Purification of a fibrolast-inhibitory factor from Actinobacillus actinomycetemcomitans Y4

Abstract A factor showing inhibitory activity against human gingival fibrolasts was extracted from the cytosol fraction of Actinobacillus actinomycetemcomitans Y4. The activity markedly inhibited the proliferation of human gingival fibrolasts, but had no effect on cell viability or gross morphology. No such activity was found in cytosol fractions from either Porphyromonas gingivalis 381 or Escherichia coli HB101. The extract from A. actinomycetemcomitans Y4 was then purified by anion-exchange chromatography, hydroxyapatite chromatography and gel-filtration chromatography to give a single band on SDS-PAGE with an apparent molecular mass of 65 kDa. The purification ratio was 183-fold with a recovery rate of 5% compared with the crude extract (starting material) when the activity was assessed by direct cell counts.     

重庆市生态风险预警等级划分及演化趋势模拟

生态风险预警等级评估和演化趋势模拟，可为生态风险管理提供可靠的辅助决策。以重庆市为研究对象，基于驱动力-压力-状态-影响-响应模型，构建重庆市生态风险预警指标体系，采用正态云模型和集对分析法，定量分析重庆市生态风险时空分异特征和演化趋势。研究结果表明：（1）2013-2019年，重庆市生态风险值呈"上升-下降"的波动趋势，综合生态风险隶属于重警等级，生态风险综合值从0.295下降到0.278，生态环境逐年好转；（2）重庆市生态风险有下降、不变、先上升后降低、先降低后上升以及一直升高5种演化趋势，分别占比39%、16%、5%、21%、24%；（3）重庆市生态风险转移分为两个方向，2013-2016年生态风险空间分异性增大，中警、轻警和无警风险等级不断向东北、东南和西部四周分散转移；2016-2019年生态风险分布格局变化较小，重警风险区在东部聚集；（4）演化趋势模拟结果表明，未来重庆市生态风险降低的区县有13个，占比34%，生态环境有向好发展的趋势；生态风险上升的区县有25个，占比66%，生态环境会有所恶化，但是恶化程度较低。将生态风险等级划分与预警演化趋势相结合，能为城市生态风险管理提供科学依据。     

基于MODIS NDVI的长江中游区域植被动态及与气候因子的关系

基于1999-2015年的MODIS NDVI时间序列遥感数据，应用趋势分析、变异系数、重标极差分析和偏相关分析等方法，分析了长江中游的植被时空变化特征及其与气象因子的关系。结果表明，长江中游地区NDVI均值总体上呈上升趋势（从0.72增加到0.80）。从空间分布来看，NDVI低值区域（0.1-0.5）占1.40%，高值区域（>0.7）占87.15%；NDVI空间格局呈"西高东低、北高南低"的分布特征，低值区域表现为以三省省会城市为中心向外辐射。Hurst指数显示，研究区大部分区域（60.54%）的NDVI变化趋势具有不确定性，持续性改善区域（34.78%）主要分布在西部山地区，持续性退化区域（3.26%）主要分布在人类活动频繁的较发达城市区域。在年际尺度上，研究区NDVI与各气象因子关系均不显著；月际尺度上，NDVI与降水、相对湿度和日照时数显著相关，降水和日照时数有明显的时滞性。区域内NDVI动态趋势以不确定性发展为主，城市群周边NDVI呈现持续退化的区域应该引起关注。     

Aspects Affecting Biosynthesis and Biotransformation of Secondary Metabolites in Plant Cell Cultures

Abstract

Biosensors are useful analytical devices that can be integrated with on-line process monitoring schemes. In this article, the principles and applications of these devices for bioprocess monitoring are considered. Several different types of biosensors are described, and the applications and limitations of flow injection analysis (FIA) for these applications are discussed. It is hoped that the background provided here can be useful to researchers in this area.     

Comparing multiple correspondence and principal component analyses with biomechanical signals. Example with turning the steering wheel

The purpose of this article is to compare Principal Component Analysis (PCA) and a much less used method, i.e. MCA (Multiple Correspondence Analysis) with data being first changed into membership values to fuzzy space windows. For such a comparison, data from an experimental study about turning the steering wheel is used. In a didactic perspective, this article only considers one multidimensional signal with 5 components: 3 linked to the steering wheel angle and hand positions and 2 to hand effort variables. A discussion weighs out the pros and the cons of both methods with criteria such as the possibility to show complex relational phenomena, the analysis/computing time or the information loss inherent to the averaging stage (in the perspective to analyze several hundreds of large multidimensional signals).     

In-depth Profiling and Quantification of the Lysine Acetylome in Hepatocellular Carcinoma with a Trapped Ion Mobility Mass Spectrometer

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death worldwide with limited therapeutic options. Comprehensive investigation of protein posttranslational modifications in HCC is still limited. Lysine acetylation is one of the most common types of posttranslational modification involved in many cellular processes and plays crucial roles in the regulation of cancer. In this study, we analyzed the proteome and K-acetylome in eight pairs of HCC tumors and normal adjacent tissues using a timsTOF Pro instrument. As a result, we identified 9219 K-acetylation sites in 2625 proteins, of which 1003 sites exhibited differential acetylation levels between tumors and normal adjacent tissues. Interestingly, many novel tumor-specific K-acetylation sites were characterized, for example, filamin A (K865), filamin B (K697), and cofilin (K19), suggesting altered activities of these cytoskeleton-modulating molecules, which may contribute to tumor metastasis. In addition, we observed an overall suppression of protein K-acetylation in HCC tumors, especially for enzymes from various metabolic pathways, for example, glycolysis, tricarboxylic acid cycle, and fatty acid metabolism. Moreover, the expression of deacetylase sirtuin 2 (SIRT2) was upregulated in HCC tumors, and its role of deacetylation in HCC cells was further explored by examining the impact of SIRT2 overexpression on the proteome and K-acetylome in Huh7 HCC cells. SIRT2 overexpression reduced K-acetylation of proteins involved in a wide range of cellular processes, including energy metabolism. Furthermore, cellular assays showed that overexpression of SIRT2 in HCC cells inhibited both glycolysis and oxidative phosphorylation. Taken together, our findings provide valuable information to better understand the roles of K-acetylation in HCC and to treat this disease by correcting the aberrant acetylation patterns.     

Prions and lymphoid organs: Solved and remaining mysteries

Prion colonization of secondary lymphoid organs (SLOs) is a critical step preceding neuroinvasion in prion pathogenesis. Follicular dendritic cells (FDCs), which depend on both tumor necrosis factor receptor 1 (TNFR1) and lymphotoxin β receptor (LTβR) signaling for maintenance, are thought to be the primary sites of prion accumulation in SLOs. However, prion titers in RML-infected TNFR1^−/− lymph nodes and rates of neuroinvasion in TNFR1^−/− mice remain high despite the absence of mature FDCs. Recently, we discovered that TNFR1-independent prion accumulation in lymph nodes relies on LTβR signaling. Loss of LTβR signaling in TNFR1^−/− lymph nodes coincided with the de-differentiation of high endothelial venules (HEVs)—the primary sites of lymphocyte entry into lymph nodes. These findings suggest that HEVs are the sites through which prions initially invade lymph nodes from the bloodstream. Identification of HEVs as entry portals for prions clarifies a number of previous observations concerning peripheral prion pathogenesis. However, a number of questions still remain: What is the mechanism by which prions are taken up by HEVs? Which cells are responsible for delivering prions to lymph nodes? Are HEVs the main entry site for prions into lymph nodes or do alternative routes also exist? These questions and others are considered in this article.