Clinical features of psychotic disorders and polymorphisms in HT2A, DRD2, DRD4, SLC6A3 (DAT1), and BDNF:a family based association study

Schizophrenia is clinically heterogeneous and multidimensional, but it is not known whether this is due to etiological heterogeneity. Previous studies have not consistently reported association between any specific polymorphisms and clinical features of schizophrenia, and have primarily used case-control designs. We tested for the presence of association between clinical features and polymorphisms in the genes for the serotonin 2A receptor (HT2A), dopamine receptor types 2 and 4, dopamine transporter (SLC6A3), and brain-derived neurotrophic factor (BDNF). Two hundred seventy pedigrees were ascertained on the basis of having two or more members with schizophrenia or poor outcome schizoaffective disorder. Diagnoses were made using a structured interview based on the SCID. All patients were rated on the major symptoms of schizophrenia scale (MSSS), integrating clinical and course features throughout the course of illness. Factor analysis revealed positive, negative, and affective symptom factors. The program QTDT was used to implement a family-based test of association for quantitative traits, controlling for age and sex. We found suggestive evidence of association between the His452Tyr polymorphism in HT2A and affective symptoms (P = 0.02), the 172-bp allele of BDNF and negative symptoms (P = 0.04), and the 480-bp allele in SLC6A3 (= DAT1) and negative symptoms (P = 0.04). As total of 19 alleles were tested, we cannot rule out false positives. However, given prior evidence of involvement of the proteins encoded by these genes in psychopathology, our results suggest that more attention should be focused on the impact of these alleles on clinical features of schizophrenia.

Single-laboratory validation of a multiplex flow cytometric immunoassay for the simultaneous detection of coccidiostats in eggs and feed

Coccidiostats are authorized in the European Union (EU) to be used as poultry feed additives. Maximum (residue) levels (M(R)Ls) have been set within the EU for consumer and animal protection against unintended carry-over, and monitoring is compulsory. This paper describes the single-laboratory validation of a previously developed multiplex flow cytometric immunoassay (FCIA) as screening method for coccidiostats in eggs and feed and provides and compares different approaches for the calculation of the cut-off levels which are not described in detail within Commission Decision 2002/657/EC. Comparable results were obtained between the statistical (reference) approach and the rapid approaches. With the most rapid approach, the cut-off levels for narasin/salinomycin, lasalocid, diclazuril, nicarbazin (DNC) and monensin in egg, calculated as percentages of inhibition (%B/B0), were 60, 32, 76, 80 and 84, respectively. In feed, the cut-off levels for narasin/salinomycin, lasalocid, nicarbazin (DNC) and monensin were 70, 64, 72 and 78, respectively, and could not be determined for diclazuril. For all analytes, except for diclazuril in feed, the rate of false positives (false non-compliant) in blank samples was lower than 1 %, and the rate of false negatives (false compliant) at the M(R)Ls was below 5 %. Additionally, very good correlations (r ranging from 0.994 to 0.9994) were observed between two different analysers, a sophisticated flow cytometer (FlexMAP 3D(®)) and a more cost-efficient and transportable planar imaging detector (MAGPIX(®)), hence demonstrating adequate transferability.

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods.

Selecting users in energy-efficient collaborative spectrum sensing

Cognitive radio network is defined as an intelligent wireless communication network that should be able to adaptively reconfigure its communication parameters to meet the demands of the transmission network or the user. In this context one possible way to utilize unused licensed spectrum without interfering with incumbent users is through spectrum sensing. Due to channel uncertainties, single cognitive (opportunistic) user cannot make a decision reliably and hence collaboration among multiple users is often required. Here collaboration among large number of users tends to increase power consumption and introduces large communication overheads. In this paper, the number of collaborating users is optimized in order to maximize the probability of detection for any given power budget in a cognitive radio network, while satisfying constraints on the false alarm probability. We show that for the maximum probability of detection, collaboration of only a subset of available opportunistic users is required. The robustness of our proposed spectrum sensing algorithm is also examined under flat Rayleigh fading and AWGN channel conditions.

Suggestive association with ocular phoria at chromosome 6p22

PURPOSE. We conducted a genome-wide association study to identify genetic factors that contribute to the etiology of heterophoria.

METHODS. We measured near and far vertical and horizontal phorias in 988 healthy adults aged 16 to 40 using the Keystone telebinocular with plates 5218 and 5219. We regressed degree of phoria against genotype at 642758 genetic loci. To control for false positives, we applied the conservative genome-wide permutation test to our data.

RESULTS. A locus at 6p22.2 was found to be associated with the degree of near horizontal phoria (P = 2.3 × 10 ). The P value resulting from a genome-wide permutation test was 0.014.

CONCLUSIONS. The strongest association signal arose from an intronic region of the gene ALDH5A1, which encodes the mitochondrial enzyme succinic semialdehyde dehydrogenase (SSADH), an enzyme involved in γ-aminobutyric acid metabolism. Succinic semialdehyde dehydrogenase deficiency, resulting from mutations of ALDH5A1, causes a variety of neural and behavioral abnormalities, including strabismus. Variation in ALDH5A1 is likely to contribute to degree of horizontal phoria.

When does information about causal structure improve statistical reasoning?

Base rate neglect on the mammography problem can be overcome by explicitly presenting a causal basis for the typically vague false-positive statistic. One account of this causal facilitation effect is that people make probabilistic judgements over intuitive causal models parameterized with the evidence in the problem. Poorly defined or difficult-to-map evidence interferes with this process, leading to errors in statistical reasoning. To assess whether the construction of parameterized causal representations is an intuitive or deliberative process, in Experiment 1 we combined a secondary load paradigm with manipulations of the presence or absence of an alternative cause in typical statistical reasoning problems. We found limited effects of a secondary load, no evidence that information about an alternative cause improves statistical reasoning, but some evidence that it reduces base rate neglect errors. In Experiments 2 and 3 where we did not impose a load, we observed causal facilitation effects. The amount of Bayesian responding in the causal conditions was impervious to the presence of a load (Experiment 1) and to the precise statistical information that was presented (Experiment 3). However, we found less Bayesian responding in the causal condition than previously reported. We conclude with a discussion of the implications of our findings and the suggestion that there may be population effects in the accuracy of statistical reasoning.

Attention during social interaction in children with autism: Comparison to specific language impairment, typical development, and links to cognition

Eye-tracking studies have shown how people with autism spend significantly less time looking at socially relevant information on-screen compared to those developing typically. This has been suggested to impact on the development of socio-cognitive skills in autism. We present novel evidence of how attention atypicalities in children with autism extend to real-life interaction, in comparison to typically developing (TD) children and children with specific language impairment (SLI). We explored the allocation of attention during social interaction with an interlocutor, and how aspects of attention (awareness checking) related to traditional measures of social cognition (false belief attribution). We found divergent attention allocation patterns across the groups in relation to social cognition ability. Even though children with autism and SLI performed similarly on the socio- cognitive tasks, there were syndrome-specific atypicalities of their attention patterns. Children with SLI were most similar to TD children in terms of prioritising attention to socially pertinent information (eyes, face, awareness checking). Children with autism showed reduced attention to the eyes and face, and slower awareness checking. This study provides unique and timely insight into real-world social gaze (a)typicality in autism, SLI and typical development, its relationship to socio-cognitive ability, and raises important issues for intervention.

Freehand core biopsy in breast cancer: an accurate predictor of tumour grade following neoadjuvant chemotherapy?

Core biopsy is an increasingly used technique in the pre-operative diagnosis of breast carcinoma, as it provides useful prognostic information with respect to tumour type and grade. Neoadjuvant chemotherapy is being used in the treatment of large and locally advanced breast cancers but little is known regarding the correlation between tumour histology on pre-treatment core biopsy and that in residual tumour following primary chemotherapy and surgery. This study aimed to evaluate the accuracy of core biopsy in predicting these features in patients treated with primary chemotherapy. One hundred and thirty-three patients with carcinoma of the breast diagnosed on clinical, radiological and cytological examination underwent core biopsy, followed by primary chemotherapy (with cyclophosphamide, vincristine, doxorubicin and prednisolone) and surgery. The false-negative rate for pre-treatment core biopsy was 14%, with 91% agreement between the grade demonstrated on core biopsy and that in the residual tumour following completion of chemotherapy. Tumour type in the residual post-chemotherapy tumour was predicted by core biopsy in 84%. This study suggests that pre-treatment core biopsy histology accurately predicts residual tumour histology following primary chemotherapy and surgery in patients with breast cancer. (C) 2002 Elsevier Science Ltd. All rights reserved.

The management of radial scars of the breast - does core biopsy help?

Purpose: To compare the effectiveness of fine needle aspiration cytology (FNAC) with core biopsy (CB) in the pre-operative diagnosis of radial scar (RS) of the breast.

Patients and methods: A retrospective analysis was made of all radial scars diagnosed on surgical histology over an 8-year period. Comparison was made between the results of different preoperative needle biopsy techniques and surgical histology findings.

Results: Forty of 47 patients with a preoperative radiological diagnosis of radial scar were included in this analysis. Thirty-eight patients had impalpable lesions diagnosed on mammography and two presented with a palpable lump. FNAC (n=17) was inadequate in 47% of patients, missed two co-existing carcinomas found in this group, and gave a false positive or suspicious result for malignancy in 4 patients. CB (n=23) suggested a RS in 15 patients, but only diagnosed 4 out of 7 co-existing carcinomas found in this group.

Conclusion: CB is more accurate than FNAC in the diagnosis of RS. However, these data demonstrate that CB may offer little to assist in the management of patients with RS. In summary, this paper advocates the use of CB in any lesion with a radiological suspicion of carcinoma and diagnostic excision of all lesions thought to be typical of RS on mammography.

The Pan-STARRS Moving Object Processing System

We describe the Pan-STARRS Moving Object Processing System (MOPS), a modern software package that produces automatic asteroid discoveries and identifications from catalogs of transient detections from next-generation astronomical survey telescopes. MOPS achieves >99.5% efficiency in producing orbits from a synthetic but realistic population of asteroids whose measurements were simulated for a Pan-STARRS4-class telescope. Additionally, using a nonphysical grid population, we demonstrate that MOPS can detect populations of currently unknown objects such as interstellar asteroids. MOPS has been adapted successfully to the prototype Pan-STARRS1 telescope despite differences in expected false detection rates, fill-factor loss, and relatively sparse observing cadence compared to a hypothetical Pan-STARRS4 telescope and survey. MOPS remains highly efficient at detecting objects but drops to 80% efficiency at producing orbits. This loss is primarily due to configurable MOPS processing limits that are not yet tuned for the Pan-STARRS1 mission. The core MOPS software package is the product of more than 15 person-years of software development and incorporates countless additional years of effort in third-party software to perform lower-level functions such as spatial searching or orbit determination. We describe the high-level design of MOPS and essential subcomponents, the suitability of MOPS for other survey programs, and suggest a road map for future MOPS development.

Genetic pleiotropy between multiple sclerosis and schizophrenia but not bipolar disorder: differential involvement of immune-related gene loci

Converging evidence implicates immune abnormalities in schizophrenia (SCZ), and recent genome-wide association studies (GWAS) have identified immune-related single-nucleotide polymorphisms (SNPs) associated with SCZ. Using the conditional false discovery rate (FDR) approach, we evaluated pleiotropy in SNPs associated with SCZ (n=21 856) and multiple sclerosis (MS) (n=43 879), an inflammatory, demyelinating disease of the central nervous system. Because SCZ and bipolar disorder (BD) show substantial clinical and genetic overlap, we also investigated pleiotropy between BD (n=16 731) and MS. We found significant genetic overlap between SCZ and MS and identified 21 independent loci associated with SCZ, conditioned on association with MS. This enrichment was driven by the major histocompatibility complex (MHC). Importantly, we detected the involvement of the same human leukocyte antigen (HLA) alleles in both SCZ and MS, but with an opposite directionality of effect of associated HLA alleles (that is, MS risk alleles were associated with decreased SCZ risk). In contrast, we found no genetic overlap between BD and MS. Considered together, our findings demonstrate genetic pleiotropy between SCZ and MS and suggest that the MHC signals may differentiate SCZ from BD susceptibility.Molecular Psychiatry advance online publication, 28 January 2014; doi:10.1038/mp.2013.195.

Green Political Economy: beyond orthodox undifferentiated economic growth as a permanent feature of the economy

This chapter outlines the main features of green political economy and the principal ways in which it differs from dominant mainstream or orthodox neoclassical economics. Neoclassical economics is critiqued on the grounds of denying its normative and ideological commitments in its false presentation of itself as ‘objective’ and ‘value neutral’. It is also critiqued for its ecologically irrational commitment to the imperative of orthodox economic growth as a permanent feature of the economy, compromising its ability to offer realistic or normatively compelling guides to how we might make the transition to a sustainable economy. Green political economy is presented as an alternative or heterodox form of economic thinking but one which explicitly expresses its normative/ideological value bases (hence it represents a return to ‘political economy’, the origins of modern economics). Green political economy also challenges the commitment to undifferentiated economic growth as a permanent objective of the human economy. In its place, green political economy promotes ‘economic security’ as a better objective for a sustainable, post-growth economy. The latter includes the transition to a low-carbon energy economy, and is also one which maximises quality of life (as oppose to formal employment, income and wealth), and actively seeks to lower socio-economic inequality. Green political economy views orthodox economic growth as having passed the threshold in most ‘advanced’ capitalist societies beyond which it has undermined quality of life and at best manages rather than reduces socially and ecologically damaging inequalities.

Targeted Impersonation As A Tool For The Detection Of Biometric System Vulnerabilities

This paper argues that biometric verification evaluations can obscure vulnerabilities that increase the chances that an attacker could be falsely accepted. This can occur because existing evaluations implicitly assume that an imposter claiming a false identity would claim a random identity rather than consciously selecting a target to impersonate. This paper shows how an attacker can select a target with a similar biometric signature in order to increase their chances of false acceptance. It demonstrates this effect using a publicly available iris recognition algorithm. The evaluation shows that the system can be vulnerable to attackers targeting subjects who are enrolled with a smaller section of iris due to occlusion. The evaluation shows how the traditional DET curve analysis conceals this vulnerability. As a result, traditional analysis underestimates the importance of an existing score normalisation method for addressing occlusion. The paper concludes by evaluating how the targeted false acceptance rate increases with the number of available targets. Consistent with a previous investigation of targeted face verification performance, the experiment shows that the false acceptance rate can be modelled using the traditional FAR measure with an additional term that is proportional to the logarithm of the number of available targets.

TARGETED BIOMETRIC IMPERSONATION

When applying biometric algorithms to forensic verification, false acceptance and false rejection can mean a failure to identify a criminal, or worse, lead to the prosecution of individuals for crimes they did not commit. It is therefore critical that biometric evaluations be performed as accurately as possible to determine their legitimacy as a forensic tool. This paper argues that, for forensic verification scenarios, traditional performance measures are insufficiently accurate. This inaccuracy occurs because existing verification evaluations implicitly assume that an imposter claiming a false identity would claim a random identity rather than consciously selecting a target to impersonate. In addition to describing this new vulnerability, the paper describes a novel Targeted.. FAR metric that combines the traditional False Acceptance Rate (FAR) measure with a term that indicates how performance degrades with the number of potential targets. The paper includes an evaluation of the effects of targeted impersonation on an existing academic face verification system. This evaluation reveals that even with a relatively small number of targets false acceptance rates can increase significantly, making the analysed biometric systems unreliable.

Identification of vegetable oil botanical speciation in refined vegetable oil blends using an innovative combination of chromatographic and spectroscopic techniques

European Regulation 1169/2011 requires producers of foods that contain refined vegetable oils to label the oil types. A novel rapid and staged methodology has been developed for the first time to identify common oil species in oil blends. The qualitative method consists of a combination of a Fourier Transform Infrared (FTIR) spectroscopy to profile the oils and fatty acid chromatographic analysis to confirm the composition of the oils when required. Calibration models and specific classification criteria were developed and all data were fused into a simple decision-making system. The single lab validation of the method demonstrated the very good performance (96% correct classification, 100% specificity, 4% false positive rate). Only a small fraction of the samples needed to be confirmed with the majority of oils identified rapidly using only the spectroscopic procedure. The results demonstrate the huge potential of the methodology for a wide range of oil authenticity work.