Three-dimensional apoptotic nuclear behavior analyzed by means of field emission in lens scanning electron microscope

Apoptosis is an essential biological function required during embryogenesis, tissue homeostasis, organ development and immune system regulation. It is an active cell death pathway involved in a variety of pathological conditions. During this process cytoskeletal proteins appear damaged and undergo an enzymatic disassembling, leading to formation of apoptotic features. This study was designed to examine the threedimensional chromatin behavior and cytoskeleton involvement, in particular actin re-modeling. HL-60 cells, exposed to hyperthermia, a known apoptotic trigger, were examined by means of a Field Emission in Lens Scanning Electron Microscope (FEISEM). Ultrastructural observations revealed in treated cells the presence of apoptotic patterns after hyperthermia trigger. In particular, three-dimensional apoptotic chromatin rearrangements appeared involving the translocation of filamentous actin from cytoplasm to the nucleus. FEISEM immunogold techniques showed actin labeling and its precise three-dimensional localization in the diffuse chromatin, well separated from the condensed one. The actin presence in dispersed chromatin inside the apoptotic nucleus can be considered an important feature, indispensable to permit the apoptotic machinery evolution

Growth hormone plus resistance exercise attenuate structural changes in rat myotendinous junctions resulting from chronic unloading.

Myotendinous junctions (MTJs) are specialized sites on the muscle surface where forces generated by myofibrils are transmitted across the sarcolemma to the extracellular matrix. At the ultrastructural level, the interface between the sarcolemma and extracellular matrix is highly folded and interdigitated at these junctions. In this study, the effect of exercise and growth hormone (GH) treatments on the changes in MTJ structure that occur during muscle unloading, has been analyzed. Twenty hypophysectomized rats were assigned randomly to one of five groups: ambulatory control, hindlimb unloaded, hindlimb unloaded plus exercise (3 daily bouts of 10 climbs up a ladder with 50% body wt attached to the tail), hindlimb unloaded plus GH (2 daily injections of 1 mg/kg body wt, i.p.), and hindlimb unloaded plus exercise plus GH. MTJs of the plantaris muscle were analyzed by electron microscopy and the contact between muscle and tendon was evaluated using an IL/B ratio, where B is the base and IL is the interface length of MTJ's digit-like processes. After 10 days of unloading, the mean IL/B ratio was significantly lower in unloaded (3.92), unloaded plus exercise (4.18), and unloaded plus GH (5.25) groups than in the ambulatory control (6.39) group. On the opposite, the mean IL/B ratio in the group treated with both exercise and GH (7.3) was similar to control. These findings indicate that the interaction between exercise and GH treatments attenuates the changes in MTJ structure that result from chronic unloading and thus can be used as a countermeasure to these adaptations

Comparison of rheological behaviour of bio-based and synthetic epoxy resins for making ecocomposites

In this paper, the rheological behaviour of a petroleum-based epoxy (EL2 laminating epoxy) was compared with the Super Sap CLR clear bio-resin epoxy. The focus of the work was on the viscous and viscoelastic performance of these epoxy resins. Rheological tests were carried out at 15, 30, and 60 min after the mixing of the pure epoxies and the hardeners at a constant temperature of 25 °C. The results obtained from the rheometer tests showed that the viscosity of both epoxy systems decreased with increasing shear rate, which is typical behaviour of a shear thinning fluid. Regarding the oscillatory rheology tests, the viscoelastic properties of both epoxy resins were studied within their linear viscoelastic region (LVER) by amplitude sweep test, which was also carried out 15, 30, and 60 min after mixing the epoxies with the hardeners. It was noticed that the petroleum-based epoxy possessed a more significant LVER relative to the bio-based resin. Finally, the storage modulus (G′), the loss modulus (G″), and the phase angle were extracted, and these parameters were investigated over low and high frequencies. From the test results, we observed that both epoxy resins showed a liquid-like viscoelastic behaviour due to their phase angle values, which were always between 45° and 90°, and by the general tendency of the G″ predominance over G′ at low and high frequencies

Melatonin prevents chemical-induced Haemopoietic cell death

Melatonin (MEL), a methoxyindole synthesized by the pineal gland, is a powerful antioxidant in tissues as well as within cells, with a fundamental role in ameliorating homeostasis in a number of specific pathologies. It acts both as a direct radical scavenger and by stimulating production/activity of intracellular antioxidant enzymes. In this work, some chemical triggers, with different mechanisms of action, have been chosen to induce cell death in U937 hematopoietic cell line. Cells were pre-treated with 100 μM MEL and then exposed to hydrogen peroxide or staurosporine. Morphological analyses, TUNEL reaction and Orange/PI double staining have been used to recognize ultrastructural apoptotic patterns and to evaluate DNA behavior. Chemical damage and potential MEL anti-apoptotic effects were quantified by means of Tali® Image-Based Cytometer, able to monitor cell viability and apoptotic events. After trigger exposure, chromatin condensation, micronuclei formation and DNA fragmentation have been observed, all suggesting apoptotic cell death. These events underwent a statistically significant decrease in samples pre-treated with MEL. After caspase inhibition and subsequent assessment of cell viability, we demonstrated that apoptosis occurs, at least in part, through the mitochondrial pathway and that MEL interacts at this level to rescue U937 cells from death. © 2014 by the authors; licensee MDPI, Basel, Switzerland

MODELING the INTERACTION BETWEEN AIDS and TUBERCULOSIS

A deterministic model is proposed for the study of the dynamics of acquired immunodeficiency syndrome (AIDS) and tuberculosis (TB) co-infection. the model is comprised by a set of sixteen ordinary differential equations representing different states of both diseases, and it is intended to provide a theoretical framework for the study of the interaction between both infections. Numerical simulations of the model resulted in three striking outcomes: first, the pathogenicity of Human Immunodeficiency Virus (HIV) is enhanced by the presence of TB, and vice-versa; second, the prevalence of AIDS is higher in the presence of TB; and third, relative risk analysis demonstrated a much stronger influence of AIDS on TB than the other way around.ESCOLA PAULISTA MED,BR-04023 São Paulo,BRAZILUNIV São Paulo,INST PHYS,São Paulo,BRAZILHCFMUSP,BR-01246 São Paulo,BRAZILESCOLA PAULISTA MED,BR-04023 São Paulo,BRAZILWeb of Scienc

Modelisation of transition and noble metal vicinal surfaces: energetics, vibrations and stability

The energetics of transition and noble metal (Rh, Pd, Cu) vicinal surfaces, i.e., surface energy, step energy, kink energy and electronic interactions between steps, is studied at 0K from electronic structure calculations in the tight-binding approximation using a {\it s, p} and {\it d} valence orbital basis set. Then, the surface phonon spectra of copper are investigated in the harmonic approximation with the help of a semi-empirical inter-atomic potential. This allows to derive the contribution of phonons at finite temperatures to the step free energy and to the interactions between steps. The last part is devoted to the stability of vicinal surfaces relative to faceting with special attention to the domain of orientations (100)-(111). Semi-empirical potentials are shown to be not realistic enough to give a reliable answer to this problem. The results derived from electronic structure calculations predict a variety of behaviors and, in particular, a possible faceting into two other vicinal orientations. Finally, temperature effects are discussed. Comparisons are made with other theoretical works and available experiments

A Minimal and Multi-Source Recording Setup for Ankle Joint Kinematics Estimation During Walking Using Only Proximal Information From Lower Limb

In this study, a minimal setup for the ankle joint kinematics estimation is proposed relying only on proximal information of the lower-limb, i.e. thigh muscles activity and joint kinematics. To this purpose, myoelectric activity of Rectus Femoris (RF), Biceps Femoris (BF), and Vastus Medialis (VM) were recorded by surface electromyography (sEMG) from six healthy subjects during unconstrained walking task. For each subject, the angular kinematics of hip and ankle joints were synchronously recorded with sEMG signal for a total of 288 gait cycles. Two feature sets were extracted from sEMG signals, i.e. time domain (TD) and wavelet (WT) and compared to have a compromise between the reliability and computational capacity, they were used for feeding three regression models, i.e. Artificial Neural Networks, Random Forest, and Least Squares - Support Vector Machine (LS-SVM). BF together with LS-SVM provided the best ankle angle estimation in both TD and WT domains (RMSE < 5.6 deg). The inclusion of Hip joint trajectory significantly enhanced the regression performances of the model (RMSE < 4.5 deg). Results showed the feasibility of estimating the ankle trajectory using only proximal and limited information from the lower limb which would maximize a potential transfemoral amputee user's comfortability while facing the challenge of having a small amount of information thus requiring robust data-driven models. These findings represent a significant step towards the development of a minimal setup useful for the control design of ankle active prosthetics and rehabilitative solutions

Intelligent Human–Computer Interaction: Combined Wrist and Forearm Myoelectric Signals for Handwriting Recognition

Recent studies have highlighted the possibility of using surface electromyographic (EMG) signals to develop human–computer interfaces that are also able to recognize complex motor tasks involving the hand as the handwriting of digits. However, the automatic recognition of words from EMG information has not yet been studied. The aim of this study is to investigate the feasibility of using combined forearm and wrist EMG probes for solving the handwriting recognition problem of 30 words with consolidated machine-learning techniques and aggregating state-of-the-art features extracted in the time and frequency domains. Six healthy subjects, three females and three males aged between 25 and 40 years, were recruited for the study. Two tests in pattern recognition were conducted to assess the possibility of classifying fine hand movements through EMG signals. The first test was designed to assess the feasibility of using consolidated myoelectric control technology with shallow machine-learning methods in the field of handwriting detection. The second test was implemented to assess if specific feature extraction schemes can guarantee high performances with limited complexity of the processing pipeline. Among support vector machine, linear discriminant analysis, and K-nearest neighbours (KNN), the last one showed the best classification performances in the 30-word classification problem, with a mean accuracy of 95% and 85% when using all the features and a specific feature set known as TDAR, respectively. The obtained results confirmed the validity of using combined wrist and forearm EMG data for intelligent handwriting recognition through pattern recognition approaches in real scenarios

A Computer-Aided Screening Solution for the Identification of Diabetic Neuropathy from Standing Balance by Leveraging Multi-Domain Features

The early diagnosis of diabetic neuropathy (DN) is fundamental in order to enact timely therapeutic strategies for limiting disease progression. In this work, we explored the suitability of standing balance task for identifying the presence of DN. Further, we proposed two diagnosis pathways in order to succeed in distinguishing between different stages of the disease. We considered a cohort of non-neuropathic (NN), asymptomatic neuropathic (AN), and symptomatic neuropathic (SN) diabetic patients. From the center of pressure (COP), a series of features belonging to different description domains were extracted. In order to exploit the whole information retrievable from COP, a majority voting ensemble was applied to the output of classifiers trained separately on different COP components. The ensemble of kNN classifiers provided over 86% accuracy for the first diagnosis pathway, made by a 3-class classification task for distinguishing between NN, AN, and SN patients. The second pathway offered higher performances, with over 97% accuracy in identifying patients with symptomatic and asymptomatic neuropathy. Notably, in the last case, no asymptomatic patient went undetected. This work showed that properly leveraging all the information that can be mined from COP trajectory recorded during standing balance is effective for achieving reliable DN identification. This work is a step toward a clinical tool for neuropathy diagnosis, also in the early stages of the disease