The small molecule inhibitor of SARS-CoV-2 3CLpro EDP-235 prevents viral replication and transmission in vivo.

The COVID-19 pandemic has led to the deaths of millions of people and severe global economic impacts. Small molecule therapeutics have played an important role in the fight against SARS-CoV-2, the virus responsible for COVID-19, but their efficacy has been limited in scope and availability, with many people unable to access their benefits, and better options are needed. EDP-235 is specifically designed to inhibit the SARS-CoV-2 3CLpro, with potent nanomolar activity against all SARS-CoV-2 variants to date, as well as clinically relevant human and zoonotic coronaviruses. EDP-235 maintains potency against variants bearing mutations associated with nirmatrelvir resistance. Additionally, EDP-235 demonstrates a ≥ 500-fold selectivity index against multiple host proteases. In a male Syrian hamster model of COVID-19, EDP-235 suppresses SARS-CoV-2 replication and viral-induced hamster lung pathology. In a female ferret model, EDP-235 inhibits production of SARS-CoV-2 infectious virus and RNA at multiple anatomical sites. Furthermore, SARS-CoV-2 contact transmission does not occur when naïve ferrets are co-housed with infected, EDP-235-treated ferrets. Collectively, these results demonstrate that EDP-235 is a broad-spectrum coronavirus inhibitor with efficacy in animal models of primary infection and transmission.

[Characteristics of Soil Organic Carbon and Its Influencing Factors of Different Plant Communities in the Yellow River Delta].

Changes in soil organic carbon （SOC） are of great importance to the evolution of soil quality. The distribution characteristics of soil organic carbon （SOC）, easily oxidizable organic carbon （EOC）, dissolved organic carbon （DOC）, and particulate organic carbon （POC） were investigated in the 0-50 cm soil layer of the Phragmites australis, Suaeda salsa, and Tamarix chinensis communities of the supratidal zone in the Yellow River Delta as the research subjects. Then, the composition and sources of soil dissolved organic matter （DOM） were analyzed based on the UV-vis spectroscopy, three-dimensional excitation emission matrix spectroscopy, and parallel factor analysis （PARAFAC）. Finally, the key factors affecting the characteristics of soil organic carbon and DOM fractions of different plant communities were finally revealed in combination with the physicochemical properties of the soil. The results showed that： ① Comparing different communities, the S. salsa community had the highest ω（SOC） at 7.53 g·kg-1, the T. chinensis community had the highest ω（DOC） at 0.98 g·kg-1, and the P. australis community had significantly higher ω（EOC） and ω（POC） than those of the S. salsa and T. chinensis communities at 1.47 g·kg-1 and 0.65 g·kg-1, respectively. The vertical distribution showed a tendency to decrease with deeper soil layers, except for POC concentration. ② The main components of soil DOM of the P. australis, S. salsa, and T. chinensis communities were humus, protein-like substances, and fulvic acid-like substances, of which exogenous components accounted for 55.80%, 56.41%, and 52.81% in the above communities, respectively. ③ Comparing different communities, the humification degree of the P. australis community was significantly higher than that of the S. salsa and T. chinensi communities, but its aromaticity and proportion of biological sources were significantly lower than those of the T. chinensi community. On the vertical profile of the soil, DOM aromaticity and humification degree gradually increased with the deepening of the soil layer, and the deeper soils were mainly dominated by small molecular weight DOM with a lower proportion of hydrophobic fraction. ④ Redundant analysis showed that N （P<0.01）, NO2--N （P<0.01）, and NH4+-N （P<0.05） were the key factors affecting the changes in soil organic carbon and DOM fractions.

[Differences in Soil Fertility and Bacterial Community Structure Between Carbon Inputs such as Biochar and Organic Fertilizer and Their Relationship].

The potato planting area of Guizhou Province ranks second in China. However, due to factors such as climatic conditions and unbalanced fertilization, soil organic matter in potato fields is consumed rapidly and has a large deficit, which affects soil biological function and soil fertility. Biochar and organic fertilizer are effective ways to supplement foreign aid organic matter to improve soil quality. However, the differences in soil fertility and microbial community structure and their relationships under the conditions of organic fertilizer or biochar combined with chemical fertilizer are not clear. In this study, three treatments of conventional fertilization （NPK）, increased application of biochar （NPKB）, and increased application of organic fertilizer （NPKO） were set up to investigate the characteristics of potato rhizosphere soil, bacterial community composition, and diversity； to analyze the effects of these factors on the soil integrated fertility index； and to explore the direct and indirect effects of IFI on soil fertility and bacterial community structure differences between treatments and their driving factors. The results showed that soil pH, available phosphorus （AP）, available potassium （AK）, total nitrogen （TN）, organic carbon （SOC）, and C/N ratio were significantly higher in the NPKB and NPKO treatments than in the NPK treatment （P<0.05）. Soil IFI was greatest for NPKO, followed by NPKB and least for the NPK treatment. A total of 8 214 ASVs were obtained from all the soil samples, belonging to 26 phyla, 75 classes, 165 orders, 176 families, and 251 genera （excluding unidentified fungi）. Proteobacteria, Actinobacteria, and Chloroflexi were the dominant phyla, accounting for 54.85% of all ASVs. Compared to that in the NPK and NPKB treatments, the NPKO treatment had the highest bacterial diversity and number of significantly different taxa, and soil AN, AP, AK, SOC, TN, and IFI were significant correlates of bacterial diversity index （P<0.05）. Additionally, pH, TN, and SOC were significant influencers of bacterial taxa differences （P<0.05）, with importance ranked as TN （70.59%） > SOC （49.42%） > pH （27.08%）. Structural equations suggested that pH-related soil properties and bacterial community diversity were the direct pathways influencing IFI, and soil pH-related soil characteristics could also indirectly affect IFI by affecting bacterial Shannon diversity. These results indicate that soil fertility and bacterial community structure were significantly different and correlated between the biochar and organic fertilizer addition treatments and that pH and bacterial community diversity were the key factors influencing IFI, with the NPKO treatment in particular having the best effect on improving IFI. Considering the effect of soil fertilization and the functional group of bacteria, NPKO is the recommended combination for the best synergistic effect of soil fertilization, that is, N 150 kg·hm-2+P2O5 135 kg·hm-2+K2O 135 kg·hm-2+organic fertilizer 6.6 t·hm-2.

[Effects of Replacing Chemical Nitrogen Fertilizer with Organic Fertilizer on Active Organic Carbon Fractions, Enzyme Activities, and Crop Yield in Yellow Soil].

Taking the typical yellow soil in Guizhou as the research object, four treatments were set up： no fertilization （CK）, single application of chemical fertilizer （NP）, 50% organic fertilizer instead of chemical nitrogen fertilizer [1/2（NPM）], and 100% organic fertilizer instead of chemical nitrogen fertilizer （M）. The effects of organic fertilizer instead of chemical nitrogen fertilizer on organic carbon and its active components, soil carbon pool management index, soil enzyme activity, and maize and soybean yield in yellow soil were studied in order to provide theoretical basis for scientific fertilization and soil quality improvement in this area. The results showed that the replacement of chemical nitrogen fertilizer by organic fertilizer significantly increased soil pH, organic carbon （SOC）, total nitrogen （TN） content, and C/N ratio. Compared with those in the CK and NP treatments, the content and distribution ratio of soil active organic carbon components and soil carbon pool management index （CPMI） were improved by replacing chemical nitrogen fertilizer with organic fertilizer, and the effect of replacing chemical nitrogen fertilizer with 50% organic fertilizer was the best. Compared with those in the NP treatment, the 1/2 （NPM） treatment significantly increased the contents of soil readily oxidizable organic carbon （ROC333, ROC167）, dissolved organic carbon （DOC）, and microbial biomass carbon （MBC） by 22.90%, 8.10%, 29.32%, and 23.22%, respectively. Compared with those under the CK and NP treatments, organic fertilizer instead of chemical nitrogen fertilizer increased soil enzyme activities. The activities of catalase, urease, sucrase, and phosphatase in the 1/2 （NPM） treatment were significantly increased by 21.89%, 8.24%, 34.91%, and 18.78%, respectively, compared with those in the NP treatment. Compared with that of the NP treatment, the maize yield of the 1/2 （NPM） and M treatments was significantly increased by 44.15% and 17.39%, respectively. There was no significant difference in soybean yield among different fertilization treatments. Correlation analysis showed that soil SOC was significantly positively correlated with ROC333, ROC167, ROC33, DOC, MBC, and soil active organic carbon components, and CPMI was significantly positively correlated with soil organic carbon and its active components （P<0.01）. Corn yield was significantly positively correlated with soil enzyme activity, CPMI, total organic carbon, and its active components （P<0.05）. Therefore, from the perspective of yield increase and soil fertility, 50% organic fertilizer instead of chemical nitrogen fertilizer was conducive to improving soil quality and soil fertility, which is the key fertilization technology to achieve a high yield of crops in the yellow soil area of Anshun, Guizhou.

[Effects of Straw and Biochar Amendments on Characteristics of Soil Fungal Community and Organic Carbon Pool in Jasminum sambac Garden].

In order to elucidate the changes in the soil fungal community and soil organic carbon components of a Jasminum sambac garden after straw and biochar application, we measured the organic carbon components and soil fungal community of the 0-15 cm soil layer in a J. sambac garden, which was divided into a control group, straw treatment group, and biochar treatment group. The carbon pool management index （CPMI） was also calculated. The results showed that the diversity of the soil fungal community was decreased after straw and biochar application, and the structure of dominant fungal genera was changed in each treatment. The soil fungal community structure in the biochar treatment was significantly different from that in the straw treatment and control groups. Redundancy analysis （RDA） showed that soil fungal community structure was mainly affected by soil bulk density, C∶N, salinity, and TN. Secondly, compared with that in the control group, soil labile organic carbon （LOC） in the straw treatment group was significantly increased by 87.44% （P<0.05）, whereas soil dissolved organic carbon （DOC） and microbial biomass carbon （MBC） in the biochar treatment group were significantly increased by 22.27% and 23.17% （P<0.05）, respectively. Further, compared with that in the control group, the carbon pool activity （L） under straw treatment was significantly increased （P<0.05）, and the carbon pool index （CPI） under biochar treatment was significantly increased （P<0.05）. Spearman correlation analysis showed that the distribution characteristics of soil organic carbon active components were regulated by the dominant fungi. FUNGuild functional prediction results showed that saprophytic and its facultative nutritional fungi had an important impact on soil organic carbon active components and carbon pool management index after straw and biochar application.

The use of the self-organizing map (SOM) methodology to study the dissolved organic matter (DOM) in different water body types.

This study investigated the characteristics of dissolved organic matter (DOM) in two distinct water bodies, through the utilization of three-dimensional fluorescence spectroscopy coupled with self-organizing map (SOM) methodology. Specifically, this analysis concentrated on neurons 3, 14, and 17 within the SOM model, identifying notable differences in the DOM compositions of a coal subsidence water body (TX) and the MaChang Reservoir (MC). The humic substance content of DOM TX exceeded that of MC. The origin of DOM in TX was primarily linked to agricultural inputs and rainfall runoff, whereas the DOM in MC was associated with human activities, displaying distinctive autochthonous features and heightened biological activity. Principal component analysis revealed that humic substances dominated the DOM in TX, while the natural DOM in MC was primarily autochthonous. Furthermore, a multiple linear regression model (MLR) determined that external pollution was responsible for 99.11% of variation in the humification index (HIX) of water bodies.

The Impact of Beeswax and Glycerol Monolaurate on Camellia Oil Oleogel's Formulation and Application in Food Products.

This study assessed the nutritional profile of camellia oil through its fatty acid composition, highlighting its high oleic acid content (81.4%), followed by linoleic (7.99%) and palmitic acids (7.74%), demonstrating its excellence as an edible oil source. The impact of beeswax (BW) and glycerol monolaurate (GML) on camellia oil oleogels was investigated, revealing that increasing BW or GML concentrations enhanced hardness and springiness, with 10% BW oleogel exhibiting the highest hardness and springiness. FTIR results suggested that the structure of the oleogels was formed by interactions between molecules without altering the chemical composition. In biscuits, 10% BW oleogel provided superior crispness, expansion ratio, texture, and taste, whereas GML imparted a distinct odor. In sausages, no significant differences were observed in color, water retention, and pH between the control and replacement groups; however, the BW group scored higher than the GML group in the sensory evaluation. The findings suggest that the BW oleogel is an effective fat substitute in biscuits and sausages, promoting the application of camellia oil in food products.

Bioremediation of organic pollutants by laccase-metal-organic framework composites: A review of current knowledge and future perspective.

Immobilized laccases are widely used as green biocatalysts for bioremediation of phenolic pollutants and wastewater treatment. Metal-organic frameworks (MOFs) show potential application for immobilization of laccase. Their unique adsorption properties provide a synergic effect of adsorption and biodegradation. This review focuses on bioremediation of wastewater pollutants using laccase-MOF composites, and summarizes the current knowledge and future perspective of their biodegradation and the enhancement strategies of enzyme immobilization. Mechanistic strategies of preparation of laccase-MOF composites were mainly investigated via physical adsorption, chemical binding, and de novo/co-precipitation approaches. The influence of architecture of MOFs on the efficiency of immobilization and bioremediation were discussed. Moreover, as sustainable technology, the integration of laccases and MOFs into wastewater treatment processes represents a promising approach to address the challenges posed by industrial pollution. The MOF-laccase composites can be promising and reliable alternative to conventional techniques for the treatment of wastewaters containing pharmaceuticals, dyes, and phenolic compounds. The detailed exploration of various immobilization techniques and the influence of MOF architecture on performance provides valuable insights for optimizing these composites, paving the way for future advancements in environmental biotechnology. The findings of this research have the potential to influence industrial wastewater treatment and promoting cleaner treatment processes and contributing to sustainability efforts.

Coordination of elemental sulfur and organic carbon source stimulates simultaneous nitrification and denitrification toward low C/N ratio wastewater.

The feasibility of inducing simultaneous nitrification and denitrification (SND) by S0 for low carbon to nitrogen (C/N) ratio wastewater remediation was investigated. Compared with S0 and/or organics absent systems (-3.4 %∼5.0 %), the higher nitrogen removal performance (18.2 %∼59.8 %) was achieved with C/N ratios and S0 dosages increasing when S0 and organics added simultaneously. The synergistic effect of S0 and organics stimulated extracellular polymeric substances secretion and weakened intermolecular binding force of S0, facilitating S0 bio-utilization and reducing the external organics requirement. It also promoted microbial metabolism (0.16 âˆ¼ 0.24 µg O2/(g VSS·h)) and ammonia assimilation (5.9 %∼20.5 %), thereby enhancing the capture of organics and providing more electron donors for SND. Furthermore, aerobic denitrifiers (15.91 %∼27.45 %) and aerobic denitrifying (napA and nirS) and ammonia assimilating genes were accumulated by this synergistic effect. This study revealed the mechanism of SND induced by coordination of S0 and organics and provided an innovative strategy for triggering efficient and stable SND.

Enhancing Molecular Characterization of Dissolved Organic Matter by Integrative Direct Infusion and Liquid Chromatography Nontargeted Workflows.

Dissolved organic matter (DOM) in aquatic systems is a highly heterogeneous mixture of water-soluble organic compounds, acting as a major carbon reservoir driving biogeochemical cycles. Understanding DOM molecular composition is thus of vital interest for the health assessment of aquatic ecosystems, yet its characterization poses challenges due to its complex and dynamic chemical profile. Here, we performed a comprehensive chemical analysis of DOM from highly urbanized river and seawater sources and compared it to drinking water. Extensive analyses by nontargeted direct infusion (DI) and liquid chromatography (LC) high-resolution mass spectrometry (HRMS) through Orbitrap were integrated with novel computational workflows to allow molecular- and structural-level characterization of DOM. Across all water samples, over 7000 molecular formulas were calculated using both methods (∼4200 in DI and ∼3600 in LC). While the DI approach was limited to molecular formula calculation, the downstream data processing of MS2 spectral information combining library matching and in silico predictions enabled a comprehensive structural-level characterization of 16% of the molecular space detected by LC-HRMS across all water samples. Both analytical methods proved complementary, covering a broad chemical space that includes more highly polar compounds with DI and more less polar ones with LC. The innovative integration of diverse analytical techniques and computational workflow introduces a robust and largely available framework in the field, providing a widely applicable approach that significantly contributes to understanding the complex molecular composition of DOM.

Natural Attenuation of Groundwater Uranium in Post-Neutral-Mining Sites Evidenced from Multiple Isotopes and Dissolved Organic Matter.

Although natural attenuation is an economic remediation strategy for uranium (U) contamination, the role of organic molecules in driving U natural attenuation in postmining aquifers is not well-understood. Groundwaters were sampled to investigate the chemical, isotopic, and dissolved organic matter (DOM) compositions and their relationships to U natural attenuation from production wells and postmining wells in a typical U deposit (the Qianjiadian U deposit) mined by neutral in situ leaching. Results showed that Fe(II) concentrations and δ34SSO4 and δ18OSO4 values increased, but U concentrations decreased significantly from production wells to postmining wells, indicating that Fe(III) reduction and sulfate reduction were the predominant processes contributing to U natural attenuation. Microbial humic-like and protein-like components mediated the reduction of Fe(III) and sulfate, respectively. Organic molecules with H/C > 1.5 were conducive to microbe-mediated reduction of Fe(III) and sulfate and facilitated the natural attenuation of dissolved U. The average U attenuation rate was -1.07 mg/L/yr, with which the U-contaminated groundwater would be naturally attenuated in approximately 11.2 years. The study highlights the specific organic molecules regulating the natural attenuation of groundwater U via the reduction of Fe(III) and sulfate.

Field Detection of Uranyl in Coastal Water of China Using a Portable Device via DNA Photocleavage.

The urgent need for field detection of uranium in seawater is 2-fold: to provide prompt guidance for uranium extraction and to prevent human exposure to nuclear radiation. However, current methods for this purpose are largely hindered by bulky instrumentation, high costs of developed materials, and severe matrix interferences, which limit their further application in the field. Herein, we demonstrated a portable and label-free strategy for the field detection of uranyl in seawater based on the efficient photocleavage of DNA. Further experiments confirmed the generation of ultraviolet (UV) light-induced reactive oxygen species (ROS), such as O2•- and •OH, which fragmented oligomeric DNA in the presence of uranyl and UV light. Detailed studies showed that DNA significantly enhances uranyl absorption in the UV-visible region, leading to the generation of more ROS. A fluorescence system for the selective detection of uranyl in seawater was established by immobilizing two complementary oligonucleotides with the fluorescent dye SYBR Green I. The strategy of UV-induced photocleavage offers high selectivity, excellent interference immunity, and high sensitivity for uranyl, with a detection limit of 6.8 nM. Additionally, the fluorescence can be visually detected using a 3D-printed miniaturized device integrated with a smartphone. This method has been successfully applied to the on-site detection of uranyl in seawater in 18 Chinese coastal cities and along the coast of Hainan Island within 3 min for a single sample. The sample testing and field analysis results indicate that this strategy has promising potential for real-time monitoring of trace uranyl in China's coastal waters. It is expected to be utilized for the rapid assessment of nuclear contamination and nuclear engineering construction.

Oxidation and mineralization rates of harmful organic chemicals in hydroxyl radical induced reactions.

In most of advanced oxidation processes (AOPs) used to destroy harmful organic chemicals in water/wastewater hydroxyl radical (•OH) reactions oxidize (increasing the oxygen/carbon ratio in the molecules) and mineralize (transforming them to inorganic molecules, H2O, CO2, etc.) these contaminants. In this paper, we used the radiolysis of water to produce •OH and characterised the rate of oxidation and mineralization by the dose dependences of the Chemical Oxygen Demand (COD) and Total Organic Carbon (TOC) content values. Analysis of the dose dependences for 34 harmful organic compounds showed large differences in the oxidation and mineralization rates and these parameters are characteristic to the given group of chemicals. E.g., the rate of oxidation is relatively low for fluoroquinolone antibiotics; it is high for ß-blocker medicines. Mineralization rates are low for both fluoroquinolones and ß-blockers. The one-electron-oxidant •OH in most cases induces two - four-electron-oxidations. Most of the degradation takes place gradually, through several stable molecule intermediates. However, based on the results it is likely, that some part of the oxidation and mineralization takes place parallel. The organic radicals formed in •OH reactions react with several O2 molecules and release several inorganic fragments during the radical life cycle.

Meta-Analysis and Machine Learning Models for Anaerobic Biodegradation Rates of Organic Contaminants in Sediments and Sludge.

Anaerobic biodegradation rates (half-lives) of organic chemicals are pivotal for environmental risk assessment and remediation. Traditional experimental evaluation, constrained by prolonged, oxygen-free conditions, struggles to keep pace with emerging contaminants. Data-driven machine learning (ML) models serve as promising complements. However, reported quantitative structure-biodegradation relationships or ML models on anaerobic biodegradation are mostly based on small data sets (<100 records) and neglect experimental conditions, usually achieving compromised predictions. This work aimed to develop ML models for predicting the biodegradation half-lives of organic pollutants in anaerobic environments (i.e., sediment/soil and sludge). Focusing on important features of both chemicals and experimental conditions, we first curated two data sets, one for sediment/soil (SED) and the other for sludge (SLD), covering 978 records for 206 chemicals from the literature, and then conducted a meta-analysis. Next, we built a binary classification (half-life of 30 days as the cutoff) model with an accuracy of 81% and a regression model with R2 of 0.56 for SED based on LightGBM (80% and 0.31 for SLD based on Extra tree, respectively). The model interpretations underscored the significance of experimental conditions (e.g., temperature and inoculum dosage), as evidenced by their high feature importance, and the models were found to correctly capture the effects of chemical substructures, for example, branched structures and aromatic rings prolonged half-lives while methyl group and ortho-substitution on rings shortened half-lives. The applicability domains of the models were also defined, resulting in reasonable prediction for the half-lives of 41% (SED) or 67% (SLD) of over 4000 persistent, bioaccumulative, and toxic chemicals. Overall, this study pioneers ML models for predicting the anaerobic degradation half-lives, offering valuable support for future evaluation and implementation of chemical anaerobic biodegradation.

The Influence of Simulated Organic Matter on the Inactivation of Viruses: A Review.

Viruses impose a significant public health burden globally, and one of the key elements in controlling their transmission is the ability to inactivate them using disinfectants. However, numerous challenges to inactivating foodborne viruses exist due to inherent viral characteristics (such as recalcitrance to commonly used inactivation agents) and external factors (such as improper cleaning before application of inactivation agent, improper contact time, etc.). Given the potential for improper application of disinfectants (such as shorter than recommended contact time, improper disinfectant concentration, etc.), understanding the performance of a disinfectant in the presence of an organic load is important. To accomplish this, the introduction of simulated organic loads is often used when studying the efficacy of a disinfectant against different viruses. However, the different types of simulated organic loads used in foodborne virus inactivation studies or their relative effects on inactivation have not been reviewed. The purpose of this review is to survey different simulated organic load formulations used in studying foodborne virus inactivation, as well as present and compare the influence of these different formulations on viral inactivation. The findings included in this review suggest that many simulated organic load formulations can reduce disinfectants' efficacy against viruses. Based on the findings in this review, blood, particularly serum or feces, are among the most commonly used and efficacious forms of simulated organic load in many tests.

Impact of Air Bubbles on the Saltiness Perception of NaCl-Loaded Oleogel-Stabilized Water-in-Oil Emulsions.

Reducing salt intake without affecting the saltiness perception remains a great challenge for the food industry. Herein, the demulsification of water droplets and air bubbles was controlled to modulate the release of sodium from oleogel-stabilized water-in-oil emulsions (OGEs) stabilized by monoglyceride crystals. The effect of monoglycerides with carbon chain length (glycerol monolaurate-GML, glyceryl monostearate-GMS, and glycerol monopalmitate-GMP) and homogenization methods (hand-shaking or high-speed blender) on sodium release and saltiness was investigated by in vitro and in vivo oral processing tests. Milky-white stable emulsions were formed with both water droplets and air bubbles dispersing in the oil phase, regardless of the selected homogenization methods. Air bubbles were more unstable than water droplets during oral digestion. GML OGEs with more and larger air bubbles and the lowest hardness exhibited the highest sodium release rate and the strongest saltiness, independent of homogenization methods. The balance between air bubbles and water droplets in the GMS and GMP OGEs caused slower sodium release and lower saltiness. Overall, the presence of air bubbles in NaCl-loaded W/O oleogel-based emulsions was shown to have important implications for tailoring their sodium release and saltiness.

Chitosan-Based Oleogels: Emulsion Drying Kinetics and Physical, Rheological, and Textural Characteristics of Olive Oil Oleogels.

Oleogels are of high interest as promising substitutes for trans fats in foods. An emulsion-templated method was used to trap olive oil in the chitosan crosslinked with vanillin matrix. Oil in water emulsions (50:50 w/w) with different chitosan content (0.7 and 0.8% w/w) with a constant vanillin/chitosan ratio (1.3) were air-dried at different temperatures (50, 60, 70, and 80 °C) and freeze-dried (-26 °C and 0.1 mbar) to produce oleogels. Only falling rate periods were determined during air-drying kinetics and were successfully modeled with empirical and diffusional models. At a drying temperature of 70 °C, the drying kinetics were the fastest. The viscoelasticity of oleogels showed that the elastic modulus significantly increased after drying at 60 and 70 °C, and those dried at 50 °C and freeze-dried were weaker. All oleogels showed high oil binding capacity (>91%), but the highest values (>97%) were obtained in oleogels with a threshold elastic modulus (50,000 Pa). The oleogels' color depended on the drying temperature and chitosan content (independent of the drying method). Significant differences were observed between air-dried and freeze-dried oleogels with respect to oxidative stability. Oxidation increased with the air-drying time regardless of chitosan content. The found results indicated that drying conditions must be carefully selected to produce oleogels with specific features.

Spatiotemporal response of the optical characteristics of dissolved organic matter to seasonality and land use in tropical island rivers.

Dissolved organic matter (DOM), a pivotal component in the global carbon cycle, plays a crucial role in maintaining the productivity and functionality of aquatic ecosystems. However, the driving factors of variations in the properties of riverine DOM in tropical islands still remain unclear. In this study, the spatiotemporal response of the optical characteristics of riverine DOM to seasonality and land use on Hainan Island in southern China was investigated. Our results revealed that DOM in the rivers of Hainan Island exhibited a relatively high proportion of fulvic acid and demonstrated strong terrestrial sources. The optical properties of DOM exhibited significant variations both seasonally and spatially. Land use exerted a dominant influence on riverine DOM. Specifically, during the wet season, riverine DOM exhibited larger molecular weight, increased chromophoric DOM (CDOM) abundance, and higher Fmax compared to the dry season. Furthermore, riverine DOM influenced by grassland and farmland showed higher CDOM abundance, Fmax, and humification degree in contrast to those impacted by forest and urban. Random forest and correlation analysis results indicated that grassland and farmland enhanced the Fmax of DOM by increasing levels of TP, NO3--N, Chl a, and NH4+-N in the dry season. However, during the wet season, the increased Fmax of DOM induced by grassland and farmland relied on the increments of Chl a and TP concentrations. This study improves our understanding of the spatiotemporal fluctuations of DOM in the rivers of Hainan Island, highlighting the effects of season and land use on DOM. It offers valuable support for improving water quality and contributes to enhancing human comprehension of the global carbon cycle.

[Estimation of soil moisture and organic matter content in saline alkali farmland by using CARS algorithm combined with covariates]. / 利用CARS算法联合协变量估算盐碱农田土壤水分和有机质含量.

Rapid acquisition of the data of soil moisture content (SMC) and soil organic matter (SOM) content is crucial for the improvement and utilization of saline alkali farmland soil. Based on field measurements of hyperspectral reflectance and soil properties of farmland soil in the Hetao Plain, we used a competitive adaptive reweighted sampling algorithm (CARS) to screen sensitive bands after transforming the original spectral reflectance (Ref) into a standard normal variable (SNV). Strategies Ⅰ, Ⅱ, and Ⅲ were used to model the input variables of Ref, Ref SNV, Ref-SNV+ soil covariate (SC), and digital elevation model (DEM). We constructed SMC and SOM estimation models based on random forest (RF) and light gradient boosting machine (LightGBM), and then verified and compared the accuracy of the models. The results showed that after CARS screening, the sensitive bands of SMC and SOM were compressed to below 3.3% of the entire band, which effectively optimized band selection and reduced redundant spectral information. Compared with the LightGBM model, the RF model had higher accuracy in SMC and SOM estimation, and the input variable strategy Ⅲ was better than Ⅱ and Ⅰ. The introduction of auxiliary variables effectively improved the estimation ability of the model. Based on comprehensive analysis, the coefficient of determination (Rp2), root mean square error (RMSE), and relative analysis error (RPD) of the SMC estimation model validation based on strategy Ⅲ-RF were 0.63, 3.16, and 2.01, respectively. The SOM estimation models based on strategy Ⅲ-RF had Rp2, RMSE, and RPD of 0.93, 1.15, and 3.52, respectively. The strategy Ⅲ-RF model was an effective method for estimating SMC and SOM. Our results could provide a new method for the rapid estimation of soil moisture and organic matter content in saline alkali farmland.