Fighting the Huntington’s Disease with a G-Quadruplex-Forming Aptamer Specifically Binding to Mutant Huntingtin Protein: Biophysical Characterization,In Vitro and In Vivo Studies

A set of guanine-rich aptamers able to preferentially recognize full-length huntingtin with an expanded polyglutamine tract has been recently identified, showing high efficacy in modulating the functions of the mutated protein in a variety of cell experiments. We here report a detailed biophysical characterization of the best aptamer in the series, named MS3, proved to adopt a stable, parallel G-quadruplex structure and show high nuclease resistance in serum. Confocal microscopy experiments on HeLa and SH-SY5Y cells, as models of non-neuronal and neuronal cells, respectively, showed a rapid, dose-dependent uptake of fluorescein-labelled MS3, demonstrating its effective internalization, even in the absence of transfecting agents, with no general cytotoxicity. Then, using a well-established Drosophila melanogaster model for Huntington’s disease, which expresses the mutated form of human huntingtin, a significant improvement in the motor neuronal function in flies fed with MS3 was observed, proving the in vivo efficacy of this aptamer.     

Albumin Binds Doxorubicin via Self–Assembling Dyes as Specific Polymolecular Ligands

Congo red (CR) type self–assembled ribbon–like structures (SRLS) were previously shown to interact with some proteins, including albumin. SRLS also complex with some drugs with a flat, ring–shaped structure with aromatic characteristics, intercalating them into their ribbon structure. The combination of interaction with proteins and drug binding by SRLS enables the use of such systems for immunotargeting. It is especially interesting in the case of chemotherapeutic agents. The present experiments aimed to show that the model carrier system composed of supramolecular albumin and Congo red efficiently binds doxorubicin (Dox) and that the drug can be released at reduced pH. The presented results come from the studies on such complexes differing in the molar ratio of CR to Dox. The following methods were used for the analysis: electrophoresis, dialysis, gel filtration, spectral analysis, and analysis of the size of the hydrodynamic radius using the dynamic light scattering method (DLS). The applied methods confirmed the formation of the CR–Dox complex, with large dimensions and changed properties compared with free CR. The presented results show that albumin binds both CR and its complex with Dox. Various CR–Dox molar ratios, 5:1, 2:1, and 1:1, were analyzed. The confirmation of the possibility of releasing the drug from the carriers thus formed was also obtained. The presented research is important due to the search for optimal solutions for the use of SRLS in drug immunotargeting, with particular emphasis on chemotherapeutic agents.     

The Use of Molecular Dynamics Simulation Method to Quantitatively Evaluate the Affinity between HBV Antigen T Cell Epitope Peptides and HLA-A Molecules

Chronic hepatitis B virus (HBV), a potentially life-threatening liver disease, makes people vulnerable to serious diseases such as cancer. T lymphocytes play a crucial role in clearing HBV virus, while the pathway depends on the strong binding of T cell epitope peptide and HLA. However, the experimental identification of HLA-restricted HBV antigenic peptides is extremely time-consuming. In this study, we provide a novel prediction strategy based on structure to assess the affinity between the HBV antigenic peptide and HLA molecule. We used residue scanning, peptide docking and molecular dynamics methods to obtain the molecular docking model of HBV peptide and HLA, and then adopted the MM-GBSA method to calculate the binding affinity of the HBV peptide–HLA complex. Overall, we collected 59 structures of HLA-A from Protein Data Bank, and finally obtained 352 numerical affinity results to figure out the optimal bind choice between the HLA-A molecules and 45 HBV T cell epitope peptides. The results were highly consistent with the qualitative affinity level determined by the competitive peptide binding assay, which confirmed that our affinity prediction process based on an HLA structure is accurate and also proved that the homologous modeling strategy for HLA-A molecules in this study was reliable. Hence, our work highlights an effective way by which to predict and screen for HLA-peptide binding that would improve the treatment of HBV infection.     

STN7 Kinase Is Essential for Arabidopsis thaliana Fitness under Prolonged Darkness but Not under Dark-Chilling Conditions

Reversible phosphorylation of photosystem II light harvesting complexes (LHCII) is a well-established protective mechanism enabling efficient response to changing light conditions. However, changes in LHCII phosphorylation were also observed in response to abiotic stress regardless of photoperiod. This study aimed to investigate the impact of dark-chilling on LHCII phosphorylation pattern in chilling-tolerant Arabidopsis thaliana and to check whether the disturbed LHCII phosphorylation process will impact the response of Arabidopsis to the dark-chilling conditions. We analyzed the pattern of LHCII phosphorylation, the organization of chlorophyll–protein complexes, and the level of chilling tolerance by combining biochemical and spectroscopy techniques under dark-chilling and dark conditions in Arabidopsis mutants with disrupted LHCII phosphorylation. Our results show that during dark-chilling, LHCII phosphorylation decreased in all examined plant lines and that no significant differences in dark-chilling response were registered in tested lines. Interestingly, after 24 h of darkness, a high increase in LHCII phosphorylation was observed, co-occurring with a significant F_V/F_M parameter decrease. The highest drop of F_V/F_M was detected in the stn7-1 line–mutant, where the LHCII is not phosphorylated, due to the lack of STN7 kinase. Our results imply that STN7 kinase activity is important for mitigating the adverse effects of prolonged darkness.     

Video game training to improve selective visual attention in older adults

The current study investigated the effect of video game training on older adult’s useful field of view performance (the UFOV® test). Fifty-eight older adult participants were randomized to receive practice with the target action game (Medal of Honor), a placebo control arcade game (Tetris), a clinically validated UFOV training program, or into a no contact control group. Examining pretest–posttest change in selective visual attention, the UFOV improved significantly more than the game groups; all three intervention groups improved significantly more than no-contact controls. There was a lack of difference between the two game conditions, differing from findings with younger adults. Discussion considers whether games posing less challenge might still be effective interventions for elders, and whether optimal training dosages should be higher.     

Automatic word naming recognition for an on-line aphasia treatment system

One of the most common effects among aphasia patients is the difficulty to recall names or words. Typically, word retrieval problems can be treated through word naming therapeutic exercises. In fact, the frequency and the intensity of speech therapy are key factors in the recovery of lost communication functionalities. In this sense, speech and language technology can have a relevant contribution in the development of automatic therapy methods. In this work, we present an on-line system designed to behave as a virtual therapist incorporating automatic speech recognition technology that permits aphasia patients to perform word naming training exercises. We focus on the study of the automatic word naming detector module and on its utility for both global evaluation and treatment. For that purpose, a database consisting of word naming therapy sessions of aphasic Portuguese native speakers has been collected. In spite of the different patient characteristics and speech quality conditions of the collected data, encouraging results have been obtained thanks to a calibration method that makes use of the patients’ word naming ability to automatically adapt to the patients’ speech particularities.     

Similarity reasoning for the semantic web based on fuzzy concept lattices: An informal approach

Similarity Reasoning in the presence of vague information is becoming fundamental in several research areas and, in particular, in the Semantic Web. Fuzzy Formal Concept Analysis (FFCA) is a generalization of Formal Concept Analysis (FCA) for modeling uncertainty information. Although FFCA has become very interesting for supporting different activities for the development of the Semantic Web, in the literature it is usually addressed at a technical level and intended for a restricted audience. This paper proposes a similarity measure for FFCA concepts. The key notions underlying the proposed approach are presented informally, in order to reach a broad audience of readers.     

Compact DSOP and Partial DSOP Forms

Given a Boolean function f on n variables, a Disjoint Sum-of-Products (DSOP) of f is a set of products (ANDs) of subsets of literals whose sum (OR) equals f, such that no two products cover the same minterm of f. DSOP forms are a special instance of partial DSOPs, i.e. the general case where a subset of minterms must be covered exactly once and the other minterms (typically corresponding to don’t care conditions of f) can be covered any number of times. We discuss finding DSOPs and partial DSOPs with a minimal number of products, a problem theoretically connected with various properties of Boolean functions and practically relevant in the synthesis of digital circuits. Finding an absolute minimum is hard, in fact we prove that the problem of absolute minimization of partial DSOPs is NP-hard. Therefore it is crucial to devise a polynomial time heuristic that compares favorably with the known minimization tools. To this end we develop a further piece of theory starting from the definition of the weight of a cube c as a functions of the number of fragments induced on other cubes by the selection of c, and show how cube weights can be exploited for building a class of minimization heuristics for DSOP and partial DSOP synthesis. A set of experiments conducted on major benchmark functions show that our method, with a family of variants, always generates better results than the ones of previous heuristics, including the method based on a BDD representation of f.     

Nonlinear model identification and see-through cancelation from recto–verso data

The problem of see-through cancelation in digital images of double-sided documents is addressed. We show that a nonlinear convolutional data model proposed elsewhere for moderate show-through can also be effective on strong back-to-front interferences, provided that the recto and verso pure patterns are estimated jointly. To this end, we propose a restoration algorithm that does not need any classification of the pixels. The see-through PSFs are estimated off-line, and an iterative procedure is then employed for a joint estimation of the pure patterns. This simple and fast algorithm can be used on both grayscale and color images and has proved to be very effective in real-world cases. The experimental results we report in this paper demonstrate that our algorithm outperforms the ones based on linear models with no need to tune free parameters and remains computationally inexpensive despite the nonlinear model and the iterative solution adopted. Strategies to overcome some of the residual difficulties are also envisaged.