Biochemical characterization of Aprataxin, the protein deficient in Ataxia with Oculomotor Apraxia type 1

Neurodegenerative disorders are heterogenous in nature and include a range of ataxias with oculomotor apraxia, which are characterised by a wide variety of neurological and ophthalmological features. This family includes recessive and dominant disorders. A subfamily of autosomal recessive cerebellar ataxias are characterised by defects in the cellular response to DNA damage. These include the well characterised disorders Ataxia-Telangiectasia (A-T) and Ataxia-Telangiectasia Like Disorder (A-TLD) as well as the recently identified diseases Spinocerebellar ataxia with axonal neuropathy Type 1 (SCAN1), Ataxia with Oculomotor Apraxia Type 2 (AOA2), as well as the subject of this thesis, Ataxia with Oculomotor Apraxia Type 1 (AOA1). AOA1 is caused by mutations in the APTX gene, which is located at chromosomal locus 9p13. This gene codes for the 342 amino acid protein Aprataxin. Mutations in APTX cause destabilization of Aprataxin, thus AOA1 is a result of Aprataxin deficiency. Aprataxin has three functional domains, an N-terminal Forkhead Associated (FHA) phosphoprotein interaction domain, a central Histidine Triad (HIT) nucleotide hydrolase domain and a C-terminal C2H2 zinc finger. Aprataxins FHA domain has homology to FHA domain of the DNA repair protein 5’ polynucleotide kinase 3’ phosphatase (PNKP). PNKP interacts with a range of DNA repair proteins via its FHA domain and plays a critical role in processing damaged DNA termini. The presence of this domain with a nucleotide hydrolase domain and a DNA binding motif implicated that Aprataxin may be involved in DNA repair and that AOA1 may be caused by a DNA repair deficit. This was substantiated by the interaction of Aprataxin with proteins involved in the repair of both single and double strand DNA breaks (XRay Cross-Complementing 1, XRCC4 and Poly-ADP Ribose Polymerase-1) and the hypersensitivity of AOA1 patient cell lines to single and double strand break inducing agents. At the commencement of this study little was known about the in vitro and in vivo properties of Aprataxin. Initially this study focused on generation of recombinant Aprataxin proteins to facilitate examination of the in vitro properties of Aprataxin. Using recombinant Aprataxin proteins I found that Aprataxin binds to double stranded DNA. Consistent with a role for Aprataxin as a DNA repair enzyme, this binding is not sequence specific. I also report that the HIT domain of Aprataxin hydrolyses adenosine derivatives and interestingly found that this activity is competitively inhibited by DNA. This provided initial evidence that DNA binds to the HIT domain of Aprataxin. The interaction of DNA with the nucleotide hydrolase domain of Aprataxin provided initial evidence that Aprataxin may be a DNA-processing factor. Following these studies, Aprataxin was found to hydrolyse 5’adenylated DNA, which can be generated by unscheduled ligation at DNA breaks with non-standard termini. I found that cell extracts from AOA1 patients do not have DNA-adenylate hydrolase activity indicating that Aprataxin is the only DNA-adenylate hydrolase in mammalian cells. I further characterised this activity by examining the contribution of the zinc finger and FHA domains to DNA-adenylate hydrolysis by the HIT domain. I found that deletion of the zinc finger ablated the activity of the HIT domain against adenylated DNA, indicating that the zinc finger may be required for the formation of a stable enzyme-substrate complex. Deletion of the FHA domain stimulated DNA-adenylate hydrolysis, which indicated that the activity of the HIT domain may be regulated by the FHA domain. Given that the FHA domain is involved in protein-protein interactions I propose that the activity of Aprataxins HIT domain may be regulated by proteins which interact with its FHA domain. We examined this possibility by measuring the DNA-adenylate hydrolase activity of extracts from cells deficient for the Aprataxin-interacting DNA repair proteins XRCC1 and PARP-1. XRCC1 deficiency did not affect Aprataxin activity but I found that Aprataxin is destabilized in the absence of PARP-1, resulting in a deficiency of DNA-adenylate hydrolase activity in PARP-1 knockout cells. This implies a critical role for PARP-1 in the stabilization of Aprataxin. Conversely I found that PARP-1 is destabilized in the absence of Aprataxin. PARP-1 is a central player in a number of DNA repair mechanisms and this implies that not only do AOA1 cells lack Aprataxin, they may also have defects in PARP-1 dependant cellular functions. Based on this I identified a defect in a PARP-1 dependant DNA repair mechanism in AOA1 cells. Additionally, I identified elevated levels of oxidized DNA in AOA1 cells, which is indicative of a defect in Base Excision Repair (BER). I attribute this to the reduced level of the BER protein Apurinic Endonuclease 1 (APE1) I identified in Aprataxin deficient cells. This study has identified and characterised multiple DNA repair defects in AOA1 cells, indicating that Aprataxin deficiency has far-reaching cellular consequences. Consistent with the literature, I show that Aprataxin is a nuclear protein with nucleoplasmic and nucleolar distribution. Previous studies have shown that Aprataxin interacts with the nucleolar rRNA processing factor nucleolin and that AOA1 cells appear to have a mild defect in rRNA synthesis. Given the nucleolar localization of Aprataxin I examined the protein-protein interactions of Aprataxin and found that Aprataxin interacts with a number of rRNA transcription and processing factors. Based on this and the nucleolar localization of Aprataxin I proposed that Aprataxin may have an alternative role in the nucleolus. I therefore examined the transcriptional activity of Aprataxin deficient cells using nucleotide analogue incorporation. I found that AOA1 cells do not display a defect in basal levels of RNA synthesis, however they display defective transcriptional responses to DNA damage. In summary, this thesis demonstrates that Aprataxin is a DNA repair enzyme responsible for the repair of adenylated DNA termini and that it is required for stabilization of at least two other DNA repair proteins. Thus not only do AOA1 cells have no Aprataxin protein or activity, they have additional deficiencies in PolyADP Ribose Polymerase-1 and Apurinic Endonuclease 1 dependant DNA repair mechanisms. I additionally demonstrate DNA-damage inducible transcriptional defects in AOA1 cells, indicating that Aprataxin deficiency confers a broad range of cellular defects and highlighting the complexity of the cellular response to DNA damage and the multiple defects which result from Aprataxin deficiency. My detailed characterization of the cellular consequences of Aprataxin deficiency provides an important contribution to our understanding of interlinking DNA repair processes.

Within-session variability modelling for factor analysis speaker verification

This work presents an extended Joint Factor Analysis model including explicit modelling of unwanted within-session variability. The goals of the proposed extended JFA model are to improve verification performance with short utterances by compensating for the effects of limited or imbalanced phonetic coverage, and to produce a flexible JFA model that is effective over a wide range of utterance lengths without adjusting model parameters such as retraining session subspaces. Experimental results on the 2006 NIST SRE corpus demonstrate the flexibility of the proposed model by providing competitive results over a wide range of utterance lengths without retraining and also yielding modest improvements in a number of conditions over current state-of-the-art.

The X-Factor and its relationship to golfing performance

It is often postulated that an increased hip to shoulder differential angle (`X-Factor') during the early downswing better utilises the stretch-shorten cycle and improves golf performance. The current study aims to examine the potential relationship between the X-Factor and performance during the tee-shot. Seven golfers with handicaps between 0 and 10 strokes comprised the low-handicap group, whilst the high-handicap group consisted of eight golfers with handicaps between 11 and 20 strokes. The golfers performed 20 drives and three-dimensional kinematic data were used to quantify hip and shoulder rotation and the subsequent X-Factor. Compared with the low-handicap group, the high-handicap golfers tended to demonstrate greater hip rotation at the top of the backswing and recorded reduced maximum X-Factor values. The inconsistencies evident in the literature may suggest that a universal method of measuring rotational angles during the golf swing would be beneficial for future studies, particularly when considering potential injury.

Low-fat oxidation may be a factor in obesity among men with schizophrenia

Objective: Obesity associated with atypical antipsychotic medications is an important clinical issue for people with schizophrenia. The purpose of this project was to determine whether there were any differences in resting energy expenditure (REE) and respiratory quotient (RQ) between men with schizophrenia and controls. Method: Thirty-one men with schizophrenia were individually matched for age and relative body weight with healthy, sedentary controls. Deuterium dilution was used to determine total body water and subsequently fat-free mass (FFM). Indirect calorimetry using a Deltatrac metabolic cart was used to determine REE and RQ. Results: When corrected for FFM, there was no significant difference in REE between the groups. However, fasting RQ was significantly higher in the men with schizophrenia than the controls. Conclusion: Men with schizophrenia oxidised proportionally less fat and more carbohydrate under resting conditions than healthy controls. These differences in substrate utilisation at rest may be an important consideration in obesity in this clinical group.

Multi-factor password-authenticated key exchange

We consider a new form of authenticated key exchange which we call multi-factor password-authenticated key exchange, where session establishment depends on successful authentication of multiple short secrets that are complementary in nature, such as a long-term password and a one-time response, allowing the client and server to be mutually assured of each other's identity without directly disclosing private information to the other party. Multi-factor authentication can provide an enhanced level of assurance in higher-security scenarios such as online banking, virtual private network access, and physical access because a multi-factor protocol is designed to remain secure even if all but one of the factors has been compromised. We introduce a security model for multi-factor password-authenticated key exchange protocols, propose an efficient and secure protocol called MFPAK, and provide a security argument to show that our protocol is secure in this model. Our security model is an extension of the Bellare-Pointcheval-Rogaway security model for password-authenticated key exchange and accommodates an arbitrary number of symmetric and asymmetric authentication factors.

Vitronectin modulates human mesenchymal stem cell response to insulin-like growth factor-I and transforming growth factor beta 1 in a serum-free environment

The use of animal sera for the culture of therapeutically important cells impedes the clinical use of the cells. We sought to characterize the functional response of human mesenchymal stem cells (hMSCs) to specific proteins known to exist in bone tissue with a view to eliminating the requirement of animal sera. Insulin-like growth factor-I (IGF-I), via IGF binding protein-3 or -5 (IGFBP-3 or -5) and transforming growth factor-beta 1 (TGF-beta(1)) are known to associate with the extracellular matrix (ECM) protein vitronectin (VN) and elicit functional responses in a range of cell types in vitro. We found that specific combinations of VN, IGFBP-3 or -5, and IGF-I or TGF-beta(1) could stimulate initial functional responses in hMSCs and that IGF-I or TGF-beta(1) induced hMSC aggregation, but VN concentration modulated this effect. We speculated that the aggregation effect may be due to endogenous protease activity, although we found that neither IGF-I nor TGF-beta(1) affected the functional expression of matrix metalloprotease-2 or -9, two common proteases expressed by hMSCs. In summary, combinations of the ECM and growth factors described herein may form the basis of defined cell culture media supplements, although the effect of endogenous protease expression on the function of such proteins requires investigation.

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

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.