919 resultados para Detecting


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MADAM, Androgenetic alopecia (AGA) is a common age-dependent trait, characterized by a progressive loss of hair from the scalp. The hair loss may commence during puberty and up to 80% of white men experience some degree of AGA during their lifetime.1 Research has established that two essential aetiological factors for AGA are a genetic predisposition and the presence of androgens (male sex hormones).1,2 A recent meta-analysis of genome-wide association studies (GWAS) has increased the number of identified loci associated with this trait at the molecular level to a total of eight.3 However, despite these successes, a large fraction of the genetic contribution remains to be identified. One way to identify further genetic loci is to combine the resource of GWAS datasets with knowledge about specific biological factors likely to be involved in the development of disease. The focused evaluation of a limited number of candidate genes in GWAS datasets avoids the necessity for extensive correction for multiple testing, which typically limits the power for detecting genetic loci at a genome-wide level.4 Because the presence of genetic association suggests that candidate genes are likely to operate early in the causative chain of events leading to the phenotype, this approach may also function to favour biological pathways for their importance in the development of AGA.

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The male-to-female sex ratio at birth is constant across world populations with an average of 1.06 (106 male to 100 female live births) for populations of European descent. The sex ratio is considered to be affected by numerous biological and environmental factors and to have a heritable component. The aim of this study was to investigate the presence of common allele modest effects at autosomal and chromosome X variants that could explain the observed sex ratio at birth. We conducted a large-scale genome-wide association scan (GWAS) meta-analysis across 51 studies, comprising overall 114 863 individuals (61 094 women and 53 769 men) of European ancestry and 2 623 828 common (minor allele frequency >0.05) single-nucleotide polymorphisms (SNPs). Allele frequencies were compared between men and women for directly-typed and imputed variants within each study. Forward-time simulations for unlinked, neutral, autosomal, common loci were performed under the demographic model for European populations with a fixed sex ratio and a random mating scheme to assess the probability of detecting significant allele frequency differences. We do not detect any genome-wide significant (P < 5 x 10(-8)) common SNP differences between men and women in this well-powered meta-analysis. The simulated data provided results entirely consistent with these findings. This large-scale investigation across ~115 000 individuals shows no detectable contribution from common genetic variants to the observed skew in the sex ratio. The absence of sex-specific differences is useful in guiding genetic association study design, for example when using mixed controls for sex-biased traits.

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Over the past years, much research on sarcomas based on low-resolution cytogenetic and molecular cytogenetic methods has been published, leading to the identification of genetic abnormalities partially underlying the tumourigenesis. Continued progress in the identification of genetic events such as copy number aberrations relies upon adapting the rapidly evolving high-resolution microarray technology, which will eventually provide novel insights into sarcoma biology, and targets for both diagnostics and drug development. The aim of this Thesis was to characterize DNA copy number changes that are involved in the pathogenesis of soft tissue leiomyosarcoma (LMS), dermatofibrosarcoma protuberans (DFSP), osteosarcoma (OS), malignant fibrous histiocytoma (MFH), and uterine leiomyosarcoma (ULMS) by applying fine resolution array comparative genomic hybridization (aCGH) technology. Both low- and high-grade LMS tumours showed distinct copy number patterns, in addition to sharing two minimal common regions of gains and losses. Small aberrations were detected by aCGH, which were beyond the resolution of chromosomal comparative genomic hybridization (cCGH). DFSP tumours analysed by aCGH showed gains in 17q, 22q, and 21 additional gained regions, but only one region (22q) with copy number loss. Recurrent amplicons identified in OS by aCGH were 12q11-q15, 8q, 6p12-p21, and 17p. Amplicons 12q and 17p were further characterized in detail. The amplicon at 17p was characterized by aCGH in low- and high-grade LMS, OS, and MFH. In all but one case this amplicon, with minimal common regions of gains at 17p11-p12, started with the distal loss of 17p13-pter. OS and high-grade LMS were grouped together as they showed a complex pattern of copy number gains and amplifications at 17p, whereas MFH and low-grade LMS showed a continuous pattern of copy number gains and amplification at 17p. In addition to the commonly gained and lost regions identified in ULMS by aCGH, various biological processes affected by these copy number changes were also indicated by pathway analysis. The three novel findings obtained in this work were: characterization of amplicon 17p in low- and high-grade LMS and MFH, profiles of DNA copy number changes in LMS, and detection of various pathways affected by copy number changes in ULMS. These studies have not been undertaken previously by aCGH technology, thus this Thesis adds new information regarding DNA copy number changes in sarcomas. In conclusion, the aCGH technique used in this Thesis has provided new insights into the genetics of sarcomas by detecting the precise regions affected by copy number changes and some potential candidate target genes within those regions, which had not been uncovered by previously applied low resolution techniques.

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In this study, a predisposing gene for a recently characterized cancer syndrome, hereditary leiomyomatosis and renal cell cancer (HLRCC), was identified and the role of the gene was investigated in other familial cancers and in nonsyndromic tumorigenesis. HLRCC is a dominantly inherited disorder predisposing predominantly to uterine and skin leiomyomas, and also to renal cell cancer and uterine leiomyosarcoma. The disease gene was recently localized in Finnish families to 1q42-q43 by a genome-wide linkage search. Independently in the UK, a clinically similar condition, multiple cutaneous and uterine leiomyomata (MCUL), was linked to the same chromosomal region, strongly suggesting that HLRCC and MCUL are actually a single syndrome. Linkage results were confirmed by detecting loss of heterozygosity (LOH) at the disease locus in most of the patients' tumors, suggesting that this predisposing gene acts as a tumor suppressor. Through detailed investigation by genotyping of microsatellite markers and haplotype construction in Finnish and UK HLRCC/MCUL families we were able to narrow the disease locus down to 1.6 Mb. Extensive mutation screening of known and predicted transcripts in the target region resulted in identification of the HLRCC predisposing gene, fumarase (fumarate hydratase, FH). FH is a key enzyme in energy metabolism, catalyzing fumarate to malate in the tricarboxylic acid cycle (TCAC) in mitochondria. Germline alterations in FH segregating with the disease were detected in 25 of 42 HLRCC/MCUL families including whole-gene deletions, truncating small deletions/insertions and nonsense mutations, as well as substitutions or deletions of highly conserved amino acids. Biallelic inactivation was detected in almost all studied tumors of HLRCC patients. Furthermore, FH enzyme activity was reduced in the patients' normal tissues and was completely or virtually absent from tumors. Based on these findings, we extensively demonstrated that mutations in FH underlie the HLRCC/MCUL syndrome. In our studies of other familial cancers, evidence for involvement of FH defects was not found in familial prostate and breast cancers. To investigate the role of FH in sporadic tumorigenesis, we analyzed 652 lesions, including a series of 353 nonsyndromic counterparts of tumor types associated with HLRCC. Mutations in nonsyndromic tumors were rare and appeared to be limited to tumor types observed in the hereditary form of the disease. Biallelic inactivation of FH was detected in a uterine leiomyosarcoma, a cutaneous leiomyoma, a soft-tissue sarcoma, and in two uterine leiomyomas. In the uterine leiomyosarcoma and the cutaneous lesion FH mutations originated from the germline whereas the soft-tissue sarcoma harbored purely somatic changes. In uterine leiomyomas somatic mutations were detected in the two out of five tumors with LOH at the FH locus. Our findings demonstrate that FH inactivation is also involved in nonhereditary tumor development, and further support the hypothesis that FH acts as a tumor suppressor. The role of FH in predisposition to malignancies, renal cell carcinoma and leiomyosarcoma is important in the diagnosis and prevention of cancer among HLRCC patients. This study is of general clinical interest, because prior to our findings, little was known about the molecular genetics of uterine leiomyomas, the most common tumors of women.

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Streptococcus pyogenes (group A streptococcus) is an important human pathogen, causing a wide array of infections ranging in severity. The majority of S. pyogenes infections are mild upper respiratory tract or skin infections. Severe, invasive infections, such as bacteraemia, are relatively rare, but constitute a major global burden with a high mortality. Certain streptococcal types are associated with a more severe disease and higher mortality. Bacterial, non-necrotizing cellulitis and erysipelas are localised infections of the skin, and although they are usually not life-threatening, they have a tendency to recur and therefore cause substantial morbidity. Despite several efforts aimed at developing an effective and safe vaccine against S. pyogenes infections, no vaccine is yet available. In this study, the epidemiology of invasive S. pyogenes infections in Finland was described over a decade of national, population-based surveillance. Recent trends in incidence, outcome and bacterial types were investigated. The beta-haemolytic streptococci causing cellulitis and erysipelas infections in Finland were studied in a case-control study. Bacterial isolates were characterised using both conventional and molecular typing methods, such as the emm typing, which is the most widely used typing method for beta-haemolytic streptococci. The incidence of invasive S. pyogenes disease has had an increasing trend during the past ten years in Finland, especially from 2006 onwards. Age- and sex-specific differences in the incidence rate were identified, with men having a higher incidence than women, especially among persons aged 45-64 years. In contrast, more infections occurred in women aged 25-34 years than men. Seasonal patterns with occasional peaks during the midsummer and midwinter were observed. Differences in the predisposing factors and underlying conditions of patients may contribute to these distinctions. Case fatality associated with invasive S. pyogenes infections peaked in 2005 (12%) but remained at a reasonably low level (8% overall during 2004-2007) compared to that of other developed countries (mostly exceeding 10%). Changes in the prevalent emm types were associated with the observed increases in incidence and case fatality. In the case-control study, acute bacterial non-necrotizing cellulitis was caused predominantly by Streptococcus dysgalactiae subsp. equisimilis, instead of S. pyogenes. The recurrent nature of cellulitis became evident. This study adds to our understanding of S. pyogenes infections in Finland and provides a basis for comparison to other countries and future trends. emm type surveillance and outcome analyses remain important for detecting such changes in type distribution that might lead to increases in incidence and case fatality. Bacterial characterisation serves as a basis for disease pathogenesis studies and vaccine development.

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Detecting spores with UAV.

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Aims: Helicobacter pylori infection, although the prevalence is declining in Western world, is still responsible for several clinically important diseases. None of the diagnostic tests is perfect and in this study, the performance of three stool antigen tests was assessed. In areas of high H. pylori prevalence, the definition of patients with the greatest benefit from eradication therapy may be a problem; the role of duodenal gastric metaplasia in categorizing patients at risk for duodenal ulcer was evaluated in this respect. Whether persistent chronic inflammation and elevated H. pylori antibodies after successful eradication are associated with each other or with atrophic gastritis, a long term sequelae of H. pylori infection, were also studied. Patients and methods: The three stool antigen tests were assessed in pre- and post-eradication settings among 364 subjects in two studies as compared to the rapid urease test (RUT), histology, culture, the 13C-urea breath test (UBT) and enzyme immunoassay (EIA) based H. pylori serology. The association between duodenal gastric metaplasia with duodenal ulcer was evaluated in a retrospective study including 1054 patients gastroscopied due to clinical indications and 154 patients previously operated for duodenal ulcer. The extent of duodenal gastric metaplasia was assessed from histological specimens in different patient groups formed on the basis of gastroscopy findings and H. pylori infection. Chronic gastric inflammation (108 patients) and H. pylori antibodies and serum markers for atrophy (77 patients) were assessed in patients earlier treated for H. pylori. Results: Of the stool antigen tests studied, the monoclonal antibody-based EIA-test showed the highest sensitivity and specificity both in the pre-treatment setting (96.9% and 95.9%) and after therapy (96.9% and 97.8%). The polyclonal stool antigen test and the in-office test had at baseline a sensitivity of 91% and 94%, and a specificity of 96% and 89%, respectively and in a post-treatment setting, a sensitivity of 78% and 91%, and a specificity of 97%, respectively. Duodenal gastric metaplasia was strongly associated with H. pylori positive duodenal ulcer (odds ratio 42). Although common still five years after eradication, persistent chronic gastric inflammation (21%) and elevated H. pylori antibodies (33%) were neither associated with each other nor with atrophic gastritis. Conclusions: Current H. pylori infection can feasibly be diagnosed by a monoclonal antibody-based EIA test with the accuracy comparable to that of reference methods. The performance of the polyclonal test as compared to the monoclonal test was inferior especially in the post-treatment setting. The in-office test had a low specificity for primary diagnosis and hence positive test results should probably be confirmed with another test before eradication therapy is prescribed. The presence of widespread duodenal gastric metaplasia showed promising results in detecting patients who should be treated for H. pylori due to an increased risk of duodenal ulcer. If serology is used later on in patients with earlier successfully treated for H. pylori, it should be taken into account that H. pylori antibodies may persist elevated for years for unknown reason. However, this phenomenon was not found to be associated with persistent chronic inflammation or atrophic changes.

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Dengue is a mosquito-borne viral disease caused by the four dengue virus serotypes (DENV-1-4) and is currently considered as the most important arthropod-borne viral disease in the world. Nearly half of the human population lives in risk areas, and 50-100 million infections occur yearly according to World Health Organization. The disease can vary from a mild febrile disease to severe haemorrhagic fever and shock. A secondary infection with heterologous serotype increases the risk for severe disease outcome. During the last three decades the impact of dengue has dramatically increased in the endemic areas including the tropics and subtropics of the world. The current situation with massive epidemics of severe disease forms has been associated with socio-ecological changes that have increased the transmission and enabled the co-circulation of different serotypes. Consequently, an increase of dengue has also been observed in travelers visiting these areas. Currently approximately 30 cases are diagnosed yearly in Finnish travelers. In travelers dengue is rarely a life-threatening disease, however in the current study, a fatality was documented in a young Finnish patient who experienced a prolonged primary dengue infection. To improve particularly early laboratory diagnostics, a novel real-time RT-PCR method was developed for the detection of DENV-1-4 RNA based on TaqMan chemistry. The method was shown to be sensitive and specific for detecting DENV RNA and suitable for diagnostic use. The newly developed real-time RT-PCR was compared to other available early diagnostic methods including IgM and NS1 antigen detection using a panel of selected patient samples. The results suggest that the best diagnostic rates are achieved by a combination of IgM with RNA or NS1 detection. The dengue virus strains studied here included the first DENV strains isolated from serum samples of Finnish travelers collected in 2000-2005. The results of sequence analysis demonstrated that the 11 isolates included all four DENV serotypes and presented a global sample of DENV strains from different geographical areas including Asia, Africa and South America. In the present study sequence analysis was also carried out for a collection of 23 novel DENV-2 isolates from Venezuelan patients collected in 1999-2005. The Venezuelan DENV-2 exclusively represented the American-Asian genotype, suggesting that no foreign DENV-2 lineages have recently been introduced to the country. The results also suggest that the DENV-2 viruses detected earlier from Venezuela have been maintained in the area where they have evolved into several lineages. This is in contrast to the pattern observed in some other dengue endemic areas, where introductions of novel virus types and lineages are frequently detected.

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The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

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We compare two popular methods for estimating the power spectrum from short data windows, namely the adaptive multivariate autoregressive (AMVAR) method and the multitaper method. By analyzing a simulated signal (embedded in a background Ornstein-Uhlenbeck noise process) we demonstrate that the AMVAR method performs better at detecting short bursts of oscillations compared to the multitaper method. However, both methods are immune to jitter in the temporal location of the signal. We also show that coherence can still be detected in noisy bivariate time series data by the AMVAR method even if the individual power spectra fail to show any peaks. Finally, using data from two monkeys performing a visuomotor pattern discrimination task, we demonstrate that the AMVAR method is better able to determine the termination of the beta oscillations when compared to the multitaper method.

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Mass occurrences (blooms) of cyanobacteria are common in aquatic environments worldwide. These blooms are often toxic, due to the presence of hepatotoxins or neurotoxins. The most common cyanobacterial toxins are hepatotoxins: microcystins and nodularins. In freshwaters, the main producers of microcystins are Microcystis, Anabaena, and Planktothrix. Nodularins are produced by strains of Nodularia spumigena in brackish waters. Toxic and nontoxic strains of cyanobacteria co-occur and cannot be differentiated by conventional microscopy. Molecular biological methods based on microcystin and nodularin synthetase genes enable detection of potentially hepatotoxic cyanobacteria. In the present study, molecular detection methods for hepatotoxin-producing cyanobacteria were developed, based on microcystin synthetase gene E (mcyE) and the orthologous nodularin synthetase gene F (ndaF) sequences. General primers were designed to amplify the mcyE/ndaF gene region from microcystin-producing Anabaena, Microcystis, Planktothrix, and Nostoc, and nodularin-producing Nodularia strains. The sequences were used for phylogenetic analyses to study how cyanobacterial mcy genes have evolved. The results showed that mcy genes and microcystin are very old and were already present in the ancestor of many modern cyanobacterial genera. The results also suggested that the sporadic distribution of biosynthetic genes in modern cyanobacteria is caused by repeated gene losses in the more derived lineages of cyanobacteria and not by horizontal gene transfer. Phylogenetic analysis also proposed that nda genes evolved from mcy genes. The frequency and composition of the microcystin producers in 70 lakes in Finland were studied by conventional polymerase chain reaction (PCR). Potential microcystin producers were detected in 84% of the lakes, using general mcyE primers, and in 91% of the lakes with the three genus-specific mcyE primers. Potential microcystin-producing Microcystis were detected in 70%, Planktothrix in 63%, and Anabaena in 37% of the lakes. The presence and co-occurrence of potential microcystin producers were more frequent in eutrophic lakes, where the total phosphorus concentration was high. The PCR results could also be associated with various environmental factors by correlation and regression analyses. In these analyses, the total nitrogen concentration and pH were both associated with the presence of multiple microcystin-producing genera and partly explained the probability of occurrence of mcyE genes. In general, the results showed that higher nutrient concentrations increased the occurrence of potential microcystin producers and the risk for toxic bloom formation. Genus-specific probe pairs for microcystin-producing Anabaena, Microcystis, Planktothrix, and Nostoc, and nodularin-producing Nodularia were designed to be used in a DNA-chip assay. The DNA-chip can be used to simultaneously detect all these potential microcystin/nodularin producers in environmental water samples. The probe pairs detected the mcyE/ndaF genes specifically and sensitively when tested with cyanobacterial strains. In addition, potential microcystin/nodularin producers were identified in lake and Baltic Sea samples by the DNA-chip almost as sensitively as by quantitative real-time PCR (qPCR), which was used to validate the DNA-chip results. Further improvement of the DNA-chip assay was achieved by optimization of the PCR, the first step in the assay. Analysis of the mcy and nda gene clusters from various hepatotoxin-producing cyanobacteria was rewarding; it revealed that the genes were ancient. In addition, new methods detecting all the main producers of hepatotoxins could be developed. Interestingly, potential microcystin-producing cyanobacterial strains of Microcystis, Planktothrix, and Anabaena, co-occurred especially in eutrophic and hypertrophic lakes. Protecting waters from eutrophication and restoration of lakes may thus decrease the prevalence of toxic cyanobacteria and the frequency of toxic blooms.

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Interference fits are used extensively in aircraft structural joints because of their improved fatigue performance. Recent advances in analysis of these joints have increased understanding of the nonlinear load-contact and load-interfacial slip variations in these joints. Experimental work in these problems is lacking due to difficulties in determining partial contact and partial slip along the pin-hole interface. In this paper, an experimental procedure is enumerated for determining load-contact relations in interference/clearance fits, using photoelastic models and applying a technique for detecting progress of separation/contact up to predetermined locations. The study incorporates a detailed procedure for model making, controlling interference, locating break of contact up to known locations around the interface, estimating optically the degree of interference, determining interfacial friction and evaluating stresses in the sheet. Experiments, simulating joints in large sheets, were carried out under both pin and plate loads. The present studies provide load-separation behavior in interference joint with finite interfacial friction.

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Differences in morphology have provided a basis for detecting natural interspecific hybridisation in forest trees for decades but have come to prominence again more recently as a means for directly measuring gene flow from planted forests. Here we examined the utility of seedling morphology for hybrid discrimination in three hybrid groups relevant to the monitoring of gene flow from plantings of Corymbia (L.D. Pryor & L.A.S. Johnson ex Brooker) taxa in subtropical Australia. Thirty leaf and stem characters were assessed on 907 8-month old seedlings from four parental and six hybrid taxa grown in a common garden. Outbred F1 hybrids between spotted gums (Corymbia citriodora subspecies variegata, C. citriodora subspecies citriodora and Corymbia henryi) tended to more closely resemble their maternal Corymbia torelliana parent and the most discriminating characters were the ratio of blade length to maximum perpendicular width, the presence or absence of a lignotuber, and specific leaf weight. Assignment of individuals into genealogical classes based on a multivariate model limited to a set of the more discriminating and independent characters was highest in the hybrid group, where parental taxa were genetically most divergent. Overall power to resolve among outbred F1 hybrids from both parental taxa was low to moderate, but this may not be a limitation to its likely major application of identifying hybrids in seedlots from native spotted gum stands. Advanced generation hybrids (outbred F2 and outbred backcrosses) were more difficult to resolve reliably due to the higher variances of hybrid taxa and the tendency of backcrosses to resemble their recurrent parents. Visual assessments of seedling morphology may provide a filter allowing screening of the large numbers needed to monitor gene flow, but will need to be combined with other hybrid detection methods to ensure hybrids are detected.

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Various intrusion detection systems (IDSs) reported in the literature have shown distinct preferences for detecting a certain class of attack with improved accuracy, while performing moderately on the other classes. In view of the enormous computing power available in the present-day processors, deploying multiple IDSs in the same network to obtain best-of-breed solutions has been attempted earlier. The paper presented here addresses the problem of optimizing the performance of IDSs using sensor fusion with multiple sensors. The trade-off between the detection rate and false alarms with multiple sensors is highlighted. It is illustrated that the performance of the detector is better when the fusion threshold is determined according to the Chebyshev inequality. In the proposed data-dependent decision ( DD) fusion method, the performance optimization of ndividual IDSs is first addressed. A neural network supervised learner has been designed to determine the weights of individual IDSs depending on their reliability in detecting a certain attack. The final stage of this DD fusion architecture is a sensor fusion unit which does the weighted aggregation in order to make an appropriate decision. This paper theoretically models the fusion of IDSs for the purpose of demonstrating the improvement in performance, supplemented with the empirical evaluation.

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The chemical composition of breast milk has been studied in detail in the past decades. Hundreds of new antibacterial and antiviral components have been found. Several molecules have been found to promote the proper function of neonatal intestine. However, microbiological studies of breast milk have been, until recently, focused mainly on detecting harmful and pathogenic bacteria and viruses. Natural microbial diversity of human milk has not been widely studied before the work reported in this thesis. This is mainly because breast milk has traditionally been thought to be sterile - even if a certain amount of commensal bacteria have usually been detected in milk samples. The first part of this licentiate thesis contains a short literature review about the anatomy and physiology of breast feeding, human milk chemical and microbiological composition, mastitis, intestinal flora and bacteriocins. The second part reports on the experiments of the licentiate work, concentrating on the microbial diversity in the milk of healthy breast-feeding mothers, and the ability of these bacteria to produce antibacterial substances against pathogenic bacteria. The results indicate that human milk is a source of commensal bacteria for infant intestine. 509 random isolates from 40 breast milk samples were isolated and identified by 16S rRNA sequencing. Median bacterial count was about 600 colony forming units per milliliter. Over half of the isolates were staphylococci, and almost one third streptococci. The most common species were skin bacteria Staphylococcus epidermidis and oral bacteria Streptococcus salivarius and Streptococcus mitis. Lactic acid bacteria, identified as members of Lactobacillus-, Lactococcus- and Leuconostoc -genera, were found in five milk samples. Enterococci were found in three samples. A novel finding in this study is the capability of these commensal bacteria to inhibit the growth of pathogens. In 90 precent of the milk samples commensal bacteria inhibiting the growth of Staphylococcus aureus were found. In 40 precent of samples the colonies could block the growth completely. One fifth of the isolated Staph. epidermidis strains, half of Str. salivarius strains, and all lactic acid bacteria and enterococci could inhibit or block the growth of Staph. aureus. In further study also Listeria innocua- and Micrococcus luteus active isolates were found in 33 and 11 precent of milk samples (out of 140). Furthermore, two Lactococcus lactis isolates from the breast milk were shown to produce bacteriocin nisin, which is an antimicrobial molecule used as a food preservative. The importance of these human milk commensal bacteria in the development of newborn intestinal flora and immune system, as well as in preventing maternal breast infections, should be further explored.