Mate detection success of maleClethrionomys rufocanus in relation to the spatial distribution of sexually receptive females

Summary Mate detection success of male grey-sided voles,Clethrionomys rufocanus, in relation to the spatial distribution of sexually receptive females was studied in an experimental island population. The spatiotemporal distribution of receptive females was controlled by containing females in small, mobile wire-mesh cages, whereas the response by free-ranging males was monitored by means of radiotelemetry. Males were on average more successful in finding oestrous females when females were spatially clumped than when females were spatially overdispersed. In addition, the variance (CV) in male mate detecting success was highest when females had an overdispersed spatial distribution. These results are consistent with predictions from a theoretical model (Ims, 1988b) analysing the effect of mate distribution on male mating success, and with empirical results on prey detection success of predators searching for prey.     

Effect of pea bacterial blight (Pseudomonas syringae pv. pisi) on the yield of spring sown combining peas (Pisum sativum)

Field trials to examine the effect of pea bacterial blight (Pseudomonas syringae pv. pisi) (Psp) on the yield of combining peas were carried out at five sites (HRI Wellesbourne, ADAS Rosemaund, ADAS Terrington, PGRO, SASA East Craigs) in the UK in 1990, 1991 and 1992. Healthy seed, cv. Solara, and seed naturally infected with Psp Race 2 was sown in large plots (c. 200 m²) in the open or under nets to prevent bird damage by pigeons. Despite relatively low disease severity levels (< 15% leaf area) and separation by at least 12 m of cv. Consort (resistant to Race 2) between plots there was considerable spread of disease into plots sown with healthy seed. Regression analysis demonstrated a significant relationship between yield and disease. Of the disease measurements examined, disease severity on the leaves (stipules) at growth stage 208 was found to be the best predictor of yield. A model containing environmental and bird damage terms, in addition to disease, suggested that a yield loss of 0.98 t/ha would be expected for a disease severity score of 1, equivalent to 5% leaf area affected, at growth stage 208.     

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。     

县域城镇空间形态与居住建筑能耗关联性的连续尺度研究——以浙江长兴、福建连江为例

居住建筑能耗受建筑周边空间形态的直接影响，确定空间形态低碳效应及其最佳尺度将有助于实现县域城镇低碳转型。以浙江省长兴县、福建省连江县为例，共计选取49个具有代表性的居住建筑样本，采用GIS分析与数理统计相结合的方式，在居住建筑1800m半径范围内，以200m为间隔建立缓冲区，开展全年、最冷月份能耗期及最热月份能耗期建筑能耗与周边空间形态关联性的连续尺度研究。结果表明：(1)道路密度、开发密度、容积率均与建筑能耗呈正相关，但各指标对应的能耗时期、尺度范围有较大差异。(2)水面率、土地利用混合度是与建筑能耗相关的共性指标，但在不同地区的正负效应及尺度范围不同；(3)影响浙闽地区县域城镇最热月份能耗期能耗的关键形态因子为1000m-道路密度、800m-水面率、1600m-开放空间率；影响连江最冷月份能耗期能耗的关键形态因子为800m-水面率。(4)就控碳单元设置而言，长兴县可重点关注1000—1200m半径范围，连江县可重点关注800—1000m、1400m半径范围。(5)浙闽地区县域城镇特性指标为开放空间率，与最热月份能耗期建筑能呈负相关；长兴县特性指标为容积率、水岸密度，分别与全年、最冷...     

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.