33 resultados para Screening tools


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The first line medication for mild to moderate Alzheimer s disease (AD) is based on cholinesterase inhibitors which prolong the effect of the neurotransmitter acetylcholine in cholinergic nerve synapses which relieves the symptoms of the disease. Implications of cholinesterases involvement in disease modifying processes has increased interest in this research area. The drug discovery and development process is a long and expensive process that takes on average 13.5 years and costs approximately 0.9 billion US dollars. Drug attritions in the clinical phases are common due to several reasons, e.g., poor bioavailability of compounds leading to low efficacy or toxic effects. Thus, improvements in the early drug discovery process are needed to create highly potent non-toxic compounds with predicted drug-like properties. Nature has been a good source for the discovery of new medicines accounting for around half of the new drugs approved to market during the last three decades. These compounds are direct isolates from the nature, their synthetic derivatives or natural mimics. Synthetic chemistry is an alternative way to produce compounds for drug discovery purposes. Both sources have pros and cons. The screening of new bioactive compounds in vitro is based on assaying compound libraries against targets. Assay set-up has to be adapted and validated for each screen to produce high quality data. Depending on the size of the library, miniaturization and automation are often requirements to reduce solvent and compound amounts and fasten the process. In this contribution, natural extract, natural pure compound and synthetic compound libraries were assessed as sources for new bioactive compounds. The libraries were screened primarily for acetylcholinesterase inhibitory effect and secondarily for butyrylcholinesterase inhibitory effect. To be able to screen the libraries, two assays were evaluated as screening tools and adapted to be compatible with special features of each library. The assays were validated to create high quality data. Cholinesterase inhibitors with various potencies and selectivity were found in natural product and synthetic compound libraries which indicates that the two sources complement each other. It is acknowledged that natural compounds differ structurally from compounds in synthetic compound libraries which further support the view of complementation especially if a high diversity of structures is the criterion for selection of compounds in a library.

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The feasibility of different modern analytical techniques for the mass spectrometric detection of anabolic androgenic steroids (AAS) in human urine was examined in order to enhance the prevalent analytics and to find reasonable strategies for effective sports drug testing. A comparative study of the sensitivity and specificity between gas chromatography (GC) combined with low (LRMS) and high resolution mass spectrometry (HRMS) in screening of AAS was carried out with four metabolites of methandienone. Measurements were done in selected ion monitoring mode with HRMS using a mass resolution of 5000. With HRMS the detection limits were considerably lower than with LRMS, enabling detection of steroids at low 0.2-0.5 ng/ml levels. However, also with HRMS, the biological background hampered the detection of some steroids. The applicability of liquid-phase microextraction (LPME) was studied with metabolites of fluoxymesterone, 4-chlorodehydromethyltestosterone, stanozolol and danazol. Factors affecting the extraction process were studied and a novel LPME method with in-fiber silylation was developed and validated for GC/MS analysis of the danazol metabolite. The method allowed precise, selective and sensitive analysis of the metabolite and enabled simultaneous filtration, extraction, enrichment and derivatization of the analyte from urine without any other steps in sample preparation. Liquid chromatographic/tandem mass spectrometric (LC/MS/MS) methods utilizing electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI) and atmospheric pressure photoionization (APPI) were developed and applied for detection of oxandrolone and metabolites of stanozolol and 4-chlorodehydromethyltestosterone in urine. All methods exhibited high sensitivity and specificity. ESI showed, however, the best applicability, and a LC/ESI-MS/MS method for routine screening of nine 17-alkyl-substituted AAS was thus developed enabling fast and precise measurement of all analytes with detection limits below 2 ng/ml. The potential of chemometrics to resolve complex GC/MS data was demonstrated with samples prepared for AAS screening. Acquired full scan spectral data (m/z 40-700) were processed by the OSCAR algorithm (Optimization by Stepwise Constraints of Alternating Regression). The deconvolution process was able to dig out from a GC/MS run more than the double number of components as compared with the number of visible chromatographic peaks. Severely overlapping components, as well as components hidden in the chromatographic background could be isolated successfully. All studied techniques proved to be useful analytical tools to improve detection of AAS in urine. Superiority of different procedures is, however, compound-dependent and different techniques complement each other.

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Solid materials can exist in different physical structures without a change in chemical composition. This phenomenon, known as polymorphism, has several implications on pharmaceutical development and manufacturing. Various solid forms of a drug can possess different physical and chemical properties, which may affect processing characteristics and stability, as well as the performance of a drug in the human body. Therefore, knowledge and control of the solid forms is fundamental to maintain safety and high quality of pharmaceuticals. During manufacture, harsh conditions can give rise to unexpected solid phase transformations and therefore change the behavior of the drug. Traditionally, pharmaceutical production has relied on time-consuming off-line analysis of production batches and finished products. This has led to poor understanding of processes and drug products. Therefore, new powerful methods that enable real time monitoring of pharmaceuticals during manufacturing processes are greatly needed. The aim of this thesis was to apply spectroscopic techniques to solid phase analysis within different stages of drug development and manufacturing, and thus, provide a molecular level insight into the behavior of active pharmaceutical ingredients (APIs) during processing. Applications to polymorph screening and different unit operations were developed and studied. A new approach to dissolution testing, which involves simultaneous measurement of drug concentration in the dissolution medium and in-situ solid phase analysis of the dissolving sample, was introduced and studied. Solid phase analysis was successfully performed during different stages, enabling a molecular level insight into the occurring phenomena. Near-infrared (NIR) spectroscopy was utilized in screening of polymorphs and processing-induced transformations (PITs). Polymorph screening was also studied with NIR and Raman spectroscopy in tandem. Quantitative solid phase analysis during fluidized bed drying was performed with in-line NIR and Raman spectroscopy and partial least squares (PLS) regression, and different dehydration mechanisms were studied using in-situ spectroscopy and partial least squares discriminant analysis (PLS-DA). In-situ solid phase analysis with Raman spectroscopy during dissolution testing enabled analysis of dissolution as a whole, and provided a scientific explanation for changes in the dissolution rate. It was concluded that the methods applied and studied provide better process understanding and knowledge of the drug products, and therefore, a way to achieve better quality.

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A population-based early detection program for breast cancer has been in progress in Finland since 1987. According to regulations during the study period 1987-2001, free of charge mammography screening was offered every second year to women aged 50-59 years. Recently, the screening service was decided to be extended to age group 50-69. However, the scope of the program is still frequently discussed in public and information about potential impacts of mass-screening practice changes on future breast cancer burden is required. The aim of this doctoral thesis is to present methodologies for taking into account the mass-screening invitation information in breast cancer burden predictions, and to present alternative breast cancer incidence and mortality predictions up to 2012 based on scenarios of the future screening policy. The focus of this work is not on assessing the absolute efficacy but the effectiveness of mass-screening, and, by utilizing the data on invitations, on showing the estimated impacts of changes in an existing screening program on the short-term predictions. The breast cancer mortality predictions are calculated using a model that combines incidence, cause-specific and other cause survival on individual level. The screening invitation data are incorporated into modeling of breast cancer incidence and survival by dividing the program into separate components (first and subsequent rounds and years within them, breaks, and post screening period) and defining a variable that gives the component of the screening program. The incidence is modeled using a Poisson regression approach and the breast cancer survival by applying a parametric mixture cure model, where the patient population is allowed to be a combination of cured and uncured patients. The patients risk to die from other causes than breast cancer is allowed to differ from that of a corresponding general population group and to depend on age and follow-up time. As a result, the effects of separate components of the screening program on incidence, proportion of cured and the survival of the uncured are quantified. According to the predictions, the impacts of policy changes, like extending the program from age group 50-59 to 50-69, are clearly visible on incidence while the effects on mortality in age group 40-74 are minor. Extending the screening service would increase the incidence of localized breast cancers but decrease the rates of non-localized breast cancer. There were no major differences between mortality predictions yielded by alternative future scenarios of the screening policy: Any policy change would have at the most a 3.0% reduction on overall breast cancer mortality compared to continuing the current practice in the near future.

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Much of the global cancer research is focused on the most prevalent tumors; yet, less common tumor types warrant investigation, since A rare disorder is not necessarily an unimportant one . The present work discusses a rare tumor type, the benign adenomas of the pituitary gland, and presents the advances which, during the course of this thesis work, contributed to the elucidation of a fraction of their genetic background. Pituitary adenomas are benign neoplasms of the anterior pituitary lobe, accounting for approximately 15% of all intracranial tumors. Pituitary adenoma cells hypersecrete the hormones normally produced by the anterior pituitary tissue, such as growth hormone (GH) and prolactin (PRL). Despite their non-metastasizing nature, these adenomas can cause significant morbidity and have to be adequately treated; otherwise, they can compromise the patient s quality of life, due to conditions provoked by hormonal hypersecretion, such as acromegaly in the case of GH-secreting adenomas, or due to compressive effects to surrounding tissues. The vast majority of pituitary adenomas arise sporadically, whereas a small subset occur as component of familial endocrine-related tumor syndromes, such as Multiple Endocrine Neoplasia type 1 (MEN1) and Carney complex (CNC). MEN1 is caused by germline mutations in the MEN1 tumor suppressor gene (11q13), whereas the majority of CNC cases carry germline mutations in the PRKAR1A gene (17q24). Pituitary adenomas are also encountered in familial settings outside the context of MEN1 and CNC, but unlike in the latter syndromes, their genetic background until recently remained elusive. Evidence in previous literature supported the notion that a tumor suppressor gene on 11q13, residing very close to but still distinct from MEN1, causes genetic susceptibility to pituitary tumors. The aim of the study was to identify the genetic cause of a low penetrance form of Pituitary Adenoma Predisposition (PAP) in families from Northern Finland. The present work describes the methodological approach that led to the identification of aryl hydrocarbon receptor interacting protein (AIP) as the gene causing PAP. Combining chip-based technologies (SNP and gene expression arrays) with traditional gene mapping methods and genealogy data, we showed that germline AIP mutations cause PAP in familial and sporadic settings. PAP patients were diagnosed with mostly adenomas of the GH/PRL-secreting cell lineage. In Finland, two AIP mutations accounted for 16% of all patients diagnosed with GH-secreting adenomas, and for 40% of patients being younger than 35 years of age at diagnosis. AIP is suggested to act as a tumor suppressor gene, a notion supported by the nature of the identified mutations (most are truncating) and the biallelic inactivation of AIP in the tumors studied. AIP has been best characterized as a cytoplasmic interaction partner of aryl hydrocarbon receptor (AHR), also known as dioxin receptor, but it has other partners as well. The mechanisms that underlie AIP-mediated pituitary tumorigenesis are to date largely unknown and warrant further investigation. Because AIP was identified in the genetically homogeneous Finnish population, it was relevant to examine its contribution to PAP in other, more heterogeneous, populations. Analysis of pituitary adenoma patient series of various ethnic origins and differing clinical settings revealed germline AIP mutations in all cohorts studied, albeit with low frequencies (range 0.8-7.4%). Overall, PAP patients were typically diagnosed at a young age (range 8-41 years), mainly with GH-secreting adenomas, without strong family history of endocrine disease. Because many PAP patients did not display family history of pituitary adenomas, detection of the condition appeared challenging. AIP immunohistochemistry was tested as a molecular pre-screening tool on mutation-positive versus mutation-negative tumors, and proved to be a potentially useful predictor of PAP. Mutation screening of a large cohort of colorectal, breast, and prostate tumors did not reveal somatic AIP mutations. These tumors, apart from being the most prevalent among men and women worldwide, have been associated with acromegaly, particularly colorectal neoplasia. In this material, AIP did not appear to contribute to the pathogenesis of these common tumor types and other genes seem likely to play a role in such tumorigenesis. Finally, the contribution of AIP in pediatric onset pituitary adenomas was examined in a unique population-based cohort of sporadic pituitary adenoma patients from Italy. Germline AIP mutations may account for a subset of pediatric onset GH-secreting adenomas (in this study one of seven GH-secreting adenoma cases or 14.3%), and appear to be enriched among young (≤25 years old) patients. In summary, this work reveals a novel tumor susceptibility gene, namely AIP, which causes genetic predisposition to pituitary adenomas, in particular GH-secreting adenomas. Moreover, it provides molecular tools for identification of individuals predisposed for PAP. Further elaborate studies addressing the functional role of AIP in normal and tumor cells will hopefully expand our knowledge on endocrine neoplasia and reveal novel cellular mechanisms of pituitary tumorigenesis, including potential drug targets.

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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.