20 resultados para coating process


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This thesis studies human gene expression space using high throughput gene expression data from DNA microarrays. In molecular biology, high throughput techniques allow numerical measurements of expression of tens of thousands of genes simultaneously. In a single study, this data is traditionally obtained from a limited number of sample types with a small number of replicates. For organism-wide analysis, this data has been largely unavailable and the global structure of human transcriptome has remained unknown. This thesis introduces a human transcriptome map of different biological entities and analysis of its general structure. The map is constructed from gene expression data from the two largest public microarray data repositories, GEO and ArrayExpress. The creation of this map contributed to the development of ArrayExpress by identifying and retrofitting the previously unusable and missing data and by improving the access to its data. It also contributed to creation of several new tools for microarray data manipulation and establishment of data exchange between GEO and ArrayExpress. The data integration for the global map required creation of a new large ontology of human cell types, disease states, organism parts and cell lines. The ontology was used in a new text mining and decision tree based method for automatic conversion of human readable free text microarray data annotations into categorised format. The data comparability and minimisation of the systematic measurement errors that are characteristic to each lab- oratory in this large cross-laboratories integrated dataset, was ensured by computation of a range of microarray data quality metrics and exclusion of incomparable data. The structure of a global map of human gene expression was then explored by principal component analysis and hierarchical clustering using heuristics and help from another purpose built sample ontology. A preface and motivation to the construction and analysis of a global map of human gene expression is given by analysis of two microarray datasets of human malignant melanoma. The analysis of these sets incorporate indirect comparison of statistical methods for finding differentially expressed genes and point to the need to study gene expression on a global level.

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In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.

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Composting refers to aerobic degradation of organic material and is one of the main waste treatment methods used in Finland for treating separated organic waste. The composting process allows converting organic waste to a humus-like end product which can be used to increase the organic matter in agricultural soils, in gardening, or in landscaping. Microbes play a key role as degraders during the composting-process, and the microbiology of composting has been studied for decades, but there are still open questions regarding the microbiota in industrial composting processes. It is known that with the traditional, culturing-based methods only a small fraction, below 1%, of the species in a sample is normally detected. In recent years an immense diversity of bacteria, fungi and archaea has been found to occupy many different environments. Therefore the methods of characterising microbes constantly need to be developed further. In this thesis the presence of fungi and bacteria in full-scale and pilot-scale composting processes was characterised with cloning and sequencing. Several clone libraries were constructed and altogether nearly 6000 clones were sequenced. The microbial communities detected in this study were found to differ from the compost microbes observed in previous research with cultivation based methods or with molecular methods from processes of smaller scale, although there were similarities as well. The bacterial diversity was high. Based on the non-parametric coverage estimations, the number of bacterial operational taxonomic units (OTU) in certain stages of composting was over 500. Sequences similar to Lactobacillus and Acetobacteria were frequently detected in the early stages of drum composting. In tunnel stages of composting the bacterial community comprised of Bacillus, Thermoactinomyces, Actinobacteria and Lactobacillus. The fungal diversity was found to be high and phylotypes similar to yeasts were abundantly found in the full-scale drum and tunnel processes. In addition to phylotypes similar to Candida, Pichia and Geotrichum moulds from genus Thermomyces and Penicillium were observed in tunnel stages of composting. Zygomycetes were detected in the pilot-scale composting processes and in the compost piles. In some of the samples there were a few abundant phylotypes present in the clone libraries that masked the rare ones. The rare phylotypes were of interest and a method for collecting them from clone libraries for sequencing was developed. With negative selection of the abundant phylotyps the rare ones were picked from the clone libraries. Thus 41% of the clones in the studied clone libraries were sequenced. Since microbes play a central role in composting and in many other biotechnological processes, rapid methods for characterization of microbial diversity would be of value, both scientifically and commercially. Current methods, however, lack sensitivity and specificity and are therefore under development. Microarrays have been used in microbial ecology for a decade to study the presence or absence of certain microbes of interest in a multiplex manner. The sequence database collected in this thesis was used as basis for probe design and microarray development. The enzyme assisted detection method, ligation-detection-reaction (LDR) based microarray, was adapted for species-level detection of microbes characteristic of each stage of the composting process. With the use of a specially designed control probe it was established that a species specific probe can detect target DNA representing as little as 0.04% of total DNA in a sample. The developed microarray can be used to monitor composting processes or the hygienisation of the compost end product. A large compost microbe sequence dataset was collected and analysed in this thesis. The results provide valuable information on microbial community composition during industrial scale composting processes. The microarray method was developed based on the sequence database collected in this study. The method can be utilised in following the fate of interesting microbes during composting process in an extremely sensitive and specific manner. The platform for the microarray is universal and the method can easily be adapted for studying microbes from environments other than compost.

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Cytomegalovirus (CMV) is a major cause of morbidity, costs and even mortality in organ transplant recipients. CMV may also enhance the development of chronic allograft nephropathy (CAN), which is the most important cause of graft loss after kidney transplantation. The evidence for the role of CMV in chronic allograft nephropathy is somewhat limited, and controversial results have also been reported. The aim of this study was to investigate the role of CMV in the pathogenesis of CAN. Material for the purpose of this study was available from altogether 70 kidney transplant recipients who received a kidney transplant between the years 1992-2000. CMV infection was diagnosed with pp65 antigenemia test or by viral culture from blood, urine, or both. CMV proteins were demonstrated in the kidney allograft biopsies by immunohistochemisrty and CMV-DNA by in situ hybridization. Cytokines, adhesion molecules, and growth factors were demonstrated from allograft biopsies by immunohistochemistry, and from urinary samples by ELISA-methods. CMV proteins were detectable in the 6-month protocol biopsies from 18/41 recipients with evidence of CMV infection. In the histopathological analysis of the 6-month protocol biopsies, presence of CMV in the allograft together with a previous history of acute rejection episodes was associated with increased arteriosclerotic changes in small arterioles. In urinary samples collected during CMV infection, excretion of TGF-β was significantly increased. In recipients with increased urinary excretion of TGF-β, increased interstitial fibrosis was recorded in the 6- month protocol biopsies. In biopsies taken after an active CMV infection, CMV persisted in the kidney allograft in 17/48 recipients, as CMV DNA or antigens were detected in the biopsies more than 2 months after the last positive finding in blood or urine. This persistence was associated with increased expression of TGF-β, PDGF, and ICAM-1 and with increased vascular changes in the allografts. Graft survival and graft function one and two years after transplantation were reduced in recipients with persistent intragraft CMV. Persistent intragraft CMV infection was also a risk factor for reduced graft survival in Cox regression analysis, and an independent risk factor for poor graft function one and two years after transplantation in logistic regression analysis. In conclusion, these results show that persistent intragraft CMV infection is detrimental to kidney allografts, causing increased expression of growth factors and increased vascular changes, leading to reduced graft function and survival. Effective prevention, diagnosis and treatment of CMV infections may a major factor in improving the long term survival of kidney allograft.

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The main obstacle for the application of high quality diamond-like carbon (DLC) coatings has been the lack of adhesion to the substrate as the coating thickness is increased. The aim of this study was to improve the filtered pulsed arc discharge (FPAD) method. With this method it is possible to achieve high DLC coating thicknesses necessary for practical applications. The energy of the carbon ions was measured with an optoelectronic time-of-flight method. An in situ cathode polishing system used for stabilizing the process yield and the carbon ion energies is presented. Simultaneously the quality of the coatings can be controlled. To optimise the quality of the deposition process a simple, fast and inexpensive method using silicon wafers as test substrates was developed. This method was used for evaluating the suitability of a simplified arc-discharge set-up for the deposition of the adhesion layer of DLC coatings. A whole new group of materials discovered by our research group, the diamond-like carbon polymer hybrid (DLC-p-h) coatings, is also presented. The parent polymers used in these novel coatings were polydimethylsiloxane (PDMS) and polytetrafluoroethylene (PTFE). The energy of the plasma ions was found to increase when the anode-cathode distance and the arc voltage were increased. A constant deposition rate for continuous coating runs was obtained with an in situ cathode polishing system. The novel DLC-p-h coatings were found to be water and oil repellent and harder than any polymers. The lowest sliding angle ever measured from a solid surface, 0.15 ± 0.03°, was measured on a DLC-PDMS-h coating. In the FPAD system carbon ions can be accelerated to high energies (≈ 1 keV) necessary for the optimal adhesion (the substrate is broken in the adhesion and quality test) of ultra thick (up to 200 µm) DLC coatings by increasing the anode-cathode distance and using high voltages (up to 4 kV). An excellent adhesion can also be obtained with the simplified arc-discharge device. To maintain high process yield (5µm/h over a surface area of 150 cm2) and to stabilize the carbon ion energies and the high quality (sp3 fraction up to 85%) of the resulting coating, an in situ cathode polishing system must be used. DLC-PDMS-h coating is the superior candidate coating material for anti-soiling applications where also hardness is required.