Mechanical fatigue performance of PCL-chondroprogenitor constructs after cell culture under bioreactor mechanical stimulus

In tissue engineering of cartilage, polymeric scaffolds are implanted in the damaged tissue and subjected to repeated compression loading cycles. The possibility of failure due to mechanical fatigue has not been properly addressed in these scaffolds. Nevertheless, the macroporous scaffold is susceptible to failure after repeated loading-unloading cycles. This is related to inherent discontinuities in the material due to the micropore structure of the macro-pore walls that act as stress concentration points. In this work, chondrogenic precursor cells have been seeded in Poly-ε-caprolactone (PCL) scaffolds with fibrin and some were submitted to free swelling culture and others to cyclic loading in a bioreactor. After cell culture, all the samples were analyzed for fatigue behavior under repeated loading-unloading cycles. Moreover, some components of the extracellular matrix (ECM) were identified. No differences were observed between samples undergoing free swelling or bioreactor loading conditions, neither respect to matrix components nor to mechanical performance to fatigue. The ECM did not achieve the desired preponderance of collagen type II over collagen type I which is considered the main characteristic of hyaline cartilage ECM. However, prediction in PCL with ECM constructs was possible up to 600 cycles, an enhanced performance when compared to previous works. PCL after cell culture presents an improved fatigue resistance, despite the fact that the measured elastic modulus at the first cycle was similar to PCL with poly(vinyl alcohol) samples. This finding suggests that fatigue analysis in tissue engineering constructs can provide additional information missed with traditional mechanical measurements.

In vitro mechanical fatigue behavior of poly-ε-caprolactone macroporous scaffolds for cartilage tissue engineering: Influence of pore filling by a poly(vinyl alcohol) gel

Polymeric scaffolds used in regenerative therapies are implanted in the damaged tissue and subjected to repeated loading cycles. In the case of articular cartilage engineering, an implanted scaffold is typically subjected to long term dynamic compression. The evolution of the mechanical properties of the scaffold during bioresorption has been deeply studied in the past, but the possibility of failure due to mechanical fatigue has not been properly addressed. Nevertheless, the macroporous scaffold is susceptible to failure after repeated loading-unloading cycles. In this work fatigue studies of polycaprolactone scaffolds were carried by subjecting the scaffold to repeated compression cycles in conditions simulating the scaffold implanted in the articular cartilage. The behaviour of the polycaprolactone sponge with the pores filled with a poly(vinyl alcohol) gel simulating the new formed tissue within the pores was compared with that of the material immersed in water. Results were analyzed with Morrow’s criteria for failure and accurate fittings are obtained just up to 200 loading cycles. It is also shown that the presence of poly(vinyl alcohol) increases the elastic modulus of the scaffolds, the effect being more pronounced with increasing the number of freeze/thawing cycles.

Erratum: Influence of oxygen plasma treatment parameters on poly(vinylidene fluoride) electrospun fiber mats wettability

Electrospun poly(vinylidene fluoride) (PVDF) fiber mats find applications in an increasing number of areas, such as battery separators, filtration and detection membranes, due to their excellent properties. However, there are limitations due to the hydrophobic nature and low surface energy of PVDF. In this work, oxygen plasma treatment has been applied in order to modify the surface wettability of PVDF fiber mats and superhydrophilic PVDF electrospun membranes have been obtained. Further, plasma treatment does not significantly influences fiber average size (~400 ± 200 nm), morphology, electroactive -phase content (~80-85%) or the degree of crystallinity (Xc of 42 ± 2%), allowing to maintain the excellent physical-chemical characteristics of PVDF. Plasma treatment mainly induces surface chemistry modifications, such as the introduction of oxygen and release of fluorine atoms that significantly changes polymer membrane wettability by a reduction of the contact angle of the polymer fibers and an overall decrease of the surface tension of the membranes.

Bacterial cellulose-lactoferrin as an antimicrobial edible packaging

Bacterial cellulose (BC) films from two distinct sources (obtained by static culture with Gluconacetobacter xylinus ATCC 53582 (BC1) and from a commercial source (BC2)) were modified by bovine lactoferrin (bLF) adsorption. The functionalized films (BC+bLF) were assessed as edible antimicrobial packaging, for use in direct contact with highly perishable foods, specifically fresh sausage as a model of meat products. BC+bLF films and sausage casings were characterized regarding their water vapour permeability (WVP), mechanical properties, and bactericidal efficiency against two food pathogens, Escherichia coli and Staphylococcus aureus. Considering their edibility, an in vitro gastrointestinal tract model was used to study the changes occurring in the BC films during passage through the gastrointestinal tract. Moreover, the cytotoxicity of the BC films against 3T3 mouse embryo fibroblasts was evaluated. BC1 and BC2 showed equivalent density, WVP and maximum tensile strength. The percentage of bactericidal efficiency of BC1 and BC2 with adsorbed bLF (BC1+bLF and BC2+bLF, respectively) in the standalone films and in inoculated fresh sausages, was similar against E. coli (mean reduction 69 % in the films per se versus 94 % in the sausages) and S. aureus (mean reduction 97 % in the films per se versus 36 % in the case sausages). Moreover, the BC1+bLF and BC2+bLF films significantly hindered the specific growth rate of both bacteria. Finally, no relevant cytotoxicity against 3T3 fibroblasts was found for the films before and after the simulated digestion. BC films with adsorbed bLF may constitute an approach in the development of bio-based edible antimicrobial packaging systems.

Automatic Recognition of Leaves by Shape Detection Pre-Processing with Ica

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used to characterize the leaves. Independent Component Analysis (ICA) is then applied in order to study which is the best number of components to be considered for the classification task, implemented by means of an Artificial Neural Network (ANN). Obtained results with ICA as a pre-processing tool are satisfactory, and compared with some references our system improves the recognition success up to 80.8% depending on the number of considered independent components.

Coherency and sharpness measures by using ICA algorithms. An investigation for Alzheimer’s disease discrimination

In this paper, we present a comprehensive study of different Independent Component Analysis (ICA) algorithms for the calculation of coherency and sharpness of electroencephalogram (EEG) signals, in order to investigate the possibility of early detection of Alzheimer’s disease (AD). We found that ICA algorithms can help in the artifact rejection and noise reduction, improving the discriminative property of features in high frequency bands (specially in high alpha and beta ranges). In addition to different ICA algorithms, the optimum number of selected components is investigated, in order to help decision processes for future works.

Investigation of ICA algorithms for feature extraction of EEG signals in discrimination of Alzheimer disease

In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.

Differences of Functional Connectivity Brain Network in Emotional Judgment

Using combined emotional stimuli, combining photos of faces and recording of voices, we investigated the neural dynamics of emotional judgment using scalp EEG recordings. Stimuli could be either combioned in a congruent, or a non-congruent way.. As many evidences show the major role of alpha in emotional processing, the alpha band was subjected to be analyzed. Analysis was performed by computing the synchronization of the EEGs and the conditions congruent vs. non-congruent were compared using statistical tools. The obtained results demonstrate that scalp EEG ccould be used as a tool to investigate the neural dynamics of emotional valence and discriminate various emotions (angry, happy and neutral stimuli).

Parameterization of written signatures based on EFD

In this work we propose a method to quantify written signatures from digitalized images based on the use of Elliptical Fourier Descriptors (EFD). As usually signatures are not represented as a closed contour, and being that a necessary condition in order to apply EFD, we have developed a method that represents the signatures by means of a set of closed contours. One of the advantages of this method is that it can reconstruct the original shape from all the coefficients, or an approximated shape from a reduced set of them finding the appropriate number of EFD coefficients required for preserving the important information in each application. EFD provides accurate frequency information, thus the use of EFD opens many possibilities. The method can be extended to represent other kind of shapes.

Empirical mode decomposition-based face recognition system

In this work we explore the multivariate empirical mode decomposition combined with a Neural Network classifier as technique for face recognition tasks. Images are simultaneously decomposed by means of EMD and then the distance between the modes of the image and the modes of the representative image of each class is calculated using three different distance measures. Then, a neural network is trained using 10- fold cross validation in order to derive a classifier. Preliminary results (over 98 % of classification rate) are satisfactory and will justify a deep investigation on how to apply mEMD for face recognition.

Emergence of oriented circuits driven by synaptic pruning associated with spike-timing-dependent plasticity (STDP)

ABSTRACT: Massive synaptic pruning following over-growth is a general feature of mammalian brain maturation. Pruning starts near time of birth and is completed by time of sexual maturation. Trigger signals able to induce synaptic pruning could be related to dynamic functions that depend on the timing of action potentials. Spike-timing-dependent synaptic plasticity (STDP) is a change in the synaptic strength based on the ordering of pre- and postsynaptic spikes. The relation between synaptic efficacy and synaptic pruning suggests that the weak synapses may be modified and removed through competitive "learning" rules. This plasticity rule might produce the strengthening of the connections among neurons that belong to cell assemblies characterized by recurrent patterns of firing. Conversely, the connections that are not recurrently activated might decrease in efficiency and eventually be eliminated. The main goal of our study is to determine whether or not, and under which conditions, such cell assemblies may emerge out of a locally connected random network of integrate-and-fire units distributed on a 2D lattice receiving background noise and content-related input organized in both temporal and spatial dimensions. The originality of our study stands on the relatively large size of the network, 10,000 units, the duration of the experiment, 10E6 time units (one time unit corresponding to the duration of a spike), and the application of an original bio-inspired STDP modification rule compatible with hardware implementation. A first batch of experiments was performed to test that the randomly generated connectivity and the STDP-driven pruning did not show any spurious bias in absence of stimulation. Among other things, a scale factor was approximated to compensate for the network size on the ac¬tivity. Networks were then stimulated with the spatiotemporal patterns. The analysis of the connections remaining at the end of the simulations, as well as the analysis of the time series resulting from the interconnected units activity, suggest that feed-forward circuits emerge from the initially randomly connected networks by pruning. RESUME: L'élagage massif des synapses après une croissance excessive est une phase normale de la ma¬turation du cerveau des mammifères. L'élagage commence peu avant la naissance et est complété avant l'âge de la maturité sexuelle. Les facteurs déclenchants capables d'induire l'élagage des synapses pourraient être liés à des processus dynamiques qui dépendent de la temporalité rela¬tive des potentiels d'actions. La plasticité synaptique à modulation temporelle relative (STDP) correspond à un changement de la force synaptique basé sur l'ordre des décharges pré- et post- synaptiques. La relation entre l'efficacité synaptique et l'élagage des synapses suggère que les synapses les plus faibles pourraient être modifiées et retirées au moyen d'une règle "d'appren¬tissage" faisant intervenir une compétition. Cette règle de plasticité pourrait produire le ren¬forcement des connexions parmi les neurones qui appartiennent à une assemblée de cellules caractérisée par des motifs de décharge récurrents. A l'inverse, les connexions qui ne sont pas activées de façon récurrente pourraient voir leur efficacité diminuée et être finalement éliminées. Le but principal de notre travail est de déterminer s'il serait possible, et dans quelles conditions, que de telles assemblées de cellules émergent d'un réseau d'unités integrate-and¬-fire connectées aléatoirement et distribuées à la surface d'une grille bidimensionnelle recevant à la fois du bruit et des entrées organisées dans les dimensions temporelle et spatiale. L'originalité de notre étude tient dans la taille relativement grande du réseau, 10'000 unités, dans la durée des simulations, 1 million d'unités de temps (une unité de temps correspondant à une milliseconde), et dans l'utilisation d'une règle STDP originale compatible avec une implémentation matérielle. Une première série d'expériences a été effectuée pour tester que la connectivité produite aléatoirement et que l'élagage dirigé par STDP ne produisaient pas de biais en absence de stimu¬lation extérieure. Entre autres choses, un facteur d'échelle a pu être approximé pour compenser l'effet de la variation de la taille du réseau sur son activité. Les réseaux ont ensuite été stimulés avec des motifs spatiotemporels. L'analyse des connexions se maintenant à la fin des simulations, ainsi que l'analyse des séries temporelles résultantes de l'activité des neurones, suggèrent que des circuits feed-forward émergent par l'élagage des réseaux initialement connectés au hasard.

ICA Cleaning procedure for EEG signals analysis: application to Alzheimer's disease detection

To develop systems in order to detect Alzheimer’s disease we want to use EEG signals. Available database is raw, so the first step must be to clean signals properly. We propose a new way of ICA cleaning on a database recorded from patients with Alzheimer's disease (mildAD, early stage). Two researchers visually inspected all the signals (EEG channels), and each recording's least corrupted (artefact-clean) continuous 20 sec interval were chosen for the analysis. Each trial was then decomposed using ICA. Sources were ordered using a kurtosis measure, and the researchers cleared up to seven sources per trial corresponding to artefacts (eye movements, EMG corruption, EKG, etc), using three criteria: (i) Isolated source on the scalp (only a few electrodes contribute to the source), (ii) Abnormal wave shape (drifts, eye blinks, sharp waves, etc.), (iii) Source of abnormally high amplitude ( �100 �V). We then evaluated the outcome of this cleaning by means of the classification of patients using multilayer perceptron neural networks. Results are very satisfactory and performance is increased from 50.9% to 73.1% correctly classified data using ICA cleaning procedure.

Population ageing and ICT: An exploratory review of technology innovation trough digital applications

The multidimensional process of physical, psychological, and social change produced by population ageing affects not only the quality of life of elderly people but also of our societies. Some dimensions of population ageing grow and expand over time (e.g. knowledge of the world events, or experience in particular situations), while others decline (e.g. reaction time, physical and psychological strength, or other functional abilities like reduced speed and tiredness). Information and Communication Technologies (ICTs) can help elderly to overcome possible limitations due to ageing. As a particular case, biometrics can allow the development of new algorithms for early detection of cognitive impairments, by processing continuous speech, handwriting or other challenged abilities. Among all possibilities, digital applications (Apps) for mobile phones or tablets can allow the dissemination of such tools. In this article, after presenting and discussing the process of population ageing and its social implications, we explore how ICTs through different Apps can lead to new solutions for facing this major demographic challenge.

A Preliminary Review of Behavioural Biometrics for Health Monitoring in the Elderly

This article explores the potential of ICT-based biometrics for monitoring the health status of the elderly people. It departs from specific ageing and biometric traits to then focus on behavioural biometric traits like handwriting, speech and gait to finally explore their practical application in health monitoring of elderly.