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Calo A.,IBEC Institute for Bioengineering of Catalonia | Sanmarti-Espinal M.,IBEC Institute for Bioengineering of Catalonia | Sanmarti-Espinal M.,University of Barcelona | Iavicoli P.,IBEC Institute for Bioengineering of Catalonia | And 7 more authors.
Soft Matter | Year: 2012

Natural vesicles produced from genetically engineered cells with tailored membrane receptor composition are promising building blocks for sensing biodevices. This is particularly true for the case of G-protein coupled receptors (GPCRs) present in many sensing processes in cells, whose functionality crucially depends on their lipid environment. However, the controlled production of natural vesicles containing GPCRs and their reproducible deposition on biosensor surfaces are among the outstanding challenges in the road map to realize practical biomolecular devices based on GPCRs. In this work we present the production and characterization of membrane nanovesicles from Saccharomyces cerevisiae containing heterologously expressed olfactory receptors - a member of the family of GPCRs - and study their deposition onto substrates used as biosensor supports. We show by direct observation with Atomic Force Microscopy that nanovesicles deposit and flatten without rupturing on glass substrates following approximately a diffusive law. We show that surface coverages larger than 20-25% of the substrate can be reproducibly achieved under practical nanovesicle concentrations and reasonable time scales, while keeping to the minimum the presence of background residuals coming from the nanovesicles production process. Surface chemistry modification of gold substrates indicates a higher affinity of natural nanovesicles for acid modified surfaces as compared to amino or alcohol modified surfaces. Present results constitute an important step in the practical realization of biosensor devices based on natural nanovesicles integrating G-protein coupled membrane receptors. This journal is © 2012 The Royal Society of Chemistry.


Gonzalez L.,University of Barcelona | Otero J.,University of Barcelona | Otero J.,IBEC Institute for Bioengineering of Catalonia | Agusil J.P.,IBEC Institute for Bioengineering of Catalonia | And 5 more authors.
Ultramicroscopy | Year: 2014

Quartz tuning fork devices are increasingly being used as nanosensors in Scanning Probe Microscopy. They offer some benefits with respect to standard microfabricated cantilevers in certain experimental setups including the study of biomolecules under physiological conditions. In this work, we compare three different working modes for imaging micropatterned antibodies with quartz tuning fork sensors: apart from the classical amplitude and frequency modulation strategies, for first time the jumping mode is implemented using tuning forks. Our results show that the molecules suffer less degradation when working in the jumping mode, due to the reduction of the interaction forces. © 2013 Elsevier B.V.


Castells X.,Autonomous University of Barcelona | Acebes J.J.,Hospital Universitari Of Bellvitge | Acebes J.J.,Research Center Biomedica en Red en Bioingenieria Biomateriales y Nanomedicina | Majos C.,Lhospitalet Of Llobregat | And 10 more authors.
OMICS A Journal of Integrative Biology | Year: 2015

Glioblastoma (Gb) is one of the most deadly tumors. Its molecular subtypes are yet to be fully characterized while the attendant efforts for personalized medicine need to be intensified in relation to glioblastoma diagnosis, treatment, and prognosis. Several molecular signatures based on gene expression microarrays were reported, but the use of microarrays for routine clinical practice is challenged by attendant economic costs. Several authors have proposed discriminant equations based on RT-PCR. Still, the discriminant threshold is often incompletely described, which makes proper validation difficult. In a previous work, we have reported two Gb subtypes based on the expression levels of four genes: CHI3L1, LDHA, LGALS1, and IGFBP3. One Gb subtype presented with low expression of the four genes mentioned, and of MGMT in a large portion of the patients (with anticipated high methylation of its promoter), and mutated IDH1. Here, we evaluate the robustness of the equations fitted with these genes using RT-PCR values in a set of 64 cases and importantly, define an unequivocal discriminant threshold with a view to prognostic implications. We developed two approaches to generate the discriminant equations: 1) using the expression level of the four genes mentioned above, and 2) using those genes displaying the highest correlation with survival among the aforementioned four ones, plus MGMT, as an attempt to further reduce the number of genes. The ease of equations' applicability, reduction in cost for raw data, and robustness in terms of resampling-based classification accuracy warrant further evaluation of these equations to discern Gb tumor biopsy heterogeneity at molecular level, diagnose potential malignancy, and prognosis of individual patients with glioblastomas. © 2015 Mary Ann Liebert, Inc..


El Halabi F.,Aragon Institute of Engineering Research | El Halabi F.,Research Center Biomedica en Red en Bioingenieria Biomateriales y Nanomedicina | Gonzalez D.,Aragon Institute of Engineering Research | Chico-Roca A.,Ascamm Technology Center | And 3 more authors.
Computer Methods in Applied Mechanics and Engineering | Year: 2013

Multidimensional problems are found in almost every scientific field. In particular, this is standard in parametric design, inverse analysis, in optimization and in metamodeling analysis, whereby statistical or deterministic approximations of multiparametric solutions are built from the results of experimental campaigns or computer simulations. Multidimensional fitting or approximation of response functions exponentially increase their complexity and computational cost with the number of dimensions responding to the well-known " curse of dimensionality" To reduce the order of complexity and make the solution of many-parameter problems affordable, we propose to combine the model reduction technique known as Proper Generalized Decomposition (PGD) and the response surface (RSM) methodology. As a proof of concept we have used a simple fitting procedure as it is least squares, although other more complex fitting procedures may be easily included. The combined algorithm is presented and its capabilities discussed in a set of multidimensional examples. The data samples to be fit in each of these examples are obtained by means of appropriate discretizing the interval of interest for each design factor and then generating the output values (exact or stochastically modified) by means of virtual experiments. To have an idea of the number of discretization points needed along each direction, the Taguchi's design of experiments is used. The obtained results show evident improvements in computer time and accuracy when compared to other traditional multiparametric approximation techniques based on polynomial functions and the standard Levenberg-Marquardt algorithm, especially in problems with non-linear behavior and with high number of design parameters. Further comparison was done with the PARAFAC-ALS algorithm. The combination of PGD and RSM seems to be an appealing tool for accurately modelling multiparametric problems in almost real-time if a sufficient set of previous off-line results is available despite the intrinsic complexity of the problem and of the number of parameters involved. © 2012 Elsevier B.V.


Gonzalez D.,Aragon Institute of Engineering Research | Gonzalez D.,Research Center Biomedica en Red en Bioingenieria Biomateriales y Nanomedicina | Alfaro I.,Aragon Institute of Engineering Research | Alfaro I.,Research Center Biomedica en Red en Bioingenieria Biomateriales y Nanomedicina | And 4 more authors.
Computer Methods in Applied Mechanics and Engineering | Year: 2015

In this paper a novel strategy is presented for the real-time simulation of contact between non-linear deformable solids at haptic feedback rates. The proposed method is somehow related to the Voxmap Pointshell method for two deformable solids. Its novelty and crucial advantages over existing implementations of this algorithm come from the intensive use of computational vademecums. These are in essence a pre-computed solution of a parametric model in which every possible situation during the on-line phase of the method has been considered through the introduction of the appropriate parameters. Such a high-dimensional parametric model is efficiently solved by using Proper Generalized Decompositions (PGD) and stored in memory as a set of vectors. The paper presents a thorough description of the developed algorithm together with some examples of its performance. © 2014 Elsevier B.V.


Hernandez R.C.,Technical University of Madrid | Hernandez R.C.,Research Center Biomedica en Red en Bioingenieria Biomateriales y Nanomedicina | Moreno J.M.M.,Technical University of Madrid | Moreno J.M.M.,Research Center Biomedica en Red en Bioingenieria Biomateriales y Nanomedicina | And 18 more authors.
IFMBE Proceedings | Year: 2011

Neuropsychological Rehabilitation is a complex clinic process which tries to restore or compensate cognitive and behavioral disorders in people suffering from a central nervous system injury. Information and Communication Technologies (ICTs) in Biomedical Engineering play an essential role in this field, allowing improvement and expansion of present rehabilitation programs. This paper presents a set of cognitive rehabilitation 2D-Tasks for patients with Acquired Brain Injury (ABI). These tasks allow a high degree of personalization and individualization in therapies, based on the opportunities offered by new technologies. © 2011 Springer-Verlag Berlin Heidelberg.


Esquivel J.P.,CSIC - National Center of Microelectronics | Colomer-Farrarons J.,University of Barcelona | Castellarnau M.,Massachusetts Institute of Technology | Salleras M.,CSIC - National Center of Microelectronics | And 6 more authors.
Lab on a Chip - Miniaturisation for Chemistry and Biology | Year: 2012

The present paper reports for the first time the integration of a microfluidic system, electronics modules, amperometric sensor and display, all powered by a single micro direct methanol fuel cell. In addition to activating the electronic circuitry, the integrated power source also acts as a tuneable micropump. The electronics fulfil several functions. First, they regulate the micro fuel cell output power, which off-gas controls the flow rate of different solutions toward an electrochemical sensor through microfluidic channels. Secondly, as the fuel cell powers a three-electrode electrochemical cell, the electronics compare the working electrode output signal with a set reference value. Thirdly, if the concentration measured by the sensor exceeds this threshold value, the electronics switch on an integrated organic display. This integrated approach pushes forward the development of truly autonomous point-of-care devices relying on electrochemical detection. © 2012 The Royal Society of Chemistry.

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