6 resultados para domoic acid, biotoxins, detection
em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland
Resumo:
Polysialic acid is a carbohydrate polymer which consist of N-acetylneuraminic acid units joined by alpha2,8-linkages. It is developmentally regulated and has an important role during normal neuronal development. In adults, it participates in complex neurological processes, such as memory, neural plasticity, tumor cell growth and metastasis. Polysialic acid also constitutes the capsule of some meningitis and sepsis-causing bacteria, such as Escherichia coli K1, group B meningococci, Mannheimia haemolytica A2 and Moraxella nonliquefaciens. Polysialic acid is poorly immunogenic; therefore high affinity antibodies against it are difficult to prepare, thus specific and fast detection methods are needed. Endosialidase is an enzyme derived from the E. coli K1 bacteriophage, which specifically recognizes and degrades polysialic acid. In this study, a novel detection method for polysialic acid was developed based on a fusion protein of inactive endosialidase and the green fluorescent protein. It utilizes the ability of the mutant, inactive endosialidase to bind but not cleave polysialic acid. Sequencing of the endosialidase gene revealed that amino acid substitutions near the active site of the enzyme differentiate the active and inactive forms of the enzyme. The fusion protein was applied for the detection of polysialic acid in bacteria and neuroblastoma. The results indicate that the fusion protein is a fast, sensitive and specific reagent for the detection of polysialic acid. The use of an inactive enzyme as a specific molecular tool for the detection of its substrate represents an approach which could potentially find wide applicability in the specific detection of diverse macromolecules.
Resumo:
This MSc work was done in the project of BIOMECON financed by Tekes. The prime target of the research was, to develop methods for separation and determination of carbohydrates (sugars), sugar acids and alcohols, and some other organic acids in hydrolyzed pulp samples by capillary electrophoresis (CE) using UV detection. Aspen, spruce, and birch pulps are commonly used for production of papers in Finland. Feedstock components in pulp predominantly consist of carbohydrates, organic acids, lignin, extractives, and proteins. Here in this study, pulps have been hydrolyzed in analytical chemistry laboratories of UPM Company and Lappeenranta University in order to convert them into sugars, acids, alcohols, and organic acids. Foremost objective of this study was to quantify and identify the main and by-products in the pulp samples. For the method development and optimization, increased precision in capillary electrophoresis was accomplished by calculating calibration data of 16 analytes such as D-(-)-fructose, D(+)-xylose, D(+)-mannose, D(+)-cellobiose, D-(+)-glucose, D-(+)-raffinose, D(-)-mannitol, sorbitol, rhamnose, sucrose, xylitol, galactose, maltose, arabinose, ribose, and, α-lactose monohydratesugars and 16 organic acids such as D-glucuronic, oxalic, acetic, propionic, formic, glycolic, malonic, maleic, citric, L-glutamic, tartaric, succinic, adipic, ascorbic, galacturonic, and glyoxylic acid. In carbohydrate and polyalcohol analyses, the experiments with CE coupled to direct UV detection and positive separation polarity was performed in 36 mM disodium hydrogen phosphate electrolyte solution. For acid analyses, CE coupled indirect UV detection, using negative polarity, and electrolyte solution made of 2,3 pyridinedicarboxylic acid, Ca2+ salt, Mg2+ salts, and myristyltrimethylammonium hydroxide in water was used. Under optimized conditions, limits of detection, relative standard deviations and correlation coefficients of each compound were measured. The optimized conditions were used for the identification and quantification of carbohydrates and acids produced by hydrolyses of pulp. The concentrations of the analytes varied between 1 mg – 0.138 g in liter hydrolysate.
Resumo:
Background: In Finland, breast cancer (BC) is the most common cancer among women, and prostate cancer (PC) that among men. At the metastatic stage both cancers remain essentially incurable. The goals of therapy include palliation of symptoms, improvement or maintenance of quality of life (QoL), delay of disease progression, and prolongation of survival. Balancing between efficacy and toxicity is the major challenge. With increasing costs of new treatments, appropriate use of resources is paramount. When new treatment regimes are introduced into clinical practice a comprehensive assessment of clinical benefit, adverse effects and cost is necessary. Both BC and PC show a predilection to metastasize to bone. Bone metastases cause significant morbidity impairing the patients´ QoL. Diagnosis of bone metastases relies mainly on radiological methods, which however lack optimal sensitivity and specificity. New tools are needed for detection and follow-up of bone metastases. Aims: Anthracyclines and taxanes are effective chemotherapeutic agents in the treatment of metastatic breast cancer (MBC) with different mechanisms of action. Therefore, evaluation of the combination of anthracyclines with taxanes was a justifiable approach in the treatment of MBC patients. We assessed the efficacy, toxicity, cost of treatment and QoL of BC patients treated with first-line chemotherapy for metastatic disease with the combination epirubicin and docetaxel. We also evaluated the diagnostic potential of tartrate-resistant acid phosphatase 5b (TRACP 5b) and carboxyterminal telopeptides of type I collagen (ICTP) in the diagnosis of bone metastases in BC and TRACP 5b in PC patients. Results: The combination of epirubicin and docetaxel was effective in this phase II study, but required individual dose adjustment to avoid neutropenic infections, and the use of growth factors to maintain a feasible dose level. The response rate was 54 % (95 % CI 37-71) and the median overall survival (OS) was 26 months. Of the patients, 87 % were treated for infections. The treatment of adverse events required additional use of health resources mainly due to neutropenic infections, thereby raising direct treatment costs by 20 %. Despite adverse events, the global QoL was not significantly compromised during the treatment. Clinically evident acute cardiac toxicity was not observed. The combination of serum TRACP 5b and ICTP was at least equally sensitive and specific in detection of of bone metastases as commonly used total alkaline phosphatise (tALP) in BC patients. In contrast, TRACP 5b was less specific and sensitive than tALP as a marker of skeletal changes in PC patients. Conclusions: Treatment with epirubicin and docetaxel showed high efficacy in first-line chemotherapy of MBC. The relatively high incidence of neutropenic infections requiring hospitalization increased the treatment costs. Despite adverse events, the global QoL of the patients was not significantly compromised. The combination of TRACP 5b and ICTP showed similar activity as tALP in detecting bone metastases in MBC. In contrast, TRACP 5b was less specific and sensitive than tALP as a marker of skeletal changes in PC.
Resumo:
Binary probes are oligonucleotide probe pairs that hybridize adjacently to a complementary target nucleic acid. In order to detect this hybridization, the two probes can be modified with, for example, fluorescent molecules, chemically reactive groups or nucleic acid enzymes. The benefit of this kind of binary probe based approach is that the hybridization elicits a detectable signal which is distinguishable from background noise even though unbound probes are not removed by washing before measurement. In addition, the requirement of two simultaneous binding events increases specificity. Similarly to binary oligonucleotide probes, also certain enzymes and fluorescent proteins can be divided into two parts and used in separation-free assays. Split enzyme and fluorescent protein reporters have practical applications among others as tools to investigate protein-protein interactions within living cells. In this study, a novel label technology, switchable lanthanide luminescence, was introduced and used successfully in model assays for nucleic acid and protein detection. This label technology is based on a luminescent lanthanide chelate divided into two inherently non-luminescent moieties, an ion carrier chelate and a light harvesting antenna ligand. These form a highly luminescent complex when brought into close proximity; i.e., the label moieties switch from a dark state to a luminescent state. This kind of mixed lanthanide complex has the same beneficial photophysical properties as the more typical lanthanide chelates and cryptates - sharp emission peaks, long emission lifetime enabling time-resolved measurement, and large Stokes’ shift, which minimize the background signal. Furthermore, the switchable lanthanide luminescence technique enables a homogeneous assay set-up. Here, switchable lanthanide luminescence label technology was first applied to sensitive, homogeneous, single-target nucleic acid and protein assays with picomolar detection limits and high signal to background ratios. Thereafter, a homogeneous four-plex nucleic acid array-based assay was developed. Finally, the label technology was shown to be effective in discrimination of single nucleotide mismatched targets from fully matched targets and the luminescent complex formation was analyzed more thoroughly. In conclusion, this study demonstrates that the switchable lanthanide luminescencebased label technology can be used in various homogeneous bioanalytical assays.
Resumo:
Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.
Resumo:
Picornaviruses are the most common human viruses and the identification of the picornaviruses is nowadays based on molecular techniques, for example, reverse transcriptase polymerase chain reaction (RT-PCR). One aim of this thesis was to improve the identification of picornaviruses, especially rhino- and enteroviruses, with a real-time assay format and, also, to improve the differentiation of the viruses with genus-specific locked nucleic acid (LNA) probes. Another aim was to identify and study the causative agent of the enterovirus epidemics that appeared in Finland during seasons 2008-2010. In this thesis, the first version of picornavirus qRT-PCR with a melting curve analysis was used in a study of rhinovirus transmission within families with a rhinovirus positive index child where rhinovirus infection was monitored in all family members. In conclusion, rhinoviruses spread effectively within families causing mostly symptomatic infections in children and asymptomatic infections in adults. To improve the differentiation between rhino- and enterovirus the picornavirus qRT-PCR was modified with LNA-incorporated probes. The LNA probes were validated with picornavirus prototypes and different clinical specimen types. The LNA probe-based picornavirus qRT-PCR was able to differentiate all rhino- and enteroviruses correctly, which makes it suitable for diagnostic use. Moreover, in this thesis enterovirus outbreaks were studied with a well-observed method to create a strain-specific qRT-PCR from the typing region VP1 protein. In a hand-foot-and-mouth-disease (HFMD) outbreak in 2008, the causative agent was identified as CV-A6 and when the molecular evolution of the new HFMD CV-A6 strain was studied it was found that CV-A6 was the emerging agent for HFMD and onychomadesis. Furthermore, unusual E-30 meningitis epidemics that apeared during seasons 2009 and 2010 were studied with strain-specific qRT-PCR. The E-30 affected mostly adolescents and was probably spread in sports teams.