A High-Content Small Molecule Screen Identifies Sensitivity of Glioblastoma Stem Cells to Inhibition of Polo-Like Kinase 1

Glioblastoma multiforme (GBM) is the most common primary brain cancer in adults and there are few effective treatments. GBMs contain cells with molecular and cellular characteristics of neural stem cells that drive tumour growth. Here we compare responses of human glioblastoma-derived neural stem (GNS) cells and genetically normal neural stem (NS) cells to a panel of 160 small molecule kinase inhibitors. We used live-cell imaging and high content image analysis tools and identified JNJ-10198409 (J101) as an agent that induces mitotic arrest at prometaphase in GNS cells but not NS cells. Antibody microarrays and kinase profiling suggested that J101 responses are triggered by suppression of the active phosphorylated form of polo-like kinase 1 (Plk1) (phospho T210), with resultant spindle defects and arrest at prometaphase. We found that potent and specific Plk1 inhibitors already in clinical development (BI 2536, BI 6727 and GSK 461364) phenocopied J101 and were selective against GNS cells. Using a porcine brain endothelial cell blood-brain barrier model we also observed that these compounds exhibited greater blood-brain barrier permeability in vitro than J101. Our analysis of mouse mutant NS cells (INK4a/ARF^−/−, or p53^−/−), as well as the acute genetic deletion of p53 from a conditional p53 floxed NS cell line, suggests that the sensitivity of GNS cells to BI 2536 or J101 may be explained by the lack of a p53-mediated compensatory pathway. Together these data indicate that GBM stem cells are acutely susceptible to proliferative disruption by Plk1 inhibitors and that such agents may have immediate therapeutic value.     

INFOS: spectrum fitting software for NMR analysis

Software for fitting of NMR spectra in MATLAB is presented. Spectra are fitted in the frequency domain, using Fourier transformed lineshapes, which are derived using the experimental acquisition and processing parameters. This yields more accurate fits compared to common fitting methods that use Lorentzian or Gaussian functions. Furthermore, a very time-efficient algorithm for calculating and fitting spectra has been developed. The software also performs initial peak picking, followed by subsequent fitting and refinement of the peak list, by iteratively adding and removing peaks to improve the overall fit. Estimation of error on fitting parameters is performed using a Monte-Carlo approach. Many fitting options allow the software to be flexible enough for a wide array of applications, while still being straightforward to set up with minimal user input.     

福建冬青属二新种

本文描述了发现于福建的冬青科冬青属2新种——泰宁冬青Ilex tainingensis G. S. He和南平冬青I. nanpingensis G. S. He，并分别说明两者与其他近缘种的区别要点。泰宁冬青与太平山冬青I. sugerokii Maxim.的区别在于前种小枝被毛，无棱槽，叶片宽卵圆形，花淡紫色，分核表面具细条纹，背后中部有一凹槽。南平冬青与拟榕叶冬青I. subficoidea S. Y. Hu区别在于前种果为椭圆形，较大，表面光滑无腺点，果梗长于1 cm，每分核上端有2尖角，均可以区别。     

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。     

Occupancy in dynamic systems: accounting for multiple scales and false positives using environmental DNA to inform monitoring

Occupancy is an important metric to understand current and future trends in populations that have declined globally. In addition, occupancy can be an efficient tool for conducting landscape-scale and long-term monitoring. A challenge for occupancy monitoring programs is to determine the appropriate spatial scale of analysis and to obtain precise occupancy estimates for elusive species. We used a multi-scale occupancy model to assess occupancy of Columbia spotted frogs in the Great Basin, USA, based on environmental DNA (eDNA) detections. We collected three replicate eDNA samples at 220 sites across the Great Basin. We estimated and modeled ecological factors that described watershed and site occupancy at multiple spatial scales simultaneously while accounting for imperfect detection. Additionally, we conducted visual and dipnet surveys at all sites and used our paired detections to estimate the probability of a false positive detection for our eDNA sampling. We applied the estimated false positive rate to our multi-scale occupancy dataset and assessed changes in model selection. We had higher naïve occupancy estimates for eDNA (0.37) than for traditional survey methods (0.20). We estimated our false positive detection rate per qPCR replicate at 0.023 (95% CI: 0.016–0.033). When the false positive rate was applied to the multi-scale dataset, we did not observe substantial changes in model selection or parameter estimates. Conservation and resource managers have an increasing need to understand species occupancy in highly variable landscapes where the spatial distribution of habitat changes significantly over time due to climate change and human impact. A multi-scale occupancy approach can be used to obtain regional occupancy estimates that can account for spatially dynamic differences in availability over time, especially when assessing potential declines. Additionally, this study demonstrates how eDNA can be used as an effective tool for improved occupancy estimates across broad geographic scales for long-term monitoring.