The subcortical confinement hypothesis: A neurological model for schizotypal hallucinations

Introduction Different types of hallucinations are symptomatic of different conditions. Schizotypal hallucinations are unique in that they follow existing delusional narrative patterns: they are often bizarre, they are generally multimodal, and they are particularly vivid (the experience of a newsreader abusing you personally over the TV is both visual and aural. Patients who feel and hear silicone chips under their skin suffer from haptic hallucinations as well as aural ones, etc.) Although there are a number of hypotheses for hallucinations, few cogently grapple the sheer bizarreness of the ones experienced in schizotypal psychosis. Methods A review-based hypothesis, traversing theory from the molecular level to phenomenological expression as a distinct and recognizable symptomatology. Conclusion Hallucinations appear to be caused by a two-fold dysfunction in the mesofrontal dopamine pathway, which is considered here to mediate attention of different types: in the anterior medial frontal lobe, the receptors (largely D1 type) mediate declarative awareness, whereas the receptors in the striatum (largely D2 type) mediate latent awareness of known schemata. In healthy perception, most of the perceptual load is performed by the latter: by the top-down predictive and mimetic engine, with the bottom-up mechanism being used as a secondary tool to bring conscious deliberation to stimuli that fails to match up against expectations. In schizophrenia, the predictive mode is over-stimulated, while the bottom-up feedback mechanism atrophies. The dysfunctional distribution pattern effectively confines dopamine activity to the striatum, thereby stimulating the structural components of thought and behaviour: well-learned routines, narrative structures, lexica, grammar, schemata, archetypes, and other procedural resources. Meanwhile, the loss of activity in the frontal complex reduces the capacity for declarative awareness and for processing anything that fails to meet expectations.

Do pollutions deter foreign direct investment in China?

The scale of environmental problems in China is clearly evident. This paper analyses foreign direct investment (FDI) in China with a finite mixture model, also known as latent class model to understand the relationship between FDI and several pollutions. This is used to regresses FDI as function covariates including pollutants. The results reveal that FDI is affected by pollutants. There are cases reducing pollution deters foreign investment in China.

Alternate destinies for survey items destined for the island of misfit toys: An analysis of teachers' perceptions of NAPLAN

This is a methodological paper describing when and how manifest items dropped from a latent construct measurement model (e.g., factor analysis) can be retained for additional analysis. Presented are protocols for assessment for retention in the measurement model, evaluation of dropped items as potential items separate from the latent construct, and post hoc analyses that can be conducted using all retained (manifest or latent) variables. The protocols are then applied to data relating to the impact of the NAPLAN test. The variables examined are teachers’ achievement goal orientations and teachers’ perceptions of the impact of the test on curriculum and pedagogy. It is suggested that five attributes be considered before retaining dropped manifest items for additional analyses. (1) Items can be retained when employed in service of an established or hypothesized theoretical model. (2) Items should only be retained if sufficient variance is present in the data set. (3) Items can be retained when they provide a rational segregation of the data set into subsamples (e.g., a consensus measure). (4) The value of retaining items can be assessed using latent class analysis or latent mean analysis. (5) Items should be retained only when post hoc analyses with these items produced significant and substantive results. These suggested exploratory strategies are presented so that other researchers using survey instruments might explore their data in similar and more innovative ways. Finally, suggestions for future use are provided.

Is there a link between poverty and food security?

This paper addresses the gap in economic theory underlying the multidimensional concept of food security and observed data by deriving a composite food security index using the latent class model. The link between poverty and food security is then examined using the new food security index and the robustness of the link is compared with two unidimensional measures often used in the literature. Using Vietnam as a case study, it was found that a weak link exists for the rural but not for the urban composite food security index. The unidimensional measures on the other hand show a strong link in both the rural and urban regions. The results on the link are also different and mixed when two poverty types given by persistent and transient poverty are considered. These findings have important policy implications for a targeted approach to addressing food security.

Genome-wide association study using extreme truncate selection identifies novel genes affecting bone mineral density and fracture risk

Osteoporotic fracture is a major cause of morbidity and mortality worldwide. Low bone mineral density (BMD) is a major predisposing factor to fracture and is known to be highly heritable. Site-, gender-, and age-specific genetic effects on BMD are thought to be significant, but have largely not been considered in the design of genome-wide association studies (GWAS) of BMD to date. We report here a GWAS using a novel study design focusing on women of a specific age (postmenopausal women, age 55-85 years), with either extreme high or low hip BMD (age- and gender-adjusted BMD z-scores of +1.5 to +4.0, n = 1055, or -4.0 to -1.5, n = 900), with replication in cohorts of women drawn from the general population (n = 20,898). The study replicates 21 of 26 known BMD-associated genes. Additionally, we report suggestive association of a further six new genetic associations in or around the genes CLCN7, GALNT3, IBSP, LTBP3, RSPO3, and SOX4, with replication in two independent datasets. A novel mouse model with a loss-of-function mutation in GALNT3 is also reported, which has high bone mass, supporting the involvement of this gene in BMD determination. In addition to identifying further genes associated with BMD, this study confirms the efficiency of extreme-truncate selection designs for quantitative trait association studies. © 2011 Duncan et al.

Low temperature solar cooling system with absorption chiller and desiccant wheel

Nowadays Solar Cooling systems are becoming popular to reduce the carbon footprint of air conditioning. The use of an absorption chiller connected to solar thermal panels is increasing, but little study has been carried out to assess the advantage of join together an absorption chiller and a desiccant wheel to remove the sensible heat and the latent heat in different ways than the current design adopted in the industry. In this work I assess the possibility of implement a desiccant wheel in a conventional solar cooling system and the possibility of recovering the heat rejected by the absorption chiller which is then used for the regeneration of the desiccant wheel. The implementation of a desiccant wheel and the recovery of the heat rejected could provide a significant energy saving when compared to traditional solar cooling system. The results assist in the practical development of a solar cooling system which simultaneously uses absorption and adsorption technology.

Do motor vehicle crashes arise from single or multiple unique risk processes? An inquiry into crash causes and modelling

Crashes at any particular transport network location consist of a chain of events arising from a multitude of potential causes and/or contributing factors whose nature is likely to reflect geometric characteristics of the road, spatial effects of the surrounding environment, and human behavioural factors. It is postulated that these potential contributing factors do not arise from the same underlying risk process, and thus should be explicitly modelled and understood. The state of the practice in road safety network management applies a safety performance function that represents a single risk process to explain crash variability across network sites. This study aims to elucidate the importance of differentiating among various underlying risk processes contributing to the observed crash count at any particular network location. To demonstrate the principle of this theoretical and corresponding methodological approach, the study explores engineering (e.g. segment length, speed limit) and unobserved spatial factors (e.g. climatic factors, presence of schools) as two explicit sources of crash contributing factors. A Bayesian Latent Class (BLC) analysis is used to explore these two sources and to incorporate prior information about their contribution to crash occurrence. The methodology is applied to the state controlled roads in Queensland, Australia and the results are compared with the traditional Negative Binomial (NB) model. A comparison of goodness of fit measures indicates that the model with a double risk process outperforms the single risk process NB model, and thus indicating the need for further research to capture all the three crash generation processes into the SPFs.

Interaction between ERAP1 and HLA-B27 in ankylosing spondylitis implicates peptide handling in the mechanism for HLA-B27 in disease susceptibility

Ankylosing spondylitis is a common form of inflammatory arthritis predominantly affecting the spine and pelvis that occurs in approximately 5 out of 1,000 adults of European descent. Here we report the identification of three variants in the RUNX3, LTBR-TNFRSF1A and IL12B regions convincingly associated with ankylosing spondylitis (P < 5 × 10-8 in the combined discovery and replication datasets) and a further four loci at PTGER4, TBKBP1, ANTXR2 and CARD9 that show strong association across all our datasets (P < 5 × 10-6 overall, with support in each of the three datasets studied). We also show that polymorphisms of ERAP1, which encodes an endoplasmic reticulum aminopeptidase involved in peptide trimming before HLA class I presentation, only affect ankylosing spondylitis risk in HLA-B27-positive individuals. These findings provide strong evidence that HLA-B27 operates in ankylosing spondylitis through a mechanism involving aberrant processing of antigenic peptides.

In situ investigation of explosive crystallization in a-Ge: Experimental determination of the interface response function using dynamic transmission electron microscopy

The crystallization of amorphous semiconductors is a strongly exothermic process. Once initiated the release of latent heat can be sufficient to drive a self-sustaining crystallization front through the material in a manner that has been described as explosive. Here, we perform a quantitative in situ study of explosive crystallization in amorphous germanium using dynamic transmission electron microscopy. Direct observations of the speed of the explosive crystallization front as it evolves along a laser-imprinted temperature gradient are used to experimentally determine the complete interface response function (i.e., the temperature-dependent front propagation speed) for this process, which reaches a peak of 16 m/s. Fitting to the Frenkel-Wilson kinetic law demonstrates that the diffusivity of the material locally/immediately in advance of the explosive crystallization front is inconsistent with those of a liquid phase. This result suggests a modification to the liquid-mediated mechanism commonly used to describe this process that replaces the phase change at the leading amorphous-liquid interface with a change in bonding character (from covalent to metallic) occurring in the hot amorphous material.

Changes in depression during and following pregnancy

Rates of depression were studied in a sample of over 9000 women who were participants in the Avon Longitudinal Study of Pregnancy and Childhood. Assessments of depression were made at 18 and 32 weeks gestation, and at 8 and 32 weeks postpartum. Changes in depressive status across time were modelled using latent Markov modelling methods. This analysis showed that when classification errors were taken into account there was relatively high stability in diagnostic status during pregnancy and after pregnancy. However, the transition from late pregnancy to the early postnatal period showed evidence of increased instability and remission of depression. The net effects of this were that rates of depression tended to decline following childbirth. The implications of these results for a series of issues including measurement errors in depression reports and the prevalence of depression before and after childbirth are discussed.

Unsupervised Domain Adaptation by Domain Invariant Projection

Domain-invariant representations are key to addressing the domain shift problem where the training and test exam- ples follow different distributions. Existing techniques that have attempted to match the distributions of the source and target domains typically compare these distributions in the original feature space. This space, however, may not be di- rectly suitable for such a comparison, since some of the fea- tures may have been distorted by the domain shift, or may be domain specific. In this paper, we introduce a Domain Invariant Projection approach: An unsupervised domain adaptation method that overcomes this issue by extracting the information that is invariant across the source and tar- get domains. More specifically, we learn a projection of the data to a low-dimensional latent space where the distance between the empirical distributions of the source and target examples is minimized. We demonstrate the effectiveness of our approach on the task of visual object recognition and show that it outperforms state-of-the-art methods on a stan- dard domain adaptation benchmark dataset

Accelerating Pseudo-Marginal MCMC using Gaussian Processes

Pseudo-marginal methods such as the grouped independence Metropolis-Hastings (GIMH) and Markov chain within Metropolis (MCWM) algorithms have been introduced in the literature as an approach to perform Bayesian inference in latent variable models. These methods replace intractable likelihood calculations with unbiased estimates within Markov chain Monte Carlo algorithms. The GIMH method has the posterior of interest as its limiting distribution, but suffers from poor mixing if it is too computationally intensive to obtain high-precision likelihood estimates. The MCWM algorithm has better mixing properties, but less theoretical support. In this paper we propose to use Gaussian processes (GP) to accelerate the GIMH method, whilst using a short pilot run of MCWM to train the GP. Our new method, GP-GIMH, is illustrated on simulated data from a stochastic volatility and a gene network model.

A mega-analysis of genome-wide association studies for major depressive disorder

Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 x 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 x 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.

Migraine symptomatology and major depressive disorder

INTRODUCTION AND OBJECTIVE Migraine and major depressive disorder (MDD) frequently co-occur, but it is unclear whether depression is associated with a specific subtype of migraine. The objective of this study was to investigate whether migraine is qualitatively different in MDD patients (N = 1816) and non-depressed controls (N = 3428). METHODS Migraine symptom data were analyzed using multi-group Latent Class Analysis, and a qualitative comparison was made between the symptom profiles of MDD patients and controls, while allowing for differences in migraine prevalence and severity between groups. RESULTS In both groups, three migrainous headache classes were identified, which differed primarily in terms of severity. Both mild and severe migrainous headaches were two to three times more prevalent in MDD patients. Migraine symptom profiles showed only minor qualitative differences in the MDD and non-MDD groups: in the severe migrainous headache class, significant differences were observed only in the prevalence of aggravation by physical activity (83% and 91% for the non-MDD and MDD groups, respectively) and aura (42% vs. 53%, respectively). CONCLUSION The similar overall symptom profiles observed in the MDD and non-MDD subjects suggest that a similar disease process may underlie migraine in both groups.

A genome-wide linkage scan provides evidence for both new and previously reported loci influencing common migraine

Latent class analysis was performed on migraine symptom data collected in a Dutch population sample (N = 12,210, 59% female) in order to obtain empirical groupings of individuals suffering from symptoms of migraine headache. Based on these heritable groupings (h(2) = 0.49, 95% CI: 0.41-0.57) individuals were classified as affected (migrainous headache) or unaffected. Genome-wide linkage analysis was performed using genotype data from 105 families with at least 2 affected siblings. In addition to this primary phenotype, linkage analyses were performed for the individual migraine symptoms. Significance levels, corrected for the analysis of multiple traits, were determined empirically via a novel simulation approach. Suggestive linkage for migrainous headache was found on chromosomes 1 (LOD = 1.63; pointwise P = 0.0031), 13 (LOD = 1.63; P = 0.0031), and 20 (LOD = 1.85; P = 0.0018). Interestingly, the chromosome 1 peak was located close to the ATP1A2 gene, associated with familial hemiplegic migraine type 2 (FHM2). Individual symptom analysis produced a LOD score of 1.97 (P = 0.0013) on chromosome 5 (photo/phonophobia), a LOD score of 2.13 (P = 0.0009) on chromosome 10 (moderate/severe pain intensity) and a near significant LOD score of 3.31 (P = 0.00005) on chromosome 13 (pulsating headache). These peaks were all located near regions previously reported in migraine linkage studies. Our results provide important replication and support for the presence of migraine susceptibility genes within these regions, and further support the utility of an LCA-based phenotyping approach and analysis of individual symptoms in migraine genetic research. Additionally, our novel "2-step" analysis and simulation approach provides a powerful means to investigate linkage to individual trait components.