Unveiling the Effect of Low pH on the SARS-CoV-2 Main Protease by Molecular Dynamics Simulations

(1) Background: Main Protease (Mpro) is an attractive therapeutic target that acts in the replication and transcription of the SARS-CoV-2 coronavirus. Mpro is rich in residues exposed to protonation/deprotonation changes which could affect its enzymatic function. This work aimed to explore the effect of the protonation/deprotonation states of Mpro at different pHs using computa- tional techniques. (2) Methods: The different distribution charges were obtained in all the evaluated pHs by the Semi-Grand Canonical Monte Carlo (SGCMC) method. A set of Molecular Dynamics (MD) simulations was performed to consider the different protonation/deprotonation during 250 ns, verifying the structural stability of Mpro at different pHs. (3) Results: The present findings demon- strate that active site residues and residues that allow Mpro dimerisation was not affected by pH changes. However, Mpro substrate-binding residues were altered at low pHs, allowing the increased pocket volume. Additionally, the results of the solvent distribution around Sγ, Hγ, Nδ1 and Hδ1 atoms of the catalytic residues Cys145 and His41 showed a low and high-water affinity at acidic pH, respectively. It which could be crucial in the catalytic mechanism of SARS-CoV-2 Mpro at low pHs. Moreover, we analysed the docking interactions of PF-00835231 from Pfizer in the preclinical phase, which shows excellent affinity with the Mpro at different pHs. (4) Conclusion: Overall, these findings indicate that SARS-CoV-2 Mpro is highly stable at acidic pH conditions, and this inhibitor could have a desirable function at this condition

Applying discriminant and cluster analysis to separate allergenic from non-allergenic proteins

As a result of increased healthcare requirements and the introduction of genetically modified foods, the problem of allergies is becoming a growing health problem. The concept of allergies has prompted the use of new methods such as genomics and proteomics to uncover the nature of allergies. In the present study, a selection of 1400 food proteins was analysed by PLS-DA (Partial Least Square-based Discriminant Analysis) after suitable transformation of structural parameters into uniform vectors. Then, the resulting strings of different length were converted into vectors with equal length by Auto and Cross-Covariance (ACC) analysis. Hierarchical and non-hierarchical (K-means) Cluster Analysis (CA) was also performed in order to reach a certain level of separation within a small training set of plant proteins (16 allergenic and 16 non-allergenic) using a new three-dimensional descriptor based on surface protein properties in combination with amino acid hydrophobicity scales. The novelty of the approach in protein differentiation into allergenic and non-allergenic classes is described in the article. The general goal of the present study was to show the effectiveness of a traditional chemometric method for classification (PLS-DA) and the options of Cluster Analysis (CA) to separate by multivariate statistical methods allergenic from non-allergenic proteins

Sports, morality and body. The voices of sportswomen under Franco's dictatorship

The aim of this research is to study sportswomen's perceptions and experiences of women's sport in Francoist Spain (1939-1975). The main objective is to analyse the social, moral and aesthetic elements that are present in the experience of these athletes. This study was carried out with an intentional sample of 24 women from Andalusia, Aragon, Asturias, Basque Country, Catalonia and Valencia. They were interviewed by a network of researchers from six universities. Outstanding results show the existence of social limitations to start sports practice (particularly in the post-war period); the importance of sport as a character-building aspect; sport's remarkable influence on their body self-concept; and the incidence on sports of the mainstream moral discourse, which created a female model that even affected sports clothing. The main conclusion is that sportswomen in that period were pioneers and had to fight against most of society in order to develop their facet as athletes, as they would not follow the established model

Fiber Burden and asbestos-Related Diseases: an Umbrella Review

OBJECTIVE: What are the levels of asbestos exposure that cause each type of health effect? The objective of this study was to review the available scientific evidence on exposure levels for asbestos and their relationship to health effects. METHOD: An umbrella review of English-language reviews and meta-analyses, from 1980 to March 2021 was conducted. We included reviews involving quantified asbestos exposures and health outcomes. The review has been adapted to the indications of the PRISMA declaration. Methodological quality of the selected studies was assessed using the AMSTAR instrument. RESULTS: We retrieved 196 references. After applying the search strategy and quality analysis, 10 reviews were selected for in-depth analysis. For lung cancer, the highest risk was observed with exposure to amphiboles. Longer, thinner fibers had the greatest capacity to cause lung cancer, especially those \u3e 10 μm in length. For mesothelioma, longer and thinner fibers were also more pathogenic; amphiboles ≥ 5 μm are especially associated with increased mesothelioma risk. No studies observed an increased risk for lung cancer or mesothelioma at asbestos exposure levels CONCLUSIONS: Banning all asbestos exposure remains the best measure to preventing its negative health effects. The highest quality reviews and meta-analyses support that there is little risk of lung cancer or mesothelioma at daily exposure levels below 0.1 f/ml

Simultaneous GLP-1 and Insulin Administration Acutely Enhances Their Vasodilatory, Antiinflammatory, and Antioxidant Action in Type 2 Diabetes

OBJECTIVE To test the hypothesis that the simultaneous administration of GLP-1 and insulin may increase their vasodilatory, antiinflammatory, and antioxidant action in type 2 diabetes. RESEARCH DESIGN AND METHODS In two groups of persons with type 2 diabetes, two sets of experiments were performed. The first group had two normoglycemic-normoinsulinemic clamps with or without GLP-1 and two normoglycemic-hyperinsulinemic clamps with or without GLP-1. The second group had two hyperglycemic-normoinsulinemic clamps and two hyperglycemic-hyperinsulinemic clamps with or without GLP-1. RESULTS During the normoglycemic-hyperinsulinemic clamp, flow-mediated dilatation (FMD) increased, while soluble intercellular adhesion molecule (sICAM-1), plasma 8-iso-prostaglandin F2α (8-iso-PGF2α), nitrotyrosine, and interleukin (IL)-6 decreased compared with normoglycemic-normoinsulinemic clamp. Similar results were obtained with the infusion of GLP-1 during the normoglycemic-normoinsulinemic clamp. The combination of hyperinsulinemia and GLP-1 in normoglycemia was accompanied by a further FMD increase and sICAM-1, 8-iso-PGF2α, nitrotyrosine, and IL-6 decrease. During the hyperglycemic-normoinsulinemic clamp, FMD significantly decreased, while sICAM-1, 8-iso-PGF2α, nitrotyrosine, and IL-6 significantly increased. When hyperglycemia was accompanied by hyperinsulinemia or by the simultaneous infusion of GLP-1, these phenomena were attenuated. The simultaneous presence of hyperinsulinemia and GLP-1 had an increased beneficial effect. CONCLUSIONS Our results show that the combination of insulin and GLP-1 is more effective than insulin or GLP-1 alone in improving endothelial dysfunction, inflammation, and oxidative stress in type 2 diabetes

Non-monotonic behavior of weak-polyelectrolytes adsorption on a cationic surface: A Monte Carlo simulation study

In this work, the weak polyelectrolyte (PE) adsorption on a strong cationic surface is studied with constant pH Monte Carlo simulations using a coarse-grained model. When a large number of PE chains is added to the system, the PE adsorbed amount vs pH curve exhibits a non-monotonic behavior, with the appearance of a maximum close to the intrinsic pKa0-value of the PE titratable groups. The apparent pKa-value of the PE chains shows a non-trivial tendency depending on the pH-value and the surface coverage degree. In increasing the pH-value, the small anions that accompany the cationic surface are replaced by PE chains and small cations. For pH>pKa0+1, an evident charge reversion of surface is observed. These results are explained analyzing the interplay between the attractive and repulsion electrostatic interactions between the different components of the system (inter- and intra-charged monomers of PE chains, the strong cationic surface and small ions) and their effects on the PE chain ionization.Fil: Narambuena, Claudio Fabian. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - San Luis. Instituto de Fisica Aplicada "dr. Jorge Andres Zgrablich". Grupo Vinculado Bionanotecnologia y Sistemas Complejos | Universidad Nacional de San Luis. Facultad de Cs.fisico Matematicas y Naturales. Instituto de Fisica Aplicada "dr. Jorge Andres Zgrablich". Grupo Vinculado Bionanotecnologia y Sistemas Complejos. - Universidad Tecnologica Nacional. Facultad Reg.san Rafael. Grupo Vinculado Bionanotecnologia y Sistemas Complejos.; ArgentinaFil: Blanco, Pablo M.. Universidad de Barcelona. Facultad de Quimica. Instituto de Quimica Teorica y Computacional.; EspañaFil: Rodriguez, Adrian. Universidad Tecnológica Nacional. Facultad Reg. Neuquen; ArgentinaFil: Rodríguez, Diego E.. Universidad Tecnológica Nacional. Facultad Reg. Neuquen; ArgentinaFil: Madurga, Sergio. Universidad de Barcelona. Facultad de Quimica. Instituto de Quimica Teorica y Computacional.; EspañaFil: Garcés, José L.. Universidad de Barcelona. Facultad de Quimica. Instituto de Quimica Teorica y Computacional.; EspañaFil: Mas Pujadas, Francesc. Universidad de Barcelona. Facultad de Quimica. Instituto de Quimica Teorica y Computacional.; Españ

Wnt9a deficiency discloses a repressive role of Tcf7l2 on endocrine differentiation in the embryonic pancreas

Transcriptional and signaling networks establish complex cross-regulatory interactions that drive cellular differentiation during development. Using microarrays we identified the gene encoding the ligand Wnt9a as a candidate target of Neurogenin3, a basic helix-loop-helix transcription factor that functions as a master regulator of pancreatic endocrine differentiation. Here we show that Wnt9a is expressed in the embryonic pancreas and that its deficiency enhances activation of the endocrine transcriptional program and increases the number of endocrine cells at birth. We identify the gene encoding the endocrine transcription factor Nkx2-2 as one of the most upregulated genes in Wnt9a-ablated pancreases and associate its activation to reduced expression of the Wnt effector Tcf7l2. Accordingly, in vitro studies confirm that Tcf7l2 represses activation of Nkx2-2 by Neurogenin3 and inhibits Nkx2-2 expression in differentiated β-cells. Further, we report that Tcf7l2 protein levels decline upon initiation of endocrine differentiation in vivo, disclosing the downregulation of this factor in the developing endocrine compartment. These findings highlight the notion that modulation of signalling cues by lineage-promoting factors is pivotal for controlling differentiation programs

The SST-1M camera for the Cherenkov Telescope Array

The prototype camera of the single-mirror Small Size Telescopes (SST-1M) proposed for the Cherenkov Telescope Array (CTA) project has been designed to be very compact and to deliver high performance over thirty years of operation. The camera is composed of an hexagonal photo-detection plane made of custom designed large area hexagonal silicon photomultipliers and a high throughput, highly configurable, fully digital readout and trigger system (DigiCam). The camera will be installed on the telescope structure at the H. Niewodnicza{\'n}ski institute of Nuclear Physics in Krakow in fall 2015. In this contribution, we review the steps that led to the development of the innovative photo-detection plane and readout electronics, and we describe the test and calibration strategy adopted.Comment: In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.05894; Full consortium author list at http://cta-observatory.or

Prediction of incident cardiovascular events using machine learning and CMR radiomics.

OBJECTIVES: Evaluation of the feasibility of using cardiovascular magnetic resonance (CMR) radiomics in the prediction of incident atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), and stroke using machine learning techniques. METHODS: We identified participants from the UK Biobank who experienced incident AF, HF, MI, or stroke during the continuous longitudinal follow-up. The CMR indices and the vascular risk factors (VRFs) as well as the CMR images were obtained for each participant. Three-segmented regions of interest (ROIs) were computed: right ventricle cavity, left ventricle (LV) cavity, and LV myocardium in end-systole and end-diastole phases. Radiomics features were extracted from the 3D volumes of the ROIs. Seven integrative models were built for each incident cardiovascular disease (CVD) as an outcome. Each model was built with VRF, CMR indices, and radiomics features and a combination of them. Support vector machine was used for classification. To assess the model performance, the accuracy, sensitivity, specificity, and AUC were reported. RESULTS: AF prediction model using the VRF+CMR+Rad model (accuracy: 0.71, AUC 0.76) obtained the best result. However, the AUC was similar to the VRF+Rad model. HF showed the most significant improvement with the inclusion of CMR metrics (VRF+CMR+Rad: 0.79, AUC 0.84). Moreover, adding only the radiomics features to the VRF reached an almost similarly good performance (VRF+Rad: accuracy 0.77, AUC 0.83). Prediction models looking into incident MI and stroke reached slightly smaller improvement. CONCLUSIONS: Radiomics features may provide incremental predictive value over VRF and CMR indices in the prediction of incident CVDs. KEY POINTS: • Prediction of incident atrial fibrillation, heart failure, stroke, and myocardial infarction using machine learning techniques. • CMR radiomics, vascular risk factors, and standard CMR indices will be considered in the machine learning models. • The experiments show that radiomics features can provide incremental predictive value over VRF and CMR indices in the prediction of incident cardiovascular diseases