Application of metal-organic frameworks and their derivates for thermal-catalytic C1 molecules conversion.

One-carbon (C1) catalysis refers to the conversion of compounds with a single carbon atom, especially carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4), into clean fuels and valuable chemicals via catalytic strategy is crucial for sustainable and green development. Among various catalytic strategies, thermal-driven process seems to be one of the most promising pathways for C1 catalysis due to the high efficiency and practical application prospect. Notably, the rational design of thermal-driven C1 catalysts plays a vital role in boosting the targeted products synthesis of C1 catalysis, which relies heavily on the choice of ideal active site support, catalyst fabrication precursor, and catalytic reaction field. As a novel crystalline porous material, metal-organic frameworks (MOFs) has made significant progress in the design and synthesis of various functional nanomaterials. However, the application of MOFs in C1 catalysis faces numerous challenges, such as thermal stability, mechanical strength, yield of MOFs, and so on. To overcome these limitations and harness the advantages of MOFs in thermal-driven C1 catalysis, researchers have developed various catalyst/carrier preparation strategies. In this review, we provide a concise overview of the recent advancements in the conversion of CO, CO2, and CH4 into clean fuels and valuable chemicals via thermal-catalytic strategy using MOFs-based catalysts. Furthermore, we discuss the main challenges and opportunities associated with MOFs-based catalysts for thermal-driven C1 catalysis in the future.

Arsenic stress on soil microbial nutrient metabolism interpreted by microbial utilization of dissolved organic carbon.

In a 120-day microcosm incubation experiment, we investigated the impact of arsenic contamination on soil microbial nutrient metabolism, focusing on carbon cycling processes. Our study encompassed soil basal respiration, key enzyme activities (particularly, ß-1,4-N-acetylglucosaminidase and phosphatases), microbial biomass, and community structure. Results revealed a substantial increase (1.21-2.81 times) in ß-1,4-N-acetylglucosaminidase activities under arsenic stress, accompanied by a significant decrease (9.86%-45.20%) in phosphatase activities (sum of acid and alkaline phosphatases). Enzymatic stoichiometry analysis demonstrated the mitigation of microbial C and P requirements in response to arsenic stress. The addition of C-sources alleviated microbial C requirements but exacerbated P requirements, with the interference amplitude increasing with the complexity of the C-source. Network analysis unveiled altered microbial nutrient requirements and an increased resistance process of microbes under arsenic stress. Microbial carbon use efficiency (CUE) and basal respiration significantly increased (1.17-1.59 and 1.18-3.56 times, respectively) under heavy arsenic stress (500 mg kg-1). Arsenic stress influenced the relative abundances of microbial taxa, with Gemmatimonadota increasing (5.5-50.5%) and Bacteroidota/ Nitrospirota decreasing (31.4-47.9% and 31.2-63.7%). Application of C-sources enhanced microbial resistance to arsenic, promoting cohesion among microorganisms. These findings deepen our understanding of microbial nutrient dynamics in arsenic-contaminated areas, which is crucial for developing enzyme-based toxicity assessment systems for soil arsenic contamination.

Quantification of the three-dimensional root system architecture using an automated rotating imaging system.

BACKGROUND: Crop breeding based on root system architecture (RSA) optimization is an essential factor for improving crop production in developing countries. Identification, evaluation, and selection of root traits of soil-grown crops require innovations that enable high-throughput and accurate quantification of three-dimensional (3D) RSA of crops over developmental time. RESULTS: We proposed an automated imaging system and 3D imaging data processing pipeline to quantify the 3D RSA of soil-grown individual plants across seedlings to the mature stage. A multi-view automated imaging system composed of a rotary table and an imaging arm with 12 cameras mounted with a combination of fan-shaped and vertical distribution was developed to obtain 3D image data of roots grown on a customized root support mesh. A 3D imaging data processing pipeline was developed to quantify the 3D RSA based on the point cloud generated from multi-view images. The global architecture of root systems can be quantified automatically. Detailed analysis of the reconstructed 3D root model also allowed us to investigate the Spatio-temporal distribution of roots. A method combining horizontal slicing and iterative erosion and dilation was developed to automatically segment different root types, and identify local root traits (e.g., length, diameter of the main root, and length, diameter, initial angle, and the number of nodal roots or lateral roots). One maize (Zea mays L.) cultivar and two rapeseed (Brassica napus L.) cultivars at different growth stages were selected to test the performance of the automated imaging system and 3D imaging data processing pipeline. CONCLUSIONS: The results demonstrated the capabilities of the proposed imaging and analytical system for high-throughput phenotyping of root traits for both monocotyledons and dicotyledons across growth stages. The proposed system offers a potential tool to further explore the 3D RSA for improving root traits and agronomic qualities of crops.

Recent water-level fluctuations, future trends and their eco-environmental impacts on Lake Qinghai.

The water level of Lake Qinghai, the largest lake on the Qinghai-Tibetan Plateau, has increased continuously, at an average speed of 0.21 m per year since 2005, causing a rapid expansion of the lake area. We investigated the hydrological processes of Lake Qinghai and the surrounding watershed that have influenced water level and lake area from 1956 to 2019. Relationships among water level, climate change and human activities were also assessed. Water level and lake area were positively correlated with precipitation and runoff into the lake, and negatively correlated with evaporation. Climate change factors including precipitation and runoff were the primary causes of lake level change, whereas human activities, including variation in a human footprint index, land use, and grassland irrigation, were secondary factors. A time series model forecasted that from 2020 to 2050 water levels will increase further by 2.45 m. Although this increase in water level may have some benefits, such as reduced local desertification, the expansion of lake area will continue to flood low beaches, pasture lands, near shore infrastructure and roads, and impact tourism locations. However, continued water level rise may also have negative ecological effects, such as reduce habitat of seasonal birds and reduced water quality due to erosion and sediment resuspension in shallow nearshore lake areas. Local stakeholders, government authorities, and scientists should give greater attention to anticipated changes in water level, and further ecological studies and infrastructure adaptation measures should be implemented.

Selection and Validation of 48 KASP Markers for Variety Identification and Breeding Guidance in Conventional and Hybrid Rice (Oryza sativa L.).

BACKGROUND: Breeding of conventional and hybrid rice (Oryza sativa L.) have solved hunger problems and increased farmers' income in the world. Molecular markers have been widely used in marker-assisted breeding and identification of larger numbers of different bred varieties in the past decades. The recently developed SNP markers are applied for more stable and detectable compared with other markers. But the cost of genotyping lots SNPs is high. So, it is essential to select less representative SNPs and inexpensive detecting methods to lower the cost and accelerate variety identification and breeding process. KASP (Kompetitive Allele-Specific PCR) is a flexible method to detect the SNPs, and large number of KASP markers have been widely used in variety identification and breeding. However, the ability of less KASP markers on massive variety identification and breeding remains unknown. RESULTS: Here, 48 KASP markers were selected from 378 markers to classify and analyze 518 varieties including conventional and hybrid rice. Through analyzing the population structure, the 48 markers could almost represent the 378 markers. In terms of variety identification, the 48 KASP markers had a 100% discrimination rate in 53 conventional indica varieties and 193 hybrid varieties, while they could distinguish 89.1% conventional japonica rice from different breeding institutes. Two more markers added would increase the ratio from 68.38 to 77.94%. Additionally, the 48 markers could be used for classification of subpopulations in the bred variety. Also, 8 markers had almost completely different genotypes between japonica and indica, and 3 markers were found to be very important for japonica hybrid rice. In hybrid varieties, the heterozygosity of chromosomes 3, 6 and 11 was relatively higher than others. CONCLUSIONS: Our results showed that 48 KASP markers could be used to identify rice varieties, and the panel we tested could provide a database for breeders to identify new breeding lines. Also, the specific markers we found were useful for marker-assisted breeding in rice, including conventional and hybrid.

Potential effect of warming on soil microbial nutrient limitations as determined by enzymatic stoichiometry in the farmland from different climate zones.

The decomposition of organic matter mediated by soil enzymes is the key process that transports carbon from the soil into the atmosphere. To better understand the effect of global warming on organic matter decomposition, we evaluated the temperature sensitivity (Q10) of invertase (EC3.2.1.26), ß-glucosidase (EC3.2.1.21), urease (EC3.1.1.5), acid phosphatase (EC3.1.3.2), and arylsulfatase (EC3.1.6.1) activities in red soil from the subtropical region and black soil from the mid-temperate region at 5, 15, 25, 35, and 45 °C. Further, the in-situ stoichiometry of the products released by enzymes was modelled. All of the enzyme activities in the tested soils increased with the increasing temperature (1.1-8.9 fold per 10 °C), indicating an enhanced degradation of the organic substrate with warming. In the lower temperature range (5-25 °C), Q10 of the enzyme activities in the red soil evaluated in terms of total enzyme activity index were more prominent than that in black soil (1.53 and 3.46 vs 1.16 and 3.19). Changes in the in-situ stoichiometry of enzyme products with warming indicated that, in colder months (Jan. to Apr. and Oct. to Dec.), the microbial nutrient demand in the red soil exhibited the following order, N > P > S > C. While in the black soil, it suggested that there is increasing microbial demand for only N and S. In the warmer months (May to Sep.), the microbial nutrient demands in the two soils were opposite to the colder months. The results suggested differential changes in microbial nutrient limitation with warming, which has significant implications for the carbon stocks management in farmlands under the changing global climate.

Tocochromanols and Chlorophylls Accumulation in Young Pomelo (Citrus maxima) during Early Fruit Development.

Pomelo is an important cultivar of the genus Citrus that contains a variety of beneficial nutrients, and its young fruit is an agricultural by-product that is currently not fully utilized because it is often thrown away during cultivation and management. In this study, the dynamics of tocochromanol during young pomelo development were investigated by measuring chlorophyll content, tocochromanol accumulation, and expression levels of related genes during early fruit development. The results showed that chlorophyll content decreased overall during these four developmental stages and had some synergism with tocochromanol. Four tocochromanol components were detected in pomelo of both genotypes, and α-tocopherol was the main component. The tocochromanol content of honey pomelo was highest in the first period, reaching 70 ± 5 µg/g in dry weight (DW), and golden pomelo peaked in the second period at 86.10 ± 0.18 µg/g DW, with an overall decreasing trend in both genotypes. The different gene expression patterns of the tocochromanol biosynthesis pathway could partially explain the changes in these components and further elucidate the regulatory mechanisms of tocochromanol accumulation during early fruit development. As a natural product, young pomelo fruit is an attractive source of tocochromanol and has potential application in industrial production. The results of this study may provide directions for the high additional value utilization of young pomelo fruit.

Kinetics and catalytic efficiency of soil fluorescein diacetate hydrolase under the pesticide parathion stress.

Fluorescein diacetate hydrolase (FDA-H) is an accurate biochemical method measuring the total microbial activity in soil, which indicates soil quality under ambient environmental changes such as pesticide parathion (PTH). However, the influence of PTH on the kinetics of FDA-H is still unknown. In this study, fifteen farmland soils were exposed to acute PTH pollution to investigate how the kinetic characteristics of FDA-H change with PTH concentration. Results showed that PTH strongly inhibited the FDA-H activities. The values of maximum reaction velocity (Vmax) ranged from 0.29 to 2.18 × 10-2 mM g-1 soil h-1 and declined by 42.30%-71.01% under PTH stress. The Michaelis constant (Km) values ranged between 2.90 and 14.17 × 10-2 mM and exhibited three forms including unchanged, increased (38.16-242.65%) and decreased (13.41-39.23%) when exposed to PTH. Based on the changes in two kinetic parameters, the inhibition of PTH on FDA-H was classified as three types, i.e., noncompetitive, linear mixed and uncompetitive inhibition. The competitive inhibition constant (Kic) and noncompetitive constant (Kiu) ranged from 0.064 to 0.447 mM and 0.209 to 0.723 mM, respectively, which were larger than the Km in values. The catalytic efficiency (Vmax/Km) of FDA-H is a sensitive integrated parameter to evaluate the PTH toxicity due to the higher inhibition ratio than the Vmax. The PTH toxicity to FDA-H decreased with increase of soil organic matter and total nitrogen contents. This implied that the PTH toxicity could be alleviated by an increasing content of soil organic matter due to its buffering capacity to PTH. Besides, soils with a higher content of total nitrogen could provide stable environment for FDA-H to maintain its functionality under PTH pollution. Thus, the results of this study have great implications to the risk assessment of parathion in soils.

The effect of arsenic on soil intracellular and potential extracellular ß-glucosidase differentiated by chloroform fumigation.

Arsenic (As) contamination of soil is a global issue of serious ecological and human health concern. For better use of soil enzymes as biological indicators of As pollution, the response of soil ß-glucosidase in different pools of soil (total, intracellular and potential extracellular) to As(V) stress was investigated. Chloroform fumigation method was employed to distinguish the intracellular and potential extracellular ß-glucosidase in three soils. The intracellular and potential extracellular ß-glucosidase accounted about 79% and 21% of the total ß-glucosidase activity in the tested soils. Moreover, it was found that the response of these three enzyme pools to As(V) pollution was different. Under the stress of 400 mg kg-1 As(V), the ß-glucosidase activities decreased by 69%, 79%, and 28% for the total, intracellular and potential extracellular pools, respectively. The calculated median ecological dose (ED50) showed the highest value for potential extracellular ß-glucosidase (19.55-27.63 mg kg-1 for total, 18.49-27.42 mg kg-1 for intracellular, and 32.27-52.69 mg kg-1 for potential extracellular ß-glucosidase). As(V) exhibited an uncompetitive inhibition for total and intracellular ß-glucosidase and non-competitive inhibition for potential extracellular enzyme. The inhibition constant (Kiu) is biggest for potential extracellular ß-glucosidase among the three enzyme pools (0.61-0.79 mmol L-1 for total, 0.34-0.36 mmol L-1 for intracellular, and 4.01-23.90 mmol L-1 for potential extracellular ß-glucosidase). Thus, compared to potential extracellular ß-glucosidase, the total and intracellular ß-glucosidases are more suitable for their use as sensitive indicators of As(V) pollution.

The distribution of arsenic fractions and alkaline phosphatase activities in different soil aggregates following four months As(V) ageing.

Soil as a heterogeneous mass is composed of different size aggregates. The distribution of different arsenic (As) fractions in soil aggregates is vital to assess the potential risk of As pollution. In this study, soil samples were aged for 4 months with different arsenate [As(V)] concentrations. Dry sieving method was used to obtain five different size aggregates and the content of As in these fractions was determined. The results showed that P4 (0.1-0.25 mm) contained the highest organic matter (OM) than other size aggregates. After 4 months of ageing, available phosphorus (AP) content increased with the increase of As(V) concentration among 5 aggregates. The distribution of different arsenic fractions among 5 aggregates was similar. The relative contents of water-soluble (F1), exchangeable (F2) and carbonate (F3) fractions increased with the increase in As concentration, while the residual fraction (F7) decreased sharply. Humic-bound (F4), and Fe and Mn oxide bound fractions (F5) were about 35% and 20% respectively, after 4 months of As(V) ageing. Generally, the alkaline phosphatase (ALP) activities of P4 were lowest among five aggregates under each concentration of As(V). Moreover, F2 and F3 exhibited a strong inhibition of ALP activity. This study demonstrates that not only water-soluble and exchangeable arsenic but also humic-bound fraction should be considered when assessing As bioavailability and toxicity.

[Low-dose digital breast tomosynthsis imaging via noise correlation based penalized weighted least-squares algorithm].

OBJECTIVE: To achieve low-dose digital breast tomosynthsis (DBT) projection recovery using penalized weighted least square algorithm incorporating accurate modeling of the variance of the projection data and noise correlation in the flat panel detector. METHODS: Models were established for the quantal noise and electronic noise in the DBT system to construct the penalized weighted least squares algorithm based on noise correlation for projection data restoration. The filter back projection algorithm was then used for DBT image reconstruction. RESULTS: The reconstruction results of the ACR phantom data at different dose levels showed a good performance of the proposed method in noise suppression and detail preservation. CNRs and LSNRs of the reconstructed images from the restored projections were increased by about 3.6 times compared to those of reconstructed images from the original projections. CONCLUSIONS: The proposed method can significantly reduce noise and improve the quality of DBT images.

[Kinetic cluster and α-divergence-based dynamic myocardial factorial analysis of positron-emission computed tomography images].

OBJECTIVE: We purpose a novel factor analysis method based on kinetic cluster and α-divergence measure for extracting the blood input function and the time-activity curve of the regional tissue from dynamic myocardial positron emission computed tomography(PET) images. METHODS: Dynamic PET images were decomposed into initial factors and factor images by minimizing the α-divergence between the factor model and actual image data. The kinetic clustering as a priori constraint was then incorporated into the model to solve the nonuniqueness problem, and the tissue time-activity curves and the tissue space distributions with physiological significance were generated. RESULTS: The model was applied to the 82RbPET myocardial perfusion simulation data and compared with the traditional model-based least squares measure and the minimal spatial overlap constraint. The experimental results showed that the proposed model performed better than the traditional model in terms of both accuracy and sensitivity. CONCLUSION: This method can select the optimal measure by α value, and incorporate the prior information of the kinetic clustering of PET image pixels to obtain the accurate time-activity curves of the tissue, which has shown good performance in visual evaluation and quantitative evaluation.