Comparison of decision tree, support vector machines, and Bayesian network approaches for classification of falls in Parkinson’s disease

Being able to accurately predict the risk of falling is crucial in patients with Parkinson’s dis- ease (PD). This is due to the unfavorable effect of falls, which can lower the quality of life as well as directly impact on survival. Three methods considered for predicting falls are decision trees (DT), Bayesian networks (BN), and support vector machines (SVM). Data on a 1-year prospective study conducted at IHBI, Australia, for 51 people with PD are used. Data processing are conducted using rpart and e1071 packages in R for DT and SVM, con- secutively; and Bayes Server 5.5 for the BN. The results show that BN and SVM produce consistently higher accuracy over the 12 months evaluation time points (average sensitivity and specificity > 92%) than DT (average sensitivity 88%, average specificity 72%). DT is prone to imbalanced data so needs to adjust for the misclassification cost. However, DT provides a straightforward, interpretable result and thus is appealing for helping to identify important items related to falls and to generate fallers’ profiles.

Insights into the growth of newly formed particles in a subtropical urban environment

The role of different chemical compounds, particularly organics, involved in the new particle formation (NPF) and its consequent growth are not fully understood. Therefore, this study was conducted to investigate the chemical composition of aerosol particles during NPF events in an urban subtropical environment. Aerosol chemical composition was measured along with particle number size distribution (PNSD) and several other air quality parameters at five sites across an urban subtropical environment. An Aerodyne compact Time-of-Flight Aerosol Mass Spectrometer (c-TOF-AMS) and a TSI Scanning Mobility Particle Sizer (SMPS) measured aerosol chemical composition (particles above 50 nm in vacuum aerodynamic diameter) and PNSD (particles within 9-414 nm in mobility diameter), respectively. Five NPF events, with growth rates in the range 3.3-4.6 nm, were detected at two of the sites. The NPF events happened on relatively warmer days with lower condensation sink (CS). Temporal percent fractions of organics increased after the particles grew enough to have a significant contribution to particles volume, while the mass fraction of ammonium and sulphate decreased. This uncovered the important role of organics in the growth of newly formed particles. Three organic markers, factors f43, f44 and f57, were calculated and the f44 vs f43 trends were compared between nucleation and non-nucleation days. K-means cluster analysis was performed on f44 vs f43 data and it was found that they follow different patterns on nucleation days compared to non-nucleation days, whereby f43 decreased for vehicle emission generated particles, while both f44 and f43 decreased for NPF generated particles. It was found for the first time that vehicle generated and newly formed particles cluster in different locations on f44 vs f43 plot and this finding can be potentially used as a tool for source apportionment of measured particles.

Senataxin controls meiotic silencing through ATR activation and chromatin remodeling

Senataxin, defective in ataxia oculomotor apraxia type 2, protects the genome by facilitating the resolution of RNA–DNA hybrids (R-loops) and other aspects of RNA processing. Disruption of this gene in mice causes failure of meiotic recombination and defective meiotic sex chromosome inactivation, leading to male infertility. Here we provide evidence that the disruption of Setx leads to reduced SUMOylation and disruption of protein localization across the XY body during meiosis. We demonstrate that senataxin and other DNA damage repair proteins, including ataxia telangiectasia and Rad3-related protein-interacting partner, are SUMOylated, and a marked downregulation of both ataxia telangiectasia and Rad3-related protein-interacting partner and TopBP1 leading to defective activation and signaling through ataxia telangiectasia and Rad3-related protein occurs in the absence of senataxin. Furthermore, chromodomain helicase DNA-binding protein 4, a component of the nucleosome remodeling and deacetylase chromatin remodeler that interacts with both ataxia telangiectasia and Rad3-related protein and senataxin was not recruited efficiently to the XY body, triggering altered histone acetylation and chromatin conformation in Setx−/− pachytene-staged spermatocytes. These results demonstrate that senataxin has a critical role in ataxia telangiectasia and Rad3-related protein- and chromodomain helicase DNA-binding protein 4-mediated transcriptional silencing and chromatin remodeling during meiosis providing greater insight into its critical role in gene regulation to protect against neurodegeneration.

R U there yet? using virtual classrooms to transform teaching practice

Access to quality higher education is challenging for many Western Australians that live outside the metropolitan area. In 2010, the School of Education moved to flexible delivery of a fully online Bachelor of Education degree for their non -metropolitan students. The new model of delivery allows access for students from any location provided they have a computer and an internet connection. A number of academic staff had previously used an asynchronous environment to deliver learning modules housed within a learning management system (LMS) but had not used synchronous software with their students. To enhance the learning environment and to provide high quality learning experiences to students learning at a distance, the adoption of synchronous software (Elluminate Live) was introduced. This software is a real-time virtual classroom environment that allows for communication through Voice over Internet Protocol (VoIP) and videoconferencing, along with a large number of collaboration tools to engage learners. This research paper reports on the integration of a live e-learning solution into the current LMS environment. Qualitative data were collected from academic staff through informal interviews and participant observation. The findings discuss (i) perceived level of support; (ii) identification of strategies used to create an effective online teacher presence; (iii) the perceived impact on the students' learning outcomes; and (iv) guidelines for professional development to enhance pedagogy within the live e-learning environment.

PolyPatEx : an R package for paternity exclusion in autopolyploids

Microsatellite markers have demonstrated their value for performing paternity exclusion and hence exploring mating patterns in plants and animals. Methodology is well established for diploid species, and several software packages exist for elucidating paternity in diploids; however, these issues are not so readily addressed in polyploids due to the increased complexity of the exclusion problem and a lack of available software. We introduce polypatex, an r package for paternity exclusion analysis using microsatellite data in autopolyploid, monoecious or dioecious/bisexual species with a ploidy of 4n, 6n or 8n. Given marker data for a set of offspring, their mothers and a set of candidate fathers, polypatex uses allele matching to exclude candidates whose marker alleles are incompatible with the alleles in each offspring–mother pair. polypatex can analyse marker data sets in which allele copy numbers are known (genotype data) or unknown (allelic phenotype data) – for data sets in which allele copy numbers are unknown, comparisons are made taking into account all possible genotypes that could arise from the compared allele sets. polypatex is a software tool that provides population geneticists with the ability to investigate the mating patterns of autopolyploids using paternity exclusion analysis on data from codominant markers having multiple alleles per locus.

Antigen-specific CD4 cells assist CD8 T-effector cells in eliminating keratinocytes

Keratinocytes expressing tumor or viral antigens can be eliminated by antigen-primed CD8 cytotoxic T cells. CD4 T-helper cells help induction of CD8 cytotoxic T cells from naive precursors and generation of CD8 T-cell memory. In this study, we show, unexpectedly, that CD4 cells are also required to assist primed CD8 effector T cells in rejection of skin expressing human growth hormone, a neo-self-antigen, in keratinocytes. The requirement for CD4 cells can be substituted by CD40 costimulation. Rejection of skin expressing ovalbumin (OVA), a non-self-antigen, by primed CD8 cytotoxic T cells can in contrast occur without help from antigen-specific CD4 T cells. However, rejection of OVA expressing keratinocytes is helped by antigen-specific CD4 T cells if only low numbers of primed or naive OVA-specific CD8 T cells are available. Effective immunotherapy directed at antigens expressed in squamous cancer may therefore be facilitated by induction of tumor antigen-specific CD4 helper T cells, as well as cytotoxic CD8 T cells.

A combination of local inflammation and central memory T cells potentiates immunotherapy in the skin

Adoptive T cell therapy uses the specificity of the adaptive immune system to target cancer and virally infected cells. Yet the mechanism and means by which to enhance T cell function are incompletely described, especially in the skin. In this study, we use a murine model of immunotherapy to optimize cell-mediated immunity in the skin. We show that in vitro - derived central but not effector memory-like T cells bring about rapid regression of skin-expressing cognate Ag as a transgene in keratinocytes. Local inflammation induced by the TLR7 receptor agonist imiquimod subtly yet reproducibly decreases time to skin graft rejection elicited by central but not effector memory T cells in an immunodeficient mouse model. Local CCL4, a chemokine liberated by TLR7 agonism, similarly enhances central memory T cell function. In this model, IL-2 facilitates the development in vivo of effector function from central memory but not effector memory T cells. In a model of T cell tolerogenesis, we further show that adoptively transferred central but not effector memory T cells can give rise to successful cutaneous immunity, which is dependent on a local inflammatory cue in the target tissue at the time of adoptive T cell transfer. Thus, adoptive T cell therapy efficacy can be enhanced if CD8+ T cells with a central memory T cell phenotype are transferred, and IL-2 is present with contemporaneous local inflammation. Copyright © 2012 by The American Association of Immunologists, Inc.

Early school-based parent involvement, children’s self-regulated learning and academic achievement: An Australian longitudinal study

Parent involvement is widely accepted as being associated with children’s improved educational outcomes. However, the role of early school-based parent involvement is still being established. This study investigated the mediating role of self-regulated learning behaviors in the relationship between early school-based parent involvement and children’s academic achievement, using data from the Longitudinal Study of Australian Children (N = 2616). Family socioeconomic position, Aboriginal and Torres Strait Islander status, language background, child gender and cognitive competence, were controlled, as well home and community based parent involvement activity in order to derive a more confident interpretation of the results. Structural equation modeling analyses showed that children’s self-regulated learning behaviors fully mediated the relationships between school-based parent involvement at Grade 1 and children’s reading achievement at Grade 3. Importantly, these relationships were evident for children across all socio-economic backgrounds. Although there was no direct relationship between parent involvement at Grade 1 and numeracy achievement at Grade 3, parent involvement was indirectly associated with higher children’s numeracy achievement through children’s self-regulation of learning behaviors, though this relationship was stronger for children from middle and higher socio-economic backgrounds. Implications for policy and practice are discussed, and further research recommended.

Prediction of individual genetic risk to prostate cancer using a polygenic score

BACKGROUND Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction. Prostate 75:1467–1474, 2015. © 2015 Wiley Periodicals, Inc.

The effects of height and BMI on prostate cancer incidence and mortality: A Mendelian randomization study in 20,848 cases and 20,214 controls from the PRACTICAL consortium

Background Epidemiological studies suggest a potential role for obesity and determinants of adult stature in prostate cancer risk and mortality, but the relationships described in the literature are complex. To address uncertainty over the causal nature of previous observational findings, we investigated associations of height- and adiposity-related genetic variants with prostate cancer risk and mortality. Methods We conducted a case–control study based on 20,848 prostate cancers and 20,214 controls of European ancestry from 22 studies in the PRACTICAL consortium. We constructed genetic risk scores that summed each man’s number of height and BMI increasing alleles across multiple single nucleotide polymorphisms robustly associated with each phenotype from published genome-wide association studies. Results The genetic risk scores explained 6.31 and 1.46 % of the variability in height and BMI, respectively. There was only weak evidence that genetic variants previously associated with increased BMI were associated with a lower prostate cancer risk (odds ratio per standard deviation increase in BMI genetic score 0.98; 95 % CI 0.96, 1.00; p = 0.07). Genetic variants associated with increased height were not associated with prostate cancer incidence (OR 0.99; 95 % CI 0.97, 1.01; p = 0.23), but were associated with an increase (OR 1.13; 95 % CI 1.08, 1.20) in prostate cancer mortality among low-grade disease (p heterogeneity, low vs. high grade <0.001). Genetic variants associated with increased BMI were associated with an increase (OR 1.08; 95 % CI 1.03, 1.14) in all-cause mortality among men with low-grade disease (p heterogeneity = 0.03). Conclusions We found little evidence of a substantial effect of genetically elevated height or BMI on prostate cancer risk, suggesting that previously reported observational associations may reflect common environmental determinants of height or BMI and prostate cancer risk. Genetically elevated height and BMI were associated with increased mortality (prostate cancer-specific and all-cause, respectively) in men with low-grade disease, a potentially informative but novel finding that requires replication.

A rare P2X7 variant Arg307Gln with absent pore formation function protects against neuroinflammation in multiple sclerosis

Multiple sclerosis (MS) is a chronic relapsing-remitting inflammatory disease of the central nervous system characterized by oligodendrocyte damage, demyelination and neuronal death. Genetic association studies have shown a 2-fold or greater prevalence of the HLA-DRB1*1501 allele in the MS population compared with normal Caucasians. In discovery cohorts of Australasian patients with MS (total 2941 patients and 3008 controls), we examined the associations of 12 functional polymorphisms of P2X7, a microglial/macrophage receptor with proinflammatory effects when activated by extracellular adenosine triphosphate (ATP). In discovery cohorts, rs28360457, coding for Arg307Gln was associated with MS and combined analysis showed a 2-fold lower minor allele frequency compared with controls (1.11% for MS and 2.15% for controls, P = 0.0000071). Replication analysis of four independent European MS case–control cohorts (total 2140 cases and 2634 controls) confirmed this association [odds ratio (OR) = 0.69, P = 0.026]. A meta-analysis of all Australasian and European cohorts indicated that Arg307Gln confers a 1.8-fold protective effect on MS risk (OR = 0.57, P = 0.0000024). Fresh human monocytes heterozygous for Arg307Gln have >85% loss of ‘pore’ function of the P2X7 receptor measured by ATP-induced ethidium uptake. Analysis shows Arg307Gln always occurred with 270His suggesting a single 307Gln–270His haplotype that confers dominant negative effects on P2X7 function and protection against MS. Modeling based on the homologous zP2X4 receptor showed Arg307 is located in a region rich in basic residues located only 12 Å from the ligand binding site. Our data show the protective effect against MS of a rare genetic variant of P2RX7 with heterozygotes showing near absent proinflammatory ‘pore’ function.

R&D in clean technology: A project choice model with learning

In this study, we investigate the qualitative and quantitative effects of an R&D subsidy for a clean technology and a Pigouvian tax on a dirty technology on environmental R&D when it is uncertain how long the research takes to complete. The model is formulated as an optimal stopping problem, in which the number of successes required to complete the R&D project is finite and learning about the probability of success is incorporated. We show that the optimal R&D subsidy with the consideration of learning is higher than that without it. We also find that an R&D subsidy performs better than a Pigouvian tax unless suppliers have sufficient incentives to continue cost-reduction efforts after the new technology success-fully replaces the old one. Moreover, by using a two-project model, we show that a uniform subsidy is better than a selective subsidy.