DTA/TGA thermal analysis, and FTIR spectroscopy. The stability and solubility were analyzed as well. Full article

Cannabis sativa L. is cultivated nowadays for agricultural, industrial, and medicinal applications and also for recreational use. The latter is due to the presence of delta-9-tetrahydrocannabinol, a psychoactive substance. Recreational cannabis policies vary between different countries, which has led to the lack of a clearly defined legal context for cannabis and also a diversity of products derived from or containing cannabis on the (il)legal market. These cannabis-derived products have regained attention, notably because of their cannabinoid content. This review aims to assess and present analytical methods developed to analyze phytocannabinoids with spectroscopic and chromatographic techniques in specific cannabis matrices: herbs and oily products. Published papers from 2018–November 2024 were searched for with precise criteria, analyzed, and summarized. In the studies, liquid and gas chromatographic techniques (>70% reviewed papers) were the most used and have been widely applied using similar methods, and most papers were focused on cannabis herbs (>75%). Techniques were also compared and future challenges were identified. A comparison of different specificities of chromatographic and spectroscopic techniques discussed in this current review has also been established and summarized. Full article

The extraction, processing and transport of crude oil in the Niger Delta region of Nigeria has long been associated with collateral environmental damage to the largest mangrove ecosystem in Africa. Oil pollution is impacting not only one of the planet’s most ecologically diverse regions but also the health, livelihoods, and social cohesion of the Delta region inhabitants. Quantifying and directly associating localised oil pollution events to specific petrochemical infrastructure is complicated by the difficulty of monitoring such vast and complex terrain, with documented concerns regarding the thoroughness and impartiality of reported oil pollution events. Earth Observation (EO) offers a means to deliver such a monitoring and assessment capability using Normalised Difference Vegetation Index (NDVI) measurements as a proxy for mangrove biomass health. However, the utility of EO can be impacted by persistent cloud cover in such regions. To overcome such challenges here, we present a workflow that leverages EO-derived high-resolution (10 m) synthetic aperture radar data from the Sentinel-1 satellite constellation combined with machine learning to conduct observations of the spatial land cover changes associated with oil pollution-induced mangrove mortality proximal to pipeline networks in a 9000 km² region of Rivers State located near Port Harcourt. Our analysis identified significant deforestation from 2016–2024, with an estimated mangrove mortality rate of 5644 hectares/year. Using our empirically derived Pipeline Impact Indicator (PII), we mapped the oil pipeline network to 1 km resolution, highlighting specific pipeline locations in need of immediate intervention and restoration, and identified several new pipeline sites showing evidence of significant oil spill damage that have yet to be formally reported. Our findings emphasise the critical need for the continuous and comprehensive monitoring of oil extractive regions using satellite remote sensing to support decision-making and policies to mitigate environmental and societal damage from pipeline oil spills, particularly in ecologically vulnerable regions such as the Niger Delta. Full article

A new meteorological station (DMS) was established at the Morning Glory summit in Zhejiang Province to provide regional background information on atmospheric composition in the Yangtze River Delta (YRD) region, China. This study investigated the first carbon monoxide (CO) records at DMS from September 2020 to January 2022. The annual average concentration of CO was 233.4 ± 3.8 ppb, which exceeded the measurements recorded at the other Asian background sites. The winter CO concentration remained elevated but peaked in March in the early spring due to the combined effect of regional emissions within the YRD and transportation impacts of North China and Southeast Asia sources. The diurnal cycle had a nocturnal peak and a morning valley but with a distinct afternoon climb, as the metropolis in the YRD contributed to a local concentration enhancement. The back trajectory analysis and the Weighted Potential Sources Contribution Function (WPSCF) maps highlighted emissions from Anhui, Jiangxi, Zhejiang, and Jiangsu provinces as significant sources. Due to well-mixed air conditions and fewer anthropogenic influences, DMS records closely aligned with the CO averages derived from the Copernicus Atmospheric Monitoring Service (CAMS) covering the YRD, confirming its representativeness for regional CO levels. This study underscored DMS as a valuable station for monitoring and understanding CO spatiotemporal characteristics in the YRD region. Full article

The widespread oil extraction in the Niger Delta and the impacts on different types of vegetation are poorly understood due to lack of ground access. This study aims to determine the impact of oil spills on vegetation in the Niger Delta using a Landsat satellite-derived normalised difference vegetation index (NDVI). The impact of oil spill volume and time after an oil spill on the health of different types of vegetation were evaluated, and the time series of the changes in NDVI were analysed to determine the medium- and long-term responses of vegetation to oil spill exposure, using a combination of linear regression and paired t-tests. With regards to the relationship between spill volume and NDVI, a moderate correlation (R² = 0.5018) was observed for spill volumes in the range of 401–1000 barrels for sparse vegetation, for volumes greater than 1000 barrels for dense vegetation (R² = 0.4356), whilst no correlation was found for mangrove vegetation at any range of spill volume. Similarly, the results of the paired t-test confirmed a significant difference (p-value < 0.05) between the change in NDVI values for spill sites and non-spill sites for all vegetation types, with the sparse vegetation being the most affected of the three types. However, the impact of the oil spill on vegetation over a period is not statistically significant. The outcomes of this study provide insights into how different types of vegetation in the Niger Delta respond to oil spills, which could ultimately help in designing an oil spill clean-up program to reduce the impact on the environment. Full article

The characterization of the lunar surface and subsurface through the utilization of synthetic aperture radar data has assumed a pivotal role in the domain of lunar exploration science. This investigation concentrated on the polarimetric analysis aimed at identifying water ice within a specific crater, designated Erlanger, located at the lunar north pole, which is fundamentally a region that is perpetually shaded from solar illumination. The area that is perpetually shaded on the moon is defined as that region that is never exposed to sunlight due to the moon’s slightly tilted rotational axis. These permanently shaded regions serve as cold traps for water molecules. To ascertain the presence of water ice within the designated study area, we conducted an analysis of two datasets from the Chandrayaan mission: Mini-SAR data from Chandrayaan-1 and Dual-Frequency Synthetic Aperture Radar (DFSAR) data from Chandrayaan-2. The polarimetric analysis of the Erlanger Crater, located in a permanently shadowed region of the lunar north pole, utilizes data from the Dual-Frequency Synthetic Aperture Radar (DFSAR) and the Mini-SAR. This study focuses exclusively on the L-band DFSAR data due to the unavailability of S-band data for the Erlanger Crater. The crater, identified by the PSR ID NP_869610_0287570, is of particular interest for its potential water ice deposits. The analysis employs three decomposition models—m-delta, m-chi, and m-alpha—derived from the Mini-SAR data, along with the H-A-Alpha model known as an Eigenvector and Eigenvalue model, applied to the DFSAR data. The H-A-Alpha helps in assessing the entropy and anisotropy of the lunar surface. The results reveal a correlation between the hybrid polarimetric models (m-delta, m-chi, and m-alpha) and fully polarimetric parameters (entropy, anisotropy, and alpha), suggesting that volume scattering predominates inside the crater walls, while surface and double bounce scattering are more prevalent in the right side of the crater wall and surrounding areas. Additionally, the analysis of the circular polarization ratio (CPR) from both datasets suggests the presence of water ice within and around the crater, as values greater than 1 were observed. This finding aligns with other studies indicating that the high CPR values are indicative of ice deposits in the lunar polar regions. The polarimetric analysis of the Erlanger Crater contributes to the understanding of lunar polar regions and highlights the potential for future exploration and resource utilization on the Moon. Full article

(1) This paper selects the modern delta formed by the Ganjiang tributary in Poyang Lake. By performing high density statistical analysis of distribution channel parameters in the area using satellite images and geographic information processing software (LucaSpaceViewer 4.5.2, ArcGIS Pro 3.0.2, Global Mapper v23.1), including length, width, bifurcation angle, bifurcation frequency, and channel sinuosity, the distribution characteristics of delta distribution channels are derived and quantitatively characterized. (2) Classification and evaluation of these characteristics are carried out using factor and cluster analysis, ultimately identifying controlling factors affecting the morphology and distribution of the distribution channels. By statistically analyzing the geometric and bifurcation data of the channels, factor and cluster analysis for data reduction and classification, the channel is finally divided into three categories: Type I channels have relatively high channel length, width, sinuosity, bending amplitude, and a lower bifurcation (or confluence) growth rate; Type II channels are characterized by low channel length, moderate channel width, low sinuosity, low bending amplitude, and a high bifurcation (or confluence) growth rate; Type III channels are defined by moderate channel length, low width, high sinuosity, high bending amplitude, and low bifurcation (or confluence) frequency. (3) After excluding the influence of other factors, it was found that the main controlling factor for the morphology of the Ganjiang Delta channel is flow velocity, which is influenced by changes in the terrain slope. Flow velocity directly affects channel sinuosity, bending amplitude, and bifurcation (or confluence) frequency, and indirectly affects channel length and width. Full article

Bats are recognized as natural reservoirs for an array of diverse viruses, particularly coronaviruses, which have been linked to major human diseases like SARS-CoV and MERS-CoV. These viruses are believed to have originated in bats, highlighting their role in virus ecology and evolution. Our study focuses on the molecular characterization of bat-derived coronaviruses (CoVs) in Canada. Tissue samples from 500 bat specimens collected in Canada were analyzed using pan-coronavirus RT-PCR assays to detect the presence of CoVs from four genera: Alpha-CoVs, Beta-CoV, Gamma-CoV, and Delta-CoV. Phylogenetic analysis was performed targeting the RNA-dependent RNA polymerase (RdRP) gene. Our results showed an overall 1.4% CoV positivity rate in our bat sample size. Phylogenetic analysis based on the ~600 bp sequences led to the identification of an unclassified subgenus of Alpha-CoV, provisionally named Eptacovirus. The findings contribute to a better understanding of the diversity and evolution of CoVs found in the bat species of Canada. The current study underscores the significance of bats in the epidemiology of CoVs and enhances the knowledge of their genetic diversity and potential impact on global public health. Full article

This paper investigates statistical methods for estimating unknown lifetime parameters using a progressive first-failure censoring dataset. The failure mode’s lifetime distribution is modeled by the odd-generalized-exponential–inverse-Weibull distribution. Maximum-likelihood estimators for the model parameters, including the survival, hazard, and inverse hazard rate functions, are obtained, though they lack closed-form expressions. The Newton–Raphson method is used to compute these estimations. Confidence intervals for the parameters are approximated via the normal distribution of the maximum-likelihood estimation. The Fisher information matrix is derived using the missing information principle, and the delta method is applied to approximate the confidence intervals for the survival, hazard rate, and inverse hazard rate functions. Bayes estimators were calculated with the squared error, linear exponential, and general entropy loss functions, utilizing independent gamma distributions for informative priors. Markov-chain Monte Carlo sampling provides the highest-posterior-density credible intervals and Bayesian point estimates for the parameters and reliability characteristics. This study evaluates these methods through Monte Carlo simulations, comparing Bayes and maximum-likelihood estimates based on mean squared errors for point estimates, average interval widths, and coverage probabilities for interval estimators. A real dataset is also analyzed to illustrate the proposed methods. Full article