The use of time-resolved fluorescence imaging in the study of protein kinase C localisation in cells

Background: Two-photon-excitation fluorescence lifetime imaging (2P-FLIM) was used to investigate the association of protein kinase C alpha (PKCα) with caveolin in CHO cells. PKCα is found widely in the cytoplasm and nucleus in most cells. Upon activation, as a result of increased intracellular Ca2+ and production of DAG, through G-protein coupled-phospholipase C signalling, PKC translocates to a variety of regions in the cell where it phosphorylates and interacts with many signalling pathways. Due to its wide distribution, discerning a particular interaction from others within the cell is extremely difficult. Results: Fluorescence energy transfer (FRET), between GFP-PKCα and DsRed-caveolin, was used to investigate the interaction between caveolin and PKC, an aspect of signalling that is poorly understood. Using 2P-FLIM measurements, the lifetime of GFP was found to decrease (quench) in certain regions of the cell from ~2.2 ns to ~1.5 ns when the GFP and DsRed were sufficiently close for FRET to occur. This only occurred when intracellular Ca2+ increased or in the presence of phorbol ester, and was an indication of PKC and caveolin co-localisation under these conditions. In the case of phorbol ester stimulated PKC translocation, as commonly used to model PKC activation, three PKC areas could be delineated. These included PKCα that was not associated with caveolin in the nucleus and cytoplasm, PKCα associated with caveolin in the cytoplasm/perinuclear regions and probably in endosomes, and PKC in the peripheral regions of the cell, possibly indirectly interacting with caveolin. Conclusion: Based on the extent of lifetime quenching observed, the results are consistent with a direct interaction between PKCα and caveolin in the endosomes, and possibly an indirect interaction in the peripheral regions of the cell. The results show that 2P-FLIM-FRET imaging offers an approach that can provide information not only confirming the occurrence of specific protein-protein interactions but where they occur within the cell

Structure and superconductivity of LiFeAs

The lithium ions in Lithium iron arsenide phases with compositions close to LiFeAs have been located using powder neutron diffraction. These phases exhibit superconductivity at temperatures at least as high as 16 K demonstrating that superconductivity in compounds with [FeAs]- anti-PbO-type anionic layers occurs in compounds with at least three different structure types and occurs for a wide range of As-Fe-As bond angles.Comment: 3 pages, 3 figures, 3 table

Supplemental peri-operative intravenous crystalloids for postoperative nausea and vomiting: an abridged Cochrane systematic review.

We conducted a Cochrane systematic review on the effectiveness of supplemental intravenous crystalloid administration in preventing postoperative nausea and vomiting. We included randomised controlled trials of patients undergoing surgery under general anaesthesia and given supplemental peri-operative intravenous crystalloid. Our primary outcomes were the risk of postoperative nausea and the risk of postoperative vomiting. We assessed the risk of bias for each included study and applied the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework for the certainty of evidence. We included 41 studies. We found that the intervention probably reduces the overall risk of postoperative nausea, the risk ratio (95%CI) being 0.62 (0.51-0.75) (I2  = 57%, p < 0.00001, 18 studies; 1766 participants; moderate-certainty evidence). It also probably reduces the risk of postoperative nausea within 6 h of surgery, with a risk ratio (95%CI) of 0.67 (0.58 to 0.78) (I2  = 9%, p < 0.00001, 20 studies; 2310 participants; moderate-certainty evidence) and by around 24 h, the risk ratio (95%CI) being 0.47 (0.32-0.69) (I2  = 38%, p = 0.0001, 17 studies; 1682 participants; moderate-certainty evidence). Supplemental intravenous crystalloid probably also reduces the overall risk of postoperative vomiting, with a risk ratio (95%CI) of 0.50 (0.40-0.63) (I2  = 31%, p < 0.00001, 20 studies; 1970 participants; moderate-certainty evidence). The beneficial effect on vomiting was seen both within 6 h and by around 24 h postoperatively

Preparation and characterization of polycaprolactone microspheres by electrospraying

This is the author accepted manuscript. Published online: 13 Sep 2016. The final version to be made available from the publisher via the DOI in this record.The ability to reproducibly produce and effectively collect electrosprayed polymeric microspheres with controlled morphology and size in bulk form is challenging. In this study, microparticles were produced by electrospraying polycaprolactone (PCL) of various molecular weights and solution concentrations in chloroform, and by collecting materials on different substrates. The resultant PCL microparticles were characterized by optical and electron microscopy to investigate the effect of molecular weight, solution concentration, applied voltage, working distance and flow rate on their morphology and size. The work demonstrates the key role of a moderate molecular weight and/or solution concentration in the formation of spherical PCL particles via an electrospraying process. Increasing the applied voltage was found to produce smaller and more uniform PCL microparticles. There was a relatively low increase in the particle average size with an increase in the working distance and flow rate. Four types of substrates were adopted to collect electrosprayed PCL particles: a glass slide, aluminium foil, liquid bath and copper wire. Unlike 2D bulk structures collected on the other substrates, a 3D tubular structure of microspheres was formed on the copper wire and could find application in the construction of 3D tumour mimics.The financial support received from the Cancer Research UK (CRUK) and Engineering and Physical Sciences Research Council (ESPRC) Cancer Imaging Centre in Cambridge and Manchester (C8742/A18097) is acknowledged

The crystalline structure of the phenazine overlayer physisorbed on a graphite surface

The monolayer crystal structure of phenazine adsorbed on graphite is determined by a combination of synchrotron X-ray diffraction and DFT calculations. The molecules adopt a rectangular unit cell with lattice parameters a = 13.55 Å and b = 10.55 Å, which contains 2 molecules. The plane group of the unit cell is p2gg, and each molecule is essentially flat to the plane of the surface, with only a small amount of out-of-plane tilt. Density Functional Theory (DFT) calculations find a minimum energy structure with a unit cell which agrees within 7.5% with that deduced by diffraction. DFT including dispersion force corrections (DFT+D) calculations help to identify the nature of the intermolecular bonding. The overlayer interactions are principally van der Waals, with a smaller contribution from weak C-H•••N hydrogen bonds. This behaviour is compared with that of 4,4’-bipyridyl.We acknowledge financial support for AB from an EPSRC DTA award from the Department of Chemistry, University of Cambridge; and BP for financial support for CT. We thank Diamond Light Source for access to beamline I11 (EE7761) that contributed to the results presented here. The DFT calculations were performed using the Darwin Supercomputer of the University of Cambridge High Performance Computing Service.This is the accepted manuscript. The final version is available from Taylor & Francis at http://www.tandfonline.com/doi/abs/10.1080/00268976.2013.793844#.VGHd34XziEo

Theoretical basis and practical aspects of small specimen creep testing

Interest in and the application of small specimen creep test techniques are increasing. This is because it is only possible to obtain small samples of material in some situations, for example, the scoop samples that are removed from in-service components, the heat-affected zones that are created when welds are used to join components and the desire to produce only small amounts of material in alloy development programmes. It is therefore important to review and compare the theoretical basis and practical aspects of each of the small specimen creep testing methods, in order to clearly understand which of the methods is the best for any specific application. This article provides the theoretical basis for each commonly used test method

A transfer-learning approach to feature extraction from cancer transcriptomes with deep autoencoders

Publicado en Lecture Notes in Computer Science.The diagnosis and prognosis of cancer are among the more challenging tasks that oncology medicine deals with. With the main aim of fitting the more appropriate treatments, current personalized medicine focuses on using data from heterogeneous sources to estimate the evolu- tion of a given disease for the particular case of a certain patient. In recent years, next-generation sequencing data have boosted cancer prediction by supplying gene-expression information that has allowed diverse machine learning algorithms to supply valuable solutions to the problem of cancer subtype classification, which has surely contributed to better estimation of patient’s response to diverse treatments. However, the efficacy of these models is seriously affected by the existing imbalance between the high dimensionality of the gene expression feature sets and the number of sam- ples available for a particular cancer type. To counteract what is known as the curse of dimensionality, feature selection and extraction methods have been traditionally applied to reduce the number of input variables present in gene expression datasets. Although these techniques work by scaling down the input feature space, the prediction performance of tradi- tional machine learning pipelines using these feature reduction strategies remains moderate. In this work, we propose the use of the Pan-Cancer dataset to pre-train deep autoencoder architectures on a subset com- posed of thousands of gene expression samples of very diverse tumor types. The resulting architectures are subsequently fine-tuned on a col- lection of specific breast cancer samples. This transfer-learning approach aims at combining supervised and unsupervised deep learning models with traditional machine learning classification algorithms to tackle the problem of breast tumor intrinsic-subtype classification.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Design of Experiments Methodology to Build a Multifactorial Statistical Model Describing the Metabolic Interactions of Alcohol Dehydrogenase Isozymes in the Ethanol Biosynthetic Pathway of the Yeast Saccharomyces cerevisiae

This is the author accepted manuscript. The final version is available from the American Chemical Society via the DOI in this recordMultifactorial approaches can quickly and efficiently model complex, interacting natural or engineered biological systems in a way that traditional one-factor-at-a-time experimentation can fail to do. We applied a Design of Experiments (DOE) approach to model ethanol biosynthesis in yeast, which is well-understood and genetically tractable, yet complex. Six alcohol dehydrogenase (ADH) isozymes catalyze ethanol synthesis, differing in their transcriptional and post-translational regulation, subcellular localization, and enzyme kinetics. We generated a combinatorial library of all ADH gene deletions and measured the impact of gene deletion(s) and environmental context on ethanol production of a subset of this library. The data were used to build a statistical model that described known behaviors of ADH isozymes and identified novel interactions. Importantly, the model described features of ADH metabolic behavior without explicit a priori knowledge. The method is therefore highly suited to understanding and optimizing metabolic pathways in less well-understood systems.We wish to thank Dr. Alex Johns for helpful discussions. S.R.B. would also like to thank Shell Biodomain for funding for this PhD research project