Identifying hotspots of endemic woody seed plant diversity in China

Aim This study aimed to detect distribution patterns and identify diversity hotspots for Chinese endemic woody seed plant species (CEWSPS). Location China. Methods Presence of 6885 CEWSPS throughout China was mapped by taking the Chinese administrative county as the basic spatial analysis unit. The diversity was measured with five indices: endemic richness (ER), weighted endemism (WE), phylogenetic diversity (PD), phylogenetic endemism (PE) and biogeographically weighted evolutionary distinctiveness (BED). Three levels of area (i.e. 1, 5 and 10% of China’s total land area) were used to identify hotspots, but the 5% level was preferred when both the total area of the hotspots identified and the diversity of CEWSPS reached by the hotspots were considered. Results Distribution patterns of CEWSPS calculated with the five indices are consistent with each other over the national extent. However, the hotspots do not show a high degree of consistency among the results derived from the five indices. Those identified with ER and PD are very similar, and so are those with WE and BED. In total, 20 hotspots covering 7.9% of China’s total land area were identified, among which 11 were identified with all the five indices, including the Hengduan Mountains, Xishuangbanna Region, Hainan Island, and eight mountainous areas located in east Chongqing and west Hubei, in east Yunnan and west Guangxi, in north Guangxi, south‐east Guizhou and south‐west Hunan, in north Guangdong and south Hunan, in south‐east Tibet, and in south‐east Hubei and north‐west Jiangxi. Taiwan Island was also identified as a major hotspot with WE, PE and BED. Main conclusions Hotspots of CEWSPS were identified with five indices considering both distributional and phylogenetic information. They cover most of the key areas of biodiversity defined by previous researchers using other approaches. This further verifies the importance of these areas for China’s biodiversity conservation.     

Ordered Hexagonal Nanoplasmonic Au Nanoparticle Arrays: AAO-Assisted Thermal Treatment Synthesis and Application as Surface-Enhanced Raman Scattering Substrates

We have reported on the synthesis of ordered hexagonal Au nanoparticle (NPs) arrays by anodic alumina oxide templates (AAO)-assisted thermal treatment. This simple process has led to the formation of an ordered hexagonal array of Au NPs on the surface of AAO. SERS properties of the ordered hexagonal Au NPs could be obtained by varying the size of Au NPs. Compared with the Au thin film on AAO, the SERS intensity of rhodamine adsorbed on the ordered hexagonal Au NPs was about 1000 times stronger. And the hexagonal Au NPs array films have had stronger Raman-enhanced signal compared to the disorder Au NPs films. Simulations according to the three-dimensional finite-difference time domain (3D-FDTD) have displayed that these electric field enhancements of the ordered hexagonal Au NPs are strongly dependent on the gap distance. Plasmonic ordered hexagonal Au NPs could provide us new platforms to realize novel optoelectronic devices.

     

中国巢鼠属分类与分布的讨论

巢鼠属(Micromys Dehne, 1841)隶属于啮齿目(Rodentia)鼠科(Muridae),是最小的啮齿动物之一。此前的研究显示该属包含巢鼠(M. minutus)和红耳巢鼠(M. erythrotis)两个物种,但由于数据缺乏,红耳巢鼠的有效种地位仍存争议,且两个物种在中国的地理分布也不确定。本研究在安徽清凉峰国家级自然保护区采集到一批巢鼠属标本,经形态与分子学鉴定发现其包含巢鼠和红耳巢鼠两个物种,它们在清凉峰海拔1 600 m处同域分布,支持红耳巢鼠的有效种地位。基于安徽清凉峰巢鼠和红耳巢鼠的外形特点,本文对国家动物标本资源库的巢鼠属照片进行了分析,并结合相关文献资料,对中国巢鼠属的地理分布进行了整理,同时绘制了地理分布图。结果显示:在我国巢鼠主要分布在黑龙江、吉林、辽宁、内蒙古、河北、陕西、甘肃、新疆、江苏、安徽、浙江、湖南、江西、广东、福建、台湾;红耳巢鼠主要分布在云南、四川、陕西、湖北、西藏、贵州、重庆、安徽、福建、广西;两者在安徽清凉峰和陕西镇巴县、城固县皆有分布。此外,分子系统学分析显示,我国巢鼠属多样性仍被低估,极有可能存在未知的分类单元,巢鼠属的分类研究...     

Metabonomic fingerprints of fasting plasma and spot urine reveal human pre-diabetic metabolic traits

Impaired glucose tolerance (IGT) which precedes overt type 2 diabetes (T2DM) for decades is associated with multiple metabolic alterations in insulin sensitive tissues. In an UPLC-qTOF-mass spectrometry-driven non-targeted metabonomics approach we investigated plasma as well as spot urine of 51 non-diabetic, overnight fasted individuals aiming to separate subjects with IGT from controls thereby identify pathways affected by the pre-diabetic metabolic state. We could clearly demonstrate that normal glucose tolerant (NGT) and IGT subjects clustered in two distinct groups independent of the investigated metabonome. These findings reflect considerable differences in individual metabolite fingerprints, both in plasma and urine. Pre-diabetes associated alterations in fatty acid-, tryptophan-, uric acid-, bile acid-, and lysophosphatidylcholine-metabolism, as well as the TCA cycle were identified. Of note, individuals with IGT also showed decreased levels of gut flora-associated metabolites namely hippuric acid, methylxanthine, methyluric acid, and 3-hydroxyhippuric acid. The findings of our non-targeted UPLC-qTOF-MS metabonomics analysis in plasma and spot urine of individuals with IGT vs NGT offers novel insights into the metabolic alterations occurring in the long, asymptomatic period preceding the manifestation of T2DM thereby giving prospects for new intervention targets.     

福建沙溪口水电站库区混合输移参数研究

本文以沙溪口水电站水库为例,对河道式水库混合输移参数的识别作了若干研究。阐述示踪实验确定这些参数的原理、方法,提供沙溪口电站库区河段枯水期的参数值。在示踪实验基础上,提出适用于水电站不同运行状态混合输移参数的估算公式。可为有关部门研究水环境容量,制订水质规划等提供参考。     

Identification of SLITRK6 as a Novel Biomarker in hepatocellular carcinoma by comprehensive bioinformatic analysis

Hepatocellular carcinoma (HCC) is the most common primary malignancy of the adult liver and morbidity are increasing in recent years, however, there is still no effective strategy to prevent and diagnose HCC. Therefore, it is urgent to research the effective biomarker to predict clinical outcomes of HCC tumorigenesis. In the current study, differentially expressed genes in HCC and normal tissues were investigated using the Gene Expression Omnibus (GEO) dataset GSE144269 and The Cancer Genome Atlas (TCGA). Gene differential expression analysis and weighted correlation network analysis (WGCNA) methods were used to identify nine and 16 key gene modules from the GEO dataset and TCGA dataset, respectively, in which the green module in the GEO dataset and magenta module in TCGA were significantly correlated with HCC occurrence. Third, the enrichment score of gene function annotation results showed that these two key modules focus on the positive regulation of inflammatory response and cell differentiation, etc. Besides, PPI network analysis, mutation analysis, and survival analysis found that SLITRK6 had high connectivity, and its mutation significantly impacted overall survival. In addition, SLITRK6 was found to be low expressed in tumor cells. To summarize, SLITRK6 mutation was found to significantly affect the occurrence and prognosis of HCC. SLITRK6 was confirmed as a new potential gene target for HCC, which may provide a new theoretical basis for personalized diagnosis and chemotherapy of HCC in the future.     

Expression of Aquaporin 4 and Breakdown of the Blood-Brain Barrier after Hypoglycemia-Induced Brain Edema in Rats

Background

Hypoglycemia-induced brain edema is a severe clinical event that often results in death. The mechanisms by which hypoglycemia induces brain edema are unclear.

Methods

In a hypoglycemic injury model established in adult rats, brain edema was verified by measuring brain water content and visualizing water accumulation using hematoxylin and eosin staining. Temporal expression of aquaporin 4 (AQP4) and the integrity of the blood-brain barrier (BBB) were evaluated. We assessed the distribution and expression of AQP4 following glucose deprivation in astrocyte cultures.

Results

Brain edema was induced immediately after severe hypoglycemia but continued to progress even after recovery from hypoglycemia. Upregulation of AQP4 expression and moderate breakdown of the BBB were observed 24 h after recovery. In vitro, significant redistribution of AQP4 to the plasma membrane was induced following 6 h glucose deprivation.

Conclusion

Hypoglycemia-induced brain edema is caused by cytotoxic and vasogenic factors. Changes in AQP4 location and expression may play a protective role in edema resolution.     

三峡库区常绿阔叶林优势种群的结构和格局动态

重庆丰都世坪森林公园的常绿阔叶林是长江三峡库区低海拔区残存的较典型的常绿阔叶林.在此地选择具有代表性群落设立1hm2固定样地,应用相邻格子法进行每木调查,通过乔木层优势种群结构和格局研究,探讨群落的特点和动态.结果表明(1)此群落的优势树种是小红栲(Castanopsis carlesii)、丝栗栲(Castanopsis fargesii)和枫香(Liquidambar formosana).(2)小红栲和丝栗栲种群立木级结构呈不规则金字塔型,幼苗储备丰富,为增长种群,种群从Ⅰ、Ⅱ级幼苗发育到幼树过程中的死亡率较高,中等径级的株数偏少.枫香种群幼苗缺乏,为衰退种群.(3)应用偏离指数、Lloyd的平均拥挤度和聚块性指数及Morisita指数,在10×10m2尺度下对优势种群进行格局分析,发现3种优势种群成树总体上均为集群分布;小红栲和丝栗栲种群在发育过程中分布格局是由集群分布过渡到随机分布,而枫香是由随机分布过渡到集群分布.     

Caspase-8 auto-cleavage regulates programmed cell death and collaborates with RIPK3/MLKL to prevent lymphopenia

Caspase-8 is an initiator of death receptor-induced apoptosis and an inhibitor of RIPK3-MLKL-dependent necroptosis. In addition, caspase-8 has been implicated in diseases such as lymphoproliferation, immunodeficiency, and autoimmunity in humans. Although auto-cleavage is indispensable for caspase-8 activation, its physiological functions remain poorly understood. Here, we generated a caspase-8 mutant lacking E385 in auto-cleavage site knock-in mouse (Casp8^{ΔE385/ΔE385}). Casp8^{ΔE385/ΔE385} cells were expectedly resistant to Fas-induced apoptosis, however, Casp8^{ΔE385/ΔE385} cells could switch TNF-α-induced apoptosis to necroptosis by attenuating RIPK1 cleavage. More importantly, CASP8(ΔE385) sensitized cells to RIPK3-MLKL-dependent necroptosis through promoting complex II formation and RIPK1-RIPK3 activation. Notably, Casp8^{ΔE385/ΔE385}Ripk3^−/− mice partially rescued the perinatal death of Ripk1^−/− mice by blocking apoptosis and necroptosis. In contrast to the Casp8^−/−Ripk3^−/− and Casp8^−/−Mlkl^−/− mice appearing autoimmune lymphoproliferative syndrome (ALPS), both Casp8^{ΔE385/ΔE385}Ripk3^−/− and Casp8^{ΔE385/ΔE385}Mlkl^−/− mice developed transplantable lymphopenia that could be significantly reversed by RIPK1 heterozygosity, but not by RIPK1 kinase dead mutation. Collectively, these results demonstrate previously unappreciated roles for caspase-8 auto-cleavage in regulating necroptosis and maintaining lymphocytes homeostasis.Subject terms: Cell death and immune response, Immune cell death