Comparison of change-based and shape-based data fusion methods in fine-resolution land surface phenology monitoring with Landsat and Sentinel-2 data.

Fine-resolution land surface phenology (LSP) is urgently required for applications on agriculture management and vegetation-climate interaction, especially over heterogeneous areas, such as agricultural lands and fragmented forests. The critical challenge of fine-resolution LSP monitoring is how to reconstruct the spatiotemporal continuous vegetation index time series. To solve this problem, various data fusion methods have been devised; however, the comprehensive inter-comparison is lacking across different spatial heterogeneity, data quality, and vegetation types. We divide these methods into two main categories: the change-based methods fusing satellite observations with different spatiotemporal resolutions, and the shape-based methods fusing prior knowledge of shape models and satellite observations. We selected four methods to rebuilt two-band enhanced vegetation index (EVI2) series based on the harmonized Landsat and Sentinel-2 (HLS) data, including two change-based methods, namely the Spatial and temporal Adaptive Reflectance Fusion Model (STARFM), the Flexible Spatiotemporal DAta Fusion (FSDAF), and two shape-based methods, namely the Multiple-year Weighting Shape-Matching (MWSM), and the Spatiotemporal Shape-Matching Model (SSMM). Four phenological transition dates were extracted, evaluated with PhenoCam observations and the 500 m Visible Infrared Imaging Radiometer Suite (VIIRS) phenology product. The 30 m transition dates show more spatial details and reveal more apparent intra-class and inter-class phenology variation compared with 500 m product. The four transition dates of SSMM and FSDAF (R2>0.74, MAD<15 days) show better agreement with PhenoCam-derived dates. The performance difference between fusion methods over various application scenarios are then analyzed. Fusion results are more robust when temporal frequency is higher than 15 observations per year. The shape-based methods are less sensitive to temporal sampling irregularity than change-based methods. Both change-based methods and shape-based methods cannot perform well when the region is heterogeneous. Among different vegetation types, SSMM-like methods have the highest overall accuracy. The findings in this paper can provide references for regional and global fine-resolution phenology monitoring.

Allosteric aptasensor-initiated target cycling and transcription amplification of light-up RNA aptamer for sensitive detection of protein.

The early detection of biomarker proteins in clinical samples is of great significance for the diagnosis of diseases. However, it is still a challenge to detect low-concentration protein. Herein, a label-free aptamer-based amplification assay, termed the ATC-TA system, that allows fluorescence detection of very low numbers of protein without time-consuming washing steps and pre-treatment was developed. The target induces a conformational change in the allosteric aptasensor, triggers the target cycling and transcription amplification, and ultimately converts the input of the target protein into the output of the light-up aptamer (R-Pepper). It exhibits ultrahigh sensitivity with a detection limit of 5.62 fM at 37 â„ƒ and the accuracy is comparable to conventional ELISA. ATC-TA has potential application for the detection of endogenous PDGF-BB in serum samples to distinguish tumor mice from healthy mice at an early stage. It also successfully detects exogenous SARS-CoV-2 spike proteins in human serum. Therefore, this high-sensitive, universality, easy-to-operate and cost-effective biosensing platform holds great clinical application potential in early clinical diagnosis.

Optimizing the spatial pattern of land use in a prominent grain-producing area: A sustainable development perspective.

Spatial patterns are essential for examining the sustainability derived from land systems. Constructing spatial patterns for sustainable land development is now high on the global agenda to guarantee human welfare. However, there is as yet no consensus on the comprehensive framework for optimizing the spatial pattern of land development (SPLD) contrapose a prominent grain-producing area (PGPA). To narrow this gap, we propose a synthetic framework to shape a more reasonable SPLD for a sustainable development strategy by measuring the equilibrium between the production-living-ecological space (PLES) functions and the resource and environment carrying capacity (RECC). Taking a prominent grain-producing area (PGPA) as the object, a case study involving the Jianghan Plain (JHP) in China is conducted, leading to the following novel insights. (i) The quality of PLES and RECC in a PGPA is affected by multiple dimensions: agriculture, ecology, environment, and society. The indices of the PLES function and the RECC have significant spatial heterogeneity. SPLD in regions with fragile ecological environments and strong development is often under overload pressure. (ii) Based on the spatial zoning results of SPLD, the five partitions were taken as the optimized objects, including zones of the eco-economic, model-agricultural, core-living, eco-conservation, and coordinated-development. The land function definition of these five types of zoning covers the production-living-ecological function orientation in a PGPA. (iii) The SPLD optimization framework proposed above has strong universality because it comprehensively considers the multi-dimensional spatial functional needs of PGPA. In this study, an optimization decision framework of SPLD based on measurement and zoning was established for a PGPA. Significantly, the introduced framework is applicable and practical for optimizing SPLD from a sustainable equilibrium perspective, and the findings have considerable implications for sustainable development in prominent grain-producing areas.

A genetically encoded fluorescent biosensor for monitoring ATP in living cells with heterobifunctional aptamers.

Visualizing the dynamics of ATP in living cells is key to understanding cellular energy metabolism and related diseases. However, the live-cell applications of current methods are still limited due to challenges in biological compatibility and sensitivity to pH. Herein, a novel label-free fluorescent " turn-on " biosensor for monitoring ATP in living bacterias and mammalian cells was developed. This biosensor (Broc-ATP) employed heterobifunctional aptamers to detect ATP with high sensitivity in vitro. In our system, a very useful tandem method was established by combining four Broc-ATPs with 3 × F30 three-way junction scaffold to construct an intracellular biosensor that achieves sufficient fluorescence to respond to intracellular ATP. This intracellular biosensor can be used for sensitive and specific dynamic imaging of ATP in mammalian cells. Hence, this genetically encoded biosensor provides a robust and efficient tool for the detection of intracellular ATP dynamics and 3 × F30 tandem method expands the application of heterobifunctional aptamers in mammalian cells.

A critical review of microplastics in the soil-plant system: Distribution, uptake, phytotoxicity and prevention.

Microplastics (MPs) are creating an emerging threat on the soil ecosystems and are of great global concern. However, the distribution in soil-plant system, as well as the phytotoxicity and impact mechanisms of MPs remain largely unexplored so far. This study introduced the diverse sources of MPs and showed the significant spatial variation in the global geographic distribution of MPs contamination based on data collected from 116 studies (1003 sampling sites). We systematically discussed MPs phytotoxicity, such as plant uptake and migration to stems and leaves, delaying seed germination, impeding plant growth, inhibiting photosynthesis, interfering with nutrient metabolism, causing oxidative damage, and producing genotoxicity. We further highlighted the alterations of soil structure and function by MPs, as well as their self and load toxicity, as potential mechanisms that threaten plants. Finally, this paper provided several preventive strategies to mitigate soil MPs pollution and presented research gaps in the biogeochemical behavior of MPs in soil-plant systems. Meanwhile, we recommended that methods for the quantitative detection of MPs accumulated in plant tissues should be explored and established as soon as possible. This review will improve the understanding of the environmental behavior of MPs in soil-plant systems and provide a theoretical reference to better assess the ecological risk of MPs.

Coagulation factors VII, IX and X are effective antibacterial proteins against drug-resistant Gram-negative bacteria.

Infections caused by drug-resistant "superbugs" pose an urgent public health threat due to the lack of effective drugs; however, certain mammalian proteins with intrinsic antibacterial activity might be underappreciated. Here, we reveal an antibacterial property against Gram-negative bacteria for factors VII, IX and X, three proteins with well-established roles in initiation of the coagulation cascade. These factors exert antibacterial function via their light chains (LCs). Unlike many antibacterial agents that target cell metabolism or the cytoplasmic membrane, the LCs act by hydrolyzing the major components of bacterial outer membrane, lipopolysaccharides, which are crucial for the survival of Gram-negative bacteria. The LC of factor VII exhibits in vitro efficacy towards all Gram-negative bacteria tested, including extensively drug-resistant (XDR) pathogens, at nanomolar concentrations. It is also highly effective in combating XDR Pseudomonas aeruginosa and Acinetobacter baumannii infections in vivo. Through decoding a unique mechanism whereby factors VII, IX and X behave as antimicrobial proteins, this study advances our understanding of the coagulation system in host defense, and suggests that these factors may participate in the pathogenesis of coagulation disorder-related diseases such as sepsis via their dual functions in blood coagulation and resistance to infection. Furthermore, this study may offer new strategies for combating Gram-negative "superbugs".

High resolution analysis of tropical forest fragmentation and its impact on the global carbon cycle.

Deforestation in the tropics is not only responsible for direct carbon emissions but also extends the forest edge wherein trees suffer increased mortality. Here we combine high-resolution (30 m) satellite maps of forest cover with estimates of the edge effect and show that 19% of the remaining area of tropical forests lies within 100 m of a forest edge. The tropics house around 50 million forest fragments and the length of the world's tropical forest edges sums to nearly 50 million km. Edge effects in tropical forests have caused an additional 10.3 Gt (2.1-14.4 Gt) of carbon emissions, which translates into 0.34 Gt per year and represents 31% of the currently estimated annual carbon releases due to tropical deforestation. Fragmentation substantially augments carbon emissions from tropical forests and must be taken into account when analysing the role of vegetation in the global carbon cycle.

Habitat fragmentation and its lasting impact on Earth's ecosystems.

We conducted an analysis of global forest cover to reveal that 70% of remaining forest is within 1 km of the forest's edge, subject to the degrading effects of fragmentation. A synthesis of fragmentation experiments spanning multiple biomes and scales, five continents, and 35 years demonstrates that habitat fragmentation reduces biodiversity by 13 to 75% and impairs key ecosystem functions by decreasing biomass and altering nutrient cycles. Effects are greatest in the smallest and most isolated fragments, and they magnify with the passage of time. These findings indicate an urgent need for conservation and restoration measures to improve landscape connectivity, which will reduce extinction rates and help maintain ecosystem services.