Street trees are an important part of urban facilities, and they can provide both aesthetic benefits and ecological benefits for urban environments. Ecological benefits of street trees now are ...attracting more attention because of environmental deterioration in cities. Conventional methods of evaluating ecological benefits require a lot of labor and time, and establishing an efficient and effective evaluating method is challenging. In this study, we investigated the feasibility to use mobile laser scanning (MLS) data to evaluate carbon sequestration and fine particulate matter (PM2.5) removal of street trees. We explored the approach to extract individual street trees from MLS data, and street trees of three streets in Nantong City were extracted. The correctness rates and completeness rates of extraction results were both over 92%. Morphological parameters, including tree height, crown width, and diameter at breast height (DBH), were measured for extracted street trees, and parameters derived from MLS data were in a good agreement with field-measured parameters. Necessary information about street trees, including tree height, DBH, and tree species, meteorological data and PM2.5 deposition velocities were imported into i-Tree Eco model to estimate carbon sequestration and PM2.5 removal. The estimation results indicated that ecological benefits generated by different tree species were considerably varied and the differences for trees of the same species were mainly caused by the differences in morphological parameters (tree height and DBH). This study succeeds in estimating the amount of carbon sequestration and PM2.5 removal of individual street trees with MLS data, and provides researchers with a novel and efficient way to investigate ecological benefits of urban street trees or urban forests.
In temperate forests, autumn leaf phenology signals the end of leaf growing season and shows large variability across tree-crowns, which importantly mediates photosynthetic seasonality, hydrological ...regulation, and nutrient cycling of forest ecosystems. However, critical challenges remain with the monitoring of autumn leaf phenology at the tree-crown scale due to the lack of spatially explicit information for individual tree-crowns and high (spatial and temporal) resolution observations with nadir view. Recent availability of the PlanetScope constellation with a 3 m spatial resolution and near-daily nadir view coverage might help address these observational challenges, but remains underexplored. Here we developed an integration of PlanetScope with drone observations for improved monitoring of crown-scale autumn leaf phenology in a temperate forest in Northeast China. This integration includes: 1) visual identification of individual tree-crowns (and species) from drone observations; 2) extraction of time series of PlanetScope vegetation indices (VIs) for each identified tree-crown; 3) derivation of three metrics of autumn leaf phenology from the extracted VI time series, including the start of fall (SOF), middle of fall (MOF), and end of fall (EOF); and 4) accuracy assessments of the PlanetScope-derived phenology metrics with reference from local phenocams. Our results show that (1) the PlanetScope-drone integration captures large inter-crown phenological variations, with a range of 28 days, 25 days, and 30 days for SOF, MOF, and EOF, respectively, (2) the extracted crown-level phenology metrics strongly agree with those derived from local phenocams, with a root-mean-square-error (RMSE) of 4.1 days, 3.0 days and 5.4 days for SOF, MOF, and EOF, respectively, and (3) PlanetScope maps large variations in autumn leaf phenology over the entire forest landscape with spatially explicit information. These results demonstrate the ability of our proposed method in monitoring the large spatial heterogeneity of crown-scale autumn leaf phenology in the temperate forest, suggesting the potential of using high-resolution satellites to advance crown-scale phenology studies over large geographical areas.
In tropical forests, leaf phenology signals leaf-on/off status and exhibits considerable variability across scales from a single tree-crown to the entire forest ecosystem. Such phenology signals ...importantly regulate large-scale biogeochemical cycles and regional climate. PlanetScope CubeSats data with a 3-m resolution and near-daily global coverage provide an unprecedented opportunity to monitor both fine- and ecosystem-scale phenology variability along large environmental gradients. However, a scalable method that accurately characterizes leaf phenology from PlanetScope with biophysically meaningful metrics remains lacking. We developed an index-guided, ecologically constrained autoencoder (IG-ECAE) method to automatically derive a deciduousness metric (percentage of upper tree canopies with leaf-off status within an image pixel) from PlanetScope. The IG-ECAE first estimated the reflectance spectra of leafy/leafless canopies based on their spectral indices characteristics, then used the derived reflectance spectra to guide an autoencoder deep learning method with additional ecological constraints to refine the reflectance spectra, and finally used linear spectral unmixing to estimate the relative abundance of leafless canopies (or deciduousness) per PlanetScope image pixel. We tested the IG-ECAE method at 16 tropical forest sites spanning multiple continents and a large precipitation gradient (1470–2819 mm year−1). Among these sites, we evaluated the PlanetScope-derived deciduousness against corresponding measures derived from WorldView-2 (n = 9 sites) and local phenocams (n = 9 sites). Our results show that PlanetScope-derived deciduousness agrees: 1) with that derived from WorldView-2 at the patch level (90 m × 90 m) with r2 = 0.89 across all sites; and 2) with that derived from phenocams to quantify ecosystem-scale seasonality with r2 ranging from 0.62 to 0.96. These results demonstrate the effectiveness and scalability of IG-ECAE in characterizing the wide variability in deciduousness across scales from pixels to forest ecosystems, and from a single date to the full annual cycle, indicating the potential for using high-resolution satellites to track the large-scale phenological patterns and response of tropical forests to climate change.
•An ecologically constrained deep learning method is developed for tropical phenology monitoring with PlanetScope.•The method is evaluated across 16 tropical sites spanning a large rainfall gradient.•The method assesses cross-scale phenology variability with a deciduousness metric.•The method demonstrates effectiveness and scalability with local measurements.
Cervical cancer is a leading cause of cancer-related mortality in females worldwide, necessitating urgent solutions for effective treatment. Paclitaxel (PTX), a natural diterpene alkaloid compound, ...has the ability to inhibit mitosis and induce programmed apoptosis in tumor cells. However, its toxicity and drug resistance limit its efficacy in certain cervical cancer patients. β-elemene (β-ELE) can reverse multidrug resistance by inhibiting ATP-binding cassette transporters, thereby enhancing chemotherapy drug retention. Therefore, we propose a combination therapy using PTX/β-ELE to improve chemotherapy sensitivity. To enhance targeted drug delivery, we developed M1-macrophage-membrane-coated nanoparticles (M1@PLGA/PTX/β-ELE) for co-delivery of PTX&β-ELE. Through both in vitro and in vivo cervical cancer models, we demonstrated that M1@PLGA/PTX/β-ELE effectively suppressed tumor progression and polarization of tumor-associated macrophages. Furthermore, H&E staining confirmed the high therapeutic biosafety of M1@PLGA/PTX/β-ELE as there was no significant damage observed in major organs throughout the entire therapeutic process. Overall, this study presents a targeted biomimetic nanoplatform and combinatorial strategy that synergistically enhances chemosensitivity in malignant tumors.
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Background:
The larval stages of
Echinococcus granulosus sensu lato
(
E. granulosus s.l
) infection can alter B cell function and affect host anti-infective immunity, but the underlying mechanism ...remains unclear. The newly emerging immunometabolism highlights that several metabolites are key factors in determining the fate of immune cells, which provides a new insight for exploring how larval
E. granulosus s.l
. infection remodels B cell function. This study investigated the metabolomic profiles of B cells in mice infected with
E. granulosus s.l
. protoscoleces (PSC).
Results:
Total CD19
+
B cells, purified from the spleen of infected mice, showed significantly increased production of IL-6, TNF-α, and IL-10 after exposure to LPS
in vitro
. Moreover, the mRNA expression of metabolism related enzymes in B cells was remarkably disordered post infection. In addition, differential metabolites were identified in B cells after infection. There were 340 differential metabolites (83 upregulated and 257 downregulated metabolites) identified in the positive ion model, and 216 differential metabolites (97 upregulated and 119 downregulated metabolites) identified in the negative ion mode. Among these, 64 differential metabolites were annotated and involved in 68 metabolic pathways, including thyroid hormone synthesis, the metabolic processes of glutathione, fructose, mannose, and glycerophospholipid. Furthermore, several differential metabolites such as glutathione, taurine, and inosine were validated to regulate the cytokine production in LPS stimulated B cells.
Conclusion:
Infection with the larval
E. granulosus s.l
. causes metabolic reprogramming in the intrinsic B cells of mice, which provides the first evidence for understanding the role and mechanism of B cells in parasite anti-infective immunity from the viewpoint of immunometabolism.
This paper constructs a sticky price Dynamic Stochastic General Equilibrium model with multi-regions. Producers from different regions would range in price rigidity, production function, the regional ...structures of intermediate inputs. That is, firms from each area, can get intermediates and investments from all the regions in the country following the empirical Multi-region Input-Output table in China. Different from the previous symmetry model, the model in this paper allows idiosyncratic regional dynamics to the national monetary shocks. This model is calculated by the Bayesian estimation method using the regional and aggregate China empirical data.
The proper management of radioactive iodine waste generated from nuclear energy has become one of the challenges in the sustainable development of nuclear power. With the continuous development of ...POPs materials, their high-efficiency iodine adsorption performance has been demonstrated to be related to the material's structural units and porous structure. In light of this, three two-dimensional porous organic polymers were synthesized using environmentally friendly non-metallic catalyzed coupling reactions. Their excellent chemical stability and nitrogen-rich porous structure endowed them with the ability to exhibit outstanding capture performance and recyclability in various media. Its iodine adsorption performance reached 3.81 g/g, 3.55 g/g and 3.19 g/g respectively. The research results provide a potential pathway for the design and synthesis of organic porous polymers with good chemical stability and iodine adsorption performance, showcasing the significant potential of POP-PDTE, POP-PDTK, and POP-PDTB in capturing radioactive pollutants.
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•Efficient synthesis of organic porous polymers with mild reaction conditions.•The POP-PDTE has iodine adsorption performance in various media.•The polymers exhibit amenable to cyclic utilization.
Iodine fission products with high radioactivity generated in the nuclear fuel fission process usually exist in the form of two isotopes, 131I and 129I. Since radioactive iodine is difficult to be ...effectively disposed of in the natural physical environment, it is imperative to formulate effective coping strategies to ensure the safe use of nuclear technology. Compared with other solid iodine adsorbents, porous organic polymers (POPs) have shown satisfactory results in terms of capture capability per unit mass and reusable due to their low density and high porosity. In view of this, this study adopted the Schiff base condensation reaction with in-situ generated imines under room temperature and took non-planar piperazine-based building blocks as reactants to synthesize a flexible polymer POP-PDTR and rigid polymers POP-PDTP and POP-PDTA. Iodine adsorption experiments have verified that their adsorption capacities can reach 3.90 g/g, 3.34 g/g, and 2.59 g/g, respectively. Their excellent chemical structural stability enables them to be reused for at least 5 cycles with stable performance. The results provide a new idea for designing and synthesizing persistent organic pollutant materials with excellent chemical stability and iodine adsorption performance.
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•Efficient synthesis of organic porous polymers at room temperature with mild reaction conditions.•The piperazine group was innovatively introduced as an iodine adsorption organic porous polymer, and showed excellent iodine adsorption performance.•The polymers exhibit robust iodine adsorption capabilities, amenable to cyclic utilization, and hold promise for large-scale production endeavors.
Proteomics is increasingly used for exploring disease biomarkers and therapeutic targets. The data-independent acquisition (DIA) method collects all peptide signals in a sample, and provides a ...convenient way to archive disease-related molecular features for further exploration. In this study, we first established a high-coverage human hepatocellular carcinoma (HCC) spectral library containing 9393 protein groups, 119,903 peptides. Furthermore, we optimised the DIA method with respect to four key parameters: settings for mass spectrometry acquisition, gradient length, amount of sample loading, and length of analytical column. More than 6000 proteins from HepG2 cells could be stably quantified using the optimised one-shot DIA approach with a 2 h gradient time. One-shot DIA identified a similar number of proteins as did multi-fraction data-dependent acquisition (DDA) from the same group of HCC samples, but at a quarter of the total acquisition time. DIA data could recapture the classification results obtained from DDA data, thus paving the way for large-scale, multi-centre proteomics analysis of clinical samples.
The organ-specific spectral library for HCC and the optimised 2 h DIA approach met the urgent demands for large-scale quantitative proteomics analysis of HCC clinical samples. Compared with multi-fraction-DDA, the optimised one-shot DIA could reach a similar identification while consuming shorter acquisition time, thus making it possible to analyse thousands of clinical samples.
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•A high-coverage HCC spectral library with 9393 protein was established.•Optimised data-independent acquisition (DIA) methods were built on a 30-cm column.•One-shot DIA method quantified >6000 proteins from HepG2 cells in 2 h gradient.•Reanalysis of DDA data recaptured the subtyping result with much shorter time.
Foliar functional traits are essential for understanding plant adaptation strategies and ecosystem function. Due to limited in-situ observational data, there is a growing interest in upscaling these ...traits from field sites to regional and global levels. However, limitations persist: (1) global/national scale upscaling that relies on plant functional type (PFT) maps, environmental variables or coarse resolution multispectral images, which fail to capture local-scale trait variability; (2) airborne imaging spectroscopy that enables high-resolution and accurate mapping but is restricted to site scale and is costly; and (3) multispectral satellites like Sentinel-2 that offer global coverage but have limited spectral bands and resolution. While previous research has demonstrated the connection between traits and vegetation phenology, our study seeks to build upon this foundation by further exploring the integration of phenological information for large-scale trait prediction. We examined the integration of Sentinel-2 data with its time series (for phenology information) to map 12 foliar functional traits across 14 National Ecological Observatory Network (NEON) sites in the eastern United States. Our results show that time-series Sentinel-2 models effectively capture the variance in these 12 traits (R2 = 0.60–0.80) when compared with benchmark trait data generated by state-of-the-art airborne imaging spectroscopy. The models adequately capture considerable trait variations observed within sites and PFTs. Our approach outperforms existing methods that rely on environmental variables, or a single Sentinel-2 image as predictors across examined NEON sites in eastern United States. Interestingly, including environmental variables in our models does not significantly improve predictive power. Further analysis reveals that a ‘fast-slow’ principal axis predominantly explains the covariation in Enhanced Vegetation Index amplitude (a proxy for leaf longevity), leaf mass per area, and leaf nitrogen content across PFTs. This finding highlights the importance of incorporating phenological information for trait mapping and suggests a potential mechanism underlying these spectra-based models. Our proposed method, which simultaneously achieves high accuracy, large-scale scalability, and high spatial resolution, represents a promising avenue for future global trait mapping. Validation on a larger scale to fully realize its potential in addressing fundamental ecological questions will be a key future focus.
•Time-series Sentinel-2 data accurately map 12 foliar traits across 14 NEON sites.•Spectra-phenology integration advances trait mapping accuracy over previous methods.•Biophysical and LES mechanism of the proposed method is consistent with literature.•Global Sentinel-2 archives enable the scalability for large-scale trait mapping.
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