Molecular basis for the mechanism of action of an anti-TACE antibody

Inhibitors of tumor necrosis factor-α converting enzyme (TACE) have potential as therapeutics for various diseases. Many small molecule inhibitors, however, exhibit poor specificity profiles because they target the highly conserved catalytic cleft of TACE. We report for the first time the molecular interaction of a highly specific anti-TACE antagonistic antibody (MEDI3622). We characterized the binding of MEDI3622 using mutagenesis, as well as structural modeling and docking approaches. We show that MEDI3622 recognizes a unique surface loop of sIVa-sIVb β-hairpin on TACE M-domain, but does not interact with the conserved catalytic cleft or its nearby regions. The exquisite specificity of MEDI3622 is mediated by this distinct structural feature on the TACE M-domain. These findings may aid the design of antibody therapies against TACE.     

Feeder-free Derivation of Melanocytes from Human Pluripotent Stem Cells

Human pluripotent stem cells (hPSCs) represent a platform to study human development in vitro under both normal and disease conditions. Researchers can direct the differentiation of hPSCs into the cell type of interest by manipulating the culture conditions to recapitulate signals seen during development. One such cell type is the melanocyte, a pigment-producing cell of neural crest (NC) origin responsible for protecting the skin against UV irradiation. This protocol presents an extension of a currently available in vitro Neural Crest differentiation protocol from hPSCs to further differentiate NC into fully pigmented melanocytes. Melanocyte precursors can be enriched from the Neural Crest protocol via a timed exposure to activators of WNT, BMP, and EDN3 signaling under dual-SMAD-inhibition conditions. The resultant melanocyte precursors are then purified and matured into fully pigmented melanocytes by culture in a selective medium. The resultant melanocytes are fully pigmented and stain appropriately for proteins characteristic of mature melanocytes.     

Sensitivity analysis of Repast computational ecology models with R/Repast

Computational ecology is an emerging interdisciplinary discipline founded mainly on modeling and simulation methods for studying ecological systems. Among the existing modeling formalisms, the individual‐based modeling is particularly well suited for capturing the complex temporal and spatial dynamics as well as the nonlinearities arising in ecosystems, communities, or populations due to individual variability. In addition, being a bottom‐up approach, it is useful for providing new insights on the local mechanisms which are generating some observed global dynamics. Of course, no conclusions about model results could be taken seriously if they are based on a single model execution and they are not analyzed carefully. Therefore, a sound methodology should always be used for underpinning the interpretation of model results. The sensitivity analysis is a methodology for quantitatively assessing the effect of input uncertainty in the simulation output which should be incorporated compulsorily to every work based on in‐silico experimental setup. In this article, we present R/Repast a GNU R package for running and analyzing Repast Simphony models accompanied by two worked examples on how to perform global sensitivity analysis and how to interpret the results.     

北美刺龙葵在中国的适生区预测

【背景】北美刺龙葵是一种全球广泛分布的恶性杂草,已被列入我国进境检疫性有害生物名单。近年来北美刺龙葵不断随进口货物传入我国,明确其传入途径和适生区对控制其入侵具有重要意义。【方法】采用GIS、空间统计学、Maxent生态位模型等方法分析了北美刺龙葵的传入途径与潜在分布区,并通过ROC分析法对模型进行检验。【结果】跨区域农产品贸易是北美刺龙葵全球扩散的驱动力与传入我国的主要途径。生态模型预测结果表明,北美刺龙葵在我国具有广阔的适生区,除黑龙江、吉林、内蒙古、青海、甘肃、西藏、四川西北部以外的区域都是其在我国的适生区,其中高风险区主要集中在东部和南部沿海、西南边境和新疆的部分地区。AUC值为0.789,表明本研究建立的Maxent模型的预测能力较强,能够很好地拟合物种已知分布的环境生态位。【结论与意义】北美刺龙葵在我国的传入风险极高。基于北美刺龙葵在我国的主要传入途径与潜在扩散媒介的时空分布,划定了重点监测的区域,建议对适生区内极易传入的高风险区如港口、机场、物流中转站、加工厂等开展早期监测预警,以预防其再次入侵与进一步扩散蔓延。     

Investigation and modeling of the effects of light spectrum and incident angle on the growth of Chlorella vulgaris in photobioreactors

An in‐depth investigation of how various illumination conditions influence microalgal growth in photobioreactors (PBR) has been presented. Effects of both the light emission spectrum (white and red) and the light incident angle (0° and 60°) on the PBR surface were investigated. The experiments were conducted in two fully controlled lab‐scale PBRs, a torus PBR and a thin flat‐panel PBR for high cell density culture. The results obtained in the torus PBR were used to build the kinetic growth model of Chlorella vulgaris taken as a model species. The PBR model was then applied to the thin flat‐panel PBR, which was run with various illumination conditions. Its detailed representation of local rate of photon absorption under various conditions (spectral calculation of light attenuation, incident angle influence) enabled the model to take into account all the tested conditions with no further adjustment. This allowed a detailed investigation of the coupling between radiation field and photosynthetic growth. Effects of all the radiation conditions together with pigment acclimation, which was found to be relevant, were investigated in depth. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:247–261, 2016     

Toward intensifying design of experiments in upstream bioprocess development: An industrial Escherichia coli feasibility study

In this study, step variations in temperature, pH, and carbon substrate feeding rate were performed within five high cell density Escherichia coli fermentations to assess whether intraexperiment step changes, can principally be used to exploit the process operation space in a design of experiment manner. A dynamic process modeling approach was adopted to determine parameter interactions. A bioreactor model was integrated with an artificial neural network that describes biomass and product formation rates as function of varied fed‐batch fermentation conditions for heterologous protein production. A model reliability measure was introduced to assess in which process region the model can be expected to predict process states accurately. It was found that the model could accurately predict process states of multiple fermentations performed at fixed conditions within the determined validity domain. The results suggest that intraexperimental variations of process conditions could be used to reduce the number of experiments by a factor, which in limit would be equivalent to the number of intraexperimental variations per experiment. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1343–1352, 2016