Effect of temperature and moisture on high pressure lipid/oil extraction from microalgae

Commercially viable carbon–neutral biodiesel production from microalgae has potential for replacing depleting petroleum diesel. The process of biodiesel production from microalgae involves harvesting, drying and extraction of lipids which are energy- and cost-intensive processes. The development of effective large-scale lipid extraction processes which overcome the complexity of microalgae cell structure is considered one of the most vital requirements for commercial production. Thus the aim of this work was to investigate suitable extraction methods with optimised conditions to progress opportunities for sustainable microalgal biodiesel production. In this study, the green microalgal species consortium, Tarong polyculture was used to investigate lipid extraction with hexane (solvent) under high pressure and variable temperature and biomass moisture conditions using an Accelerated Solvent Extraction (ASE) method. The performance of high pressure solvent extraction was examined over a range of different process and sample conditions (dry biomass to water ratios (DBWRs): 100%, 75%, 50% and 25% and temperatures from 70 to 120 ºC, process time 5–15 min). Maximum total lipid yields were achieved at 50% and 75% sample dryness at temperatures of 90–120 ºC. We show that individual fatty acids (Palmitic acid C16:0; Stearic acid C18:0; Oleic acid C18:1; Linolenic acid C18:3) extraction optima are influenced by temperature and sample dryness, consequently affecting microalgal biodiesel quality parameters. Higher heating values and kinematic viscosity were compliant with biodiesel quality standards under all extraction conditions used. Our results indicate that biodiesel quality can be positively manipulated by selecting process extraction conditions that favour extraction of saturated and mono-unsaturated fatty acids over optimal extraction conditions for polyunsaturated fatty acids, yielding positive effects on cetane number and iodine values. Exceeding biodiesel standards for these two parameters opens blending opportunities with biodiesels that fall outside the minimal cetane and maximal iodine values.

Glucocorticoid receptor haploinsufficiency causes hypertension and attenuates hypothalamic-pituitary-adrenal axis and blood pressure adaptions to high-fat diet

Glucocorticoid hormones are critical to respond and adapt to stress. Genetic variations in the glucocorticoid receptor (GR) gene alter hypothalamic-pituitary-adrenal (HPA) axis activity and associate with hypertension and susceptibility to metabolic disease. Here we test the hypothesis that reduced GR density alters blood pressure and glucose and lipid homeostasis and limits adaption to obesogenic diet. Heterozygous GR βgeo/+ mice were generated from embryonic stem (ES) cells with a gene trap integration of a β-galactosidase-neomycin phosphotransferase (βgeo) cassette into the GR gene creating a transcriptionally inactive GR fusion protein. Although GRβgeo/+ mice have 50% less functional GR, they have normal lipid and glucose homeostasis due to compensatory HPA axis activation but are hypertensive due to activation of the renin-angiotensin- aldosterone system (RAAS). When challenged with a high-fat diet, weight gain, adiposity, and glucose intolerance were similarly increased in control and GRβgeo/+ mice, suggesting preserved control of intermediary metabolism and energy balance. However, whereas a high-fat diet caused HPA activation and increased blood pressure in control mice, these adaptions were attenuated or abolished in GRβgeo/+ mice. Thus, reduced GR density balanced by HPA activation leaves glucocorticoid functions unaffected but mineralocorticoid functions increased, causing hypertension. Importantly, reduced GR limits HPA and blood pressure adaptions to obesogenic diet.

A non-linear interface element model for thin layer high adhesive mortared masonry

A nonlinear interface element modelling method is formulated for the prediction of deformation and failure of high adhesive thin layer polymer mortared masonry exhibiting failure of units and mortar. Plastic flow vectors are explicitly integrated within the implicit finite element framework instead of relying on predictor–corrector like approaches. The method is calibrated using experimental data from uniaxial compression, shear triplet and flexural beam tests. The model is validated using a thin layer mortared masonry shear wall, whose experimental datasets are reported in the literature and is used to examine the behaviour of thin layer mortared masonry under biaxial loading.

Approximate Bayesian Computation for astronomical model analysis : a case study in galaxy demographics and morphological transformation at high redshift

Approximate Bayesian Computation’ (ABC) represents a powerful methodology for the analysis of complex stochastic systems for which the likelihood of the observed data under an arbitrary set of input parameters may be entirely intractable – the latter condition rendering useless the standard machinery of tractable likelihood-based, Bayesian statistical inference [e.g. conventional Markov chain Monte Carlo (MCMC) simulation]. In this paper, we demonstrate the potential of ABC for astronomical model analysis by application to a case study in the morphological transformation of high-redshift galaxies. To this end, we develop, first, a stochastic model for the competing processes of merging and secular evolution in the early Universe, and secondly, through an ABC-based comparison against the observed demographics of massive (Mgal > 1011 M⊙) galaxies (at 1.5 < z < 3) in the Cosmic Assembly Near-IR Deep Extragalatic Legacy Survey (CANDELS)/Extended Groth Strip (EGS) data set we derive posterior probability densities for the key parameters of this model. The ‘Sequential Monte Carlo’ implementation of ABC exhibited herein, featuring both a self-generating target sequence and self-refining MCMC kernel, is amongst the most efficient of contemporary approaches to this important statistical algorithm. We highlight as well through our chosen case study the value of careful summary statistic selection, and demonstrate two modern strategies for assessment and optimization in this regard. Ultimately, our ABC analysis of the high-redshift morphological mix returns tight constraints on the evolving merger rate in the early Universe and favours major merging (with disc survival or rapid reformation) over secular evolution as the mechanism most responsible for building up the first generation of bulges in early-type discs.

The complete genome sequence of Escherichia coli EC958: a high quality reference sequence for the globally disseminated multidrug resistant E. coli O25b:H4-ST131 clone

Escherichia coli ST131 is now recognised as a leading contributor to urinary tract and bloodstream infections in both community and clinical settings. Here we present the complete, annotated genome of E. coli EC958, which was isolated from the urine of a patient presenting with a urinary tract infection in the Northwest region of England and represents the most well characterised ST131 strain. Sequencing was carried out using the Pacific Biosciences platform, which provided sufficient depth and read-length to produce a complete genome without the need for other technologies. The discovery of spurious contigs within the assembly that correspond to site-specific inversions in the tail fibre regions of prophages demonstrates the potential for this technology to reveal dynamic evolutionary mechanisms. E. coli EC958 belongs to the major subgroup of ST131 strains that produce the CTX-M-15 extended spectrum β-lactamase, are fluoroquinolone resistant and encode the fimH30 type 1 fimbrial adhesin. This subgroup includes the Indian strain NA114 and the North American strain JJ1886. A comparison of the genomes of EC958, JJ1886 and NA114 revealed that differences in the arrangement of genomic islands, prophages and other repetitive elements in the NA114 genome are not biologically relevant and are due to misassembly. The availability of a high quality uropathogenic E. coli ST131 genome provides a reference for understanding this multidrug resistant pathogen and will facilitate novel functional, comparative and clinical studies of the E. coli ST131 clonal lineage.