Crystallization and preliminary x-ray diffraction studies of a novel bacterial esterase.

Journal ArticleResearch Support, Non-U.S. Gov'tA novel bacterial esterase has been crystallized in two forms suitable for X-ray diffraction studies. Crystals have been obtained by vapour-phase diffusion at 290 K using ammonium sulfate as precipitant. The first crystals grew in space group C2 with unit-cell parameters a = 134.7, b = 55.8, c = 110.3 A, beta = 125.1 degrees. A monoclinic data set has been collected to 2.0 A resolution. Microseeding yielded a second crystal form which grew in space group P212121 with unit-cell parameters a = 57.1, b = 115.4, c = 130.4 A. Native data from these crystals have been collected to 1.6 A resolution. A molecular envelope has been determined using an uranyl acetate derivative for phase calculation.BBSRCSmithKline Beecham PharmaceuticalsEuropean Unio

Algorithms for the self-optimisation of chemical reactions

Self-optimising chemical systems have experienced a growing momentum in recent years, with the evolution of self-optimising platforms leading to their application for reaction screening and chemical synthesis. With the desire for improved process sustainability, self-optimisation provides a cheaper, faster and greener approach to the chemical development process. The use of such platforms aims to enhance the capabilities of the researcher by removing the need for labor-intensive experimentation, allowing them to focus on more challenging tasks. The establishment of these systems have enabled opportunities for self-optimising platforms to become a key element of a laboratory’s repertoire. To enable the wider adoption of self-optimising chemical platforms, this review summarises the history of algorithmic usage in chemical reaction self-optimisation, detailing the functionality of the algorithms and their applications in a way that is accessible for chemists and highlights opportunities for the further exploitation of algorithms in chemical synthesis moving forward

A Hybridised Optimisation of an Automated Photochemical Continuous Flow Reactor

A new hybridized algorithm that combines process optimisation with response surface mapping was developed and applied in an automated continuous flow reaction. Moreover, a photochemical cascade CSTR was developed and characterised by chemical actinometry, showing photon flux density of ten times greater than previously reported in batch. The success of the algorithm was then evaluated in the aerobic oxidation of sp3 C–H bonds using benzophenone as photosensitizer in the newly developed photo reactor

Automated Self-Optimisation of Multi-Step Reaction and Separation Processes Using Machine Learning

There has been an increasing interest in the use of automated self-optimising continuous flow platforms for the development and manufacture in synthesis in recent years. Such processes include multiple reactive and work-up steps, which need to be efficiently optimised. Here, we report the combination of multi-objective optimisation based on machine learning methods (TSEMO algorithm) with self-optimising platforms for the optimisation of multi-step continuous reaction processes. This is demonstrated for a pharmaceutically relevant Sonogashira reaction. We demonstrate how optimum reaction conditions are re-evaluated with the changing downstream work-up specifications in the active learning process. Furthermore, a Claisen-Schmidt condensation reaction with subsequent liquid-liquid separation was optimised with respect to three-objectives. This approach provides the ability to simultaneously optimise multi-step processes with respect to multiple objectives, and thus has the potential to make substantial savings in time and resources

Imaging fetal anatomy.

Due to advancements in ultrasound techniques, the focus of antenatal ultrasound screening is moving towards the first trimester of pregnancy. The early first trimester however remains in part, a 'black box', due to the size of the developing embryo and the limitations of contemporary scanning techniques. Therefore there is a need for images of early anatomical developmental to improve our understanding of this area. By using new imaging techniques, we can not only obtain better images to further our knowledge of early embryonic development, but clear images of embryonic and fetal development can also be used in training for e.g. sonographers and fetal surgeons, or to educate parents expecting a child with a fetal anomaly. The aim of this review is to provide an overview of the past, present and future techniques used to capture images of the developing human embryo and fetus and provide the reader newest insights in upcoming and promising imaging techniques. The reader is taken from the earliest drawings of da Vinci, along the advancements in the fields of in utero ultrasound and MR imaging techniques towards high-resolution ex utero imaging using Micro-CT and ultra-high field MRI. Finally, a future perspective is given about the use of artificial intelligence in ultrasound and new potential imaging techniques such as synchrotron radiation-based CT to increase our knowledge regarding human development

Cortical Factor Feedback Model for Cellular Locomotion and Cytofission

Eukaryotic cells can move spontaneously without being guided by external cues. For such spontaneous movements, a variety of different modes have been observed, including the amoeboid-like locomotion with protrusion of multiple pseudopods, the keratocyte-like locomotion with a widely spread lamellipodium, cell division with two daughter cells crawling in opposite directions, and fragmentations of a cell to multiple pieces. Mutagenesis studies have revealed that cells exhibit these modes depending on which genes are deficient, suggesting that seemingly different modes are the manifestation of a common mechanism to regulate cell motion. In this paper, we propose a hypothesis that the positive feedback mechanism working through the inhomogeneous distribution of regulatory proteins underlies this variety of cell locomotion and cytofission. In this hypothesis, a set of regulatory proteins, which we call cortical factors, suppress actin polymerization. These suppressing factors are diluted at the extending front and accumulated at the retracting rear of cell, which establishes a cellular polarity and enhances the cell motility, leading to the further accumulation of cortical factors at the rear. Stochastic simulation of cell movement shows that the positive feedback mechanism of cortical factors stabilizes or destabilizes modes of movement and determines the cell migration pattern. The model predicts that the pattern is selected by changing the rate of formation of the actin-filament network or the threshold to initiate the network formation

Rapid, Automated Determination of Reaction Models and Kinetic Parameters

We herein report a novel kinetic modelling methodology whereby identification of the correct reaction model and kinetic parameters is conducted by an autonomous framework combined with transient flow measurements to enable comprehensive process understanding with minimal user input. An automated flow chemistry platform was employed to initially conduct linear flow-ramp experiments to rapidly map the reaction profile of three processes using transient flow data. Following experimental data acquisition, a computational approach was utilised to discriminate between all possible reaction models as well as identify the correct kinetic parameters for each process. Species that are known to participate in the process (starting materials, intermediates, products) are initially inputted by the user prior to flow ramp experiments, then all possible model candidates are compiled into a model library based on their potential to occur after mass balance assessment. Parallel computational optimisation then evaluates each model by algorithmically altering the kinetic parameters of the model to allow convergence of a simulated kinetic curve to the experimental data provided. Statistical analysis then determines the most likely reaction model based on model simplicity and agreement with experimental data. This automated approach to gaining full process understanding, whereby a small number of data-rich experiments are conducted, and the kinetics are evaluated autonomously, shows significant improvements on current industrial optimisation techniques in terms of labour, time and overall cost. The computational approach herein described can be employed using data from any set of experiments and the code is open-source

The Early Postnatal Nonhuman Primate Neocortex Contains Self-Renewing Multipotent Neural Progenitor Cells

The postnatal neocortex has traditionally been considered a non-neurogenic region, under non-pathological conditions. A few studies suggest, however, that a small subpopulation of neural cells born during postnatal life can differentiate into neurons that take up residence within the neocortex, implying that postnatal neurogenesis could occur in this region, albeit at a low level. Evidence to support this hypothesis remains controversial while the source of putative neural progenitors responsible for generating new neurons in the postnatal neocortex is unknown. Here we report the identification of self-renewing multipotent neural progenitor cells (NPCs) derived from the postnatal day 14 (PD14) marmoset monkey primary visual cortex (V1, striate cortex). While neuronal maturation within V1 is well advanced by PD14, we observed cells throughout this region that co-expressed Sox2 and Ki67, defining a population of resident proliferating progenitor cells. When cultured at low density in the presence of epidermal growth factor (EGF) and/or fibroblast growth factor 2 (FGF-2), dissociated V1 tissue gave rise to multipotent neurospheres that exhibited the ability to differentiate into neurons, oligodendrocytes and astrocytes. While the capacity to generate neurones and oligodendrocytes was not observed beyond the third passage, astrocyte-restricted neurospheres could be maintained for up to 6 passages. This study provides the first direct evidence for the existence of multipotent NPCs within the postnatal neocortex of the nonhuman primate. The potential contribution of neocortical NPCs to neural repair following injury raises exciting new possibilities for the field of regenerative medicine

Gated Diffusion-controlled Reactions

The binding and active sites of proteins are often dynamically occluded by motion of the nearby polypeptide. A variety of theoretical and computational methods have been developed to predict rates of ligand binding and reactivity in such cases. Two general approaches exist, "protein centric" approaches that explicitly treat only the protein target, and more detailed dynamical simulation approaches in which target and ligand are both treated explicitly. This mini-review describes recent work in this area and some of the biological implications

Revisiting Date and Party Hubs: Novel Approaches to Role Assignment in Protein Interaction Networks

The idea of 'date' and 'party' hubs has been influential in the study of protein-protein interaction networks. Date hubs display low co-expression with their partners, whilst party hubs have high co-expression. It was proposed that party hubs are local coordinators whereas date hubs are global connectors. Here we show that the reported importance of date hubs to network connectivity can in fact be attributed to a tiny subset of them. Crucially, these few, extremely central, hubs do not display particularly low expression correlation, undermining the idea of a link between this quantity and hub function. The date/party distinction was originally motivated by an approximately bimodal distribution of hub co-expression; we show that this feature is not always robust to methodological changes. Additionally, topological properties of hubs do not in general correlate with co-expression. Thus, we suggest that a date/party dichotomy is not meaningful and it might be more useful to conceive of roles for protein-protein interactions rather than individual proteins. We find significant correlations between interaction centrality and the functional similarity of the interacting proteins.Comment: 27 pages, 5 main figures, 4 supplementary figure