939 resultados para Microarray electrodes
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In the present work, the development of a genosensor for the event-specific detection of MON810 transgenic maize is proposed. Taking advantage of nanostructuration, a cost-effective three dimensional electrode was fabricated and a ternary monolayer containing a dithiol, a monothiol and the thiolated capture probe was optimized to minimize the unspecific signals. A sandwich format assay was selected as a way of precluding inefficient hybridization associated with stable secondary target structures. A comparison between the analytical performance of the Au nanostructured electrodes and commercially available screen-printed electrodes highlighted the superior performance of the nanostructured ones. Finally, the genosensor was effectively applied to detect the transgenic sequence in real samples, showing its potential for future quantitative analysis.
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A new environmentally friendly Au nanoparticles (Au NPs) synthesis in glycerol by using ultraviolet irradiation and without extra-added stabilizers is described. The synthesis proposed in this work may impact on the non-polluting production of noble nanoparticles with simple chemicals normally found in standard laboratories. These Au NPs were used to modify a carbon paste electrode (CPE) without having to separate them from the reaction medium. This green electrode was used as an electrochemical sensor for the nitrite detection in water. At the optimum conditions the green sensor presented a linear response in the 2.0×10−7–1.5×10−5 M concentration range, a good detection sensitivity (0.268 A L mol−1), and a low detection limit of 2.0×10−7 M of nitrite. The proposed modified green CPE was used to determine nitrite in tap water samples.
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J Biol Inorg Chem. 2008 Jun;13(5):779-87. doi: 10.1007/s00775-008-0365-8
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The MAP-i Doctoral Program of the Universities of Minho, Aveiro and Porto
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Electroactive polymers are one of the most interesting class of polymers used as smart materials in various applications, such as the development of sensors and actuators for biomedical applications in areas such as smart prosthesis, implantable biosensors and biomechanical signal monitoring, among others. For acquiring or applying the electrical signal from/to the piezoelectric material, suitable electrodes can be produced from Ti based coatings with tailored multifunctional properties, conductivity and antibacterial characteristics, through Ag inclusions. This work reports on Ag-TiNx electrodes, deposited by d. c. and pulsed magnetron sputtering at room temperature on poly(vinylidene fluoride), PVDF, the all-round best piezoelectric polymer.. Composition of the electrodes was assessed by microanalysis X-ray system (EDS - energy dispersive spectrometer). The XRD results revealed that the deposition conditions preserve the polymer structure and suggested the presence of crystalline fcc-TiN phase and fcc-Ag phase in samples with N2 flow above 3 sccm. According to the results obtained from SEM analysis, the coatings are homogeneous and Ag clusters were found for samples with nitrogen flow above 3 sccm. With increasing nitrogen flow, the sheet resistivity tend to be lower than the samples without nitrogen, leading also to a decrease of the piezoelectric response. It is concluded that the deposition conditions do significantly affect the piezoelectric polymer, which maintain its characteristics for sensor/actuator applications.
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Polycrystalline AlN coatings deposited on Ti-electrodes films were sputtered by using nitrogen both as reactive gas and sputtering gas, in order to obtain high purity coatings with appropriate properties to be further integrated into wear resistance coatings as a piezoelectric monitoring wear sensor. The chemical composition, the structure and the morphology of the films were investigated by X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy and atomic force microscopy techniques. These measurements show the formation of highly (101), (102) and (103) oriented AlN films with good piezoelectric and mechanical properties suitable for applications in electronic devices. Through the use of lower nitrogen flow a densification of the AlN coating occurs in the microstructure, with an improvement of the crystallinity along with the increase of the hardness. Thermal stability of aluminum nitride coatings at high temperature was also examined. It was found an improvement of the piezoelectric properties of the highly (10x) oriented AlN films which became c-axis (002) oriented after annealing. The mechanical behavior after heat treatment shows an important enhancement of the surface hardness and Young’s modulus, which decrease rapidly with the increase of the indentation depth until approach constant values close to the substrate properties after annealing. Thus, thermal annealing energy promotes not only the rearrangement of Al–N network, but also the occurrence of a nitriding process of unsaturated Al atoms which cause a surface hardening of the film.
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DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus.
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Poly(dimethylsiloxane) (PDMS) is an organosilicon polymer widely used in the fabrication of microfluidic systems to integrate biochips. In this study, we propose the use of an adapted PDMS mould for the creation of a miniaturized, reusable, reference electrode for in-chip electrochemical measurements. Through its integrated microfluidic system it is possible to replenish internal buffer solutions, unclog critical junctions and treat the electrode’s surface, assuring a long term reuse of the same device. Planar Ag/AgCl reference electrodes were microfabricated over a passivated p-type Silicon Wafer. The PDMS mould, containing an integrated microfluidic system, was fabricated based on patterned SU-8 mould, which includes a lateral horizontal inlet access point. Surface oxidation was used for irreversible permanent bondage between flat surfaces. The final result was planar Ag/AgCl reference electrode with integrated microfluidic that allows for electrochemical analysis in biochips
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MOTIVATION: Microarray results accumulated in public repositories are widely reused in meta-analytical studies and secondary databases. The quality of the data obtained with this technology varies from experiment to experiment, and an efficient method for quality assessment is necessary to ensure their reliability. RESULTS: The lack of a good benchmark has hampered evaluation of existing methods for quality control. In this study, we propose a new independent quality metric that is based on evolutionary conservation of expression profiles. We show, using 11 large organ-specific datasets, that IQRray, a new quality metrics developed by us, exhibits the highest correlation with this reference metric, among 14 metrics tested. IQRray outperforms other methods in identification of poor quality arrays in datasets composed of arrays from many independent experiments. In contrast, the performance of methods designed for detecting outliers in a single experiment like Normalized Unscaled Standard Error and Relative Log Expression was low because of the inability of these methods to detect datasets containing only low-quality arrays and because the scores cannot be directly compared between experiments. AVAILABILITY AND IMPLEMENTATION: The R implementation of IQRray is available at: ftp://lausanne.isb-sib.ch/pub/databases/Bgee/general/IQRray.R. CONTACT: Marta.Rosikiewicz@unil.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Cheap and massively parallel methods to assess the DNA-binding specificity of transcription factors are actively sought, given their prominent regulatory role in cellular processes and diseases. Here we evaluated the use of protein-binding microarrays (PBM) to probe the association of the tumor suppressor AP2α with 6000 human genomic DNA regulatory sequences. We show that the PBM provides accurate relative binding affinities when compared to quantitative surface plasmon resonance assays. A PBM-based study of human healthy and breast tumor tissue extracts allowed the identification of previously unknown AP2α target genes and it revealed genes whose direct or indirect interactions with AP2α are affected in the diseased tissues. AP2α binding and regulation was confirmed experimentally in human carcinoma cells for novel target genes involved in tumor progression and resistance to chemotherapeutics, providing a molecular interpretation of AP2α role in cancer chemoresistance. Overall, we conclude that this approach provides quantitative and accurate assays of the specificity and activity of tumor suppressor and oncogenic proteins in clinical samples, interfacing genomic and proteomic assays.
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Background: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e. g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones. Results: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/similar to vpopovic/research/ Conclusion: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable.
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Profiling miRNA levels in cells with miRNA microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. We have developed a method to select nonchanging miRNAs (invariants) and use them to compute linear regression normalization coefficients or variance stabilizing normalization (VSN) parameters. We compared the invariants normalization to normalization by scaling, quantile, and VSN with default parameters as well as to no normalization using samples with strong differential expression of miRNAs (heart-brain comparison) and samples where only a few miRNAs are affected (by p53 overexpression in squamous carcinoma cells versus control). All normalization methods performed better than no normalization. Normalization procedures based on the set of invariants and quantile were the most robust over all experimental conditions tested. Our method of invariant selection and normalization is not limited to Agilent miRNA arrays and can be applied to other data sets including those from one color miRNA microarray platforms, focused gene expression arrays, and gene expression analysis using quantitative PCR.
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Aim: The adrenolytic agent mitotane is widely used in the treatment of adrenocortical cancer; however, its mechanism of action is poorly elucidated. We have studied mitotane-induced mRNA expression changes in the NCI-H295R adrenocortical cancer cell line. Materials & methods: Cell viability and hormone assays were used to select the optimal mitotane concentration effectively inhibiting hormone secretion without affecting cell viability. RNA isolated from cultures treated for 48 and 72 h was subjected to Agilent 4×44K microarray platforms. Microarray results were validated by quantitative reverse-transcription PCR. Results: Altogether, 117 significantly differentially expressed genes were detected at 48 h and 72 h (p < 0.05) in mitotane-treated samples relative to controls. Three significantly underexpressed genes involved in steroid hormone biosynthesis (HSD3B1, HSD3B2 and CYP21A2) and four significantly overexpressed genes (GDF15, ALDH1L2, TRIB3 and SERPINE2) have been validated. Conclusion: Gene-expression changes might be involved in the adrenal action of mitotane and in the inhibition of hormone secretion. Original submitted 20 January 2012; Revision submitted 17 May 2012.
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Cross-reactivity of plant foods is an important phenomenon in allergy, with geographical variations with respect to the number and prevalence of the allergens involved in this process, whose complexity requires detailed studies. We have addressed the role of thaumatin-like proteins (TLPs) in cross-reactivity between fruit and pollen allergies. A representative panel of 16 purified TLPs was printed onto an allergen microarray. The proteins selected belonged to the sources most frequently associated with peach allergy in representative regions of Spain. Sera from two groups of well characterized patients, one with allergy to Rosaceae fruit (FAG) and another against pollens but tolerant to food-plant allergens (PAG), were obtained from seven geographical areas with different environmental pollen profiles. Cross-reactivity between members of this family was demonstrated by inhibition assays. Only 6 out of 16 purified TLPs showed noticeable allergenic activity in the studied populations. Pru p 2.0201, the peach TLP (41%), chestnut TLP (24%) and plane pollen TLP (22%) proved to be allergens of probable relevance to fruit allergy, being mainly associated with pollen sensitization, and strongly linked to specific geographical areas such as Barcelona, Bilbao, the Canary Islands and Madrid. The patients exhibited >50% positive response to Pru p 2.0201 and to chestnut TLP in these specific areas. Therefore, their recognition patterns were associated with the geographical area, suggesting a role for pollen in the sensitization of these allergens. Finally, the co-sensitizations of patients considering pairs of TLP allergens were analyzed by using the co-sensitization graph associated with an allergen microarray immunoassay. Our data indicate that TLPs are significant allergens in plant food allergy and should be considered when diagnosing and treating pollen-food allergy.
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The study of cross-reactivity in allergy is key to both understanding. the allergic response of many patients and providing them with a rational treatment In the present study, protein microarrays and a co-sensitization graph approach were used in conjunction with an allergen microarray immunoassay. This enabled us to include a wide number of proteins and a large number of patients, and to study sensitization profiles among members of the LTP family. Fourteen LTPs from the most frequent plant food-induced allergies in the geographical area studied were printed into a microarray specifically designed for this research. 212 patients with fruit allergy and 117 food-tolerant pollen allergic subjects were recruited from seven regions of Spain with different pollen profiles, and their sera were tested with allergen microarray. This approach has proven itself to be a good tool to study cross-reactivity between members of LTP family, and could become a useful strategy to analyze other families of allergens.