A Pattern Recognition Model of Voice-Based Personal Verification Systems for Forensic Applications

Abstract-The success of automatic speaker recognition in laboratory environments suggests applications in forensic science for establishing the Identity of individuals on the basis of features extracted from speech. A theoretical model for such a verification scheme for continuous normaliy distributed featureIss developed. The three cases of using a) single feature, b)multipliendependent measurements of a single feature, and c)multpleindependent features are explored.The number iofndependent features needed for areliable personal identification is computed based on the theoretcal model and an expklatory study of some speech featues.

Standardization and validation of an induced ovulation model system in buffalo cows: Characterization of gene expression changes in the periovulatory follicle

In bovines characterization of biochemical and molecular determinants of the dominant follicle before and during different time intervals after gonadotrophin surge requires precise identification of the dominant follicle from a follicular wave. The objectives of the present study were to standardize an experimental model in buffalo cows for accurately identifying the dominant follicle of the first wave of follicular growth and characterize changes in follicular fluid hormone concentrations as well as expression patterns of various genes associated with the process of ovulation. From the day of estrus (day 0), animals were subjected to blood sampling and ultrasonography for monitoring circulating progesterone levels and follicular growth. On day 7 of the cycle, animals were administered a PGF2α analogue (Tiaprost Trometamol, 750 μg i.m.) followed by an injection of hCG (2000 IU i.m.) 36 h later. Circulating progesterone levels progressively increased from day 1 of the cycle to 2.26 ± 0.17 ng/ml on day 7 of the cycle, but declined significantly after PGF2α injection. A progressive increase in the size of the dominant follicle was observed by ultrasonography. The follicular fluid estradiol and progesterone concentrations in the dominant follicle were 600 ± 16.7 and 38 ± 7.6 ng/ml, respectively, before hCG injection and the concentration of estradiol decreased to 125.8 ± 25.26 ng/ml, but concentration of progesterone increased to 195 ± 24.6 ng/ml, 24 h post-hCG injection. Inh-α and Cyp19A1 expressions in granulosa cells were maximal in the dominant follicle and declined in response to hCG treatment. Progesterone receptor, oxytocin and cycloxygenase-2 expressions in granulosa cells, regarded as markers of ovulation, were maximal at 24 h post-hCG. The expressions of genes belonging to the super family of proteases were also examined; Cathepsin L expression decreased, while ADAMTS 3 and 5 expressions increased 24 h post-hCG treatment. The results of the current study indicate that sequential treatments of PGF2α and hCG during early estrous cycle in the buffalo cow leads to follicular growth that culminates in ovulation. The model system reported in the present study would be valuable for examining temporo-spatial changes in the periovulatory follicle immediately before and after the onset of gonadotrophin surge.

On the order of the fractional Laplacian in determining the spatio-temporal evolution of a space-fractional model of cardiac electrophysiology

Space-fractional operators have been used with success in a variety of practical applications to describe transport processes in media characterised by spatial connectivity properties and high structural heterogeneity altering the classical laws of diffusion. This study provides a systematic investigation of the spatio-temporal effects of a space-fractional model in cardiac electrophysiology. We consider a simplified model of electrical pulse propagation through cardiac tissue, namely the monodomain formulation of the Beeler-Reuter cell model on insulated tissue fibres, and obtain a space-fractional modification of the model by using the spectral definition of the one-dimensional continuous fractional Laplacian. The spectral decomposition of the fractional operator allows us to develop an efficient numerical method for the space-fractional problem. Particular attention is paid to the role played by the fractional operator in determining the solution behaviour and to the identification of crucial differences between the non-fractional and the fractional cases. We find a positive linear dependence of the depolarization peak height and a power law decay of notch and dome peak amplitudes for decreasing orders of the fractional operator. Furthermore, we establish a quadratic relationship in conduction velocity, and quantify the increasingly wider action potential foot and more pronounced dispersion of action potential duration, as the fractional order is decreased. A discussion of the physiological interpretation of the presented findings is made.

Prevention of type 2 diabetes with lifestyle intervention - emphasis on dietary composition and identification of high-risk individuals

Type 2 diabetes is an increasing, serious, and costly public health problem. The increase in the prevalence of the disease can mainly be attributed to changing lifestyles leading to physical inactivity, overweight, and obesity. These lifestyle-related risk factors offer also a possibility for preventive interventions. Until recently, proper evidence regarding the prevention of type 2 diabetes has been virtually missing. To be cost-effective, intensive interventions to prevent type 2 diabetes should be directed to people at an increased risk of the disease. The aim of this series of studies was to investigate whether type 2 diabetes can be prevented by lifestyle intervention in high-risk individuals, and to develop a practical method to identify individuals who are at high risk of type 2 diabetes and would benefit from such an intervention. To study the effect of lifestyle intervention on diabetes risk, we recruited 522 volunteer, middle-aged (aged 40 - 64 at baseline), overweight (body mass index > 25 kg/m2) men (n = 172) and women (n = 350) with impaired glucose tolerance to the Diabetes Prevention Study (DPS). The participants were randomly allocated either to the intensive lifestyle intervention group or the control group. The control group received general dietary and exercise advice at baseline, and had annual physician's examination. The participants in the intervention group received, in addition, individualised dietary counselling by a nutritionist. They were also offered circuit-type resistance training sessions and were advised to increase overall physical activity. The intervention goals were to reduce body weight (5% or more reduction from baseline weight), limit dietary fat (< 30% of total energy consumed) and saturated fat (< 10% of total energy consumed), and to increase dietary fibre intake (15 g / 1000 kcal or more) and physical activity (≥ 30 minutes/day). Diabetes status was assessed annually by a repeated 75 g oral glucose tolerance testing. First analysis on end-points was completed after a mean follow-up of 3.2 years, and the intervention phase was terminated after a mean duration of 3.9 years. After that, the study participants continued to visit the study clinics for the annual examinations, for a mean of 3 years. The intervention group showed significantly greater improvement in each intervention goal. After 1 and 3 years, mean weight reductions were 4.5 and 3.5 kg in the intervention group and 1.0 kg and 0.9 kg in the control group. Cardiovascular risk factors improved more in the intervention group. After a mean follow-up of 3.2 years, the risk of diabetes was reduced by 58% in the intervention group compared with the control group. The reduction in the incidence of diabetes was directly associated with achieved lifestyle goals. Furthermore, those who consumed moderate-fat, high-fibre diet achieved the largest weight reduction and, even after adjustment for weight reduction, the lowest diabetes risk during the intervention period. After discontinuation of the counselling, the differences in lifestyle variables between the groups still remained favourable for the intervention group. During the post-intervention follow-up period of 3 years, the risk of diabetes was still 36% lower among the former intervention group participants, compared with the former control group participants. To develop a simple screening tool to identify individuals who are at high risk of type 2 diabetes, follow-up data of two population-based cohorts of 35-64 year old men and women was used. The National FINRISK Study 1987 cohort (model development data) included 4435 subjects, with 182 new drug-treated cases of diabetes identified during ten years, and the FINRISK Study 1992 cohort (model validation data) included 4615 subjects, with 67 new cases of drug-treated diabetes during five years, ascertained using the Social Insurance Institution's Drug register. Baseline age, body mass index, waist circumference, history of antihypertensive drug treatment and high blood glucose, physical activity and daily consumption of fruits, berries or vegetables were selected into the risk score as categorical variables. In the 1987 cohort the optimal cut-off point of the risk score identified 78% of those who got diabetes during the follow-up (= sensitivity of the test) and 77% of those who remained free of diabetes (= specificity of the test). In the 1992 cohort the risk score performed equally well. The final Finnish Diabetes Risk Score (FINDRISC) form includes, in addition to the predictors of the model, a question about family history of diabetes and the age category of over 64 years. When applied to the DPS population, the baseline FINDRISC value was associated with diabetes risk among the control group participants only, indicating that the intensive lifestyle intervention given to the intervention group participants abolished the diabetes risk associated with baseline risk factors. In conclusion, the intensive lifestyle intervention produced long-term beneficial changes in diet, physical activity, body weight, and cardiovascular risk factors, and reduced diabetes risk. Furthermore, the effects of the intervention were sustained after the intervention was discontinued. The FINDRISC proved to be a simple, fast, inexpensive, non-invasive, and reliable tool to identify individuals at high risk of type 2 diabetes. The use of FINDRISC to identify high-risk subjects, followed by lifestyle intervention, provides a feasible scheme in preventing type 2 diabetes, which could be implemented in the primary health care system.

Identification of the Meckel syndrome gene (MKS1) exposes a novel ciliopathy

Meckel syndrome (MKS, MIM 249000) is an autosomal recessive developmental disorder causing death in utero or shortly after birth. The hallmarks of the disease are cystic kidney dysplasia and fibrotic changes of the liver, occipital encephalocele with or without hydrocephalus and polydactyly. Other anomalies frequently seen in the patients are incomplete development of the male genitalia, club feet and cleft lip or palate. The clinical picture has been well characterized in the literature while the molecular pathology underlying the disease has remained unclear until now. In this study we identified the first MKS gene by utilizing the disease haplotypes in Finnish MKS families linked to the MKS1 locus on chromosome 17q23 (MKS1) locus. Subsequently, the genetic heterogeneity of MKS was established in the Finnish families. Mutations in at least four different genes can cause MKS. These genes have been mapped to the chromosomes 17q23 (MKS1), 11q13 (MKS2), 8q22 (MKS3) and 9q33 (MKS4). Two of these genes have been identified so far: The MKS1 gene (this work) and the MKS3 gene. The identified MKS1 gene was initially a novel human gene which is conserved among species. We found three different MKS mutations, one of them being the Finnish founder mutation. The information available from MKS1 orthologs in other species convinced us that the MKS1 gene is required for normal ciliogenesis. Defects of the cilial system in other human diseases and model organisms actually cause phenotypic features similar to those seen in MKS patients. The MKS3 (TMEM67) gene encodes a transmembrane protein and the gene maps to the syntenic Wpk locus in the rat, which is a model with polycystic kidney disease, agenesis of the corpus callosum and hydrocephalus. The available information from these two genes suggest that MKS1 would encode a structural component of the centriole required for normal ciliary functions, and MKS3 would be a transmembrane component most likely required for normal ciliary sensory signaling. The MKS4 locus was localized to chromosme 9q32-33 in this study by using an inbred Finnish family with two affected and two healthy children. This fourth locus contains TRIM32 gene, which is associated to another well characterized human ciliopathy, Bardet Biedl syndrome (BBS). Future studies should identify the MKS4 gene on chromosome 9q and confirm if there are more than two genes causing MKS Finnish families. The research on critical signaling pathways in organogenesis have shown that both Wnt and Hedgehog pathways are dependent on functional cilia. The MKS gene products will serve as excellent model molecules for more detailed studies of the functional role of cilia in organogenesis in more detail.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

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.

Identification of intersectional Corymbia hybrids based on seedling morphology improves with parental divergence

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.

Identification of a class of non-linear systems

This paper considers the on-line identification of a non-linear system in terms of a Hammerstein model, with a zero-memory non-linear gain followed by a linear system. The linear part is represented by a Laguerre expansion of its impulse response and the non-linear part by a polynomial. The identification procedure involves determination of the coefficients of the Laguerre expansion of correlation functions and an iterative adjustment of the parameters of the non-linear gain by gradient methods. The method is applicable to situations involving a wide class of input signals. Even in the presence of additive correlated noise, satisfactory performance is achieved with the variance of the error converging to a value close to the variance of the noise. Digital computer simulation establishes the practicability of the scheme in different situations.

Genetic differentiation analysis for the identification of complementary parental pools for sorghum hybrid breeding in Ethiopia

Key message The potential for exploiting heterosis for sorghum hybrid production in Ethiopia with improved local adaptation and farmers preferences has been investigated and populations suitable for initial hybrid development have been identified. Abstract Hybrids in sorghum have demonstrated increased productivity and stability of performance in the developed world. In Ethiopia, the uptake of hybrid sorghum has been limited to date, primarily due to poor adaptation and absence of farmer’s preferred traits in existing hybrids. This study aimed to identify complementary parental pools to develop locally adapted hybrids, through an analysis of whole genome variability of 184 locally adapted genotypes and introduced hybrid parents (R and B). Genetic variability was assessed using genetic distance, model-based STRUCTURE analysis and pair-wise comparison of groups. We observed a high degree of genetic similarity between the Ethiopian improved inbred genotypes and a subset of landraces adapted to lowland agro-ecology with the introduced R lines. This coupled with the genetic differentiation from existing B lines, indicated that these locally adapted genotype groups are expected to have similar patterns of heterotic expression as observed between introduced R and B line pools. Additionally, the hybrids derived from these locally adapted genotypes will have the benefit of containing farmers preferred traits. The groups most divergent from introduced B lines were the Ethiopian landraces adapted to highland and intermediate agro-ecologies and a subset of lowland-adapted genotypes, indicating the potential for increased heterotic response of their hybrids. However, these groups were also differentiated from the R lines, and hence are different from the existing complementary heterotic pools. This suggests that although these groups could provide highly divergent parental pools, further research is required to investigate the extent of heterosis and their hybrid performance.

The Gerbera cDNA Microarray: A Tool for Large-Scale Identification of Genes Involved in Flower Development

During the past ten years, large-scale transcript analysis using microarrays has become a powerful tool to identify and predict functions for new genes. It allows simultaneous monitoring of the expression of thousands of genes and has become a routinely used tool in laboratories worldwide. Microarray analysis will, together with other functional genomics tools, take us closer to understanding the functions of all genes in genomes of living organisms. Flower development is a genetically regulated process which has mostly been studied in the traditional model species Arabidopsis thaliana, Antirrhinum majus and Petunia hybrida. The molecular mechanisms behind flower development in them are partly applicable in other plant systems. However, not all biological phenomena can be approached with just a few model systems. In order to understand and apply the knowledge to ecologically and economically important plants, other species also need to be studied. Sequencing of 17 000 ESTs from nine different cDNA libraries of the ornamental plant Gerbera hybrida made it possible to construct a cDNA microarray with 9000 probes. The probes of the microarray represent all different ESTs in the database. From the gerbera ESTs 20% were unique to gerbera while 373 were specific to the Asteraceae family of flowering plants. Gerbera has composite inflorescences with three different types of flowers that vary from each other morphologically. The marginal ray flowers are large, often pigmented and female, while the central disc flowers are smaller and more radially symmetrical perfect flowers. Intermediate trans flowers are similar to ray flowers but smaller in size. This feature together with the molecular tools applied to gerbera, make gerbera a unique system in comparison to the common model plants with only a single kind of flowers in their inflorescence. In the first part of this thesis, conditions for gerbera microarray analysis were optimised including experimental design, sample preparation and hybridization, as well as data analysis and verification. Moreover, in the first study, the flower and flower organ-specific genes were identified. After the reliability and reproducibility of the method were confirmed, the microarrays were utilized to investigate transcriptional differences between ray and disc flowers. This study revealed novel information about the morphological development as well as the transcriptional regulation of early stages of development in various flower types of gerbera. The most interesting finding was differential expression of MADS-box genes, suggesting the existence of flower type-specific regulatory complexes in the specification of different types of flowers. The gerbera microarray was further used to profile changes in expression during petal development. Gerbera ray flower petals are large, which makes them an ideal model to study organogenesis. Six different stages were compared and specifically analysed. Expression profiles of genes related to cell structure and growth implied that during stage two, cells divide, a process which is marked by expression of histones, cyclins and tubulins. Stage 4 was found to be a transition stage between cell division and expansion and by stage 6 cells had stopped division and instead underwent expansion. Interestingly, at the last analysed stage, stage 9, when cells did not grow any more, the highest number of upregulated genes was detected. The gerbera microarray is a fully-functioning tool for large-scale studies of flower development and correlation with real-time RT-PCR results show that it is also highly sensitive and reliable. Gene expression data presented here will be a source for gene expression mining or marker gene discovery in the future studies that will be performed in the Gerbera Laboratory. The publicly available data will also serve the plant research community world-wide.

Identification of a novel FGFRL1 MicroRNA target site polymorphism for bone mineral density in meta-analyses of genome-wide association studies

MicroRNAs (miRNAs) are critical post-transcriptional regulators. Based on a previous genome-wide association (GWA) scan, we conducted a polymorphism in microRNAs' Target Sites (poly-miRTS)-centric multistage meta-analysis for lumbar spine (LS)-, total hip (HIP)-, and femoral neck (FN)-bone mineral density (BMD). In stage I, 41,102 poly-miRTSs were meta-analyzed in 7 cohorts with a genome-wide significance (GWS) α=0.05/41,102=1.22×10-6. By applying α=5×10-5 (suggestive significance), 11 poly-miRTSs were selected, with FGFRL1 rs4647940 and PRR5 rs3213550 as top signals for FN-BMD (P-value=7.67×10-6 and 1.58×10-5) in gender-combined sample. In stage II in silico replication (two cohorts), FGFRL1 rs4647940 was the only signal marginally replicated for FN-BMD (P-value=5.08×10-3) at α=0.10/11=9.09×10-3. PRR5 rs3213550 was also selected based on biological significance. In stage III de novo genotyping replication (two cohorts), FGFRL1 rs4647940 was the only signal significantly replicated for FN-BMD (P-value=7.55×10-6) at α=0.05/2=0.025 in gender-combined sample. Aggregating three stages, FGFRL1 rs4647940 was the single stage I-discovered and stages II- and III-replicated signal attaining GWS for FN-BMD (P-value=8.87×10-12). Dual-luciferase reporter assays demonstrated that FGFRL1 3' untranslated region harboring rs4647940 appears to be hsa-miR-140-5p's target site. In a zebrafish microinjection experiment, dre-miR-140-5p is shown to exert a dramatic impact on craniofacial skeleton formation. Taken together, we provided functional evidence for a novel FGFRL1 poly-miRTS rs4647940 in a previously known 4p16.3 locus, and experimental and clinical genetics studies have shown both FGFRL1 and hsa-miR-140-5p are important for bone formation. © The Author 2015. Published by Oxford University Press. All rights reserved.

Identification of Hadronically Decaying Tau Leptons in Searches for Heavy MSSM Higgs Bosons with the CMS Detector at the CERN LHC

This thesis describes methods for the reliable identification of hadronically decaying tau leptons in the search for heavy Higgs bosons of the minimal supersymmetric standard model of particle physics (MSSM). The identification of the hadronic tau lepton decays, i.e. tau-jets, is applied to the gg->bbH, H->tautau and gg->tbH+, H+->taunu processes to be searched for in the CMS experiment at the CERN Large Hadron Collider. Of all the event selections applied in these final states, the tau-jet identification is the single most important event selection criterion to separate the tiny Higgs boson signal from a large number of background events. The tau-jet identification is studied with methods based on a signature of a low charged track multiplicity, the containment of the decay products within a narrow cone, an isolated electromagnetic energy deposition, a non-zero tau lepton flight path, the absence of electrons, muons, and neutral hadrons in the decay signature, and a relatively small tau lepton mass compared to the mass of most hadrons. Furthermore, in the H+->taunu channel, helicity correlations are exploited to separate the signal tau jets from those originating from the W->taunu decays. Since many of these identification methods rely on the reconstruction of charged particle tracks, the systematic uncertainties resulting from the mechanical tolerances of the tracking sensor positions are estimated with care. The tau-jet identification and other standard selection methods are applied to the search for the heavy neutral and charged Higgs bosons in the H->tautau and H+->taunu decay channels. For the H+->taunu channel, the tau-jet identification is redone and optimized with a recent and more detailed event simulation than previously in the CMS experiment. Both decay channels are found to be very promising for the discovery of the heavy MSSM Higgs bosons. The Higgs boson(s), whose existence has not yet been experimentally verified, are a part of the standard model and its most popular extensions. They are a manifestation of a mechanism which breaks the electroweak symmetry and generates masses for particles. Since the H->tautau and H+->taunu decay channels are important for the discovery of the Higgs bosons in a large region of the permitted parameter space, the analysis described in this thesis serves as a probe for finding out properties of the microcosm of particles and their interactions in the energy scales beyond the standard model of particle physics.

The hype cycle model: A review and future directions

The hype cycle model traces the evolution of technological innovations as they pass through successive stages pronounced by the peak, disappointment, and recovery of expectations. Since its introduction by Gartner nearly two decades ago, the model has received growing interest from practitioners, and more recently from scholars. Given the model's proclaimed capacity to forecast technological development, an important consideration for organizations in formulating marketing strategies, this paper provides a critical review of the hype cycle model by seeking evidence from Gartner's own technology databases for the manifestation of hype cycles. The results of our empirical work show incongruences connected with the reports of Gartner, which motivates us to consider possible future directions, whereby the notion of hype or hyped dynamics (though not necessarily the hype cycle model itself) can be captured in existing life cycle models through the identification of peak, disappointment, and recovery patterns.

Evolution, Homology Conservation, and Identification of Unique Sequence Signatures in GH19 Family Chitinases

The discovery of GH (Glycoside Hydrolase) 19 chitinases in Streptomyces sp. raises the possibility of the presence of these proteins in other bacterial species, since they were initially thought to be confined to higher plants. The present study mainly concentrates on the phylogenetic distribution and homology conservation in GH19 family chitinases. Extensive database searches are performed to identify the presence of GH19 family chitinases in the three major super kingdoms of life. Multiple sequence alignment of all the identified GH19 chitinase family members resulted in the identification of globally conserved residues. We further identified conserved sequence motifs across the major sub groups within the family. Estimation of evolutionary distance between the various bacterial and plant chitinases are carried out to better understand the pattern of evolution. Our study also supports the horizontal gene transfer theory, which states that GH19 chitinase genes are transferred from higher plants to bacteria. Further, the present study sheds light on the phylogenetic distribution and identifies unique sequence signatures that define GH19 chitinase family of proteins. The identified motifs could be used as markers to delineate uncharacterized GH19 family chitinases. The estimation of evolutionary distance between chitinase identified in plants and bacteria shows that the flowering plants are more related to chitinase in actinobacteria than that of identified in purple bacteria. We propose a model to elucidate the natural history of GH19 family chitinases.

Identification of molecules relevant for the invasiveness of fibrosarcomas and melanomas

Cancer is becoming the leading cause of deaths in the world. As 90% of all deaths from cancer are caused by metastasis, discovery of the mechanisms behind cancer cell invasion and metastasis is of utmost importance. Only new effective therapies targeting cancer progression can reduce cancer mortality rates. The aim of this study was to identify molecules that are relevant for tumor cell invasion and spreading in fibrosarcomas and melanomas, and to analyze their potential for cancer biomarkers or therapeutic targets. First, the gene expression changes of normal cells and transformed cells showing high invasiveness, S-adenosylmethionine decarboxylase (AdoMetDC)-transfected murine fibroblasts and human melanoma cells, were studied by microarray analyses. The function of the identified candidate molecules were then studied in detail in these cell lines. Finally, the physiological relevance of the identified changes was studied by immunohistochemical analyses of human sarcoma and melanoma specimens or by a mouse xenograft model. In fibrosarcoma cells, the most remarkable change detected was a dramatic up-regulation of the actin-sequestering molecule thymosin beta 4 (TB4), which was shown to be important for the transformed phenotype of the AdoMetDC-transfected cells (Amdc-s and -as). A sponge toxin latrunculin A, inhibiting the binding of TB4 to actin, was found to selectively inhibit the migration and invasion of these cells. Further, Amdc-s-induced mouse tumors and human high-grade sarcomas were found to show intense TB4 immunostaining. In addition to TB4, integrin subunits alfa 6 and beta 7 (ItgA6 and ItgB7) were found to be up-regulated in Amdc-s and -as cells. ItgA6 was shown to dimerize mainly with ItgB1 in Amdc-s. Inhibition of ItgA6 or ItgB1 function with neutralizing antibodies fully blocked the invasiveness of Amdc-s cells, and importantly also human HT-1080 fibrosarcoma cells, in three-dimensional (3D)-Matrigel mimicking tumor extracellular matrix (ECM). By immunohistochemical analyses, strong staining for ITGA6 was detected in human high-grade fibrosarcomas and other sarcomas, especially at the invasion fronts of the tumors. In the studied melanoma cell lines, the expression levels of the adhesion-related ECM proteins tenascin-C (TN-C), fibronectin (FN), and transforming growth factor beta-induced (TGFBI) were found to be highly up-regulated. By immunohistochemistry, intense TN-C and FN staining was detected in invasive and metastatic melanoma tumors, showing co-localization (together with procollagen-I) in tubular meshworks and channels around the invading melanoma cells. In vitro, TN-C and FN were further found to directly stimulate the migration of melanoma cells in 3D-collagen-I matrix. The third candidate protein, TGFBI, was found to be an anti-adhesive molecule for melanoma cells, and knockdown of its expression in metastatic melanoma cells (TGFBI-KD cells) led to dramatically impaired tumor growth in immunocompromized mice. Interestingly, the control tumors showed intense TGFBI immunostaining in the invasion fronts, showing partial co-localization with the fibrillar FN staining, whereas the small TGFBI-KD cell-induced tumors displayed amorphous, non-fibrillar FN staining. These data suggest an important role for TGFBI in FN fibrillogenesis and melanoma progression. In conclusion, we have identified several invasion-related molecules, which show potential for cancer diagnostic or prognostic markers, or therapeutic targets. Based on our previous and present fibrosarcoma studies, we propose the possibility of using ITGA6 antagonists (affecting tumor cell adhesion) in combination with TB4 inhibitors (affecting tumor cell migration) and cathepsin L inhibitors (affecting the degradation of basement membrane and ECM proteins) for the treatment of fibrosarcomas and other tumors overexpressing these molecules. With melanoma cells, in turn, we point to the importance of three secreted ECM proteins, TN-C, FN, and TGFBI, in melanoma progression. Of these, especially the potential of TN-C as a prognostic melanoma biomarker and TGFBI as a promising therapeutic target molecule are clearly worth additional studies.