Latent class and genetic analysis does not support migraine with aura and migraine without aura as separate entities

Latent class and genetic analyses were used to identify subgroups of migraine sufferers in a community sample of 6,265 Australian twins (55% female) aged 25-36 who had completed an interview based on International Headache Society (IHS) criteria. Consistent with prevalence rates from other population-based studies, 703 (20%) female and 250 (9%) male twins satisfied the IHS criteria for migraine without aura (MO), and of these, 432 (13%) female and 166 (6%) male twins satisfied the criteria for migraine with aura (MA) as indicated by visual symptoms. Latent class analysis (LCA) of IHS symptoms identified three major symptomatic classes, representing 1) a mild form of recurrent nonmigrainous headache, 2) a moderately severe form of migraine, typically without visual aura symptoms (although 40% of individuals in this class were positive for aura), and 3) a severe form of migraine typically with visual aura symptoms (although 24% of individuals were negative for aura). Using the LCA classification, many more individuals were considered affected to some degree than when using IHS criteria (35% vs. 13%). Furthermore, genetic model fitting indicated a greater genetic contribution to migraine using the LCA classification (heritability, h(2)=0.40; 95% CI, 0.29-0.46) compared with the IHS classification (h(2)=0.36; 95% CI, 0.22-0.42). Exploratory latent class modeling, fitting up to 10 classes, did not identify classes corresponding to either the IHS MO or MA classification. Our data indicate the existence of a continuum of severity, with MA more severe but not etiologically distinct from MO. In searching for predisposing genes, we should therefore expect to find some genes that may underlie all major recurrent headache subtypes, with modifying genetic or environmental factors that may lead to differential expression of the liability for migraine.

Zygosity diagnosis in the absence of genotypic data: An approach using latent class analysis

For zygosity diagnosis in the absence of genotypic data, or in the recruitment phase of a twin study where only single twins from same-sex pairs are being screened, or to provide a test for sample duplication leading to the false identification of a dizygotic pair as monozygotic, the appropriate analysis of respondents' answers to questions about zygosity is critical. Using data from a young adult Australian twin cohort (N = 2094 complete pairs and 519 singleton twins from same-sex pairs with complete responses to all zygosity items), we show that application of latent class analysis (LCA), fitting a 2-class model, yields results that show good concordance with traditional methods of zygosity diagnosis, but with certain important advantages. These include the ability, in many cases, to assign zygosity with specified probability on the basis of responses of a single informant (advantageous when one zygosity type is being oversampled); and the ability to quantify the probability of misassignment of zygosity, allowing prioritization of cases for genotyping as well as identification of cases of probable laboratory error. Out of 242 twins (from 121 like-sex pairs) where genotypic data were available for zygosity confirmation, only a single case was identified of incorrect zygosity assignment by the latent class algorithm. Zygosity assignment for that single case was identified by the LCA as uncertain (probability of being a monozygotic twin only 76%), and the co-twin's responses clearly identified the pair as dizygotic (probability of being dizygotic 100%). In the absence of genotypic data, or as a safeguard against sample duplication, application of LCA for zygosity assignment or confirmation is strongly recommended.

Phylogenetic lineage and pilus protein Spb1/SAN1518 affect opsonin-independent phagocytosis and intracellular survival of Group B Streptococcus

Opsonin-independent phagocytosis of Group B Streptococcus (GBS) is important in defense against neonatal GBS infections. A recent study indicated a role for GBS pilus in macrophage phagocytosis (Maisey et al Faseb J 22 2008 1715-24). We studied 163 isolates from different phylogenetic backgrounds and those possessing or lacking the gene encoding the pilus backbone protein, Spb1 (SAN1518, PI-2b) and spb1-deficient mutants of wild-type (WT) serotype III-3 GBS 874391 in non-opsonic phagocytosis assays using J774A.1 macrophages. Numbers of GBS phagocytosed differed up to 23-fold depending on phylogenetic background; isolates possessing spb1 were phagocytosed more than isolates lacking spb1. Comparing WT GBS and isogenic spb1-deficient mutants showed WT was phagocytosed better compared to mutants; Spb1 also enhanced intracellular survival as mutants were killed more efficiently. Complementation of mutants restored phagocytosis and resistance to killing in J774A.1 macrophages. Spb1 antiserum revealed surface expression in WT GBS and spatial distribution relative to capsular polysaccharide. spb1 did not affect macrophage nitric oxide and TNF-alpha responses; differences in phagocytosis did not correlate with N-acetyl d-glucosamine (from GBS cell-wall) according to enzyme-linked lectin-sorbent assay. Together, these findings support a role for phylogenetic lineage and Spb1 in opsonin-independent phagocytosis and intracellular survival of GBS in J774A.1 macrophages.

Emotional climate of a pre-service science teacher education class in Bhutan

This study explored pre-service secondary science teachers’ perceptions of classroom emotional climate in the context of the Bhutanese macro-social policy of Gross National Happiness. Drawing upon sociological perspectives of human emotions and using Interaction Ritual Theory this study investigated how pre-service science teachers may be supported in their professional development. It was a multi-method study involving video and audio recordings of teaching episodes supported by interviews and the researcher’s diary. Students also registered their perceptions of the emotional climate of their classroom at 3-minute intervals using audience response technology. In this way, emotional events were identified for video analysis. The findings of this study highlighted that the activities pre-service teachers engaged in matter to them. Positive emotional climate was identified in activities involving students’ presentations using video clips and models, coteaching, and interactive whole class discussions. Decreases in emotional climate were identified during formal lectures and when unprepared presenters led presentations. Emotions such as frustration and disappointment characterized classes with negative emotional climate. The enabling conditions to sustain a positive emotional climate are identified. Implications for sustaining macro-social policy about Gross National Happiness are considered in light of the climate that develops in science teacher education classes.

Classifying patients by their characteristics and clinical presentations; the use of latent class analysis

In this article, we introduce the general statistical analysis approach known as latent class analysis and discuss some of the issues associated with this type of analysis in practice. Two recent examples from the respiratory health literature are used to highlight the types of research questions that have been addressed using this approach.

A Bayesian latent class safety performance function for identifying motor vehicle crash blackspots

The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.

Class-specific sparse codes for representing activities

In this paper we investigate the effectiveness of class specific sparse codes in the context of discriminative action classification. The bag-of-words representation is widely used in activity recognition to encode features, and although it yields state-of-the art performance with several feature descriptors it still suffers from large quantization errors and reduces the overall performance. Recently proposed sparse representation methods have been shown to effectively represent features as a linear combination of an over complete dictionary by minimizing the reconstruction error. In contrast to most of the sparse representation methods which focus on Sparse-Reconstruction based Classification (SRC), this paper focuses on a discriminative classification using a SVM by constructing class-specific sparse codes for motion and appearance separately. Experimental results demonstrates that separate motion and appearance specific sparse coefficients provide the most effective and discriminative representation for each class compared to a single class-specific sparse coefficients.

Development and reproducibility of a short questionnaire to measure use and usability of custom-made orthopaedic shoes

OBJECTIVE To develop a short and easy to use questionnaire to measure use and usability of custom-made orthopaedic shoes, and to investigate its reproducibility. DESIGN Development of the questionnaire (Monitor Orthopaedic Shoes) was based on a literature search, expert interviews, 2 expert meetings, and exploration and testing of reproducibility. The questionnaire comprises 2 parts: a pre part, measuring expectations; and a post part, measuring experiences. Patients The pre part of the final version was completed twice by 37 first-time users before delivery of their orthopaedic shoes. The post part of the final version was completed twice by 39 first-time users who had worn their orthopaedic shoes for 2–4 months. RESULTS High reproducibility scores (Cohen’s kappa > 0.60 or intra class correlation > 0.70) were found in all but one question of both parts of the final version of the Monitor Orthopaedic Shoes questionnaire. The smallest real difference on a visual analogue scale (100 mm) ranged from 21 to 50 mm. It took patients approximately 15 minutes to complete one part. CONCLUSION Monitor Orthopaedic Shoes is a practical and reproducible questionnaire that can measure relevant aspects of use and usability of orthopaedic shoes from a patient’s perspective.

See you in class: Promoting a quality program for pre-service educators in regional locations through a virtual classroom

The quality of an online university degree is paramount to the student, the reputation of the university and most importantly, the profession that will be entered. At the School of Education within Curtin University, we aim to ensure that students within rural and remote areas are provided with high quality degrees equal to their city counterparts who access face-to-face classes on campus.In 2010, the School of Education moved to flexible delivery of a fully online Bachelor of Education degree for their rural students. In previous years, the degree had been delivered in physical locations around the state. Although this served the purpose for the time, it restricted the degree to only those rural students who were able to access the physical campus. The new model in 2010 allows access for students in any rural area who have a computer and an internet connection, regardless of their geographical location. As a result enrolments have seen a positive increase in new students. Academic staff had previously used an asynchronous environment to deliver learning modules housed within a learning management system (LMS). To enhance the learning environment and to provide high quality learning experiences to students learning at a distance, the adoption of synchronous software 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 professional development of academic staff to integrate a live e-learning solution into their current LMS environment. It involved professional development, including technical orientation for teaching staff and course participants simultaneously. Further, pedagogical innovations were offered to engage the students in a collaborative learning environment. Data were collected from academic staff through semi-structured interviews and participant observation. The findings discuss the perceived value of the technology, problems encountered and solutions sought.

A potent nonporphyrin class of photodynamic therapeutic agent: Cellular localisation, cytotoxic potential and influence of hypoxia

We have developed a totally new class of nonporphyrin photodynamic therapeutic agents with a specific focus on two lead candidates azadipyrromethene (ADPM)01 and ADPM06. Confocal laser scanning microscopy imaging showed that these compounds are exclusively localised to the cytosolic compartment, with specific accumulation in the endoplasmic reticulum and to a lesser extent in the mitochondria. Light-induced toxicity assays, carried out over a broad range of human tumour cell lines, displayed EC50 values in the micro-molar range for ADPM01 and nano-molar range for ADPM06, with no discernable activity bias for a specific cell type. Strikingly, the more active agent, ADPM06, even retained significant activity under hypoxic conditions. Both photosensitisers showed low to nondeterminable dark toxicity. Flow cytometric analysis revealed that ADPM01 and ADPM06 were highly effective at inducing apoptosis as a mode of cell death. The photophysical and biological characteristics of these PDT agents suggest that they have potential for the development of new anticancer therapeutics. © 2005 Cancer Research UK.

ERAP2 functional knockout in humans does not alter surface heavy chains or HLA-B27, inflammatory cytokines or endoplasmic reticulum stress markers

Introduction Single nucleotide polymorphisms in ERAP2 are strongly associated with ankylosing spondylitis (AS). One AS-associated single nucleotide polymorphism, rs2248374, causes a truncated ERAP2 protein that is degraded by nonsense-mediated decay. Approximately 25% of the populations of European ancestry are therefore natural ERAP2 knockouts. We investigated the effect of this associated variant on HLA class I allele presentation, surface heavy chains, endoplasmic reticulum (ER) stress markers and cytokine gene transcription in AS. Methods Patients with AS and healthy controls with either AA or GG homozygous status for rs2248374 were studied. Antibodies to CD14, CD19-ECD, HLA-A-B-C, Valpha7.2, CD161, anti-HC10 and anti-HLA-B27 were used to analyse peripheral blood mononuclear cells. Expression levels of ER stress markers (GRP78 and CHOP) and proinflammatory genes (tumour necrosis factor (TNF), IL6, IL17 and IL22) were assessed by qPCR. Results There was no significant difference in HLAclass I allele presentation or major histocompatibility class I heavy chains or ER stress markers GRP78 and CHOP or proinflammatory gene expression between genotypes for rs2248374 either between cases, between cases and controls, and between controls. Discussion Large differences were not seen in HLAB27 expression or cytokine levels between subjects with and without ERAP2 in AS cases and controls. This suggests that ERAP2 is more likely to influence AS risk through other mechanisms.

R1STM: One-class support tensor machine with randomised kernel

Identifying unusual or anomalous patterns in an underlying dataset is an important but challenging task in many applications. The focus of the unsupervised anomaly detection literature has mostly been on vectorised data. However, many applications are more naturally described using higher-order tensor representations. Approaches that vectorise tensorial data can destroy the structural information encoded in the high-dimensional space, and lead to the problem of the curse of dimensionality. In this paper we present the first unsupervised tensorial anomaly detection method, along with a randomised version of our method. Our anomaly detection method, the One-class Support Tensor Machine (1STM), is a generalisation of conventional one-class Support Vector Machines to higher-order spaces. 1STM preserves the multiway structure of tensor data, while achieving significant improvement in accuracy and efficiency over conventional vectorised methods. We then leverage the theory of nonlinear random projections to propose the Randomised 1STM (R1STM). Our empirical analysis on several real and synthetic datasets shows that our R1STM algorithm delivers comparable or better accuracy to a state-of-the-art deep learning method and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

Defects in the IFT-B component IFT172 cause Jeune and Mainzer-Saldino syndromes in humans

Intraflagellar transport (IFT) depends on two evolutionarily conserved modules, subcomplexes A (IFT-A) and B (IFT-B), to drive ciliary assembly and maintenance. All six IFT-A components and their motor protein, DYNC2H1, have been linked to human skeletal ciliopathies, including asphyxiating thoracic dystrophy (ATD; also known as Jeune syndrome), Sensenbrenner syndrome, and Mainzer-Saldino syndrome (MZSDS). Conversely, the 14 subunits in the IFT-B module, with the exception of IFT80, have unknown roles in human disease. To identify additional IFT-B components defective in ciliopathies, we independently performed different mutation analyses: candidate-based sequencing of all IFT-B-encoding genes in 1,467 individuals with a nephronophthisis-related ciliopathy or whole-exome resequencing in 63 individuals with ATD. We thereby detected biallelic mutations in the IFT-B-encoding gene IFT172 in 12 families. All affected individuals displayed abnormalities of the thorax and/or long bones, as well as renal, hepatic, or retinal involvement, consistent with the diagnosis of ATD or MZSDS. Additionally, cerebellar aplasia or hypoplasia characteristic of Joubert syndrome was present in 2 out of 12 families. Fibroblasts from affected individuals showed disturbed ciliary composition, suggesting alteration of ciliary transport and signaling. Knockdown of ift172 in zebrafish recapitulated the human phenotype and demonstrated a genetic interaction between ift172 and ift80. In summary, we have identified defects in IFT172 as a cause of complex ATD and MZSDS. Our findings link the group of skeletal ciliopathies to an additional IFT-B component, IFT172, similar to what has been shown for IFT-A.

Ratios of T-cell immune-effectors with tumour associated macrophages and PD-1/PD-L1 axis immune-checkpoint molecules, as prognosticators in diffuse large B cell lymphoma: A population-based study

Background Risk-stratification of diffuse large B-cell lymphoma (DLBCL) requires identification of patients with disease that is not cured despite initial R-CHOP. Although the prognostic importance of the tumour microenvironment (TME) is established, the optimal strategy to quantify it is unknown. Methods The relationship between immune-effector and inhibitory (checkpoint) genes was assessed by NanoString™ in 252 paraffin-embedded DLBCL tissues. A model to quantify net anti-tumoural immunity as an outcome predictor was tested in 158 R-CHOP treated patients, and validated in tissue/blood from two independent R-CHOP treated cohorts of 233 and 140 patients respectively. Findings T and NK-cell immune-effector molecule expression correlated with tumour associated macrophage and PD-1/PD-L1 axis markers consistent with malignant B-cells triggering a dynamic checkpoint response to adapt to and evade immune-surveillance. A tree-based survival model was performed to test if immune-effector to checkpoint ratios were prognostic. The CD4*CD8:(CD163/CD68)*PD-L1 ratio was better able to stratify overall survival than any single or combination of immune markers, distinguishing groups with disparate 4-year survivals (92% versus 47%). The immune ratio was independent of and added to the revised international prognostic index (R-IPI) and cell-of-origin (COO). Tissue findings were validated in 233 DLBCL R-CHOP treated patients. Furthermore, within the blood of 140 R-CHOP treated patients immune-effector:checkpoint ratios were associated with differential interim-PET/CT+ve/-ve expression.

Novel synthesis of superparamagnetic Ni-Co-B nanoparticles and their effect on superconductor properties of MgB2

A new procedure for the preparation of amorphous Ni-Co-B nanoparticles is reported, with a detailed investigation of their morphology by X-ray diffraction and transmission electron microscopy, as well as their magnetic properties. Many factors, such as chemical composition, anisotropy, size and shape of the particles, were controlled through chemical synthesis, resulting in the control of morphological and magnetic properties of the nanoparticles. Controlling pH values with ethylenediamine and using sodium dodecyl sulfate surfactant lowered the size of the nanoparticles to below 10 nm. Such a small structure and chemical disorder in nanocrystalline materials lead to magnetic properties that are different from those in their bulk-sized counterparts. The obtained nanoparticles can be used for different purposes, from pharmaceutical applications to implementations in different materials technology. The focus of this research is the synthesis of Ni-Co-B nanoparticles in a new way and studying the reaction of Ni-Co-B nanoparticles with Mg and B precursors and their effect on MgB2 properties. New nanostructures are formed in the reaction of Ni-Co-B nanoparticles with Mg: Mg2Ni, Co2Mg and possibly Mg2Co.