Origin of the Significant Impact of Ta on the Creep Resistance of FeCrNi Alloys

Heat resistant FeCrNi alloys are widely used in the petrochemical industry because they exhibit a unique combination of creep and oxidation resistance at temperatures exceeding 900$^\circ$C. Their creep properties are often optimized by micro-additions of carbide forming elements. In the present work, the influence of Ta micro-additions has been experimentally investigated both on as-cast and aged microstructures to understand the origin of the significant impact of this element on the creep resistance. Calculations with thermocal software were also carried out to support experimental data. It is shown that a small addition of Ta is beneficial as it increases the volume fraction of stable MC carbides. We demonstrate also that additions of Ta may have a dramatic effect on the thermal stability of microstructures. This is attributed to a smaller equilibrium volume fraction of M23C6 and more pronounced heterogeneous precipitation at MC/matrix interfaces. The influence on the creep properties in then discussed

Graphene oxide topical administration: Skin permeability studies

Nanostructured carriers have been widely used in pharmaceutical formulations for der-matological treatment. They offer targeted drug delivery, sustained release, improved biostability, and low toxicity, usually presenting advantages over conventional formulations. Due to its large surface area, small size and photothermal properties, graphene oxide (GO) has the potential to be used for such applications. Nanographene oxide (GOn) presented average sizes of 197.6 ± 11.8 nm, and a surface charge of -39.4 ± 1.8 mV, being stable in water for over 6 months. 55.5% of the mass of GOn dispersion (at a concentration of 1000 µg mL-1 ) permeated the skin after 6 h of exposure. GOn dispersions have been shown to absorb near-infrared radiation, reaching temperatures up to 45.7¿ C, within mild the photothermal therapy temperature range. Furthermore, GOn in amounts superior to those which could permeate the skin were shown not to affect human skin fibroblasts (HFF-1) morphology or viability, after 24 h of incubation. Due to its large size, no skin permeation was observed for graphite particles in aqueous dispersions stabilized with Pluronic P-123 (Gt–P-123). Altogether, for the first time, Gon’s potential as a topic administration agent and for delivery of photothermal therapy has been demonstrated.This work was financed by FEDER funds through the COMPETE 2020–Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and by national funds (PIDDAC) through FCT/MCTES in the framework of the project POCI-01-0145-FEDER-031143, and Base Funding-UIDB/00511/2020 of the Laboratory for Process Engineering, Environment, Biotechnology and Energy–LEPABE. Additional funding included FCT/MCTES in the framework of the project “Institute for Research and Innovation in Health Sciences” (UID/BIM/04293/2019). Authors would also like to thank the support of i3S Scientific Platforms and respective funding: HEMS, member of the national infrastructure PPBI–Portuguese Platform of Bioimaging: POCI-01-0145-FEDER-022122; and Biointerfaces and Nanotechnology (BN) Laboratory, Portuguese Funds through FCT, UID/BIM/04293/2019. Artur Pinto thanks the Portuguese Foundation for Science and Technology (FCT) for the financial support of his work contract through the Scientific Employment Stimulus-Individual Call–[CEECIND/03908/2017]. Soraia Pinto (SFRH/BD/144719/2019) would like to thank FCT, Portugal for financial support

Can Score Databanks Help Teaching?

Basic courses in most medical schools assess students' performance by conferring scores. The objective of this work is to use a large score databank for the early identification of students with low performance and to identify course trends based on the mean of students' grades. METHODOLOGY/PRINCIPAL FINDINGS: We studied scores from 2,398 medical students registered in courses over a period of 10 years. Students in the first semester were grouped into those whose ratings remained in the lower quartile in two or more courses (low-performance) and students who had up to one course in the lower quartile (high-performance). ROC curves were built, aimed at the identification of a cut-off average score in the first semesters that would be able to predict low performances in future semesters. Moreover, to follow the long-term pattern of each course, the mean of all scores conferred in a semester was compared to the overall course mean obtained by averaging 10 years of data. Individuals in the low-performance group had a higher risk of being in the lower quartile of at least one course in the second semester (relative risk 3.907; 95% CI: 3.378-4.519) and in the eighth semester (relative risk 2.873; 95% CI: 2.495-3.308). The prediction analysis revealed that an average score of 7.188 in the first semester could identify students that presented scores below the lower quartiles in both the second and eighth semesters (p<0.0001 for both AUC). When scores conferred by single courses were compared over time, three time-trend patterns emerged: low variation, upward trend and erratic pattern. CONCLUSION/SIGNIFICANCE: An early identification of students with low performance may be useful in promoting pedagogical strategies for these individuals. Evaluation of the time trend of scores conferred by courses may help departments monitoring changes in personnel and methodology that may affect a student's performance

Sialic Acid Glycobiology Unveils Trypanosoma cruzi Trypomastigote Membrane Physiology.

Trypanosoma cruzi, the flagellate protozoan agent of Chagas disease or American trypanosomiasis, is unable to synthesize sialic acids de novo. Mucins and trans-sialidase (TS) are substrate and enzyme, respectively, of the glycobiological system that scavenges sialic acid from the host in a crucial interplay for T. cruzi life cycle. The acquisition of the sialyl residue allows the parasite to avoid lysis by serum factors and to interact with the host cell. A major drawback to studying the sialylation kinetics and turnover of the trypomastigote glycoconjugates is the difficulty to identify and follow the recently acquired sialyl residues. To tackle this issue, we followed an unnatural sugar approach as bioorthogonal chemical reporters, where the use of azidosialyl residues allowed identifying the acquired sugar. Advanced microscopy techniques, together with biochemical methods, were used to study the trypomastigote membrane from its glycobiological perspective. Main sialyl acceptors were identified as mucins by biochemical procedures and protein markers. Together with determining their shedding and turnover rates, we also report that several membrane proteins, including TS and its substrates, both glycosylphosphatidylinositol-anchored proteins, are separately distributed on parasite surface and contained in different and highly stable membrane microdomains. Notably, labeling for α(1,3)Galactosyl residues only partially colocalize with sialylated mucins, indicating that two species of glycosylated mucins do exist, which are segregated at the parasite surface. Moreover, sialylated mucins were included in lipid-raft-domains, whereas TS molecules are not. The location of the surface-anchored TS resulted too far off as to be capable to sialylate mucins, a role played by the shed TS instead. Phosphatidylinositol-phospholipase-C activity is actually not present in trypomastigotes. Therefore, shedding of TS occurs via microvesicles instead of as a fully soluble form

Automated smoother for the numerical decoupling of dynamics models

<p>Abstract</p> <p>Background</p> <p>Structure identification of dynamic models for complex biological systems is the cornerstone of their reverse engineering. Biochemical Systems Theory (BST) offers a particularly convenient solution because its parameters are kinetic-order coefficients which directly identify the topology of the underlying network of processes. We have previously proposed a numerical decoupling procedure that allows the identification of multivariate dynamic models of complex biological processes. While described here within the context of BST, this procedure has a general applicability to signal extraction. Our original implementation relied on artificial neural networks (ANN), which caused slight, undesirable bias during the smoothing of the time courses. As an alternative, we propose here an adaptation of the Whittaker's smoother and demonstrate its role within a robust, fully automated structure identification procedure.</p> <p>Results</p> <p>In this report we propose a robust, fully automated solution for signal extraction from time series, which is the prerequisite for the efficient reverse engineering of biological systems models. The Whittaker's smoother is reformulated within the context of information theory and extended by the development of adaptive signal segmentation to account for heterogeneous noise structures. The resulting procedure can be used on arbitrary time series with a nonstationary noise process; it is illustrated here with metabolic profiles obtained from <it>in-vivo </it>NMR experiments. The smoothed solution that is free of parametric bias permits differentiation, which is crucial for the numerical decoupling of systems of differential equations.</p> <p>Conclusion</p> <p>The method is applicable in signal extraction from time series with nonstationary noise structure and can be applied in the numerical decoupling of system of differential equations into algebraic equations, and thus constitutes a rather general tool for the reverse engineering of mechanistic model descriptions from multivariate experimental time series.</p