Multi-Scale Variability Analysis of Wheat Straw-Based Ethanol Biorefineries Identifies Bioprocess Designs Robust Against Process Input Variations

Bioprocesses based on (ligno-)cellulosic biomass are highly prone to batch-to-batch variations. Varying raw material compositions and enzyme activities hamper the prediction of process yields, economic feasibility and environmental impacts. Commonly, these performance indicators are averaged over several experiments to select suitable process designs. The variabilities in performance indicators resulting from variable process inputs are often neglected, causing a risk for faulty performance predictions and poor process design choices during scale-up. In this paper, a multi-scale variability analysis framework is presented that quantifies the effects of process input variations on performance indicators. Using the framework, a kinetic model describing simultaneous saccharification and ethanol fermentation was integrated with a flowsheet process model, techno-economic analysis and life cycle assessment in order to evaluate a wheat straw-based ethanol biorefinery. Hydrolytic activities reported in the literature for the enzyme cocktail Cellic\uae CTec2, ranging from 62 to 266 FPU\ub7mL−1, were used as inputs to the multi-scale model to compare the variability in performance indicators under batch and multi-feed operation for simultaneous saccharification and fermentation. Bioprocess simulations were stopped at ethanol productivities ≤0.1 g\ub7L−1\ub7h−1. The resulting spreads in process times, hydrolysis yields, and fermentation yields were incorporated into flowsheet, techno-economic and life cycle scales. At median enzymatic activities the payback time was 7%, equal to 0.6 years, shorter under multi-feed conditions. All other performance indicators showed insignificant differences. However, batch operation is simpler to control and well-established in industry. Thus, an analysis at median conditions might favor batch conditions despite the disadvantage in payback time. Contrary to median conditions, analyzing the input variability favored multi-feed operation due to a lower variability in all performance indicators. Variabilities in performance indicators were at least 50% lower under multi-feed operation. Counteracting the variability in enzymatic activities by adjusting the amount of added enzyme instead resulted in higher uncertainties in environmental impacts. The results show that the robustness of performance indicators against input variations must be considered during process development. Based on the multi-scale variability analysis process designs can be selected which deliver more precise performance indicators at multiple system levels

Uncertainty analysis as a tool to consistently evaluate lignocellulosic bioethanol processes at different system scales

Lignocellulosic processes are highly prone to batch-to batch variability, e.g. of raw materials and enzyme activities. Thisvariability can be propagated throughout system scales during process development and optimization, influencing the outputs ofbioreaction models, techno-economic analyses and life cycle assessments. As these outputs are the main decision variablesfor designing and developing lignocellulose-based processes, tools are required to evaluate the influences of process variation atdifferent system scales.Uncertainty analysis quantifies the effects of model input variations on model outputs. It is an effective tool to consistentlypropagate process variation throughout scales and analyse its influence on model outputs. As an example, we use a modeldescribing multi-feed simultaneous saccharification and co-fermentation (SSCF) of wheat straw. During the process enzymeshydrolyse the lignocellulosic material to release glucose which can be converted by microorganisms into ethanol. To investigatethe impact of batch-to-batch variability in enzyme cocktails, we collected literature data on the enzymatic activity of CellicCTec2. Retrieved data were propagated in models at bioreactor, techno-economic analysis and life cycle assessment scale. Weshow how uncertainty analysis can be used to guide process development by comparing different modes of operation. Themethod can identify economically feasible process ranges with low environmental impact while increasing the robustness ofbioprocesses with high variation in raw material inputs. Furthermore, uncertainty analysis could help to identify relevantparameters to choose as response variables in experimental designs

Multi-scale uncertainty analysis – A tool to systematically consider variability in lignocellulosic bioethanol processes

Bioethanol production processes from lignocellulosic raw materials are highly prone to batch-to-batch variations. For example, raw material compositions and enzymatic activities required to release fermentable sugars from lignocellulose vary significantly between batches. To develop lignocellulosic biofuel processes and evaluate their performance regarding economics and sustainability consistently, tools are required to cope with this variability.\ua0In this presentation we will propose a multi-scale uncertainty analysis strategy to propagate input variability throughout system scales. In a first step, we use meta-data obtained from literature to define uncertainties in the process inputs. Utilizing these meta-data, uncertainty analysis is performed on a macro-kinetic model by sampling from the defined uncertain input space. The results of this uncertainty analysis are transferred to process simulations to analyze the impact of input uncertainties on the process mass- and energy balances, and on the economics of building this type of bioprocess. The generated data from process simulations (mass flows, energy integration, and economic data) are in the next step extracted and used as input to an environmental impact assessment of the process. This is done whilst keeping the simulation and systems modeling parameters constant, thus the input variability is propagated throughout the different system scales. The data generated in this integrated approach will then be compared with the variations and uncertainties observed with relevance to the estimated parameters in the process simulation and environmental impact assessment. Based on this consistent strategy, we can analyze the impact of input variability from different system perspectives, identify important bottlenecks for development, and suggest robust and sustainable process designs for different conditions and under given uncertainties. \ua0In a case study we demonstrate how integrated kinetic modeling (in Matlab), process simulation (in SuperPro Designer), and environmental impact assessment together with statistical analysis can be used for assessing how variability in enzymatic activities in bioethanol production can be propagated throughout system scales. A macro-kinetic model is used to describe the enzymatic breakdown of lignocellulose-derived polysaccharides into fermentable sugars (saccharification) and the simultaneous fermentation to bioethanol. We discuss the integration of the simulation results of the macro-kinetic model into the flowsheeting software for mass and energy balance generation, and then further on to assess environmental impacts of the process. We will evaluate different process designs regarding their robustness towards input variability. Finally, we also show how propagated uncertainties at different system scales can be integrated to design experiments at laboratory scale so that these focus on the most important parameters for developing robust kinetic models, and include the parameters that are most important for sustainable design of processes and value chains

Utility of ACMG classification to support interpretation of molecular genetic test results in patients with factor VII deficiency

BackgroundThe American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) have introduced an internationally shared framework for variant classification in genetic disorders. FVII deficiency is a rare inherited autosomal recessive bleeding disorder with sparse data concerning ACMG classification.MethodsTo develop an approach which may improve the utility of molecular genetic test results, 129 patients with FVII deficiency were retrospectively assigned to six subgroups for exploratory analysis: F7 gene wildtype (group 1), ACMG 1 (benign variant) or ACMG 2 (likely benign variant), only (group 2), ACMG 3 (variant of uncertain significance) ± ACMG 1–2 heterozygous or not classified variant (group 3), ACMG 4 (likely pathogenic variant), or ACMG 5 (pathogenic variant) single heterozygous ± ACMG 1–3 single heterozygous (group 4), ACMG 4–5 homozygous or ≥2 ACMG 4–5 heterozygous or ≥1 ACMG 4–5 heterozygous plus either ACMG 1 c.1238G>A modifying variant homozygous or ≥2 ACMG 1–3 (group 5), FVII deficiency and another bleeding disorder (group 6).ResultsEleven of 31 patients (35.5%) in group 5 had abnormal ISTH-BS (n = 7) and/or history of substitution with recombinant factor VIIa (n = 5) versus 4 of 80 patients (5.0%, n = 1 abnormal ISTH-BS, n = 3 substitution) in groups 1 (n = 2/22), 2 (n = 1/29), 3 (n = 0/9), and 4 (n = 1/20). Four of 18 patients (22.2%) with FVII deficiency and another bleeding disorder (group 6) had an abnormal ISTH-BS (n = 2) and/or history of substitution with recombinant factor VIIa (n = 3).ConclusionPatients with a homozygous ACMG 4–5 variant or with specific combinations of heterozygous ACMG 4–5 ± ACMG 1–3 variants exhibited a high-risk bleeding phenotype in contrast to the remaining patients without another bleeding disorder. This result may serve as a basis to develop a genotype/phenotype prediction model in future studies

Nonminimal Couplings in the Early Universe: Multifield Models of Inflation and the Latest Observations

Models of cosmic inflation suggest that our universe underwent an early phase of accelerated expansion, driven by the dynamics of one or more scalar fields. Inflationary models make specific, quantitative predictions for several observable quantities, including particular patterns of temperature anistropies in the cosmic microwave background radiation. Realistic models of high-energy physics include many scalar fields at high energies. Moreover, we may expect these fields to have nonminimal couplings to the spacetime curvature. Such couplings are quite generic, arising as renormalization counterterms when quantizing scalar fields in curved spacetime. In this chapter I review recent research on a general class of multifield inflationary models with nonminimal couplings. Models in this class exhibit a strong attractor behavior: across a wide range of couplings and initial conditions, the fields evolve along a single-field trajectory for most of inflation. Across large regions of phase space and parameter space, therefore, models in this general class yield robust predictions for observable quantities that fall squarely within the "sweet spot" of recent observations.Comment: 17pp, 2 figs. References added to match the published version. Published in {\it At the Frontier of Spacetime: Scalar-Tensor Theory, Bell's Inequality, Mach's Principle, Exotic Smoothness}, ed. T. Asselmeyer-Maluga (Springer, 2016), pp. 41-57, in honor of Carl Brans's 80th birthda

Medication-Related Hospital Readmissions Within 30 Days of Discharge:Prevalence, Preventability, Type of Medication Errors and Risk Factors

Contains fulltext : 233572.pdf (Publisher’s version ) (Open Access

Effects of mesenchymal stem cells and heparan sulfate mimetics on urethral function and vaginal wall biomechanics in a simulated rat childbirth injury model

Introduction and hypothesis: New treatments are needed for pelvic floor disorders. ReGeneraTing Agent® (RGTA®) is a promising regenerative therapy. Therefore, the objective of this study was to compare regenerative abilities of mesenchymal stem cells (MSCs) and RGTA® on regeneration after simulated childbirth injury in rats. Methods: Rats underwent pudendal nerve crush and vaginal distension (PNC+VD) or sham injury. Rats that underwent PNC+VD were treated intravenously with vehicle, MSCs or RGTA® 1 h, 7 days, and 14 days after surgery. Sham rats received 1 ml vehicle at all time points. After 21 days, urethral function and pudendal nerve function were tested. Vaginal tissues were harvested for biomechanical testing and histology. Biaxial testing was performed to measure tissue stiffness. Results: PNC+VD decreased urethral and pudendal nerve function compared with sham. Vaginal wall stiffness was significantly decreased in longitudinal and transverse tissue axes after PNC+VD compared with sham. MSC or RGTA® did not restore urethral or pudendal nerve function. However, MSC treatment resolved loss in vaginal wall stiffness in both tissue axes and improved collagen content within the vaginal wall. RGTA® treatment increased vaginal wall anisotropy by increasing relative stiffness in the longitudinal direction. PNC+VD (with vehicle or MSCs) enhanced elastogenesis, which was not observed after RGTA® treatment. Conclusions: Treatment with MSCs facilitated recovery of vaginal wall biomechanical properties and connective tissue composition after PNC+VD, whereas treatment with RGTA® resulted in anisotropic biomechanical changes. This indicates that MSCs and RGTA® promote different aspects of vaginal tissue regeneration after simulated childbirth injury

Sialylation of campylobacter jejuni lipo-oligosaccharides: impact on phagocytosis and cytokine production in mice

<p>Background: Guillain-Barré syndrome (GBS) is a post-infectious polyradiculoneuropathy, frequently associated with antecedent Campylobacter jejuni (C. jejuni) infection. The presence of sialic acid on C. jejuni lipo-oligosaccharide (LOS) is considered a risk factor for development of GBS as it crucially determines the structural homology between LOS and gangliosides, explaining the induction of cross-reactive neurotoxic antibodies. Sialylated C. jejuni are recognised by TLR4 and sialoadhesin; however, the functional implications of these interactions in vivo are unknown.</p> <p>Methodology/Principal Findings: In this study we investigated the effects of bacterial sialylation on phagocytosis and cytokine secretion by mouse myeloid cells in vitro and in vivo. Using fluorescently labelled GM1a/GD1a ganglioside-mimicking C. jejuni strains and corresponding (Cst-II-mutant) control strains lacking sialic acid, we show that sialylated C. jejuni was more efficiently phagocytosed in vitro by BM-MΦ, but not by BM-DC. In addition, LOS sialylation increased the production of IL-10, IL-6 and IFN-β by both BM-MΦ and BM-DC. Subsequent in vivo experiments revealed that sialylation augmented the deposition of fluorescent bacteria in splenic DC, but not macrophages. In addition, sialylation significantly amplified the production of type I interferons, which was independent of pDC.</p> <p>Conclusions/Significance: These results identify novel immune stimulatory effects of C. jejuni sialylation, which may be important in inducing cross-reactive humoral responses that cause GBS</p&gt

The Efficacy of a Newly Developed Cueing Device for Gait Mobility in Parkinson’s Disease

Background. External cues are effective in improving gait in people with Parkinson’s disease (PD). However, the most effective cueing method has yet to be determined. Objective. The aim of this study was to compare the immediate effects of using visual, auditory, or somatosensory cues on their own or in combination during walking compared to no cues in people with PD. Methods. This was a single blinded, randomly selected, controlled study. Twenty people with PD with an age range of 46–79 years and Hoehn and Yahr scores of 1–3 were recruited. Participants were studied under 4 cueing conditions; no cue, visual, auditory, or somatosensory cues, which were randomly selected individually or in a combination. Results. A repeated measures ANOVA with pairwise comparisons using Bonferroni correction showed that any single or combination of the cues resulted in an improvement in gait velocity and stride length compared to no cue. Some significant differences were also seen when comparing different combinations of cues, specifically stride length showed significant improvements when additional cues were added to the light cue. The statistically significant difference was set at p<0.05. Conclusions. Walking using visual, auditory, or somatosensory cues can immediately improve gait mobility in people with PD. Any or a combination of the cues tested could be chosen depending on the ability of the individual to use that cue