Adaptive Finite Element Analysis of the Anisotropic Biphasic Theory of Tissue-Equivalent Mechanics

Abstract

The nonlinear partial differential equations of the anisotropic biphasic theory of tissue-equivalent mechanics are solved with axial symmetry by an adaptive finite element system. The adaptive procedure operates within a method-of-lines framework using finite elements in space and backward difference software in time. Spatial meshes are automatically refined, coarsened, and relocated in response to error indications and material deformation. Problems with arbitrarily complex two-dimensional regions may be addressed. With meshes graded in high-error regions, the adaptive solutions have fewer degrees of freedom than solutions with comparable accuracy obtained on fixed quasi-uniform meshes. The adaptive software is used to address problems involving an isometric cell traction assay, where a cylindrical tissue equivalent is adhered at its end to fixed circular platens; a prototypical bioartificial artery; and a novel configuration that is intended as an initial step in a study to determine bioartificial arteries having optimal collagen and cell concentrations.     

Embodied Resource Flows in a Global Economy

This article presents a methodology for identifying critical links in global resource supply chains by tracking resources from their extraction in one region of the world economy through their embodiment in intermediate products in the same and other regions to eventual embodiment in final goods. We build on previous work that applied an absorbing Markov chain (AMC) to results obtained using an input‐output (IO) model of a single region to define a resource‐specific network within that economy. In the absence of model calculations, the AMC can also be applied to standard IO data for a past year. This article first generalizes the analytic framework from a single region to the important case of the global resource‐specific network. This network typically includes cycling of embodied resources between sectors not only within each economy, but also among regions, as subsequent rounds of intermediate products are traded. Next, we refine that analysis to exhibit a crucial subnetwork, the resource end‐use network, which only tracks the portion of the resource that ends up embodied in a specific final product in a given region. Finally, we develop techniques to distinguish key branches of these networks and provide detailed insights about the structure of global resource dependence. A numerical example is applied to results of scenario analysis using an IO model of the world economy. Two alternative scenarios are compared. In each scenario, embodied resources are carried over specific branches of a global network in three regions using three resources to produce four goods.     

Acidophytic shrublands in the north-west of the Italian peninsula: Ecology,chorology and syntaxonomy

Abstract

The shrublands growing on siliceous and/or calcium-poor substrata of the hilly and mountainous areas of north-western and central Italy were studied. This secondary vegetation is dominated by several acidophilous shrubs like Ulex europaeus, Cytisus scoparius, Erica arborea, E. scoparia and Calluna vulgaris. The synecology, synchorology and syntaxonomy of this vegetation was studied using multivariate methods, and discussed in comparison with similar types described in other zones of the Italian peninsula. Two new subassociations are proposed here: Erico arboreae-Arbutetum unedonis genistetosum germanicae and Calluno-Sarothamnetum ericetosum scopariae. Calluno-Sarothamnetum is typified; the Sarothamnion alliance is discussed and referred to Cytisetea scopario-striati. The presence of Calluno-Ulicetea and Cytisetea scopario-striati classes is discussed, and a syntaxonomical scheme is proposed.     

Purification and Characterization op a 31-Kilodalton Iron-Regulated Periplasmic Protein from Pasteurella Haenolytica A1

ABSTRACT

A prominent iron-regulated periplasmic protein was purified from Pasteurella haemolytica grown in an iron-deficient chemically defined medium. The protein was purified by anion exchange chromatography and appeared as a single band by SDS-PAGE with a molecular weight of 32,000. A yield of five mg was obtained from 91 mg of protein extract. The iron-regulated protein existed as a monomer in the native state with an average molecular weight of 29,877 as determined by analytical ultracentrifugation. The protein had a molecular weight of 30,880 as determined by matrix-assisted laser desorption mass spectrometry, hence the protein is referred to as the 31 kDa protein. Isoelectric focusing showed four bands with pIs of 7.15, 6.8, 6.6, and 5.9, The secondary structure of the protein was determined by circular dichroism and contained 16% α-helical structure. The N-terminal sequence, EPFKVVTTFTVIQDIAQNVAGDKAT, showed a 95% identity with the 31 kDa iron-binding protein from Haemophilus influenzae. Isolation and characterization of iron-regulated proteins are of particular interest because of their potential roles in iron assimilation and microbial virulence.     

Deep and quantitative top-down proteomics in clinical and translational research

It has long been understood that it is proteins, expressed and post-translationally modified, that are the primary regulators of both the fate and the function of cells. The ability to measure differences in the expression of the constellation of unique protein forms (proteoforms) with complete molecular specificity has the potential to sharply improve the return on investment for mass spectrometry-based proteomics in translational research and clinical diagnostics.     

Discriminating the effects of phylogenetic hypothesis,tree resolution and clade age estimates on phylogenetic signal measurements

Understanding how species traits evolved over time is the central question to comprehend assembly rules that govern the phylogenetic structure of communities. The measurement of phylogenetic signal (PS) in ecologically relevant traits is a first step to understand phylogenetically structured community patterns. The different methods available to estimate PS make it difficult to choose which is most appropriate. Furthermore, alternative phylogenetic tree hypotheses, node resolution and clade age estimates might influence PS measurements. In this study, we evaluated to what extent these parameters affect different methods of PS analysis, and discuss advantages and disadvantages when selecting which method to use. We measured fruit/seed traits and flowering/fruiting phenology of endozoochoric species occurring in Southern Brazilian Araucaria forests and evaluated their PS using Mantel regressions, phylogenetic eigenvector regressions (PVR) and K statistic. Mantel regressions always gave less significant results compared to PVR and K statistic in all combinations of phylogenetic trees constructed. Moreover, a better phylogenetic resolution affected PS, independently of the method used to estimate it. Morphological seed traits tended to show higher PS than diaspores traits, while PS in flowering/fruiting phenology depended mostly on the method used to estimate it. This study demonstrates that different PS estimates are obtained depending on the chosen method and the phylogenetic tree resolution. This finding has implications for inferences on phylogenetic niche conservatism or ecological processes determining phylogenetic community structure.     

Specific and high-resolution identification of monoclonal antibody fragments detected by capillary electrophoresis–sodium dodecyl sulfate using reversed-phase HPLC with top-down mass spectrometry analysis

ABSTRACT

In recent years, capillary electrophoresis–sodium dodecyl sulfate (cSDS) has been widely used for high resolution separation and quantification of the fragments and aggregates of monoclonal antibodies (mAbs) to ensure the quality of mAb therapeutics. However, identification of the low-molecular-weight (LMW) and high-molecular-weight (HMW) species detected in cSDS electropherograms has been based primarily on the approximate MWs calculated from standard curves using known MW standards and correlations with fragments and aggregates identified by other methods. It is not easy to collect sufficient amounts of H/LMW species from cSDS for analysis by orthogonal methods and the direct coupling of cSDS with mass spectrometry (MS) is very difficult due to interference from SDS. In this study, we describe the precise identification of H/LMW species detected by cSDS using reversed-phase high performance liquid chromatography (RP-HPLC) coupled with top-down tandem MS analysis. The H/LMW species were first identified by on-line RP-HPLC MS analysis and the RP-HPLC fractions were then analyzed by cSDS to connect the identified H/LMW species with the peaks in the cSDS electropherogram. With this method, 58 unique H/LMW species were identified from an immunoglobulin G1 (IgG1) mAb. The identified fragments ranged from 10 kDa single chain fragments to 130 kDa triple chain fragments, including some with post-translational modifications. This is the first study to clearly identify the antibody fragments, including the exact clipping sites, observed in cSDS electropherograms. The methodology and results presented here should be applicable to most other IgG1 mAbs.     

De novo discovery of antibody drugs – great promise demands scrutiny

ABSTRACT

We live in an era of rapidly advancing computing capacity and algorithmic sophistication. “Big data” and “artificial intelligence”find progressively wider use in all spheres of human activity, including healthcare. A diverse array of computational technologies is being applied with increasing frequency to antibody drug research and development (R&D). Their successful applications are met with great interest due to the potential for accelerating and streamlining the antibody R&D process. While this excitement is very likely justified in the long term, it is less likely that the transition from the first use to routine practice will escape challenges that other new technologies had experienced before they began to blossom. This transition typically requires many cycles of iterative learning that rely on the deconstruction of the technology to understand its pitfalls and define vectors for optimization. The study by Vasquez et al. identifies a key obstacle to such learning: the lack of transparency regarding methodology in computational antibody design reports, which has the potential to mislead the community efforts