Bayes factor based speaker clustering for speaker diarization

This paper proposes the use of the Bayes Factor to replace the Bayesian Information Criterion (BIC) as a criterion for speaker clustering within a speaker diarization system. The BIC is one of the most popular decision criteria used in speaker diarization systems today. However, it will be shown in this paper that the BIC is only an approximation to the Bayes factor of marginal likelihoods of the data given each hypothesis. This paper uses the Bayes factor directly as a decision criterion for speaker clustering, thus removing the error introduced by the BIC approximation. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, leading to a 14.7% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system.

Yield-factor volatility models

The term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the shape of the yield curve. In this paper, we develop a comprehensive model for volatility dynamics in the level, slope, and curvature of the yield curve that simultaneously includes level and GARCH effects along with regime shifts. We show that the level of the short rate is useful in modeling the volatility of the three yield factors and that there are significant GARCH effects present even after including a level effect. Further, we find that allowing for regime shifts in the factor volatilities dramatically improves the model’s fit and strengthens the level effect. We also show that a regime-switching model with level and GARCH effects provides the best out-of-sample forecasting performance of yield volatility. We argue that the auxiliary models often used to estimate term structure models with simulation-based estimation techniques should be consistent with the main features of the yield curve that are identified by our model.

Brain-derived neurotrophic factor (BDNF) gene : no major impact on antidepressant treatment response

The brain-derived neurotrophic factor (BDNF) has been suggested to play a pivotal role in the aetiology of affective disorders. In order to further clarify the impact of BDNF gene variation on major depression as well as antidepressant treatment response, association of three BDNF polymorphisms [rs7103411, Val66Met (rs6265) and rs7124442] with major depression and antidepressant treatment response was investigated in an overall sample of 268 German patients with major depression and 424 healthy controls. False discovery rate (FDR) was applied to control for multiple testing. Additionally, ten markers in BDNF were tested for association with citalopram outcome in the STAR*D sample. While BDNF was not associated with major depression as a categorical diagnosis, the BDNF rs7124442 TT genotype was significantly related to worse treatment outcome over 6 wk in major depression (p=0.01) particularly in anxious depression (p=0.003) in the German sample. However, BDNF rs7103411 and rs6265 similarly predicted worse treatment response over 6 wk in clinical subtypes of depression such as melancholic depression only (rs7103411: TT

The contribution of different androgen receptor domains to receptor dimerization and signaling

The androgen receptor (AR) is a ligand-activated transcription factor of the nuclear receptor superfamily that plays a critical role in male physiology and pathology. Activated by binding of the native androgens testosterone and 5-dihydrotestosterone, the AR regulates transcription of genes involved in the development and maintenance of male phenotype and male reproductive function as well as other tissues such as bone and muscle. Deregulation of AR signaling can cause a diverse range of clinical conditions, including the X-linked androgen insensitivity syndrome, a form of motor neuron disease known as Kennedy’s disease, and male infertility. In addition, there is now compelling evidence that the AR is involved in all stages of prostate tumorigenesis including initiation, progression, and treatment resistance. To better understand the role of AR signaling in the pathogenesis of these conditions, it is important to have a comprehensive understanding of the key determinants of AR structure and function. Binding of androgens to the AR induces receptor dimerization, facilitating DNA binding and the recruitment of cofactors and transcriptional machinery to regulate expression of target genes. Various models of dimerization have been described for the AR, the most well characterized interaction being DNA-binding domain- mediated dimerization, which is essential for the AR to bind DNA and regulate transcription. Additional AR interactions with potential to contribute to receptor dimerization include the intermolecular interaction between the AR amino terminal domain and ligand-binding domain known as the N-terminal/C-terminal interaction, and ligand-binding domain dimerization. In this review, we discuss each form of dimerization utilized by the AR to achieve transcriptional competence and highlight that dimerization through multiple domains is necessary for optimal AR signaling.

Autocrine fibroblast growth factor 2 increases the multipotentiality of human adipose-derived mesenchymal stem cells

Multipotent mesenchymal stem cells (MSCs), first identified in the bone marrow, have subsequently been found in many other tissues, including fat, cartilage, muscle, and bone. Adipose tissue has been identified as an alternative to bone marrow as a source for the isolation of MSCs, as it is neither limited in volume nor as invasive in the harvesting. This study compares the multipotentiality of bone marrow-derived mesenchymal stem cells (BMSCs) with that of adipose-derived mesenchymal stem cells (AMSCs) from 12 age- and sex-matched donors. Phenotypically, the cells are very similar, with only three surface markers, CD106, CD146, and HLA-ABC, differentially expressed in the BMSCs. Although colony-forming units-fibroblastic numbers in BMSCs were higher than in AMSCs, the expression of multiple stem cell-related genes, like that of fibroblast growth factor 2 (FGF2), the Wnt pathway effectors FRAT1 and frizzled 1, and other self-renewal markers, was greater in AMSCs. Furthermore, AMSCs displayed enhanced osteogenic and adipogenic potential, whereas BMSCs formed chondrocytes more readily than AMSCs. However, by removing the effects of proliferation from the experiment, AMSCs no longer out-performed BMSCs in their ability to undergo osteogenic and adipogenic differentiation. Inhibition of the FGF2/fibroblast growth factor receptor 1 signaling pathway demonstrated that FGF2 is required for the proliferation of both AMSCs and BMSCs, yet blocking FGF2 signaling had no direct effect on osteogenic differentiation. Disclosure of potential conflicts of interest is found at the end of this article.

A new future for growth factor complexes as wound therapies?

Background: Topical administration of growth factors (GFs) has displayed some potential in wound healing, but variable efficacy, high doses and costs have hampered their implementation. Moreover, this approach ignores the fact that wound repair is driven by interactions between multiple GFs and extracellular matrix (ECM) proteins. The Problem: Deep dermal partial thickness burn (DDPTB) injuries are the most common burn presentation to pediatric hospitals and also represent the most difficult burn injury to manage clinically. DDPTB often repair with a hypertrophic scar. Wounds that close rapidly exhibit reduced scarring. Thus treatments that shorten the time taken to close DDTPB’s may coincidently reduce scarring. Basic/Clinical Science Advances: We have observed that multi-protein complexes comprised of IGF and IGF-binding proteins bound to the ECM protein vitronectin (VN) significantly enhance cellular functions relevant to wound repair in human skin keratinocytes. These responses require activation of both the IGF-1R and the VN-binding αv integrins. We have recently evaluated the wound healing potential of these GF:VN complexes in a porcine model of DDTPB injury. Clinical Care Relevance: This pilot study demonstrates that GF:VN complexes hold promise as a wound healing therapy. Enhanced healing responses were observed after treatment with nanogram doses of the GF:VN complexes in vitro and in vivo. Critically healing was achieved using substantially less GF than studies in which GFs alone have been used. Conclusion: These data suggest that coupling GFs to ECM proteins, such as VN, may ultimately prove to be an improved technique for the delivery of novel GF-based wound therapies.

A confirmatory factor analysis of the Toronto Alexithymia Scale (TAS-20) in an alcohol-dependent sample

Confirmatory factor analyses were conducted to evaluate the factorial validity of the Toronto Alexithymia Scale in an alcohol-dependent sample. Several factor models were examined, but all models were rejected given their poor fit. A revision of the TAS-20 in alcohol-dependent populations may be needed.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

Molecular markers of obesity and diabetes

Recently it has been shown that the consumption of a diet high in saturated fat is associated with impaired insulin sensitivity and increased incidence of type 2 diabetes. In contrast, diets that are high in monounsaturated fatty acids (MUFAs) or polyunsaturated fatty acids (PUFAs), especially very long chain n-3 fatty acids (FAs), are protective against disease. However, the molecular mechanisms by which saturated FAs induce the insulin resistance and hyperglycaemia associated with metabolic syndrome and type 2 diabetes are not clearly defined. It is possible that saturated FAs may act through alternative mechanisms compared to MUFA and PUFA to regulate of hepatic gene expression and metabolism. It is proposed that, like MUFA and PUFA, saturated FAs regulate the transcription of target genes. To test this hypothesis, hepatic gene expression analysis was undertaken in a human hepatoma cell line, Huh-7, after exposure to the saturated FA, palmitate. These experiments showed that palmitate is an effective regulator of gene expression for a wide variety of genes. A total of 162 genes were differentially expressed in response to palmitate. These changes not only affected the expression of genes related to nutrient transport and metabolism, they also extend to other cellular functions including, cytoskeletal architecture, cell growth, protein synthesis and oxidative stress response. In addition, this thesis has shown that palmitate exposure altered the expression patterns of several genes that have previously been identified in the literature as markers of risk of disease development, including CVD, hypertension, obesity and type 2 diabetes. The altered gene expression patterns associated with an increased risk of disease include apolipoprotein-B100 (apo-B100), apo-CIII, plasminogen activator inhibitor 1, insulin-like growth factor-I and insulin-like growth factor binding protein 3. This thesis reports the first observation that palmitate directly signals in cultured human hepatocytes to regulate expression of genes involved in energy metabolism as well as other important genes. Prolonged exposure to long-chain saturated FAs reduces glucose phosphorylation and glycogen synthesis in the liver. Decreased glucose metabolism leads to elevated rates of lipolysis, resulting in increased release of free FAs. Free FAs have a negative effect on insulin action on the liver, which in turn results in increased gluconeogenesis and systemic dyslipidaemia. It has been postulated that disruption of glucose transport and insulin secretion by prolonged excessive FA availability might be a non-genetic factor that has contributed to the staggering rise in prevalence of type 2 diabetes. As glucokinase (GK) is a key regulatory enzyme of hepatic glucose metabolism, changes in its activity may alter flux through the glycolytic and de novo lipogenic pathways and result in hyperglycaemia and ultimately insulin resistance. This thesis investigated the effects of saturated FA on the promoter activity of the glycolytic enzyme, GK, and various transcription factors that may influence the regulation of GK gene expression. These experiments have shown that the saturated FA, palmitate, is capable of decreasing GK promoter activity. In addition, quantitative real-time PCR has shown that palmitate incubation may also regulate GK gene expression through a known FA sensitive transcription factor, sterol regulatory element binding protein-1c (SREBP-1c), which upregulates GK transcription. To parallel the investigations into the mechanisms of FA molecular signalling, further studies of the effect of FAs on metabolic pathway flux were performed. Although certain FAs reduce SREBP-1c transcription in vitro, it is unclear whether this will result in decreased GK activity in vivo where positive effectors of SREBP-1c such as insulin are also present. Under these conditions, it is uncertain if the inhibitory effects of FAs would be overcome by insulin. The effects of a combination of FAs, insulin and glucose on glucose phosphorylation and metabolism in cultured primary rat hepatocytes at concentrations that mimic those in the portal circulation after a meal was examined. It was found that total GK activity was unaffected by an increased concentration of insulin, but palmitate and eicosapentaenoic acid significantly lowered total GK activity in the presence of insulin. Despite the fact that total GK enzyme activity was reduced in response to FA incubation, GK enzyme translocation from the inactive, nuclear bound, to active, cytoplasmic state was unaffected. Interestingly, none of the FAs tested inhibited glucose phosphorylation or the rate of glycolysis when insulin is present. These results suggest that in the presence of insulin the levels of the active, unbound cytoplasmic GK are sufficient to buffer a slight decrease in GK enzyme activity and decreased promoter activity caused by FA exposure. Although a high fat diet has been associated with impaired hepatic glucose metabolism, there is no evidence from this thesis that FAs themselves directly modulate flux through the glycolytic pathway in isolated primary hepatocytes when insulin is also present. Therefore, although FA affected expression of a wide range of genes, including GK, this did not affect glycolytic flux in the presence of insulin. However, it may be possible that a saturated FA-induced decrease in GK enzyme activity when combined with the onset of insulin resistance may promote the dys-regulation of glucose homeostasis and the subsequent development of hyperglycaemia, metabolic syndrome and type 2 diabetes.

The mechanism of maturation of insulin-like growth factor-1

This study, to elucidate the role of des(1-3)IGF-I in the maturation of IGF-I,used two strategies. The first was to detect the presence of enzymes in tissues, which would act on IGF-I to produce des(1-3)IGF-I, and the second was to detect the potential products of such enzymic activity, namely Gly-Pro-Glu(GPE), Gly-Pro(GP) and des(l- 3)IGF-I. No neutral tripeptidyl peptidase (TPP II), which would release the tripeptide GPE from IGF-I, was detected in brain, urine nor in red or white blood cells. The TPPlike activity which was detected, was attributed to a combined action of a dipeptidyl peptidase (DPP N) and an aminopeptidase (AP A). A true TPP II was, however, detected in platelets. Two purified TPP II enzymes were investigated but they did not release GPE from IGF-I under a variety of conditions. Consequently, TPP II seemed unlikely to participate in the formation of des(1-3)IGF-I. In contrast, an acidic tripeptidyl peptidase activity (TPP I) was detected in brain and colostrum, the former with a pH optimum of 4.5 and the latter 3.8. It seems likely that such an enzyme would participate in the formation of des( 1-3 )IGF-I in these tissues in vitro, ie. that des(1-3)IGF-I may have been produced as an artifact in the isolation of IGF-I from brain and colostrum in acidic conditions. This contrasts with suggestions of an in vivo role for des(1-3)IGF-I, as reported by others. The activity of a dipeptidyl peptidase N (DPP N) from urine, which should release the dipeptide GP from IGF-I, was assessed under a variety of conditions and with a variety of additives and potential enzyme stimulants, but there was no release of GP. The DPP N also exhibited a transferase activity with synthetic substrates in the presence of dipeptides, at lower concentrations than previously reported for other acceptors or other proteolytic enzymes. In addition, a low concentration of a product,possibly the tetrapeptide Gly-Pro-Gly-Leu, was detected with the action of the enzyme on IGF-I in the presence of the dipeptide Gly-Leu. As part of attempts to detect tissue production of des(1-3)IGF-I, a monoclonal antibody (MAb ), directed towards the GPE- end ofiGF-I was produced by immunisation with a 10-mer covalently attached to a carrier protein. By the use of indirect ELISA and inhibitor studies, the MAb was shown to selectively recognise peptides with anNterminal GPE- sequence, and applied to the indirect detection of des(1-3)IGF-I. The concentration of GPE in brain, measured by mass spectrometry ( MS), was low, and the concentration of total IGF-I (measured by ELISA with a commercial polyclonal antibody [P Ab]) was 40 times higher at 50 nmol/kg. This also, was not consistent with the action of a tripeptidyl peptidase in brain that converted all IGF-I to des(1-3)IGF-I plus GPE. Contrasting ELISA results, using the MAb prepared in this study, suggest an even higher concentration of intact IGF-I of 150 nmollkg. This would argue against the presence of any des( 1-3 )IGF-I in brain, but in turn, this indicates either the presence of other substances containing a GPE amino-terminus or other cross reacting epitope. Although the results of the specificity studies reported in Chapter 5 would make this latter possibility seem unlikely, it cannot be completely excluded. No GP was detected in brain by MS. No GPE was detected in colostrum by capillary electrophoresis (CE) but the interference from extraneous substances reduced the detectability of GPE by CE and this approach would require further, prior, purification and concentration steps. A molecule, with a migration time equal to that of the peptide GP, was detected in colostrum by CE, but the concentration (~ 10 11mo/L) was much higher than the IGF-I concentration measured by radio-immunoassay using a PAb (80 nmol/L) or using a Mab (300-400 nmolL). A DPP IV enzyme was detected in colostrum and this could account for the GP, derived from substrates other than IGF-1. Based on the differential results of the two antibody assays, there was no indication of the presence of des(1-3)IGF-I in brain or colostrum. In the absence of any enzyme activity directed towards the amino terminus of IGF-I and the absence any potential products, IGF-I, therefore, does not appear to "mature" via des(1-3)IGF-I in the brain, nor in the neutral colostrum. In spite of these results which indicate the absence of an enzymic attack on IGF-I and the absence of the expected products in tissues, the possibility that the conversion of IGF-I may occur in neutral conditions in limited amounts, cannot be ruled out. It remains possible that in the extracellular environment of the membrane, a complex interaction of IGF-I, binding protein, aminopeptidase(s) and receptor, produces des(1- 3)IGF-I as a transient product which is bound to the receptor and internalised.

A study of water binding, mobility and dehydration in contact lens hydrogels using NMR

Hydrogel polymers are used for the manufacture of soft (or disposable) contact lenses worldwide today, but have a tendency to dehydrate on the eye. In vitro methods that can probe the potential for a given hydrogel polymer to dehydrate in vivo are much sought after. Nuclear magnetic resonance (NMR) has been shown to be effective in characterising water mobility and binding in similar systems (Barbieri, Quaglia et al., 1998, Larsen, Huff et al., 1990, Peschier, Bouwstra et al., 1993), predominantly through measurement of the spin-lattice relaxation time (T1), the spinspin relaxation time (T2) and the water diffusion coefficient (D). The aim of this work was to use NMR to quantify the molecular behaviour of water in a series of commercially available contact lens hydrogels, and relate these measurements to the binding and mobility of the water, and ultimately the potential for the hydrogel to dehydrate. As a preliminary study, in vitro evaporation rates were measured for a set of commercial contact lens hydrogels. Following this, comprehensive measurement of the temperature and water content dependencies of T1, T2 and D was performed for a series of commercial hydrogels that spanned the spectrum of equilibrium water content (EWC) and common compositions of contact lenses that are manufactured today. To quantify material differences, the data were then modelled based on theory that had been used for similar systems in the literature (Walker, Balmer et al., 1989, Hills, Takacs et al., 1989). The differences were related to differences in water binding and mobility. The evaporative results suggested that the EWC of the material was important in determining a material's potential to dehydrate in this way. Similarly, the NMR water self-diffusion coefficient was also found to be largely (if not wholly) determined by the WC. A specific binding model confirmed that the we was the dominant factor in determining the diffusive behaviour, but also suggested that subtle differences existed between the materials used, based on their equilibrium we (EWC). However, an alternative modified free volume model suggested that only the current water content of the material was important in determining the diffusive behaviour, and not the equilibrium water content. It was shown that T2 relaxation was dominated by chemical exchange between water and exchangeable polymer protons for materials that contained exchangeable polymer protons. The data was analysed using a proton exchange model, and the results were again reasonably correlated with EWC. Specifically, it was found that the average water mobility increased with increasing EWe approaching that of free water. The T1 relaxation was also shown to be reasonably well described by the same model. The main conclusion that can be drawn from this work is that the hydrogel EWe is an important parameter, which largely determines the behaviour of water in the gel. Higher EWe results in a hydrogel with water that behaves more like bulk water on average, or is less strongly 'bound' on average, compared with a lower EWe material. Based on the set of materials used, significant differences due to composition (for materials of the same or similar water content) could not be found. Similar studies could be used in the future to highlight hydrogels that deviate significantly from this 'average' behaviour, and may therefore have the least/greatest potential to dehydrate on the eye.