Effects of abiotic stressors on lutein production in the green microalga Dunaliella salina.

BackgroundRecent years have witnessed a rising trend in exploring microalgae for valuable carotenoid products as the demand for lutein and many other carotenoids in global markets has increased significantly. In green microalgae lutein is a major carotenoid protecting cellular components from damage incurred by reactive oxygen species under stress conditions. In this study, we investigated the effects of abiotic stressors on lutein accumulation in a strain of the marine microalga D. salina which had been selected for growth under stress conditions of combined blue and red lights by adaptive laboratory evolution.ResultsNitrate concentration, salinity and light quality were selected as three representative influencing factors and their impact on lutein production in batch cultures of D. salina was evaluated using response surface analysis. D. salina was found to be more tolerant to hyper-osmotic stress than to hypo-osmotic stress which caused serious cell damage and death in a high proportion of cells while hyper-osmotic stress increased the average cell size of D. salina only slightly. Two models were developed to explain how lutein productivity depends on the stress factors and for predicting the optimal conditions for lutein productivity. Among the three stress variables for lutein production, stronger interactions were found between nitrate concentration and salinity than between light quality and the other two. The predicted optimal conditions for lutein production were close to the original conditions used for adaptive evolution of D. salina. This suggests that the conditions imposed during adaptive evolution may have selected for the growth optima arrived at.ConclusionsThis study shows that systematic evaluation of the relationship between abiotic environmental stresses and lutein biosynthesis can help to decipher the key parameters in obtaining high levels of lutein productivity in D. salina. This study may benefit future stress-driven adaptive laboratory evolution experiments and a strategy of applying stress in a step-wise manner can be suggested for a rational design of experiments

Quantitative time-course metabolomics in human red blood cells reveal the temperature dependence of human metabolic networks

To access publisher's full text version of this article click on the hyperlink belowThe temperature dependence of biological processes has been studied at the levels of individual biochemical reactions and organism physiology (e.g. basal metabolic rates) but has not been examined at the metabolic network level. Here, we used a systems biology approach to characterize the temperature dependence of the human red blood cell (RBC) metabolic network between 4 and 37 °C through absolutely quantified exo- and endometabolomics data. We used an Arrhenius-type model (Q10) to describe how the rate of a biochemical process changes with every 10 °C change in temperature. Multivariate statistical analysis of the metabolomics data revealed that the same metabolic network-level trends previously reported for RBCs at 4 °C were conserved but accelerated with increasing temperature. We calculated a median Q10 coefficient of 2.89 ± 1.03, within the expected range of 2-3 for biological processes, for 48 individual metabolite concentrations. We then integrated these metabolomics measurements into a cell-scale metabolic model to study pathway usage, calculating a median Q10 coefficient of 2.73 ± 0.75 for 35 reaction fluxes. The relative fluxes through glycolysis and nucleotide metabolism pathways were consistent across the studied temperature range despite the non-uniform distributions of Q10 coefficients of individual metabolites and reaction fluxes. Together, these results indicate that the rate of change of network-level responses to temperature differences in RBC metabolism is consistent between 4 and 37 °C. More broadly, we provide a baseline characterization of a biochemical network given no transcriptional or translational regulation that can be used to explore the temperature dependence of metabolism.European Research Council United States Department of Energy NHLBI, National Institutes of Healt

Áhrif fyrsta marks á úrslit leikja í pepsi deild karla og kvenna 2017

Viðfangsefni ritgerðarinnar snéri að áhrifum fyrsta marks á úrslit leikja í Pepsi deild karla og kvenna árið 2017 og tíðni og dreifingu markaskorunar eftir 15 mínútna leikhlutum. Niðurstöður voru fengnar af ksi.is og skráðar í Excel skjal. Að því loknu voru niðurstöður yfirfærðar í SPSS tölfræðiforrit sem sá um að reikna út niðurstöður eftir þeim breytum sem valdar voru. Niðurstöður voru að endingu skjalfærðar og settar fram á viðeigandi máta, svo sem niðurstöður um úrslit leikja og tíðni og dreifingu markaskorunnar. Við úrvinnslu heimilda kom í ljós að áhrif fyrsta marks á úrslit leikja eru töluverð, og að marktækur munur reynist á niðurstöðum leikja eftir því hvort lið geri fyrsta mark leiksins eður ei. Eins kom fram að Pepsi deild karla og kvenna 2017 er á lítinn hátt frábrugðin stærstu deildum heims, varðandi tíðni og hlutfallslega dreifingu eftir leikhlutu

Biocarriers facilitated gravity-driven membrane filtration of domestic wastewater in cold climate: combined effect of temperature and periodic cleaning

In this study, two lava stone biocarrier facilitated gravity-driven membrane (GDM) reactors were operated at ~8 °C and ~22 °C in parallel for treating primary wastewater effluent. Although the biocarrier reactor at 8 °C displayed less efficient removals of biodegradable organics than that at 22 °C, both GDM systems (without cleaning) showed comparable fouling resistance distribution patterns, accompanying with similar cake filtration constants and pore constriction constants by modelling simulation. Compared to the GDM at 8 °C, more foulants were accumulated on the GDM at 22 °C, but they presented similar soluble organics/inorganics contents and specific cake resistances. This indicated the cake layers at 22 °C may contain greater-sized foulants due to proliferation of both prokaryotes and eukaryotes, leading to a relatively less-porous nature. In the presence of periodic cleaning (at 50 °C), the cleaning effectiveness followed a sequence as ultrasonication-enhanced physical cleaning > two-phase flow cleaning > chemical-enhanced physical cleaning > physical cleaning, regardless of GDM operation temperature. However, significantly higher cake resistances were observed in the GDM system at 22 °C than those at 8 °C, because shear force tended to remove loosely-attached foulant layers and may compress the residual dense cake layer. The presence of periodic cleaning led to dissimilar dominant prokaryotic and eukaryotic communities in the cake layers as those without cleaning and in the lava stone biocarriers. Nevertheless, operation temperature did not influence GDM permeate quality, which met EU discharge standards.Economic Development Board (EDB)The University of Iceland is acknowledged for providing Research Fund to Bing Wu and providing PhD scholarship to Selina Hube. The Economic Development Board (EDB) of Singapore is acknowledged for funding the Singapore Membrane Technology Centre (SMTC), Nanyang Technological University

Combined effects of external moments and muscle activations on acl loading during numerical simulations of a female model in opensim

Funding text Funding: This research was funded by a U.S. Fulbright Fellowship grant (recipient; O.D.). The remaining authors were funded through a grant from The Icelandic Centre for Research (accessed on 13 December 2021), grant numbers 120410021, 903271305, 1203250031, and 185359051. No funding source had any input in the design of the study, writing of the manuscript, nor the decision to submit the manuscript for publication. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Background: Anterior cruciate ligament (ACL) injuries have been studied using a variety of methods and tools. However, each is hindered by specific limitations with respect to its application. Aim: To assess the combined effects of external moments and muscle activations on ACL loading using serial, forward dynamics (FD) simulations of single leg, hyperextension landings in OpenSim. Methods: The FD tool of OpenSim was iteratively run using different combinations of knee-spanning muscle activation levels, internal rotation and valgus knee moment magnitudes. A regression was conducted on the data in order to predict ACL loading under different conditions. Results: A purely abduction moment leads to greater mean ACL loading than a purely internal rotation moment or any combination of the two. Additionally, the generalized boosted regression model using both external moments and certain knee muscles identified the internal rotation moment as the most important variable in predicting the ACL load (R2 = 0.9; p < 0.0001). Conclusion: This study demonstrated a novel and practical application of an OpenSim musculoskeletal model that supports the ACL injury mechanism of landing with low knee flexion angles, high muscle forces of the Quadriceps muscles and an external knee valgus moment, though further investigation is needed.Peer reviewe

Analysis of Chest X-ray for COVID-19 Diagnosis as a Use Case for an HPC-Enabled Data Analysis and Machine Learning Platform for Medical Diagnosis Support

The COVID-19 pandemic shed light on the need for quick diagnosis tools in healthcare, leading to the development of several algorithmic models for disease detection. Though these models are relatively easy to build, their training requires a lot of data, storage, and resources, which may not be available for use by medical institutions or could be beyond the skillset of the people who most need these tools. This paper describes a data analysis and machine learning platform that takes advantage of high-performance computing infrastructure for medical diagnosis support applications. This platform is validated by re-training a previously published deep learning model (COVID-Net) on new data, where it is shown that the performance of the model is improved through large-scale hyperparameter optimisation that uncovered optimal training parameter combinations. The per-class accuracy of the model, especially for COVID-19 and pneumonia, is higher when using the tuned hyperparameters (healthy: 96.5%; pneumonia: 61.5%; COVID-19: 78.9%) as opposed to parameters chosen through traditional methods (healthy: 93.6%; pneumonia: 46.1%; COVID-19: 76.3%). Furthermore, training speed-up analysis shows a major decrease in training time as resources increase, from 207 min using 1 node to 54 min when distributed over 32 nodes, but highlights the presence of a cut-off point where the communication overhead begins to affect performance. The developed platform is intended to provide the medical field with a technical environment for developing novel portable artificial-intelligence-based tools for diagnosis support

Dataset on economic analysis of mass production of algae in LED-based photobioreactors

The data presented in this article are related to the research article entitled “Sugar-stimulated CO2 sequestration by the green microalga Chlorella vulgaris” (Fu et al., 2019) [1]. The data describe a rational design and scale-up of LED-based photobioreactors for producing value-added algal biomass while removing waste CO2 from flu gases from power plants. The dataset were created from growth rate experiments for biomass production including direct biomass productivity data, PBR size and setup parameters, medium composition as well as indirect energy cost and overhead in Iceland. A complete economic analysis is formed through a cost breakdown as well as PBR scalability predictions

Metabolomic analysis of platelets during storage: a comparison between apheresis- and buffy coat-derived platelet concentrates.

To access publisher's full text version of this article click on the hyperlink at the bottom of the pagePlatelet concentrates (PCs) can be prepared using three methods: platelet (PLT)-rich plasma, apheresis, and buffy coat. The aim of this study was to obtain a comprehensive data set that describes metabolism of buffy coat-derived PLTs during storage and to compare it with a previously published parallel data set obtained for apheresis-derived PLTs.During storage we measured more than 150 variables in 8 PLT units, prepared by the buffy coat method. Samples were collected at seven different time points resulting in a data set containing more than 8000 measurements. This data set was obtained by combining a series of standard quality control assays to monitor the quality of stored PLTs and a deep coverage metabolomics study using liquid chromatography coupled with mass spectrometry.Stored PLTs showed a distinct metabolic transition occurring 4 days after their collection. The transition was evident in PLT produced by both production methods. Apheresis-derived PLTs showed a clearer phenotype of PLT activation during early days of storage. The activated phenotype of apheresis PLTs was accompanied by a higher metabolic activity, especially related to glycolysis and the tricarboxylic acid cycle. Moreover, the extent of the activation differed between bags resulting in interbag variability in the storage lesion of apheresis-prepared PLTs. This may be related to donor-related polymorphism.This study demonstrated two discrete metabolic phenotypes in stored PLTs prepared with both apheresis and buffy coat methods. PLT activation occurs during the first metabolic phenotype and might lead to a low reproducibility of the apheresis PCs.info:eu-repo/grantAgreement/EC/FP7/23281

Beryl & Bobo Acrobatic comedy trampolinists in the J.C. Williamson production of The Piddington Show (2) 2 copies [picture]

Part of the collection: J.C. Williamson collection of photographs.; The Piddington show.; Also available in an electronic version via the internet at: http://nla.gov.au/nla.pic-vn3805403; Seasons in Australasia recorded in programs and ephemera held in J C Williamson collection, PROMPT Collection: 1951 commencing 1 February Empire Theatre, Sydney; 1951 commencing 3 April Comedy Theatre, Melbourne

Mannose and fructose metabolism in red blood cells during cold storage in SAGM

To access publisher's full text version of this article click on the hyperlink belowBACKGROUND: Alternate sugar metabolism during red blood cell (RBC) storage is not well understood. Here we report fructose and mannose metabolism in RBCs during cold storage in SAGM and the impact that these monosaccharides have on metabolic biomarkers of RBC storage lesion. STUDY DESIGN AND METHODS: RBCs were stored in SAGM containing uniformly labeled 13 C-fructose or 13 C-mannose at 9 or 18 mmol/L concentration for 25 days. RBCs and media were sampled at 14 time points during storage and analyzed using ultraperformance liquid chromatography-mass spectrometry. Blood banking quality assurance measurements were performed. RESULTS: Red blood cells incorporated fructose and mannose during cold storage in the presence of glucose. Mannose was metabolized in preference to glucose via glycolysis. Fructose lowered adenosine triphosphate (ATP) levels and contributed little to ATP maintenance when added to SAGM. Both monosaccharides form the advanced glycation end product glycerate. Mannose activates enzymes in the RBC that take part in glycan synthesis. CONCLUSIONS: Fructose or mannose addition to RBC SAGM concentrates may not offset the shift in metabolism of RBCs that occurs after 10 days of storage. Fructose and mannose metabolism at 4°C in SAGM reflects their metabolism at physiologic temperature. Glycerate excretion is a measure of protein deglycosylation activity in stored RBCs. No cytoprotective effect was observed upon the addition of either fructose or mannose to SAGM.European Research Council RANNIS Gran