环京津城市群生态系统服务的时空演变与驱动因素

城市群已成为全球经济竞争的新空间单元,在促进城镇化建设,实现资源优质配置和发挥辐射带动作用等方面发挥着重要的功能。但剧烈的社会经济活动必然会对城市群生态系统服务造成破坏,因此开展城市群生态系统服务的时空演变研究,进而探索不同驱动因子对其的作用机制具有重要意义。目前,在已有的研究中缺少对城市群尺度和长时间跨度下的生态系统服务水平演变与驱动因素探究。为此,选取京津及环京津地区为研究区域,通过总结区域生态问题,构建起研究区域生态系统服务评价体系,并对2000-2018年生态系统服务进行计算,分析时空演变特征。然后,通过最小二乘法模型（Ordinary Least Squares,OLS）筛选出潜在的驱动因子,并导入地理加权回归模型（Geographically Weighted Regression,GWR）进行地理加权回归计算。最后,通过对结果分析,探讨自然和社会因子对生态系统服务的作用机制。研究结果表明：1）2000-2018年,研究区域生态系统服务呈现出先上升后下降,在2015年达到最高值的发展特征。2）在空间上,研究区域生态系统服务内总体上呈现燕山山脉及太行山山脉北部区域为生态系统服务的高值区域,坝上区域为低值区的空间分异特征。同时,生态系统服务演变在空间上呈现以燕山和太行山为界,燕山和太行山区域呈现先减弱后提升的趋势,西北区域整体呈现减弱趋势,东南区域从2015年起逐渐降低的空间演化特征。3）在驱动因素方面,自然环境和社会经济因素对生态系统服务的驱动作用从强到弱排列依次是：降雨量 > 土壤含沙 > 人口密度 > 温度 > 基础设施密度。4）其中,人口密度、土壤含沙量、基础设施呈较为明显的负相关驱动特征,降雨量呈较为明显的正相关驱动特征,温度则呈南部负相关,北部正相关,由东南向西北影响增强的趋势。本研究通过评估环京津城市群生态系统服务,分析区域生态系统服务的分析演变特征,并探索区域自然、社会因子对生态系统服务的驱动作用,为环京津城市群未来的生态环境保护和规划策略制定提供了科学指导和决策依据。     

Oxidized high-density lipoprotein promotes CD36 palmitoylation and increases lipid uptake in macrophages

Oxidized high-density lipoprotein (oxHDL) reduces the ability of cells to mediate reverse cholesterol transport and also shows atherogenic properties. Palmitoylation of cluster of differentiation 36 (CD36), an important receptor mediating lipoprotein uptake, is required for fatty acid endocytosis. However, the relationship between oxHDL and CD36 has not been described in mechanistic detail. Here, we demonstrate using acyl-biotin exchange analysis that oxHDL activates CD36 by increasing CD36 palmitoylation, which promotes efficient uptake in macrophages. This modification increased CD36 incorporation into plasma lipid rafts and activated downstream signaling mediators, such as Lyn, Fyn, and c-Jun N-terminal kinase, which elicited enhanced oxHDL uptake and foam cell formation. Furthermore, blocking CD36 palmitoylation with the pharmacological inhibitor 2-bromopalmitate decreased cell surface translocation and lowered oxHDL uptake in oxHDL-treated macrophages. We verified these results by transfecting oxHDL-induced macrophages with vectors expressing wildtype or mutant CD36 (mCD36) in which the cytoplasmic palmitoylated cysteine residues were replaced. We show that cells containing mCD36 exhibited less palmitoylated CD36, disrupted plasma membrane trafficking, and reduced protein stability. Moreover, in ApoE^−/−CD36^−/− mice, lipid accumulation at the aortic root in mice receiving the mCD36 vector was decreased, suggesting that CD36 palmitoylation is responsible for lipid uptake in vivo. Finally, our data indicated that palmitoylation of CD36 was dependent on DHHC6 (Asp-His-His-Cys) acyltransferase and its cofactor selenoprotein K, which increased the CD36/caveolin-1 interaction and membrane targeting in cells exposed to oxHDL. Altogether, our study uncovers a causal link between oxHDL and CD36 palmitoylation and provides insight into foam cell formation and atherogenesis.     

Intravital lipid droplet labeling and imaging reveals the phenotypes and functions of individual macrophages in vivo

Macrophages play pivotal roles in the maintenance of tissue homeostasis. However, the reactivation of macrophages toward proinflammatory states correlates with a plethora of inflammatory diseases, including atherosclerosis, obesity, neurodegeneration, and bone marrow (BM) failure syndromes. The lack of methods to reveal macrophage phenotype and function in vivo impedes the translational research of these diseases. Here, we found that proinflammatory macrophages accumulate intracellular lipid droplets (LDs) relative to resting or noninflammatory macrophages both in vitro and in vivo, indicating that LD accumulation serves as a structural biomarker for macrophage phenotyping. To realize the staining and imaging of macrophage LDs in vivo, we developed a fluorescent fatty acid analog-loaded poly(lactic-co-glycolic acid) nanoparticle to label macrophages in mice with high efficiency and specificity. Using these novel nanoparticles, we achieved in situ functional identification of single macrophages in BM, liver, lung, and adipose tissues under conditions of acute or chronic inflammation. Moreover, with this intravital imaging platform, we further realized in vivo phenotyping of individual macrophages in the calvarial BM of mice under systemic inflammation. In conclusion, we established an efficient in vivo LD labeling and imaging system for single macrophage phenotyping, which will aid in the development of diagnostics and therapeutic monitoring. Moreover, this method also provides new avenues for the study of lipid trafficking and dynamics in vivo.Supplementary key words: macrophage, inflammation, lipid droplet, nanoparticle delivery, in vivo imaging, fatty acid analog, bone marrow, systemic inflammation, lipid trafficking, biomarker

Macrophages, a type of immune cells, almost reside in all tissues of body, from the skin to the bone marrow (BM) (1). Macrophages have remarkable plasticity, and they can be activated into specific subtypes by modifying their physiology and functions in response to local environmental cues. Activated macrophages are commonly divided into proinflammatory killing subtype and anti-inflammatory repairing subtype. Proinflammatory macrophages responding to bacteria, IFN-γ, and lipopolysaccharide (LPS) are involved in host defense and inflammation, whereas anti-inflammatory macrophages responding to interleukin-4 (IL-4), IL-10, and IL-13 play a pivotal role in tissue homeostasis and remodeling (2). Increasing evidence indicates that the reactivation of macrophages toward proinflammatory states under diverse kinds of stress is correlated with a plethora of inflammatory diseases, such as atherosclerosis, diabetes, obesity, rheumatoid arthritis, neurodegeneration, and BM failure syndromes (3, 4). Thus, characterization of macrophage activation status and the underlying molecular mechanism in situ will help elucidate their functions in these diseases; however, in vivo analysis of the macrophage activation status in their native multicellular microenvironment is challenging.Although lipid droplets (LDs) have been initially described as intracellular fat storage organelles in adipocytes, increasing studies indicate that myeloid cells also form LDs under inflammation and stress (5, 6). Macrophages, as the effector cells of innate immunity, are found to form LDs to support their host defense when exposed to pathogens, such as parasites, bacteria, and viruses (7, 8, 9, 10, 11). However, abnormal LD accumulation in tissue-resident macrophages correlates with the pathogenesis of various inflammatory diseases. For instance, foam cells in atherosclerotic lesions can maintain the local inflammatory response by secreting proinflammatory cytokines (12, 13, 14). Moreover, LD-accumulating microglia contribute to neurodegeneration by producing high levels of reactive oxygen species (ROS) and secreting proinflammatory cytokines (15). These findings indicate that LD accumulation might be a hallmark of macrophages with proinflammatory functions.In this study, based on the typical activation of in vitro BM-derived macrophages, we find that proinflammatory M_{(LPS + IFN-γ)} macrophages are characterized by LD accumulation, whereas resting macrophages and anti-inflammatory M_(IL-4) and M_(IL-10) macrophages do not contain any LDs. These features also hold for Matrigel plug-recruited macrophages and tissue-resident macrophages in mice. These findings demonstrate that LD accumulation could serve as a morphological index to distinguish proinflammatory macrophages from others.It is feasible to distinguish LD-containing cells using imaging techniques, which has translational potential for identification of proinflammatory macrophages in vivo. However, current techniques for LD visualization are traditional in vitro staining method, and in vivo staining and imaging of LD in individual macrophages remains a challenge. Through nanocarrier screening, we selected the poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) as nanocarrier to deliver the lipophilic carbocyanine dye (DiI_C18(5) solid (1,1''-dioctadecyl-3,3,3'',3''-tetramethylindodicarbocyanine, 4-chlorobenzenesulfonate salt) [DiD]) and lipid staining dye (C1-BODIPY 500/510-C12) into macrophages. Using these dual fluorescence-labeled PLGA NPs, we achieved in situ and in vivo functional identification of single macrophages in various tissues under systemic or local inflammatory stress. Collectively, this study establishes an efficient in vivo labeling and imaging system of intracellular LDs for phenotyping the activation status and functions of individual macrophages in their dynamic niche, which is pivotal for disease diagnosis and preclinical research.     

Chromosome-level genome assembly and characterization of Sophora Japonica

Sophora japonica is a medium-size deciduous tree belonging to Leguminosae family and famous for its high ecological, economic and medicinal value. Here, we reveal a draft genome of S. japonica, which was ∼511.49 Mb long (contig N50 size of 17.34 Mb) based on Illumina, Nanopore and Hi-C data. We reliably assembled 110 contigs into 14 chromosomes, representing 91.62% of the total genome, with an improved N50 size of 31.32 Mb based on Hi-C data. Further investigation identified 271.76 Mb (53.13%) of repetitive sequences and 31,000 protein-coding genes, of which 30,721 (99.1%) were functionally annotated. Phylogenetic analysis indicates that S. japonica separated from Arabidopsis thaliana and Glycine max ∼107.53 and 61.24 million years ago, respectively. We detected evidence of species-specific and common-legume whole-genome duplication events in S. japonica. We further found that multiple TF families (e.g. BBX and PAL) have expanded in S. japonica, which might have led to its enhanced tolerance to abiotic stress. In addition, S. japonica harbours more genes involved in the lignin and cellulose biosynthesis pathways than the other two species. Finally, population genomic analyses revealed no obvious differentiation among geographical groups and the effective population size continuously declined since 2 Ma. Our genomic data provide a powerful comparative framework to study the adaptation, evolution and active ingredients biosynthesis in S. japonica. More importantly, our high-quality S. japonica genome is important for elucidating the biosynthesis of its main bioactive components, and improving its production and/or processing.     

增施氮肥能够缓解麦田土壤线虫群落对O3浓度升高的响应

在辽宁沈阳农田生态系统国家野外科学观测研究站,利用运行2a的开顶式气室,研究了臭氧(O3)浓度升高和不同氮肥施用水平对土壤线虫群落的影响。结果表明:(1)O3浓度升高降低了成熟期小麦根生物量。O3浓度升高和不同氮肥施用水平的交互作用改变了小麦成熟期土壤微生物生物量碳、氮和水溶性有机碳的含量。低氮条件下,O3浓度升高降低了土壤微生物生物量碳、氮和水溶性有机碳的含量;而高氮条件下则表现出相反的趋势。(2)O3浓度升高和不同氮肥施用水平对土壤线虫总数没有产生显著影响,而在灌浆期,食细菌线虫和食真菌线虫中c-p值为4(Ba4 and Fu4)的功能团对O3浓度升高和不同氮肥施用水平的响应敏感;与对照相比,不同氮处理中,O3浓度升高均降低了灌浆期Ba4功能团线虫的数量。灌浆期,O3浓度升高条件下,与对照相比Fu4功能团线虫数量在高氮条件下表现出增加的趋势,而在低氮条件表现出降低的趋势。(3)O3浓度升高和不同氮肥施用水平的交互作用显著影响了小麦灌浆期线虫的成熟度指数(MI)和结构指数(SI)。与对照相比,线虫成熟度指数和结构指数在低氮条件下随O3浓度升高而降低;而在高氮条件下随O3浓度升高而升高。上述结果表明,氮肥的施用能够缓解O3浓度升高对土壤食物网的扰动。     

小兴安岭凉水自然保护区蝶类多样性

2012—2013年选取原始阔叶红松林、人工林、天然次生林和灌丛草甸4种典型植被生境,对小兴安岭凉水自然保护区的蝶类进行了系统研究。共捕获蝶类1438头,分属7科47属76种,4种植被生境中蝶类群落优势类群均为蛱蝶科,不同生境蝶类群落相似性与生境植被类型密切相关。计算分析了4种植被生境中蝶类多样性指数、物种丰富度、优势度指数、均匀度指数和种-多度关系,结果表明:3种森林生境蝶类多样性大于灌丛草甸,原始阔叶红松林蝶类具有最高的多样性指数、较高的物种丰富度、均匀度指数以及最低的优势度指数,种-多度分布为对数正态分布,说明环境质量优越,最适合蝶类生存和繁衍;灌丛草甸蝶类的多样性指数、物种丰富度和均匀度指数均为最低,而优势度指数最高,种-多度分布为对数级数分布,反映植物群落结构较单一,适合各种蝶类生存和繁衍的资源不足;天然次生林蝶类多样性指数、物种丰富度高于人工林,均匀度小于人工林,但前者种-多度分布为对数级数模型,后者为对数正态模型,说明在封山育林状态下,对森林植被组成进行适当合理的干扰,有利于森林的健康发展     

一株产絮凝剂不动杆菌的筛选及其絮凝特性

从活性污泥中筛选出一株高效的微生物絮凝剂产生菌,鉴定为鲍曼不动杆菌.蚕豆根尖细胞微核试验未显示该菌株所产絮凝剂具有遗传毒性.该菌产絮凝剂的最佳碳源和氮源分别为葡萄糖和酵母浸出汁,培养时间为24 h.在絮凝体系中加入Ca2 能明显提高发酵液的絮凝率.在pH为8.0时对高岭土悬浊液和污水具有良好的絮凝效果.     

DeepMHADTA: Prediction of Drug-Target Binding Affinity Using Multi-Head Self-Attention and Convolutional Neural Network

Drug-target interactions provide insight into the drug-side effects and drug repositioning. However, wet-lab biochemical experiments are time-consuming and labor-intensive, and are insufficient to meet the pressing demand for drug research and development. With the rapid advancement of deep learning, computational methods are increasingly applied to screen drug-target interactions. Many methods consider this problem as a binary classification task (binding or not), but ignore the quantitative binding affinity. In this paper, we propose a new end-to-end deep learning method called DeepMHADTA, which uses the multi-head self-attention mechanism in a deep residual network to predict drug-target binding affinity. On two benchmark datasets, our method outperformed several current state-of-the-art methods in terms of multiple performance measures, including mean square error (MSE), consistency index (CI), rm2, and PR curve area (AUPR). The results demonstrated that our method achieved better performance in predicting the drug–target binding affinity.     

Time-Series Clustering of lncRNA-mRNA Expression during the Adipogenic Transdifferentiation of Porcine Skeletal Muscle Satellite Cells

Skeletal muscle satellite cells (SMSCs), which are multifunctional muscle-derived stem cells, can differentiate into adipocytes. Long-chain non-coding RNA (lncRNA) has diverse biological functions, including the regulation of gene expression, chromosome silencing, and nuclear transport. However, the regulatory roles and mechanism of lncRNA during adipogenic transdifferentiation in muscle cells have not been thoroughly investigated. Here, porcine SMSCs were isolated, cultured, and induced for adipogenic differentiation. The expressions of lncRNA and mRNA at different time points during transdifferentiation were analysed using RNA-seq analysis. In total, 1005 lncRNAs and 7671 mRNAs showed significant changes in expression at differential differentiation stages. Time-series expression analysis showed that the differentially expressed (DE) lncRNAs and mRNAs were clustered into 5 and 11 different profiles with different changes, respectively. GO, KEGG, and REACTOME enrichment analyses revealed that DE mRNAs with increased expressions during the trans-differentiation were mainly enriched in the pathways for lipid metabolism and fat cell differentiation. The genes with decreased expressions were mainly enriched in the regulation of cell cycle and genetic information processing. In addition, 1883 DE mRNAs were regulated by 193 DE lncRNAs, and these genes were related to the controlling in cell cycle mainly. Notably, three genes in the fatty acid binding protein (FABP) family significantly and continuously increased during trans-differentiation, and 15, 13, and 11 lncRNAs may target FABP3, FABP4, and FABP5 genes by cis- or trans-regulation, respectively. In conclusion, these studies identify a set of new potential regulator for adipogenesis and cell fate and help us in better understanding the molecular mechanisms of trans-differentiation.