Dendritic Nanotheranostic for the Delivery of Infliximab: A Potential Carrier in Rheumatoid Arthritis Therapy

Antibodies are macromolecules that specifically recognize their target, making them good candidates to be employed in various therapies. The possibility of attaching a drug to an immunoglobulin makes it possible to release it specifically into the affected tissue as long as it overexpresses the target. However, chemical coupling could affect the functionality (specificity and affinity) of the antibody. It has been observed that the use of intermediaries, such as dendrimers, could resolve this issue. Because carbosilane dendrimers have aroused great interest in the field of biomedicine, this report describes the synthesis of an anionic carbosilane dendrimer with a fluorochrome on its surface that then forms a conjugate with an antibody. It has been used as immunoglobulin and infliximab, whose target is TNF-α, which is a cytokine that is overexpressed in the inflamed area or even in the blood of patients with autoimmune diseases, such as rheumatoid arthritis. In addition, the integrity and functionality of the antibody has been studied to see if they have been affected after the chemical coupling process.     

From linear temporal logic and limit-deterministic Büchi automata to deterministic parity automata

Controller synthesis for general linear temporal logic (LTL) objectives is a challenging task. The standard approach involves translating the LTL objective into a deterministic parity automaton (DPA) by means of the Safra-Piterman construction. One of the challenges is the size of the DPA, which often grows very fast in practice, and can reach double exponential size in the length of the LTL formula. In this paper, we describe a single exponential translation from limit-deterministic Büchi automata (LDBA) to DPA and show that it can be concatenated with a recent efficient translations from LTL to LDBA to yield a double exponential, ‘Safraless’ LTL-to-DPA construction. We also report on an implementation and a comparison with other LTL-to-DPA translations on several sets of formulas from the literature.

     

Computational color analysis of paintings for different artists of the XVI and XVII centuries

We have performed a computational color analysis of images of paintings for six master painters: Titian, Rubens, El Greco, Velázquez, Rembrandt, and Vermeer. These painters show the evolution from the renaissance to the baroque style. Different first and second‐order statistical parameters have been obtained and analyzed in order to fix which of them can be common for the different artists and which of them can be representative of a certain period of time or the evolution of the art. The firsts include the orientation and semi‐axes ratio of the ellipses that define the gamut in the chromaticity diagram and the dependencies with the frequency of the power of the Fourier transforms. Most differences among artists can be found in the volume and area of the gamut, the number of discernible colors which is greater for Titian, El Greco and Rubens, compared to Velázquez, Rembrandt and Vermeer, the average value of L* and the number of dark pixels.     

Expanding the Toolbox of R-Selective Amine Transaminases by Identification and Characterization of New Members

Amine transaminases (ATAs) are used to synthesize enantiomerically pure amines, which are building blocks for pharmaceuticals and agrochemicals. R-selective ATAs belong to the fold type IV PLP-dependent enzymes, and different sequence-, structure- and substrate scope-based features have been identified in the past decade. However, our knowledge is still restricted due to the limited number of characterized (R)-ATAs, with additional bias towards fungal origin. We aimed to expand the toolbox of (R)-ATAs and contribute to the understanding of this enzyme subfamily. We identified and characterized four new (R)-ATAs. The ATA from Exophiala sideris contains a motif characteristic for d -ATAs, which was previously believed to be a disqualifying factor for (R)-ATA activity. The crystal structure of the ATA from Shinella is the first from a Gram-negative bacterium. The ATAs from Pseudonocardia acaciae and Tetrasphaera japonica are the first characterized (R)-ATAs with a shortened/missing N-terminal helix. The active-site charges vary significantly between the new and known ATAs, correlating with their diverging substrate scope.     

Improving retention rate and response quality in Web-based surveys

This study centers on three parameters that can influence responses to Web-based surveys: personalization, the periodicity of follow-up mailings and incentives based on prize draws. The results show the need to send a lower number of reminders with personalized e-mail messages when the aim is for respondents to complete the full questionnaire. In contrast, the use of post-incentives based on prize draws was not found to have a significant effect on retention rate when used alone or in combination with personalized messages and/or a lower number of reminders. Moreover, none of the above factors, except personalization, improves response quality when used separately or in conjunction.     

Gene clustering for time-series microarray with production outputs

The identification of coexpressed genes from microarray data is a challenging problem in bioinformatics and computational biology. The objective of this study is to obtain knowledge about the most important genes and clusters related to production outputs of real-world time-series microarray data in the industrial microbiology area. Each sample in the microarray data experiment is complemented with the measurement of the corresponding production and growth values. A novel aspect of this research refers to considering the relation of coexpression patterns with the measured outputs to guide the biological interpretation of results. Shape-based clustering models are developed using the pattern of gene expression values over time and further incorporating knowledge about the correlation between the change in the gene expression level and the output value. Experiments are performed for time-series microarray of bacteria, and an analysis from a biological perspective is carried out. The obtained results confirm the existence of relationships between output variables and gene expressions. Moreover, the shape-based clustering methods show promising results, being able to guide metabolic engineering actions with the identification of potential targets.