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Mass remote sensing data management and processing is currently one of the most important topics. In this study, we introduce ScienceEarth, a cluster-based data processing framework. The aim of ScienceEarth is to store, manage, and process large-scale remote sensing data in a cloud-based cluster-computing environment. The platform consists of the following three main parts: ScienceGeoData, ScienceGeoIndex, and ScienceGeoSpark. ScienceGeoData stores and manages remote sensing data. ScienceGeoIndex is an index and query system, a spatial index based on quad-tree and Hilbert curve which is combined for heterogeneous tiled remote sensing data that makes efficient data retrieval in ScienceGeoData. ScienceGeoSpark is an easy-to-use computing framework in which we use Apache Spark as the analytics engine for big remote sensing data processing. The result of tests proves that ScienceEarth can efficiently store, retrieve, and process remote sensing data. The results reveal ScienceEarth has the potential and capabilities of efficient big remote sensing data processing.

The One Health concept proposes that the health of humans, animals, and the environment are interconnected. Agricultural production is a critical component of One Health as food links the environment to human health. Food not only provides nutrients to humans but also represents an important pathway for human exposure to environmental microbes as well as potentially harmful agrochemicals. In addition, inappropriate agronomic practices can cause damage to the environment which can have unintended adverse impacts on human health. Therefore, improving agricultural production systems and protecting environmental health should not be viewed as isolated goals as they are strongly interlinked. Here, we used the nexus of soil, plant, and human microbiomes to discuss sustainable agricultural production from the One Health perspective. We highlighted three interconnected challenges faced by current agronomic practices: the transmissions of pathogens in soil‐human microbial loops, the dissemination of antibiotic resistance genes in agroecosystems, and the impacts of chemical pesticides on humans and environmental health. Finally, we propose the potential of utilising microbiomes for better sustainable agronomic practices to contribute to key goals of the One Health concept. This article use the nexus of soil, plant, and human microbiomes to discuss sustainable agricultural production from the One Health perspective. Three interconnected challenges are highlighted‐ the transmissions of pathogens in soil–human microbial loops, the dissemination of antibiotic resistance genes in agroecosystems, and the impacts of chemical pesticides on humans and environmental health. Finally, we propose the potential of utilising microbiomes for better sustainable agronomic practices to contribute to key goals of the One Health concept.

Deciphering the physiological function of TGF-β (the transforming growth factor beta) family ligands is import for understanding the role of TGF-β in animals’ development and aging. Here, we investigate the function of TIG-2, one of the ligands in Caenorhabditis elegans TGF-β family, in animals’ behavioral modulation. Our results show that a loss-of-function mutation in tig-2 gene result in slower locomotion speed in the early adulthood and an increased density of cholinergic synapses, but a decreased neurotransmitter release at neuromuscular junctions (NMJs). Further tissue-specific rescue results reveal that neuronal and intestinal TIG-2 are essential for the formation of cholinergic synapses at NMJs. Interestingly, tig-2 ( ok3416 ) mutant is characterized with reduced muscle mitochondria content and adenosine triphosphate (ATP) production, although the function of muscle acetylcholine receptors and the morphology muscle fibers in the mutant are comparable to that in wild-type animals. Our result suggests that TIG-2 from different neuron and intestine regulates worm locomotion by modulating synaptogenesis and neurotransmission at NMJs, as well as energy metabolism in postsynaptic muscle cells.

Recently, the detailed etiology and pathogenesis of Parkinson's disease (PD) have not been fully clarified yet. Increasing evidences suggested that the disturbance of peripheral branched-chain amino acids (BCAAs) metabolism can promote the occurrence and progression of neurodegenerative diseases through neuroinflammatory signaling. Although there are several studies on the metabolomics of PD, longitudinal study of metabolic pathways is still lacking. Therefore, the purpose of the present study was to determine the longitudinal alterations in serum amino acid profiles in PD mouse model. Gas chromatography-mass spectrometry (GC–MS) was applied to detect serum amino acid concentrations in C57BL/6 mice after 0, 3 and 4 weeks of oral administration with rotenone. Then the data were analysed by principal component analysis (PCA) and orthogonal projection to latent structures (OPLS) analysis. Finally, the correlations between different kinds of serum amino acids and behaviors in rotenone-treated mice were also explored. Compared with 0-week mice, the levels of l-isoleucine and l-leucine were down-regulated in 3-week and 4-week mice, especially in 4-week mice. Moreover, the comprehensive analysis showed that l-isoleucine and l-leucine were negatively correlated with pole-climbing time and positively correlated with fecal weight and water content of PD mice. These results not only suggested that l-isoleucine and l-leucine may be potential biomarkers, but also pointed out the possibility of treating PD by intervening in the circulating amino acids metabolism.

Extracting water bodies from synthetic aperture radar (SAR) images plays a crucial role in the management of water resources, flood monitoring, and other applications. Recently, transformer-based models have been extensively utilized in the remote sensing domain. However, due to regular patch-partition and weak inductive bias, transformer-based models face challenges such as edge serration and high data dependency when used for water body extraction from SAR images. To address these challenges, we introduce a new model, the Superpixel-based Transformer (SPT), based on the adaptive characteristic of superpixels and knowledge constraints of the adjacency matrix. (1) To mitigate edge serration, the SPT replaces regular patch partition with superpixel segmentation to fully utilize the internal homogeneity of superpixels. (2) To reduce data dependency, the SPT incorporates a normalized adjacency matrix between superpixels into the Multi-Layer Perceptron (MLP) to impose knowledge constraints. (3) Additionally, to integrate superpixel-level learning from the SPT with pixel-level learning from the CNN, we combine these two deep networks to form SPT-UNet for water body extraction. The results show that our SPT-UNet is competitive compared with other state-of-the-art extraction models, both in terms of quantitative metrics and visual effects.

Cardiac immune-related adverse events (irAEs) from PD-1-targeting immune check-point inhibitors (ICIs) are an increasing concern due to their high mortality rate. Collagen plays a crucial role in maintaining cardiac structure, elasticity, and signal transduction; however, the effects and mechanisms of PD-1 inhibitor on cardiac collagen remodeling remain poorly understood. C57BL/6 mice were injected with anti-mouse PD-1 antibody to create a PD-1 inhibitor-treated model. Cardiac function was measured by echocardiography, and collagen distribution was analyzed with Masson's trichrome staining and Sirius Red staining. Single-nucleus RNA sequencing was performed to examine the effects of PD-1 inhibition on gene expression in cardiac fibroblasts (CFs) and endothelial cells (ECs). EC-CF crosstalk was assessed using co-culture experiments and ELISA. ChIP assay was performed to analyze the regulation of TCF12 on TGF-β1 promoter. Western blot, qRT-PCR, and immunofluorescence staining were used to detect the expression of TCF12, TGF-β1, and endothelial-to-mesenchymal transition (EndMT) markers. Reactive oxygen species (ROS) levels were evaluated by DHE staining, MDA content, and SOD activity assays. We report a newly discovered cardiotoxic effect of PD-1 inhibitor, which causes aberrant collagen distribution in the heart, marked by a decrease in interstitial collagen and an increase in perivascular collagen deposition. Mechanistically, PD-1 inhibitor does not directly affect CFs but instead impact them through EC-CF crosstalk. PD-1 inhibitor reduces TGF-β1 secretion in ECs by downregulating TCF12, which we identify as a transcriptional promoter of TGF-β1. This subsequently decreases CF activity, leading to reduced interstitial collagen deposition. Additionally, PD-1 inhibitor induces EndMT, increasing perivascular collagen deposition. The endothelial dysfunction induced by PD-1 inhibitor results from ROS accumulation in ECs. Inhibiting ROS with N-acetylcysteine (NAC) preserves normal collagen distribution and cardiac function in PD-1 inhibitor-treated mice by reversing TCF12 downregulation and EndMT in ECs. Our results suggest that PD-1 inhibitor causes ROS accumulation in cardiac ECs, leading to imbalanced collagen distribution (decrease in interstitial collagen and increase in perivascular collagen) in the heart by modulating TCF12/TGF-β1-mediated EC-CF crosstalk and EndMT. NAC supplementation could be an effective clinical strategy to mitigate PD-1 inhibitor-induced imbalanced collagen distribution and cardiac dysfunction.

Silver ion (Ag+) is one of the most common heavy metal ions that cause environmental pollution and affect human health, and therefore, its detection is of great importance in the field of analytical chemistry. Here, we report an 8-nucleotide (nt) minidumbbell DNA-based sensor (M-DNA) for Ag+ detection. The minidumbbell contained a unique reverse wobble C·C mispair in the minor groove, which served as the binding site for Ag+. The M-DNA sensor could achieve a detection limit of 2.1 nM and sense Ag+ in real environmental samples with high accuracy. More importantly, the M-DNA sensor exhibited advantages of fast kinetics and easy operation owing to the usage of an ultrashort oligonucleotide. The minidumbbell represents a new and minimal non-B DNA structural motif for Ag+ sensing, allowing for the further development of on-site environmental Ag+ detection devices.

The detection of primary and secondary schools (PSSs) is a meaningful task for composite object detection in remote sensing images (RSIs). As a typical composite object in RSIs, PSSs have diverse appearances with complex backgrounds, which makes it difficult to effectively extract their features using the existing deep-learning-based object detection algorithms. Aiming at the challenges of PSSs detection, we propose an end-to-end framework called the attention-guided dense network (ADNet), which can effectively improve the detection accuracy of PSSs. First, a dual attention module (DAM) is designed to enhance the ability in representing complex characteristics and alleviate distractions in the background. Second, a dense feature fusion module (DFFM) is built to promote attention cues flow into low layers, which guides the generation of hierarchical feature representation. Experimental results demonstrate that our proposed method outperforms the state-of-the-art methods and achieves 79.86% average precision. The study proves the effectiveness of our proposed method on PSSs detection.

A novel lipolytic gene, estq7, was identified from a fosmid metagenomic library. The recombinant enzyme EstQ7 consists of 370 amino acids with an anticipated molecular mass of 42 kDa. Multiple sequence alignments showed that EstQ7 contained a pentapeptide motif GHSMG, and a putative catalytic triad Ser174–Asp306–His344. Interestingly, EstQ7 was found to have very little similarity to the characterized lipolytic enzymes. Phylogenetic analysis revealed that EstQ7 may be a member of a novel family of lipolytic enzymes. Biochemical characterization of the recombinant enzyme revealed that it constitutes a slightly alkalophilic, moderate thermophilic and highly active carboxylesterase against short-chain fatty acid esters with optimum temperature 50 ℃ and pH 8.2. The Km and kcat values toward p-nitrophenyl acetate were determined to be 0.17 mM and 1910s−1, respectively. Moreover, EstQ7 was demonstrated to have acyltransferase activity by GC–MS analysis. Structural modeling of the three-dimensional structure of this new enzyme showed that it exhibits a typical α/β hydrolase fold, and the catalytic triad residues are spatially close. Molecular docking revealed the interactions between the enzyme and the ligand. The high levels of lipolytic activity of EstQ7, combined with its moderate thermophilic property and acyltransferase activity, render this novel enzyme a promising candidate biocatalyst for food, pharmaceutical and biotechnological applications.

Sexually dimorphic differentiation of sex-shared behaviors is observed across the animal world, but the underlying neurobiological mechanisms are not fully understood. Here we report sexual dimorphism in neurotransmitter release at the neuromuscular junctions (NMJs) of adult Caenorhabditis elegans . Studying worm locomotion confirms sex differences in spontaneous locomotion of adult animals, and quantitative fluorescence analysis shows that excitatory cholinergic synapses, but not inhibitory GABAergic synapses exhibit the adult-specific difference in synaptic vesicles between males and hermaphrodites. Electrophysiological recording from the NMJ of C. elegans not only reveals an enhanced neurotransmitter release but also demonstrates increased sensitivity of synaptic exocytosis to extracellular calcium concentration in adult males. Furthermore, the cholinergic synapses in adult males are characterized with weaker synaptic depression but faster vesicle replenishment than that in hermaphrodites. Interestingly, T-type calcium channels/CCA-1 play a male-specific role in acetylcholine release at the NMJs in adult animals. Taken together, our results demonstrate sexually dimorphic differentiation of synaptic mechanisms at the C. elegans NMJs, and thus provide a new mechanistic insight into how biological sex shapes animal behaviors through sex-shared neurons and circuits.