Mullenjokumsen6869

S100 proteins assume a diversity of oligomeric states including large order self-assemblies, with an impact on protein structure and function. Previous work has uncovered that S100 proteins, including S100B, are prone to undergo β-aggregation under destabilizing conditions. This propensity is encoded in aggregation-prone regions (APR) mainly located in segments at the homodimer interface, and which are therefore mostly shielded from the solvent and from deleterious interactions, under native conditions. As in other systems, this characteristic may be used to develop peptides with pharmacological potential that selectively induce the aggregation of S100B through homotypic interactions with its APRs, resulting in functional inhibition through a loss of function. Here we report initial studies towards this goal. We applied the TANGO algorithm to identify specific APR segments in S100B helix IV and used this information to design and synthesize S100B-derived APR peptides. We then combined fluorescence spectroscopy, transmission electron microscopy, biolayer interferometry, and aggregation kinetics and determined that the synthetic peptides have strong aggregation propensity, interact with S100B, and may promote co-aggregation reactions. In this framework, we discuss the considerable potential of such APR-derived peptides to act pharmacologically over S100B in numerous physiological and pathological conditions, for instance as modifiers of the S100B interactome or as promoters of S100B inactivation by selective aggregation.Cardiac signals have complex structures representing a combination of simpler structures. In this paper, we develop a new data analytic tool that can extract the complex structures of cardiac signals using the framework of multi-chaotic analysis, which is based on the p-norm for calculating the largest Lyapunov exponent (LLE). Appling the p-norm is useful for deriving the spectrum of the generalized largest Lyapunov exponents (GLLE), which is characterized by the width of the spectrum (which we denote by W). This quantity measures the degree of multi-chaos of the process and can potentially be used to discriminate between different classes of cardiac signals. We propose the joint use of the GLLE and spectrum width to investigate the multi-chaotic behavior of inter-beat (R-R) intervals of cardiac signals recorded from 54 healthy subjects (hs), 44 subjects diagnosed with congestive heart failure (chf), and 25 subjects diagnosed with atrial fibrillation (af). With the proposed approach, we build a regression model for the diagnosis of pathology. Multi-chaotic analysis showed a good performance, allowing the underlying dynamics of the system that generates the heart beat to be examined and expert systems to be built for the diagnosis of cardiac pathologies.This study aimed to evaluate donkey seminal plasma metabolites and relate this information to the main characteristics of sperm quality. Sperm kinetics from 10 donkey stallions were analyzed with a computerized system at the time of collection (T0) and after 24 h storage at 4 °C (T24). Seminal plasma was frozen at -80 °C for subsequent proton nuclear magnetic resonance (1H NMR) spectroscopy. On three stallions, semen collection was repeated monthly for three times and sperm analysis also included mitochondrial activity and oxidative status. One stallion was azoospermic and a second semen collection was performed after one month. In the seminal plasma, 17 metabolites were identified; their levels showed numerous significant variations between the azoospermic and the normospermic individuals and grouped in well-defined clusters in a multivariate analysis. Comparing individuals with high and low sperm motility, the only discriminating metabolite was phenylalanine, whose levels were lower in the latter, as in the azoospermic individual. Phenylalanine was also the only metabolite highly correlated with all sperm kinematic parameters at T24. In conclusion, the present study has provided relevant information on the chemical characteristics of donkey semen, identified relationships between seminal metabolites, semen parameters, and sperm kinetics, and offered insights for future technological applications.Corticobasal syndrome (CBS) is an atypical parkinsonian presentation characterized by heterogeneous clinical features and different underlying neuropathology. Most CBS cases are sporadic; nevertheless, reports of families and isolated individuals with genetically determined CBS have been reported. In this systematic review, we analyze the demographical, clinical, radiological, and anatomopathological features of genetically confirmed cases of CBS. A systematic search was performed using the PubMed, EMBASE, and Cochrane Library databases, included all publications in English from 1 January 1999 through 1 August 2020. We found forty publications with fifty-eight eligible cases. A second search for publications dealing with genetic risk factors for CBS led to the review of eight additional articles. GRN was the most common gene involved in CBS, representing 28 out of 58 cases, followed by MAPT, C9ORF72, and PRNP. A set of symptoms was shown to be significantly more common in GRN-CBS patients, including visuospatial impairment, behavioral changes, aphasia, and language alterations. learn more In addition, specific demographical, clinical, biochemical, and radiological features may suggest mutations in other genes. We suggest a diagnostic algorithm to help in identifying potential genetic cases of CBS in order to improve the diagnostic accuracy and to better understand the still poorly defined underlying pathogenetic process.Biofilms contain microbial cells which are protected by a self-produced matrix and they firmly attach themselves to many different food industry surfaces. Due to this protection, microorganisms within biofilms are much more difficult to eradicate and therefore to control than suspended cells. A bacterium that tends to produce these structures and persist in food processing plants is Listeria monocytogenes. To this effect, many attempts have been made to develop control strategies to be applied in the food industry, although there seems to be no clear direction on how to manage the risk the bacteria poses. There is no standardized protocol that is applied equally to all food sectors, so the strategies for the control of this pathogen depend on the type of surface, the nature of the product, the conditions of the food industry environment, and indeed the budget. The food industry performs different preventive and corrective measures on possible L. monocytogenes-contaminated surfaces. However, a critical evaluation of the sanitization methods applied must be performed to discern whether the treatment can be effective in the long-term.