Phase II Evaluation of Floor Pan Tearing for Cable Barrier Systems

The objective of this research effort was to mitigate the potential for floor pan tearing and penetration into the occupant compartment by modifying the posts utilized in a prototype cable barrier system. A series of dynamic component tests were conducted on the modified Midwest Weak Post (MWP). A bogie vehicle was equipped with a simulated floor pan designed to replicate the height, thickness, and strength of the floor pan of a Kia Rio. Two methods of post modification were investigated, including edge protection on the top of the MWP as well as weakening of the MWP at the ground line. Two methods of edge protection were tested, including a 31⁄2-in. x 21⁄2-in. x 3/16-in. (89-mm x 64-mm x 5-mm) thick steel tube cap and 21⁄8-in. x 13⁄8-in. x 7-gauge (54-mm x 35-mm x 5-mm) bent steel plates. Weakening of the MWPs was accomplished through two 3⁄4-in. (19-mm) diameter holes drilled through the weak-axis of the posts at the ground line. Both methods of edge protection showed potential for mitigating the propensity for floor pan tearing. In all but one test, the posts caused creasing on the simulated floor pan. In one test, test no. MWPFP-23, the edge protector connection bolt sheared and allowed the posts’ free edges to contact and tear the simulated floor pan, which would not be expected in full-scale crash testing with the 1100C vehicle. The bogie testing of MWPs with 3⁄4-in. (19-mm) diameter weakening holes with steel plate edge protectors mounted at the top of the posts resulted in only minor creasing on the simulated floor pan. Thus, a combination of weakening holes and edge protectors using steel bent plates at top of the MWP was recommended for further evaluation through full-scale vehicle crash testing

AR2, a novel automatic muscle artifact reduction software method for ictal EEG interpretation: Validation and comparison of performance with commercially available software.

Objective: To develop a novel software method (AR2) for reducing muscle contamination of ictal scalp electroencephalogram (EEG), and validate this method on the basis of its performance in comparison to a commercially available software method (AR1) to accurately depict seizure-onset location. Methods: A blinded investigation used 23 EEG recordings of seizures from 8 patients. Each recording was uninterpretable with digital filtering because of muscle artifact and processed using AR1 and AR2 and reviewed by 26 EEG specialists. EEG readers assessed seizure-onset time, lateralization, and region, and specified confidence for each determination. The two methods were validated on the basis of the number of readers able to render assignments, confidence, the intra-class correlation (ICC), and agreement with other clinical findings. Results: Among the 23 seizures, two-thirds of the readers were able to delineate seizure-onset time in 10 of 23 using AR1, and 15 of 23 using AR2 (

Identification of metabolic engineering targets through analysis of optimal and sub-optimal routes

Identification of optimal genetic manipulation strategies for redirecting substrate uptake towards a desired product is a challenging task owing to the complexity of metabolic networks, esp. in terms of large number of routes leading to the desired product. Algorithms that can exploit the whole range of optimal and suboptimal routes for product formation while respecting the biological objective of the cell are therefore much needed. Towards addressing this need, we here introduce the notion of structural flux, which is derived from the enumeration of all pathways in the metabolic network in question and accounts for the contribution towards a given biological objective function. We show that the theoretically estimated structural fluxes are good predictors of experimentally measured intra-cellular fluxes in two model organisms, namely, Escherichia coli and Saccharomyces cerevisiae. For a small number of fluxes for which the predictions were poor, the corresponding enzyme-coding transcripts were also found to be distinctly regulated, showing the ability of structural fluxes in capturing the underlying regulatory principles. Exploiting the observed correspondence between in vivo fluxes and structural fluxes, we propose an in silico metabolic engineering approach, iStruF, which enables the identification of gene deletion strategies that couple the cellular biological objective with the product flux while considering optimal as well as sub-optimal routes and their efficiency.This work was supported by the Portuguese Science Foundation [grant numbers MIT-Pt/BS-BB/0082/2008, SFRH/BPD/44180/2008 to ZS] (http://www.fct.pt/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Impact of stoichiometry representation on simulation of genotype-phenotype relationships in metabolic networks.

<div><p>Genome-scale metabolic networks provide a comprehensive structural framework for modeling genotype-phenotype relationships through flux simulations. The solution space for the metabolic flux state of the cell is typically very large and optimization-based approaches are often necessary for predicting the active metabolic state under specific environmental conditions. The objective function to be used in such optimization algorithms is directly linked with the biological hypothesis underlying the model and therefore it is one of the most relevant parameters for successful modeling. Although linear combination of selected fluxes is widely used for formulating metabolic objective functions, we show that the resulting optimization problem is sensitive towards stoichiometry representation of the metabolic network. This undesirable sensitivity leads to different simulation results when using numerically different but biochemically equivalent stoichiometry representations and thereby makes biological interpretation intrinsically subjective and ambiguous. We hereby propose a new method, Minimization of Metabolites Balance (MiMBl), which decouples the artifacts of stoichiometry representation from the formulation of the desired objective functions, by casting objective functions using metabolite turnovers rather than fluxes. By simulating perturbed metabolic networks, we demonstrate that the use of stoichiometry representation independent algorithms is fundamental for unambiguously linking modeling results with biological interpretation. For example, MiMBl allowed us to expand the scope of metabolic modeling in elucidating the mechanistic basis of several genetic interactions in <em>Saccharomyces cerevisiae</em>.</p> </div

Large-Scale Bi-Level Strain Design Approaches and Mixed-Integer Programming Solution Techniques

The use of computational models in metabolic engineering has been increasing as more genome-scale metabolic models and computational approaches become available. Various computational approaches have been developed to predict how genetic perturbations affect metabolic behavior at a systems level, and have been successfully used to engineer microbial strains with improved primary or secondary metabolite production. However, identification of metabolic engineering strategies involving a large number of perturbations is currently limited by computational resources due to the size of genome-scale models and the combinatorial nature of the problem. In this study, we present (i) two new bi-level strain design approaches using mixed-integer programming (MIP), and (ii) general solution techniques that improve the performance of MIP-based bi-level approaches. The first approach (SimOptStrain) simultaneously considers gene deletion and non-native reaction addition, while the second approach (BiMOMA) uses minimization of metabolic adjustment to predict knockout behavior in a MIP-based bi-level problem for the first time. Our general MIP solution techniques significantly reduced the CPU times needed to find optimal strategies when applied to an existing strain design approach (OptORF) (e.g., from ∼10 days to ∼5 minutes for metabolic engineering strategies with 4 gene deletions), and identified strategies for producing compounds where previous studies could not (e.g., malate and serine). Additionally, we found novel strategies using SimOptStrain with higher predicted production levels (for succinate and glycerol) than could have been found using an existing approach that considers network additions and deletions in sequential steps rather than simultaneously. Finally, using BiMOMA we found novel strategies involving large numbers of modifications (for pyruvate and glutamate), which sequential search and genetic algorithms were unable to find. The approaches and solution techniques developed here will facilitate the strain design process and extend the scope of its application to metabolic engineering

<em>Aspergillus nidulans</em> Synthesize Insect Juvenile Hormones upon Expression of a Heterologous Regulatory Protein and in Response to Grazing by <em>Drosophila melanogaster</em> Larvae.

Secondary metabolites are known to serve a wide range of specialized functions including communication, developmental control and defense. Genome sequencing of several fungal model species revealed that the majority of predicted secondary metabolite related genes are silent in laboratory strains, indicating that fungal secondary metabolites remain an underexplored resource of bioactive molecules. In this study, we combine heterologous expression of regulatory proteins in Aspergillus nidulans with systematic variation of growth conditions and observe induced synthesis of insect juvenile hormone-III and methyl farnesoate. Both compounds are sesquiterpenes belonging to the juvenile hormone class. Juvenile hormones regulate developmental and metabolic processes in insects and crustaceans, but have not previously been reported as fungal metabolites. We found that feeding by Drosophila melanogaster larvae induced synthesis of juvenile hormone in A. nidulans indicating a possible role of juvenile hormone biosynthesis in affecting fungal-insect antagonisms

Responses of Tectal Neurons to Contrasting Stimuli: An Electrophysiological Study in the Barn Owl

The saliency of visual objects is based on the center to background contrast. Particularly objects differing in one feature from the background may be perceived as more salient. It is not clear to what extent this so called “pop-out” effect observed in humans and primates governs saliency perception in non-primates as well. In this study we searched for neural-correlates of pop-out perception in neurons located in the optic tectum of the barn owl. We measured the responses of tectal neurons to stimuli appearing within the visual receptive field, embedded in a large array of additional stimuli (the background). Responses were compared between contrasting and uniform conditions. In a contrasting condition the center was different from the background while in the uniform condition it was identical to the background. Most tectal neurons responded better to stimuli in the contrsating condition compared to the uniform condition when the contrast between center and background was the direction of motion but not when it was the orientation of a bar. Tectal neurons also preferred contrasting over uniform stimuli when the center was looming and the background receding but not when the center was receding and the background looming. Therefore, our results do not support the hypothesis that tectal neurons are sensitive to pop-out per-se. The specific sensitivity to the motion contrasting stimulus is consistent with the idea that object motion and not large field motion (e.g., self-induced motion) is coded in the neural responses of tectal neurons

The clinical significance of small copy number variants in neurodevelopmental disorders

BACKGROUND Despite abundant evidence for pathogenicity of large copy number variants (CNVs) in neurodevelopmental disorders (NDDs), the individual significance of genome-wide rare CNVs <500 kb has not been well elucidated in a clinical context. METHODS By high-resolution chromosomal microarray analysis, we investigated the clinical significance of all rare non-polymorphic exonic CNVs sizing 1-500 kb in a cohort of 714 patients with undiagnosed NDDs. RESULTS We detected 96 rare CNVs <500 kb affecting coding regions, of which 58 (60.4%) were confirmed. 6 of 14 confirmed de novo, one of two homozygous and four heterozygous inherited CNVs affected the known microdeletion regions 17q21.31, 16p11.2 and 2p21 or OMIM morbid genes (CASK, CREBBP, PAFAH1B1, SATB2; AUTS2, NRXN3, GRM8). Two further de novo CNVs affecting single genes (MED13L, CTNND2) were instrumental in delineating novel recurrent conditions. For the first time, we here report exonic deletions of CTNND2 causing low normal IQ with learning difficulties with or without autism spectrum disorder. Additionally, we discovered a homozygous out-of-frame deletion of ACOT7 associated with features comparable to the published mouse model. In total, 24.1% of the confirmed small CNVs were categorised as pathogenic or likely pathogenic (median size 130 kb), 17.2% as likely benign, 3.4% represented incidental findings and 55.2% remained unclear. CONCLUSIONS These results verify the diagnostic relevance of genome-wide rare CNVs <500 kb, which were found pathogenic in ∼2% (14/714) of cases (1.1% de novo, 0.3% homozygous, 0.6% inherited) and highlight their inherent potential for discovery of new conditions

Production of mannosylglycerate in Saccharomyces cerevisiae by metabolic engineering and bioprocess optimization

Mannosylglycerate (MG) is one of the most widespread compatible solutes among marine microorganisms adapted to hot environments. This ionic solute holds excellent ability to protect proteins against thermal denaturation, hence a large number of biotechnological and clinical applications have been put forward. However, the current prohibitive production costs impose severe constraints towards large-scale applications. All known microbial producers synthesize MG from GDP-mannose and 3-phosphoglycerate via a two-step pathway in which mannosyl-3-phosphoglycerate is the intermediate metabolite. In an early work, this pathway was expressed in Saccharomyces cerevisiae with the goal to confirm gene function (Empadinhas et al. in J Bacteriol 186:4075--4084, 2004), but the level of MG accumulation was low. Therefore, in view of the potential biotechnological value of this compound, we decided to invest further effort to convert S. cerevisiae into an efficient cell factory for MG production.This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684), BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte and also by project LISBOA-01-0145-FEDER-007660 (Microbiologia Molecular, Estrutural e Celular) funded by FEDER through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI). Cristiana Faria was supported by a Ph.D. Grant from FCT (Ref. SFRH/ BD/79552/2011).info:eu-repo/semantics/publishedVersio