Model of cellular mechanotransduction via actin stress fibers

Mechanical stresses due to blood flow regulate vascular endothelial cell structure and function and play a key role in arterial physiology and pathology. In particular, the development of atherosclerosis has been shown to correlate with regions of disturbed blood flow where endothelial cells are round and have a randomly organized cytoskeleton. Thus, deciphering the relation between the mechanical environment, cell structure, and cell function is a key step toward understanding the early development of atherosclerosis. Recent experiments have demonstrated very rapid (\(\sim \)100 ms) and long-distance (\(\sim \)10 \(\upmu \)m) cellular mechanotransduction in which prestressed actin stress fibers play a critical role. Here, we develop a model of mechanical signal transmission within a cell by describing strains in a network of prestressed viscoelastic stress fibers following the application of a force to the cell surface. We find force transmission dynamics that are consistent with experimental results. We also show that the extent of stress fiber alignment and the direction of the applied force relative to this alignment are key determinants of the efficiency of mechanical signal transmission. These results are consistent with the link observed experimentally between cytoskeletal organization, mechanical stress, and cellular responsiveness to stress. Based on these results, we suggest that mechanical strain of actin stress fibers under force constitutes a key link in the mechanotransduction chain.     

Increased Reactive Oxygen Species Formation and Oxidative Stress in Rheumatoid Arthritis

BackgroundRheumatoid arthritis (RA) is an autoimmune inflammatory disorder. Highly reactive oxygen free radicals are believed to be involved in the pathogenesis of the disease. In this study, RA patients were sub-grouped depending upon the presence or absence of rheumatoid factor, disease activity score and disease duration. RA Patients (120) and healthy controls (53) were evaluated for the oxidant—antioxidant status by monitoring ROS production, biomarkers of lipid peroxidation, protein oxidation and DNA damage. The level of various enzymatic and non-enzymatic antioxidants was also monitored. Correlation analysis was also performed for analysing the association between ROS and various other parameters.MethodsIntracellular ROS formation, lipid peroxidation (MDA level), protein oxidation (carbonyl level and thiol level) and DNA damage were detected in the blood of RA patients. Antioxidant status was evaluated by FRAP assay, DPPH reduction assay and enzymatic (SOD, catalase, GST, GR) and non-enzymatic (vitamin C and GSH) antioxidants.ResultsRA patients showed a higher ROS production, increased lipid peroxidation, protein oxidation and DNA damage. A significant decline in the ferric reducing ability, DPPH radical quenching ability and the levels of antioxidants has also been observed. Significant correlation has been found between ROS and various other parameters studied.ConclusionRA patients showed a marked increase in ROS formation, lipid peroxidation, protein oxidation, DNA damage and decrease in the activity of antioxidant defence system leading to oxidative stress which may contribute to tissue damage and hence to the chronicity of the disease.     

Spectroscopic (UV/VIS,Raman) and Electrophoresis Study of Cytosine-Guanine Oligonucleotide DNA Influenced by Magnetic Field

Studying the effect of a magnetic field on oligonucleotide DNA can provide a novel DNA manipulation technique for potential application in bioengineering and medicine. In this work, the optical and electrochemical response of a 100 bases oligonucleotides DNA, cytosine-guanine (CG₁₀₀), is investigated via exposure to different magnetic fields (250, 500, 750, and 1000 mT). As a result of the optical response of CG₁₀₀ to the magnetic field, the ultra-violet-visible spectrum indicated a slight variation in the band gap of CG₁₀₀ of about 0.3 eV. Raman spectroscopy showed a significant deviation in hydrogen and phosphate bonds’ vibration after exposure to the magnetic field. Oligonucleotide DNA mobility was investigated in the external electric field using the gel electrophoresis technique, which revealed a small decrease in the migration of CG₁₀₀ after exposure to the magnetic field.     

Atrial Fibrillation Management Strategies in Routine Clinical Practice: Insights from the International RealiseAF Survey

Background

Atrial fibrillation (AF) can be managed with rhythm- or rate-control strategies. There are few data from routine clinical practice on the frequency with which each strategy is used and their correlates in terms of patients’ clinical characteristics, AF control, and symptom burden.

Methods

RealiseAF was an international, cross-sectional, observational survey of 11,198 patients with AF. The aim of this analysis was to describe patient profiles and symptoms according to the AF management strategy used. A multivariate logistic regression identified factors associated with AF management strategy at the end of the visit.

Results

Among 10,497 eligible patients, 53.7% used a rate-control strategy, compared with 34.5% who used a rhythm-control strategy. In 11.8% of patients, no clear strategy was stated. The proportion of patients with AF-related symptoms (EHRA Class > = II) was 78.1% (n = 4396/5630) for those using a rate-control strategy vs. 67.8% for those using a rhythm-control strategy (p<0.001). Multivariate logistic regression analysis revealed that age <75 years or the paroxysmal or persistent form of AF favored the choice of a rhythm-control strategy. A change in strategy was infrequent, even in patients with European Heart Rhythm Association (EHRA) Class > = II.

Conclusions

In the RealiseAF routine clinical practice survey, rate control was more commonly used than rhythm control, and a change in strategy was uncommon, even in symptomatic patients. In almost 12% of patients, no clear strategy was stated. Physician awareness regarding optimal management strategies for AF may be improved.     

Large-Scale Functional Networks Identified from Resting-State EEG Using Spatial ICA

Several methods have been applied to EEG or MEG signals to detect functional networks. In recent works using MEG/EEG and fMRI data, temporal ICA analysis has been used to extract spatial maps of resting-state networks with or without an atlas-based parcellation of the cortex. Since the links between the fMRI signal and the electromagnetic signals are not fully established, and to avoid any bias, we examined whether EEG alone was able to derive the spatial distribution and temporal characteristics of functional networks. To do so, we propose a two-step original method: 1) An individual multi-frequency data analysis including EEG-based source localisation and spatial independent component analysis, which allowed us to characterize the resting-state networks. 2) A group-level analysis involving a hierarchical clustering procedure to identify reproducible large-scale networks across the population. Compared with large-scale resting-state networks obtained with fMRI, the proposed EEG-based analysis revealed smaller independent networks thanks to the high temporal resolution of EEG, hence hierarchical organization of networks. The comparison showed a substantial overlap between EEG and fMRI networks in motor, premotor, sensory, frontal, and parietal areas. However, there were mismatches between EEG-based and fMRI-based networks in temporal areas, presumably resulting from a poor sensitivity of fMRI in these regions or artefacts in the EEG signals. The proposed method opens the way for studying the high temporal dynamics of networks at the source level thanks to the high temporal resolution of EEG. It would then become possible to study detailed measures of the dynamics of connectivity.     

Sexual size dimorphism and morphometric sexing in a North African population of Laughing Doves Spilopelia senegalensis

Like the majority of Columbiformes, the Laughing Dove Spilopelia senegalensis is sexually monomorphic in plumage, but seems to be slightly dimorphic in size. However, due to the lack of studies little is known about the sexual size dimorphism in this species. In this work, we used morphometric data on a sample of 61 Laughing Doves from southern Tunisia, and sexed using a DNA-based method, to assess size differences between males and females and to determine a discriminant function useful for sex identification. The results showed that wing length was the most dimorphic trait, which could be due to the effects of sexual selection. The best function for the discrimination between sexes included wing length and head length, which is comparable with findings on other dove species. This discriminant function accurately classified 89% of birds, providing a rapid and accurate tool for sex identification in the studied population. Further data from different populations are needed for firmer conclusions about the extent of sexual size dimorphism and the reliability of the morphometric sexing approach in this dove species.