939 resultados para Microarray electrodes
Resumo:
Att övervaka förekomsten av giftiga komponenter i naturliga vattendrag är nödvändigt för människans välmående. Eftersom halten av föroreningar i naturens ekosystem bör hållas möjligast låg, pågår en ständig jakt efter kemiska analysmetoder med allt lägre detektionsgränser. I dagens läge görs miljöanalyser med dyr och sofistikerad instrumentering som kräver mycket underhåll. Jonselektiva elektroder har flera goda egenskaper som t.ex. bärbarhet, låg energiförbrukning, och dessutom är de relativt kostnadseffektiva. Att använda jonselektiva elektroder vid miljöanalyser är möjligt om deras känslighetsområde kan utvidgas genom att sänka deras detektionsgränser. För att sänka detektionsgränsen för Pb(II)-selektiva elektroder undersöktes olika typer av jonselektiva membran som baserades på polyakrylat-kopolymerer, PVC och PbS/Ag2S. Fast-fas elektroder med membran av PbS/Ag2S är i allmänhet enklare och mer robusta än konventionella elektroder vid spårämnesanalys av joniska föroreningar. Fast-fas elektrodernas detektionsgräns sänktes i detta arbete med en nyutvecklad galvanostatisk polariseringsmetod och de kunde sedan framgångsrikt användas för kvantitativa bestämningar av bly(II)-halter i miljöprov som hade samlats in i den finska skärgården nära tidigare industriområden. Analysresultaten som erhölls med jonselektiva elektroder bekräftades med andra analytiska metoder. Att sänka detektionsgränsen m.hj.a. den nyutvecklade polariseringsmetoden möjliggör bestämning av låga och ultra-låga blyhalter som inte kunde nås med klassisk potentiometri. Den verkliga fördelen med att använda dessa blyselektiva elektroder är möjligheten att utföra mätningar i obehandlade miljöprov trots närvaron av fasta partiklar vilket inte är möjligt att göra med andra analysmetoder. Jag väntar mig att den nyutvecklade polariseringsmetoden kommer att sätta en trend i spårämnesanalys med jonselektiva elektroder.
Resumo:
Electrochemical double-layer supercapacitors have an intermediate position between rechargeable batteries, which can store high amounts of energy, and dielectric capacitors, which have high output power. Supercapacitors are widely suggested to be used in automobiles (recuperation during braking, facilitate engine starting, electric stabilization of the system), industry (forklifts, elevators), hybrid off-road machinery and also in consumer electronics. Supercapacitor electrodes require highly porous material. Typically, activated carbon is used. Specific surface area of activated carbon is approximately 1000 m2 per gram. Carbon nanotubes represent one of prospective materials. According to numerous studies this material allows to improve the properties of supercapacitors. The task of this Master‘s Thesis was to test multiwalled carbon nanotubes and become confident with the testing methods.
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cDNA microarray is an innovative technology that facilitates the analysis of the expression of thousands of genes simultaneously. The utilization of this methodology, which is rapidly evolving, requires a combination of expertise from the biological, mathematical and statistical sciences. In this review, we attempt to provide an overview of the principles of cDNA microarray technology, the practical concerns of the analytical processing of the data obtained, the correlation of this methodology with other data analysis methods such as immunohistochemistry in tissue microarrays, and the cDNA microarray application in distinct areas of the basic and clinical sciences.
Resumo:
Potentiometric sensors are very attractive tools for chemical analysis because of their simplicity, low power consumption and low cost. They are extensively used in clinical diagnostics and in environmental monitoring. Modern applications of both fields require improvements in the conventional construction and in the performance of the potentiometric sensors, as the trends are towards portable, on-site diagnostics and autonomous sensing in remote locations. The aim of this PhD work was to improve some of the sensor properties that currently hamper the implementation of the potentiometric sensors in modern applications. The first part of the work was concentrated on the development of a solid-state reference electrode (RE) compatible with already existing solid-contact ion-selective electrodes (ISE), both of which are needed for all-solid-state potentiometric sensing systems. A poly(vinyl chloride) membrane doped with a moderately lipophilic salt, tetrabutylammonium-tetrabutylborate (TBA-TBB), was found to show a satisfactory stability of potential in sample solutions with different concentrations. Its response time was nevertheless slow, as it required several minutes to reach the equilibrium. The TBA-TBB membrane RE worked well together with solid-state ISEs in several different situations and on different substrates enabling a miniature design. Solid contacts (SC) that mediate the ion-to-electron transduction are crucial components of well-functioning potentiometric sensors. This transduction process converting the ionic conduction of an ion-selective membrane to the electronic conduction in the circuit was studied with the help of electrochemical impedance spectroscopy (EIS). The solid contacts studied were (i) the conducting polymer (CP) poly(3,4-ethylienedioxythiophene) (PEDOT) and (ii) a carbon cloth having a high surface area. The PEDOT films were doped with a large immobile anion poly(styrene sulfonate) (PSS-) or with a small mobile anion Cl-. As could be expected, the studied PEDOT solid-contact mediated the ion-toelectron transduction more efficiently than the bare glassy carbon substrate, onto which they were electropolymerized, while the impedance of the PEDOT films depended on the mobility of the doping ion and on the ions in the electrolyte. The carbon cloth was found to be an even more effective ion-to-electron transducer than the PEDOT films and it also proved to work as a combined electrical conductor and solid contact when covered with an ion-selective membrane or with a TBA-TBB-based reference membrane. The last part of the work was focused on improving the reproducibility and the potential stability of the SC-ISEs, a problem that culminates to the stability of the standard potential E°. It was proven that the E° of a SC-ISE with a conducting polymer as a solid contact could be adjusted by reducing or oxidizing the CP solid contact by applying current pulses or a potential to it, as the redox state of the CP solid-contact influences the overall potential of the ISE. The slope and thus the analytical performance of the SC-ISEs were retained despite the adjustment of the E°. The shortcircuiting of the SC-ISE with a conventional large-capacitance RE was found to be a feasible instrument-free method to control the E°. With this method, the driving force for the oxidation/reduction of the CP was the potential difference between the RE and the SC-ISE, and the position of the adjusted potential could be controlled by choosing a suitable concentration for the short-circuiting electrolyte. The piece-to-piece reproducibility of the adjusted potential was promising, and the day-today reproducibility for a specific sensor was excellent. The instrumentfree approach to control the E° is very attractive considering practical applications.
Resumo:
The pipeline for macro- and microarray analyses (PMmA) is a set of scripts with a web interface developed to analyze DNA array data generated by array image quantification software. PMmA is designed for use with single- or double-color array data and to work as a pipeline in five classes (data format, normalization, data analysis, clustering, and array maps). It can also be used as a plugin in the BioArray Software Environment, an open-source database for array analysis, or used in a local version of the web service. All scripts in PMmA were developed in the PERL programming language and statistical analysis functions were implemented in the R statistical language. Consequently, our package is a platform-independent software. Our algorithms can correctly select almost 90% of the differentially expressed genes, showing a superior performance compared to other methods of analysis. The pipeline software has been applied to 1536 expressed sequence tags macroarray public data of sugarcane exposed to cold for 3 to 48 h. PMmA identified thirty cold-responsive genes previously unidentified in this public dataset. Fourteen genes were up-regulated, two had a variable expression and the other fourteen were down-regulated in the treatments. These new findings certainly were a consequence of using a superior statistical analysis approach, since the original study did not take into account the dependence of data variability on the average signal intensity of each gene. The web interface, supplementary information, and the package source code are available, free, to non-commercial users at http://ipe.cbmeg.unicamp.br/pub/PMmA.
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Ropinirole (ROP) is a dopamine agonist that has been used as therapy for Parkinson's disease. In the present study, we aimed to detect whether gene expression was modulated by ROP in SH-SY5Y cells. SH-SY5Y cell lines were treated with 10 µM ROP for 2 h, after which total RNA was extracted for whole genome analysis. Gene expression profiling revealed that 113 genes were differentially expressed after ROP treatment compared with control cells. Further pathway analysis revealed modulation of the phosphatidylinositol 3-kinase (PI3K) signaling pathway, with prominent upregulation of PIK3C2B. Moreover, batches of regulated genes, including PIK3C2B, were found to be located on chromosome 1. These findings were validated by quantitative RT-PCR and Western blot analysis. Our study, therefore, revealed that ROP altered gene expression in SH-SY5Y cells, and future investigation of PIK3C2B and other loci on chromosome 1 may provide long-term implications for identifying novel target genes of Parkinson's disease.
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The recent rapid development of biotechnological approaches has enabled the production of large whole genome level biological data sets. In order to handle thesedata sets, reliable and efficient automated tools and methods for data processingand result interpretation are required. Bioinformatics, as the field of studying andprocessing biological data, tries to answer this need by combining methods and approaches across computer science, statistics, mathematics and engineering to studyand process biological data. The need is also increasing for tools that can be used by the biological researchers themselves who may not have a strong statistical or computational background, which requires creating tools and pipelines with intuitive user interfaces, robust analysis workflows and strong emphasis on result reportingand visualization. Within this thesis, several data analysis tools and methods have been developed for analyzing high-throughput biological data sets. These approaches, coveringseveral aspects of high-throughput data analysis, are specifically aimed for gene expression and genotyping data although in principle they are suitable for analyzing other data types as well. Coherent handling of the data across the various data analysis steps is highly important in order to ensure robust and reliable results. Thus,robust data analysis workflows are also described, putting the developed tools andmethods into a wider context. The choice of the correct analysis method may also depend on the properties of the specific data setandthereforeguidelinesforchoosing an optimal method are given. The data analysis tools, methods and workflows developed within this thesis have been applied to several research studies, of which two representative examplesare included in the thesis. The first study focuses on spermatogenesis in murinetestis and the second one examines cell lineage specification in mouse embryonicstem cells.
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Dipyrromethene-Cu(II) derivatives possessing two dodecane alkyl chains have been used for the modification of gold electrodes. Electroactive host molecules have been incorporated into a lipophilic dodecanethiol SAM deposited onto gold electrodes through hydrophobic and van der Waals interactions (embedment technique). The presence of dipyrromethene-Cu(II) redox centers on the electrode surface was proved by cyclic voltammetry and Osteryoung square-wave voltammetry. The Au electrodes incorporating redox active Cu(II)-dipyrromethene SAMs were used for the direct voltammetric determination of paracetamol in human plasma.
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The main objective of this thesis work is to optimize the growth conditions for obtaining crystalline and conducting Lao.5Sro.5Co03 (LSCO) and Lao.5Sro.5Coo.5.5Nio.5O3 (LSCNO) thin films at low processing temperatures. The films are prepared by radio frequency magnetron sputtering under various deposition conditions. The thin films were used as electrodes for the fabrication of ferroelectric capacitors using BaO.7SrO.3 Ti03 (BST) and PbZro.52 Tio.4803 (PZT). The structural and transport properties of the La1_xSrxCo03 and Lao.5Sro.5Co1_xNix03 are also investigated. The characterization of the bulk and the thin films were performed using different tools. A powder X-ray diffractometer was used to analyze the crystalline nature of the material. The transport properties were investigated by measuring the temperature dependence of resistivity using a four probe technique. The magnetoresistance and thermoelectric power were also used to investigate the transport properties. Atomic force microscope was used to study the surface morphology and thin film roughness. The ferroelectric properties of the capacitors were investigated using RT66A ferroelectric tester.
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In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.
Resumo:
As the technologies for the fabrication of high quality microarray advances rapidly, quantification of microarray data becomes a major task. Gridding is the first step in the analysis of microarray images for locating the subarrays and individual spots within each subarray. For accurate gridding of high-density microarray images, in the presence of contamination and background noise, precise calculation of parameters is essential. This paper presents an accurate fully automatic gridding method for locating suarrays and individual spots using the intensity projection profile of the most suitable subimage. The method is capable of processing the image without any user intervention and does not demand any input parameters as many other commercial and academic packages. According to results obtained, the accuracy of our algorithm is between 95-100% for microarray images with coefficient of variation less than two. Experimental results show that the method is capable of gridding microarray images with irregular spots, varying surface intensity distribution and with more than 50% contamination
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Fueled by ever-growing genomic information and rapid developments of proteomics–the large scale analysis of proteins and mapping its functional role has become one of the most important disciplines for characterizing complex cell function. For building functional linkages between the biomolecules, and for providing insight into the mechanisms of biological processes, last decade witnessed the exploration of combinatorial and chip technology for the detection of bimolecules in a high throughput and spatially addressable fashion. Among the various techniques developed, the protein chip technology has been rapid. Recently we demonstrated a new platform called “Spacially addressable protein array” (SAPA) to profile the ligand receptor interactions. To optimize the platform, the present study investigated various parameters such as the surface chemistry and role of additives for achieving high density and high-throughput detection with minimal nonspecific protein adsorption. In summary the present poster will address some of the critical challenges in protein micro array technology and the process of fine tuning to achieve the optimum system for solving real biological problems.