Clinical trials in cystic fibrosis

In patients with cystic fibrosis (CF), clinical trials are of paramount importance. Here, the current status of drug development in CF is discussed and future directions highlighted. Methods for pre-clinical testing of drugs with potential activity in CF patients including relevant animal models are described. Study design options for phase II and phase III studies involving CF patients are provided, including required patient numbers, safety issues and surrogate end point parameters for drugs, tested for different disease manifestations. Finally, regulatory issues for licensing new therapies for CF patients are discussed, including new directives of the European Union and the structure of a European clinical trial network for clinical studies involving CF patients is proposed.

Laughter Induction Techniques Suitable for Generating Motion Capture Data of Laughter Associated Body Movements

Laughter is a frequently occurring social signal and an important part of human non-verbal communication. However it is often overlooked as a serious topic of scientific study. While the lack of research in this area is mostly due to laughter’s non-serious nature, it is also a particularly difficult social signal to produce on demand in a convincing manner; thus making it a difficult topic for study in laboratory settings. In this paper we provide some techniques and guidance for inducing both hilarious laughter and conversational laughter. These techniques were devised with the goal of capturing mo- tion information related to laughter while the person laughing was either standing or seated. Comments on the value of each of the techniques and general guidance as to the importance of atmosphere, environment and social setting are provided.

Behavioural and physiological responses of heifer calves to acute stressors: long-term consistency and relationship with adult reactivity to milking

The present study investigated the long-term consistency of individual differences in dairy cattles’ responses in tests of behavioural and hypothalamo–pituitary–adrenocortical (HPA) axis reactivity, as well as the relationship between responsiveness in behavioural tests and the reaction to first milking. Two cohorts of heifer calves, Cohorts 1 (N = 25) and 2 (N = 16), respectively, were examined longitudinally from the rearing period until adulthood. Cohort 1 heifers were subjected to open field (OF), novel object (NO), restraint, and response to a human tests at 7 months of age, and were again observed in an OF test during first pregnancy between 22 and 24 months of age. Subsequently, inhibition of milk ejection and stepping and kicking behaviours were recorded in Cohort 1 heifers during their first machine milking. Cohort 2 heifers were individually subjected to OF and NO tests as well as two HPA axis reactivity tests (determining ACTH and/or cortisol response profiles after administration of exogenous CRH and ACTH, respectively) at 6 months of age and during first lactation at approximately 29 months of age. Principal component analysis (PCA) was used to condense correlated response measures (to behavioural tests and to milking) within ages into independent dimensions underlying heifers’ reactivity. Heifers demonstrated consistent individual differences in locomotion and vocalisation during an OF test from rearing to first pregnancy (Cohort 1) or first lactation (Cohort 2). Individual differences in struggling in a restraint test at 7 months of age reliably predicted those in OF locomotion during first pregnancy in Cohort 1 heifers. Cohort 2 animals with high cortisol responses to OF and NO tests and high avoidance of the novel object at 6 months of age also exhibited enhanced cortisol responses to OF and NO tests at 29 months of age. Measures of HPA axis reactivity, locomotion, vocalisation and adrenocortical and behavioural responses to novelty were largely uncorrelated, supporting the idea that stress responsiveness in dairy cows is mediated by multiple independent underlying traits. Inhibition of milk ejection and stepping and kicking behaviours during first machine milking were not related to earlier struggling during restraint, locomotor responses to OF and NO tests, or the behavioural interaction with a novel object. Heifers with high rates of OF and NO vocalisation and short latencies to first contact with the human at 7 months of age exhibited better milk ejection during first machine milking. This suggests that low underlying sociality might be implicated in the inhibition of milk ejection at the beginning of lactation in heifers.

Regulator of G-protein signaling 4 (RGS4) gene is associated with schizophrenia in Irish high density families

The regulator of the G-protein signaling 4 (RGS4) gene was shown to have a different expression pattern in schizophrenia patients in a microarray study. A family-based study subsequently implicated the association of this gene with schizophrenia. We replicated the study with our sample from the Irish Study of High Density Schizophrenia Families (ISHDSF). Single marker transmission disequilibrium tests (TDT) for the four core SNPs showed modest association for SNP 18 (using a narrow diagnostic approach with FBAT P = 0.044; with PDT P = 0.0073) and a trend for SNP 4 (with FBAT P = 0.1098; with PDT P = 0.0249). For SNP 1 and 7, alleles overtransmitted to affected subjects were the same as previously reported. Haplotype analyses suggested that haplotype G-G-G for SNP1-4-18, which is the most abundant haplotype (42.3%) in the Irish families, was associated with the disease (narrow diagnosis, FBAT P = 0.0061, PDT P = 0.0498). This was the same haplotype implicated in the original study. While P values were not corrected for multiple testing because of the clear prior hypothesis, these results could be interpreted as supporting evidence for the association between RGS4 and schizophrenia.

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

Laughter Type Recognition from Whole Body Motion

Despite the importance of laughter in social interactions it remains little studied in affective computing. Respiratory, auditory, and facial laughter signals have been investigated but laughter-related body movements have received almost no attention. The aim of this study is twofold: first an investigation into observers' perception of laughter states (hilarious, social, awkward, fake, and non-laughter) based on body movements alone, through their categorization of avatars animated with natural and acted motion capture data. Significant differences in torso and limb movements were found between animations perceived as containing laughter and those perceived as nonlaughter. Hilarious laughter also differed from social laughter in the amount of bending of the spine, the amount of shoulder rotation and the amount of hand movement. The body movement features indicative of laughter differed between sitting and standing avatar postures. Based on the positive findings in this perceptual study, the second aim is to investigate the possibility of automatically predicting the distributions of observer's ratings for the laughter states. The findings show that the automated laughter recognition rates approach human rating levels, with the Random Forest method yielding the best performance.