Representation of facial expression categories in continuous arousal-valence space: Feature and correlation

Representation of facial expressions using continuous dimensions has shown to be inherently more expressive and psychologically meaningful than using categorized emotions, and thus has gained increasing attention over recent years. Many sub-problems have arisen in this new field that remain only partially understood. A comparison of the regression performance of different texture and geometric features and investigation of the correlations between continuous dimensional axes and basic categorized emotions are two of these. This paper presents empirical studies addressing these problems, and it reports results from an evaluation of different methods for detecting spontaneous facial expressions within the arousal-valence dimensional space (AV). The evaluation compares the performance of texture features (SIFT, Gabor, LBP) against geometric features (FAP-based distances), and the fusion of the two. It also compares the prediction of arousal and valence, obtained using the best fusion method, to the corresponding ground truths. Spatial distribution, shift, similarity, and correlation are considered for the six basic categorized emotions (i.e. anger, disgust, fear, happiness, sadness, surprise). Using the NVIE database, results show that the fusion of LBP and FAP features performs the best. The results from the NVIE and FEEDTUM databases reveal novel findings about the correlations of arousal and valence dimensions to each of six basic emotion categories.

Common polygenic variation contributes to risk of migraine in the Norfolk Island population

Migraine has been defined as a common disabling primary headache disorder. Epidemiology studies have provided with the undeniable evidence of genetic components as active players in the development of the disease under a polygenic model in which multiple risk alleles exert modest individual effects. Our objective was to test the contribution of a polygenic effect to migraine risk in the Norfolk Island population using a panel of SNPs reported to be disease associated in published migraine GWAS. We also investigated whether individual SNPs were associated with gene expression levels measured in whole-blood. Polygenic scores were calculated in a total of 285 related individuals (74 cases, 211 controls) from the Norfolk Island using 51 SNPs previously reported to be associated with migraine in published GWAS. The association between polygenic score and migraine case-control status was tested using logistic regression. Results indicate that a migraine polygenic risk score was associated with migraine case-control status in this population (P=0.016). This supports the hypothesis that multiple SNPs with weak effects collectively contribute to migraine risk in this population. Amongst the SNPs included in the polygenic model, 4 were associated with the expression of the USMG5 gene, including rs171251 (P = 0.012). Results from this study provide evidence for a polygenic contribution to migraine risk in an isolated population and highlight specific SNPs that regulate the expression of USMG5, a gene critical for mitochondrial function.

Using Bayesian networks to model surveillance in complex plant and animal health systems

In this chapter we consider biosecurity surveillance as part of a complex system comprising many different biological, environmental and human factors and their interactions. Modelling and analysis of surveillance strategies should take into account these complexities, and also facilitate the use and integration of the many types of different information that can provide insight into the system as a whole. After a brief discussion of a range of options, we focus on Bayesian networks for representing such complex systems. We summarize the features of Bayesian networks and describe these in the context of surveillance.

Complete genome sequence of a novel zantedeschia mild mosaic virus isolate: The first report from Australia and from Alocasia sp

The complete genome of an Australian isolate of zantedeschia mild mosaic virus (ZaMMV) causing mosaic symptoms on Alocasia sp. (designated ZaMMVAU) was cloned and sequenced. The genome comprises 9942 nucleotides (excluding the poly-A tail) and encodes a polyprotein of 3167 amino acids. The sequence is most closely related to a previously reported ZaMMV isolate from Taiwan (ZaMMV-TW), with 82 and 86 % identity at the nucleotide and amino acid level, respectively. Unlike the amino acid sequence of ZaMMV-TW, however, ZaMMV-AU does not contain a polyglutamine stretch at the N-terminus of the coat-protein-coding region upstream of the DAG motif. This is the first report of ZaMMV from Australia and from Alocasia sp.

Mutational analysis of the insulin‑like growth factor 1 receptor tyrosine kinase domain in non-small cell lung cancer patients

The insulin‑like growth factor 1 receptor (IGF1R) pathway plays an important role in the pathogenesis of non‑small cell lung cancer (NSCLC) and also provides a mechanism of resistance to targeted therapies. IGF1R is therefore an ideal therapeutic target and several inhibitors have entered clinical trials. However, thus far the response to these inhibitors has been poor, highlighting the importance of predictive biomarkers to identify patient cohorts who will benefit from these targeted agents. It is well‑documented that mutations and/or deletions in the epidermal growth factor receptor (EGFR) tyrosine kinase (TK) domain predict sensitivity of NSCLC patients to EGFR TK inhibitors. Single‑nucleotide polymorphisms (SNPs) in the IGF pathway have been associated with disease, including breast and prostate cancer. The aim of the present study was to elucidate whether the IGF1R TK domain harbours SNPs, somatic mutations or deletions in NSCLC patients and correlates the mutation status to patient clinicopathological data and prognosis. Initially 100 NSCLC patients were screened for mutations/deletions in the IGF1R TK domain (exons 16‑21) by sequencing analysis. Following the identification of SNP rs2229765, a further 98 NSCLC patients and 866 healthy disease‑free control patients were genotyped using an SNP assay. The synonymous SNP (rs2229765) was the only aberrant base change identified in the IGF1R TK domain of 100 NSCLC patients initially analysed. SNP rs2229765 was detected in exon 16 and was found to have no significant association between IGF1R expression and survival. The GA genotype was identified in 53.5 and 49.4% of NSCLC patients and control individuals, respectively. No significant difference was found in the genotype (P=0.5487) or allele (P=0.9082) frequencies between the case and control group. The present findings indicate that in contrast to the EGFR TK domain, the IGF1R TK domain is not frequently mutated in NSCLC patients. The synonymous SNP (rs2229765) had no significant association between IGF1R expression and survival in the cohort of NSCLC patients.