Aggregation Behavior,Antibacterial Activity and Biocompatibility of Catanionic Assemblies Based on Amino Acid-Derived Surfactants

The surface activity, aggregates morphology, size and charge characteristics of binary catanionic mixtures containing a cationic amino acid-derived surfactant N(π), N(τ)-bis(methyl)-L-Histidine tetradecyl amide (DMHNHC₁₄) and an anionic surfactant (the lysine-based surfactant N^α-lauroyl-N^εacetyl lysine (C₁₂C₃L) or sodium myristate) were investigated for the first time. The cationic surfactant has an acid proton which shows a strong pK_a shift irrespective of aggregation. The resulting catanionic mixtures exhibited high surface activity and low critical aggregation concentration as compared with the pure constituents. Catanionic vesicles based on DMHNHC₁₄/sodium myristate showed a monodisperse population of medium-size aggregates and good storage stability. According to Small-Angle X-Ray Scattering (SAXS), the characteristics of the bilayers did not depend strongly on the system composition for the positively charged vesicles. Negatively charged vesicles (cationic surfactant:myristate ratio below 1:2) had similar bilayer composition but tended to aggregate. The DMHNHC₁₄-rich vesicles exhibited good antibacterial activity against Gram-positive bacteria and their bactericidal effectivity declined with the decrease of the cationic surfactant content in the mixtures. The hemolytic activity and cytotoxicity of these catanionic formulations against non-tumoral (3T3, HaCaT) and tumoral (HeLa, A431) cell lines also improved by increasing the ratio of cationic surfactant in the mixture. These results indicate that the biological activity of these systems is mainly governed by the cationic charge density, which can be modulated by changing the cationic/anionic surfactant ratio in the mixtures. Remarkably, the incorporation of cholesterol in those catanionic vesicles reduces their cytotoxicity and increases the safety of future biomedical applications of these systems.     

The moderating role of just‐in‐time on sociotechnical practices' effect over quality and workers' health

Sociotechnical (ST) theory emphasizes the notion that the design and performance of new systems can be improved, and can only work satisfactorily within an organization if the social and the technical aspects are brought together and treated as interdependent aspects of a work system. The implementation of lean manufacturing (LM) principles and practices has become popular, despite increasing demand on the current and emerging workforce to achieve higher levels of quality and flexibility with lower costs. Exploratory studies that investigate how LM practices influence the effect of ST practices on performance are still scarce, and a holistic view of such a relationship is needed. In this context, this study aims at verifying the moderating effect of just‐in‐time (JIT) practices on the relationship between ST practices and the performance of quality and workers' health. We carried out a survey with 144 different companies from Southern Brazil that are undergoing a lean implementation. Results indicate that ST practices have a positive significant relationship with such performance, and the concurrent adoption of JIT does not undermine quality and workers' health.     

Influence of ionic liquid composition on the stability of polyvinyl chloride‐based ionic liquid inclusion membranes in aqueous solution

Membrane technology has gained significant importance with the incorporation of ionic liquids into their structure. This work shows the influence of ionic liquid composition on the stability of PVC‐based polymer ionic liquid inclusion membranes (PILIMs) in aqueous solution. Among the ILs investigated, those membranes which contain between 20 and 30%_w/w of the least soluble, [OMIM⁺][PF₆^?] and [OMIM⁺][Ntf₂^?], exhibit losses of IL lower than 10%. For both ILs, the amount immobilized was maximum for the membranes with 30%_w/w of IL (0.0838 and 0.0832 g, respectively). On the contrary, the ionic liquid loss increases as its solubility in water increase, reaching 99.52% when PILIMs are prepared with 70%_w/w of [OMIM⁺][BF₄^?]. The results demonstrate that the stability of PILIMs depends on the solubility of the IL in the surrounding phase and the specific interaction between the IL and the polymeric support for PVC‐to‐IL ratios higher than 30%_w/w. © 2016 American Institute of Chemical Engineers AIChE J, 63: 770–780, 2017     

Sequencing analysis of a 40·2 kb fragment of yeast chromosome X reveals 19 open reading frames including URA2 (5′ end), TRK1, PBS2, SPT10, GCD14, RPE1, PHO86, NCA3, ASF1, CCT7, GZF3, two tRNA genes,three remnant delta elements and a Ty4 transposon

The complete sequence of a 40 247 bp DNA segment located on the left arm of chromosome X of Saccharomyces cerevisiae has been determined and analysed. The sequence encodes the 5′ coding region of the URA2 gene and 18 open reading frames of at least 100 amino acids. Ten of these correspond to known genes, whereas eight correspond to new genes. In addition, the sequence contains a tRNA-Ala gene, a tRNA-Asp gene, a Ty4 transposable element and three delta elements. The sequence has been deposited in the EMBL databank under Accession Numbers: Z49405, Z49404, Z49403, Z49402, Z49401, Z49400, Z49399, Z49398, Z49397, Z49396, Z49394, Z49392, Z49391, Z49390, Z49389, Z49387, Z49386, Z49385.     

Quantification of the Immune Content in Neuroblastoma: Deep Learning and Topological Data Analysis in Digital Pathology

We introduce here a novel machine learning (ML) framework to address the issue of the quantitative assessment of the immune content in neuroblastoma (NB) specimens. First, the EUNet, a U-Net with an EfficientNet encoder, is trained to detect lymphocytes on tissue digital slides stained with the CD3 T-cell marker. The training set consists of 3782 images extracted from an original collection of 54 whole slide images (WSIs), manually annotated for a total of 73,751 lymphocytes. Resampling strategies, data augmentation, and transfer learning approaches are adopted to warrant reproducibility and to reduce the risk of overfitting and selection bias. Topological data analysis (TDA) is then used to define activation maps from different layers of the neural network at different stages of the training process, described by persistence diagrams (PD) and Betti curves. TDA is further integrated with the uniform manifold approximation and projection (UMAP) dimensionality reduction and the hierarchical density-based spatial clustering of applications with noise (HDBSCAN) algorithm for clustering, by the deep features, the relevant subgroups and structures, across different levels of the neural network. Finally, the recent TwoNN approach is leveraged to study the variation of the intrinsic dimensionality of the U-Net model. As the main task, the proposed pipeline is employed to evaluate the density of lymphocytes over the whole tissue area of the WSIs. The model achieves good results with mean absolute error 3.1 on test set, showing significant agreement between densities estimated by our EUNet model and by trained pathologists, thus indicating the potentialities of a promising new strategy in the quantification of the immune content in NB specimens. Moreover, the UMAP algorithm unveiled interesting patterns compatible with pathological characteristics, also highlighting novel insights into the dynamics of the intrinsic dataset dimensionality at different stages of the training process. All the experiments were run on the Microsoft Azure cloud platform.     

A bibliometric portrait of the evolution, scientific roots and influence of the literature on university–industry links

The study of university?Cindustry (U?CI) relations has been the focus of growing interest in the literature. However, to date, a quantitative overview of the existing literature in this field has yet to be accomplished. This study intends to fill this gap through the use of bibliometric techniques. By using three different yet interrelated databases??a database containing the articles published on U?CI links, which encompass 534 articles published between 1986 and 2011; a ??roots?? database, which encompasses over 20,000 references to the articles published on U?CI relations; and a ??influences?? database which includes more than 15,000 studies that cited the articles published on U?CI relations??we obtained the following results: (1) ??Academic spin offs??, ??Scientific and technological policies?? and (to a greater extent) ??Knowledge Transfer Channels?? are topics in decline; (2) ??Characteristics of universities, firms and scientists??, along with ??Regional spillovers??, show remarkable growth, and ??Measures and indicators?? can be considered an emergent topic; (3) clear tendency towards ??empirical?? works, although ??appreciative and empirical?? papers constitute the bulk of this literature; (4) the multidisciplinary nature of the intellectual roots of the U?CI literature??an interesting blending of neoclassical economics (focused on licensing, knowledge transfer and high-tech entrepreneurship) and heterodox approaches (mainly related to systems of innovation) is observed in terms of intellectual roots; (5) the influence of the U?CI literature is largely concentrated on the industrialized world and on the research area of innovation and technology (i.e., some ??scientific endogamy?? is observed).