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Now showing 1 - 10 of 38
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    ConsensusPrime—A Bioinformatic Pipeline for Ideal Consensus Primer Design
    (Basel : MDPI, 2022) Collatz, Maximilian; Braun, Sascha D.; Monecke, Stefan; Ehricht, Ralf
    Background: High-quality oligonucleotides for molecular amplification and detection procedures of diverse target sequences depend on sequence homology. Processing input sequences and identifying homogeneous regions in alignments can be carried out by hand only if they are small and contain sequences of high similarity. Finding the best regions for large and inhomogeneous alignments needs to be automated. Results: The ConsensusPrime pipeline was developed to sort out redundant and technical interfering data in multiple sequence alignments and detect the most homologous regions from multiple sequences. It automates the prediction of optimal consensus primers for molecular analytical and sequence-based procedures/assays. Conclusion: ConsensusPrime is a fast and easy-to-use pipeline for predicting optimal consensus primers that is executable on local systems without depending on external resources and web services. An implementation in a Docker image ensures platform-independent executability and installability despite the combination of multiple programs. The source code and installation instructions are publicly available on GitHub.
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    Raman spectroscopy follows time-dependent changes in T lymphocytes isolated from spleen of endotoxemic mice
    (Rockville : American Association of Immunologists, 2019) Ramoji, Anuradha; Ryabchykov, Oleg; Galler, Kerstin; Tannert, Astrid; Markwart, Robby; Requardt, Robert Pascal; Rubio, Ignacio; Bauer, Michael; Bocklitz, Thomas W.; Popp, Jürgen; Neugebauer, Ute
    T lymphocytes (T cells) are highly specialized members of the adaptive immune system and hold the key to the understanding the hosts’ response toward invading pathogen or pathogen-associated molecular patterns such as LPS. In this study, noninvasive Raman spectroscopy is presented as a label-free method to follow LPS-induced changes in splenic T cells during acute and postacute inflammatory phases (1, 4, 10, and 30 d) with a special focus on CD4+ and CD8+ T cells of endotoxemic C57BL/6 mice. Raman spectral analysis reveals highest chemical differences between CD4+ and CD8+ T cells originating from the control and LPS-treated mice during acute inflammation, and the differences are visible up to 10 d after the LPS insult. In the postacute phase, CD4+ and CD8+ T cells from treated and untreated mice could not be differentiated anymore, suggesting that T cells largely regained their original status. In sum, the biological information obtained from Raman spectra agrees with immunological readouts demonstrating that Raman spectroscopy is a well-suited, label-free method for following splenic T cell activation in systemic inflammation from acute to postacute phases. The method can also be applied to directly study tissue sections as is demonstrated for spleen tissue one day after LPS insult.T lymphocytes (T cells) are highly specialized members of the adaptive immune system and hold the key to the understanding the hosts’ response toward invading pathogen or pathogen-associated molecular patterns such as LPS. In this study, noninvasive Raman spectroscopy is presented as a label-free method to follow LPS-induced changes in splenic T cells during acute and postacute inflammatory phases (1, 4, 10, and 30 d) with a special focus on CD4+ and CD8+ T cells of endotoxemic C57BL/6 mice. Raman spectral analysis reveals highest chemical differences between CD4+ and CD8+ T cells originating from the control and LPS-treated mice during acute inflammation, and the differences are visible up to 10 d after the LPS insult. In the postacute phase, CD4+ and CD8+ T cells from treated and untreated mice could not be differentiated anymore, suggesting that T cells largely regained their original status. In sum, the biological information obtained from Raman spectra agrees with immunological readouts demonstrating that Raman spectroscopy is a well-suited, label-free method for following splenic T cell activation in systemic inflammation from acute to postacute phases. The method can also be applied to directly study tissue sections as is demonstrated for spleen tissue one day after LPS insult.
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    Particulate Matter Dispersion Modeling in Agricultural Applications: Investigation of a Transient Open Source Solver
    (Basel : MDPI, 2021) Janke, David; Swaminathan, Senthilathiban; Hempel, Sabrina; Kasper, Robert; Amon, Thomas
    Agriculture is a major emitter of particulate matter (PM), which causes health problems and can act as a carrier of the pathogen material that spreads diseases. The aim of this study was to investigate an open-source solver that simulates the transport and dispersion of PM for typical agricultural applications. We investigated a coupled Eulerian–Lagrangian solver within the open source software package OpenFOAM. The continuous phase was solved using transient large eddy simulations, where four different subgrid-scale turbulence models and an inflow turbulence generator were tested. The discrete phase was simulated using two different Lagrangian solvers. For the validation case of a turbulent flow of a street canyon, the flowfield could be recaptured very well, with errors of around 5% for the non-equilibrium turbulence models (WALE and dynamicKeq) in the main regions. The inflow turbulence generator could create a stable and accurate boundary layer for the mean vertical velocity and vertical profile of the turbulent Reynolds stresses R11. The validation of the Lagrangian solver showed mixed results, with partly good agreements (simulation results within the measurement uncertainty), and partly high deviations of up to 80% for the concentration of particles. The higher deviations were attributed to an insufficient turbulence regime of the used validation case, which was an experimental chamber. For the simulation case of PM dispersion from manure application on a field, the solver could capture the influence of features such as size and density on the dispersion. The investigated solver is especially useful for further investigations into time-dependent processes in the near-source area of PM sources.
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    Simulating Cotton Growth and Productivity Using AquaCrop Model under Deficit Irrigation in a Semi-Arid Climate
    (Basel : MDPI AG, 2022) Aziz, Marjan; Rizvi, Sultan Ahmad; Sultan, Muhammad; Bazmi, Muhammad Sultan Ali; Shamshiri, Redmond R.; Ibrahim, Sobhy M.; Imran, Muhammad A.
    AquaCrop is a water-driven model that simulates the effect of environment and management on crop production under deficit irrigation. The model was calibrated and validated using three databases and four irrigation treatments (i.e., 100%ET, 80%ET, 70%ET, and 50%ET). Model performance was evaluated by simulating canopy cover (CC), biomass accumulation, and water productivity (WP). Statistics of root mean square error (RMSE) and Willmott’s index of agreement (d) showed that model predictions are suitable for non-stressed and moderate stressed conditions. The results showed that the simulated biomass and yield were consistent with the measured values with a coefficient of determination (R2) of 0.976 and 0.950, respectively. RMSE and d-index values for canopy cover (CC) were 2.67% to 4.47% and 0.991% to 0.998% and for biomass were 0.088 to 0.666 ton/ha and 0.991 to 0.999 ton/ha, respectively. Prediction of simulated and measured biomass and final yield was acceptable with deviation ˂10%. The overall value of R2 for WP in terms of yield was 0.943. Treatment with 80% ET consumed 20% less water than the treatment with 100%ET and resulted in high WP in terms of yield (0.6 kg/m3) and biomass (1.74 kg/m3), respectively. The deviations were in the range of −2% to 11% in yield and −2% to 4% in biomass. It was concluded that AquaCrop is a useful tool in predicting the productivity of cotton under different irrigation scenarios.
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    An extended hybrid input-output model applied to fossil- and bio-based plastics
    (Amsterdam [u.a.] : Elsevier, 2021) Jander, Wiebke
    Matrix augmentation method is developed further and described transparently for enabling more specific input-output analyses of bio- vs. fossil-based sectors. A number of economic and environmental effects of substitution can be estimated, compared, and managed. While the model was applied for the first time to the German plastics industry, it can be well integrated into existing bioeconomy monitorings to represent substitution in sectors and countries. • Original matrix augmentation method is described in much detail for the first time considering available data for bio- and fossil-based industries. • Particular attention is paid to balancing cost and benefit in model building so that indicators can be integrated in a continuous monitoring of the bioeconomy. Hence, industry data is prefered to process data whenever possible. • Input structures of bio-based imports are considered in single-region input-output analysis.
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    Changes in the Spectrum of Free Fatty Acids in Blood Serum of Dairy Cows during a Prolonged Summer Heat Wave
    (Basel : MDPI, 2021) Mylostyvyi, Roman; Sejian, Veerasamy; Izhboldina, Olena; Kalinichenko, Olena; Karlova, Lina; Lesnovskay, Olena; Begma, Natalia; Marenkov, Oleh; Lykhach, Vadym; Midyk, Svitlana; Cherniy, Nikolay; Gutyj, Bogdan; Hoffmann, Gundula
    This experiment was conducted to study the effect of a prolonged hot period on the fatty acid (FA) composition in blood serum of dairy cows. Eighteen multiparous Holstein cows were randomly assigned to the hyperthermia group (HYP, n = 8) in August (summer season) and the control group (CON, n = 10) in October (autumn season). Blood from animals of the HYP group was collected in one heat wave, which was preceded by a long period of heat stress (HS, temperature-humidity index (THI ≥ 72)). Blood from cows of the CON group was collected under thermal comfort conditions (THI < 68). The spectrum of free fatty acids (FFA) in the blood serum was analyzed by gas chromatography. The concentration of FFA increased, including saturated FAs and monounsaturated FAs, in the blood serum of cows under conditions of prolonged HS. This was associated with the mobilization of FA into the bloodstream from adipose tissue, as a consequence of negative energy balance. An increase in the ratio of n-6/n-3 polyunsaturated FAs may indicate biomembrane dysfunction and adversely affect dairy cows. This study showed that prolonged periods of heat can affect the FA composition of blood. How much this leads to changes in the FA composition of milk and the quality of food products remains to be seen in further research.
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    The Effect of Diet and Farm Management on N2O Emissions from Dairy Farms Estimated from Farm Data
    (Basel : MDPI, 2021) Menardo, Simona; Lanza, Giacomo; Berg, Werner
    The N2O emissions of 21 dairy farms in Germany were evaluated to determine the feasi-bility of an estimation of emissions from farm data and the effects of the farm management, along with possible mitigation strategies. Emissions due to the application of different fertilisers, manure storage and grazing were calculated based on equations from the IPCC (Intergovernmental Panel of Climate Change) and German emission inventory. The dependence of the N2O emissions on fertiliser type and quantity, cultivated crops and diet composition was assessed via correlation analysis and linear regression. The N2O emissions ranged between 0.11 and 0.29 kg CO2eq per kilogram energy-corrected milk, with on average 60% resulting from fertilisation and less than 30% from fertiliser storage and field applications. The total emissions had a high dependence on the diet composition; in particular, on the grass/maize ratio and the protein content of the animal diet, as well as from the manure management. A linear model for the prediction of the N2O emissions based on the diet composition and the fertilisation reached a predictive power of R2 = 0.89. As a possible mitigation strategy, the substitution of slurry for solid manure would reduce N2O emissions by 40%. Feeding cows maize-based diets instead of grass-based diets could reduce them by 14%. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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    Revealing the Chemical Composition of Birch Pollen Grains by Raman Spectroscopic Imaging
    (Basel : Molecular Diversity Preservation International (MDPI), 2022) Stiebing, Clara; Post, Nele; Schindler, Claudia; Göhrig, Bianca; Lux, Harald; Popp, Jürgen; Heutelbeck, Astrid; Schie, Iwan W.
    The investigation of the biochemical composition of pollen grains is of the utmost interest for several environmental aspects, such as their allergenic potential and their changes in growth conditions due to climatic factors. In order to fully understand the composition of pollen grains, not only is an in-depth analysis of their molecular components necessary but also spatial information of, e.g., the thickness of the outer shell, should be recorded. However, there is a lack of studies using molecular imaging methods for a spatially resolved biochemical composition on a single-grain level. In this study, Raman spectroscopy was implemented as an analytical tool to investigate birch pollen by imaging single pollen grains and analyzing their spectral profiles. The imaging modality allowed us to reveal the layered structure of pollen grains based on the biochemical information of the recorded Raman spectra. Seven different birch pollen species collected at two different locations in Germany were investigated and compared. Using chemometric algorithms such as hierarchical cluster analysis and multiple-curve resolution, several components of the grain wall, such as sporopollenin, as well as the inner core presenting high starch concentrations, were identified and quantified. Differences in the concentrations of, e.g., sporopollenin, lipids and proteins in the pollen species at the two different collection sites were found, and are discussed in connection with germination and other growth processes.
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    Process disturbances in agricultural biogas production—causes, mechanisms and effects on the biogas microbiome: A review
    (Basel : MDPI AG, 2019) Theuerl, S.; Klang, J.; Prochnow, A.
    Disturbances of the anaerobic digestion process reduce the economic and environmental performance of biogas systems. A better understanding of the highly complex process is of crucial importance in order to avoid disturbances. This review defines process disturbances as significant changes in the functionality within the microbial community leading to unacceptable and severe decreases in biogas production and requiring an active counteraction to be overcome. The main types of process disturbances in agricultural biogas production are classified as unfavorable process temperatures, fluctuations in the availability of macro- and micronutrients (feedstock variability), overload of the microbial degradation potential, process-related accumulation of inhibiting metabolites such as hydrogen (H 2 ), ammonium/ammonia (NH 4 + /NH 3 ) or hydrogen sulphide (H 2 S) and inhibition by other organic and inorganic toxicants. Causes, mechanisms and effects on the biogas microbiome are discussed. The need for a knowledge-based microbiome management to ensure a stable and efficient production of biogas with low susceptibility to disturbances is derived and an outlook on potential future process monitoring and control by means of microbial indicators is provided.
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    Membrane technologies for lactic acid separation from fermentation broths derived from renewable resources
    (Basel : MDPI AG, 2018) Alexandri, M.; Schneider, R.; Venus, J.
    Lactic acid (LA) was produced on a pilot scale using a defined medium with glucose, acid whey, sugar bread and crust bread. The fermentation broths were then subjected to micro-and nanofiltration. Microfiltration efficiently separated the microbial cells. The highest average permeate flow flux was achieved for the defined medium (263.3 L/m2/h) and the lowest for the crust bread-based medium (103.8 L/m2/h). No LA losses were observed during microfiltration of the acid whey, whilst the highest retention of LA was 21.5% for crust bread. Nanofiltration led to high rejections of residual sugars, proteins and ions (sulphate, magnesium, calcium), with a low retention of LA. Unconverted sugar rejections were 100% and 63% for crust bread and sugar bread media respectively, with corresponding LA losses of 22.4% and 2.5%. The membrane retained more than 50% of the ions and proteins present in all media and more than 60% of phosphorus. The average flux was highly affected by the nature of the medium as well as by the final concentration of LA and sugars. The results of this study indicate that micro-and nanofiltration could be industrially employed as primary separation steps for the biotechnologically produced LA.