Demonstrating mood repair with a situation-based measure of self-compassion and self-criticism.

The clinical significance of self-criticism and self-compassion has prompted the development of questionnaires assessing these constructs. However, there is a lack of measures assessing their interaction within specific contexts and potential involvement in mood repair processes

Embodying self-compassion within virtual reality and its effects on patients with depression

Background: Self-criticism is a ubiquitous feature of psychopathology and can be combatted by increasing levels of self-compassion. However, some patients are resistant to self-compassion. Aims: To investigate whether the effects of self-identification with virtual bodies within immersive virtual reality could be exploited to increase self-compassion in patients with depression. Method: We developed an 8-minute scenario in which 15 patients practised delivering compassion in one virtual body and then experienced receiving it from themselves in another virtual body. Results: In an open trial, three repetitions of this scenario led to significant reductions in depression severity and self-criticism, as well as to a significant increase in self-compassion, from baseline to 4-week follow-up. Four patients showed clinically significant improvement. Conclusions: The results indicate that interventions using immersive virtual reality may have considerable clinical potential and that further development of these methods preparatory to a controlled trial is now warranted

The genetics of mate preferences in hybrids between two young and sympatric Lake Victoria cichlid species

The genetic architecture of mate preferences is likely to affect significant evolutionary processes, including speciation and hybridization. Here, we investigate laboratory hybrids between a pair of sympatric Lake Victoria cichlid fish species that appear to have recently evolved from a hybrid population between similar predecessor species. The species demonstrate strong assortative mating in the laboratory, associated with divergent male breeding coloration (red dorsum versus blue). We show in a common garden experiment, using DNA-based paternity testing, that the strong female mate preferences among males of the two species are fully recovered in a large fraction of their F2 hybrid generation. Individual hybrid females often demonstrated consistent preferences in multiple mate choice trials (more than or equal to five) across a year or more. This result suggests that female mate preference is influenced by relatively few major genes or genomic regions. These preferences were not changed by experience of a successful spawning event with a male of the non-preferred species in a no-choice single-male trial. We found no evidence for imprinting in the F2 hybrids, although the F1 hybrid females may have been imprinted on their mothers. We discuss this nearly Mendelian inheritance of consistent innate mate preferences in the context of speciation theory

Multi-locus approaches for the measurement of selection on correlated genetic loci

The study of ecological speciation is inherently linked to the study of selection. Methods for estimating phenotypic selection within a generation based on associations between trait values and fitness (e.g., survival) of individuals are established. These methods attempt to disentangle selection acting directly on a trait from indirect selection caused by correlations with other traits via multivariate statistical approaches (i.e., inference of selection gradients). The estimation of selection on genotypic or genomic variation could also benefit from disentangling direct and indirect selection on genetic loci. However, achieving this goal is difficult with genomic data because the number of potentially correlated genetic loci (p) is very large relative to the number of individuals sampled (n). In other words, the number of model parameters exceeds the number of observations (p ≫ n). We present simulations examining the utility of whole genome regression approaches (i.e., Bayesian sparse linear mixed models) for quantifying direct selection in cases where p ≫ n. Such models have been used for genome-wide association mapping and are common in artificial breeding. Our results show they hold promise for studies of natural selection in the wild, and thus of ecological speciation. But we also demonstrate important limitations to the approach and discuss study designs required for more robust inferences

Diffusion magnetic resonance imaging assessment of regional white matter maturation in preterm neonates

PURPOSE: Diffusion magnetic resonance imaging (dMRI) studies report altered white matter (WM) development in preterm infants. Neurite orientation dispersion and density imaging (NODDI) metrics provide more realistic estimations of neurite architecture in vivo compared with standard diffusion tensor imaging (DTI) metrics. This study investigated microstructural maturation of WM in preterm neonates scanned between 25 and 45 weeks postmenstrual age (PMA) with normal neurodevelopmental outcomes at 2 years using DTI and NODDI metrics. METHODS: Thirty-one neonates (n = 17 male) with median (range) gestational age (GA) 32+1 weeks (24+2-36+4) underwent 3 T brain MRI at median (range) post menstrual age (PMA) 35+2 weeks (25+3-43+1). WM tracts (cingulum, fornix, corticospinal tract (CST), inferior longitudinal fasciculus (ILF), optic radiations) were delineated using constrained spherical deconvolution and probabilistic tractography in MRtrix3. DTI and NODDI metrics were extracted for the whole tract and cross-sections along each tract to assess regional development. RESULTS: PMA at scan positively correlated with fractional anisotropy (FA) in the CST, fornix and optic radiations and neurite density index (NDI) in the cingulum, CST and fornix and negatively correlated with mean diffusivity (MD) in all tracts. A multilinear regression model demonstrated PMA at scan influenced all diffusion measures, GA and GAxPMA at scan influenced FA, MD and NDI and gender affected NDI. Cross-sectional analyses revealed asynchronous WM maturation within and between WM tracts.). CONCLUSION: We describe normal WM maturation in preterm neonates with normal neurodevelopmental outcomes. NODDI can enhance our understanding of WM maturation compared with standard DTI metrics alone

Exploring the multiple-hit hypothesis of preterm white matter damage using diffusion MRI.

Background: Preterm infants are at high risk of diffuse white matter injury and adverse neurodevelopmental outcome. The multiple hit hypothesis suggests that the risk of white matter injury increases with cumulative exposure to multiple perinatal risk factors. Our aim was to test this hypothesis in a large cohort of preterm infants using diffusion weighted magnetic resonance imaging (dMRI). Methods: We studied 491 infants (52% male) without focal destructive brain lesions born at < 34 weeks, who underwent structural and dMRI at a specialist Neonatal Imaging Centre. The median (range) gestational age (GA) at birth was 30+ 1 (23+ 2-33+ 5) weeks and median postmenstrual age at scan was 42+ 1 (38-45) weeks. dMRI data were analyzed using tract based spatial statistics and the relationship between dMRI measures in white matter and individual perinatal risk factors was assessed. We tested the hypothesis that increased exposure to perinatal risk factors was associated with lower fractional anisotropy (FA), and higher radial, axial and mean diffusivity (RD, AD, MD) in white matter. Neurodevelopmental performance was investigated using the Bayley Scales of Infant and Toddler Development, Third Edition (BSITD-III) in a subset of 381 infants at 20 months corrected age. We tested the hypothesis that lower FA and higher RD, AD and MD in white matter were associated with poorer neurodevelopmental performance. Results: Identified risk factors for diffuse white matter injury were lower GA at birth, fetal growth restriction, increased number of days requiring ventilation and parenteral nutrition, necrotizing enterocolitis and male sex. Clinical chorioamnionitis and patent ductus arteriosus were not associated with white matter injury. Multivariate analysis demonstrated that fetal growth restriction, increased number of days requiring ventilation and parenteral nutrition were independently associated with lower FA values. Exposure to cumulative risk factors was associated with reduced white matter FA and FA values at term equivalent age were associated with subsequent neurodevelopmental performance. Conclusion: This study suggests multiple perinatal risk factors have an independent association with diffuse white matter injury at term equivalent age and exposure to multiple perinatal risk factors exacerbates dMRI defined, clinically significant white matter injury. Our findings support the multiple hit hypothesis for preterm white matter injury

Compassionate faces: Evidence for distinctive facial expressions associated with specific prosocial motivations

Compassion is a complex cognitive, emotional and behavioural process that has important real-world consequences for the self and others. Considering this, it is important to understand how compassion is communicated. The current research investigated the expression and perception of compassion via the face. We generated exemplar images of two compassionate facial expressions induced from two mental imagery tasks with different compassionate motivations (Study 1). Our kind- and empathic compassion faces were perceived differently and the empathic-compassion expression was perceived as best depicting the general definition of compassion (Study 2). Our two composite faces differed in their perceived happiness, kindness, sadness, fear and concern, which speak to their underling motivation and emotional resonance. Finally, both faces were accurately discriminated when presented along a compassion continuum (Study 3). Our results demonstrate two perceptually and functionally distinct facial expressions of compassion, with potentially different consequences for the suffering of others

Introgression of a major QTL from an inferior into a superior population using genomic selection

<p>Abstract</p> <p>Background</p> <p>Selection schemes aiming at introgressing genetic material from a donor into a recipient line may be performed by backcross-breeding programs combined with selection to preserve the favourable characteristics of the donor population. This stochastic simulation study investigated whether genomic selection can be effective in preserving a major quantitative trait locus (QTL) allele from a donor line during the backcrossing phase.</p> <p>Methods</p> <p>In a simulation study, two fish populations were generated: a recipient line selected for a production trait and a donor line characterized by an enhanced level of disease resistance. Both traits were polygenic, but one major QTL affecting disease resistance was segregating only within the donor line. Backcrossing was combined with three types of selection (for total merit index) among the crossbred individuals: classical selection, genomic selection using genome-wide dense marker maps, and gene-assisted genomic selection. It was assumed that production could be observed directly on the selection candidates, while disease resistance had to be inferred from tested sibs of the selection candidates.</p> <p>Results</p> <p>Classical selection was inefficient in preserving the target QTL through the backcrossing phase. In contrast, genomic selection (without specific knowledge of the target QTL) was usually effective in preserving the target QTL, and had higher genetic response to selection, especially for disease resistance. Compared with pure genomic selection, gene-assisted selection had an advantage with respect to disease resistance (28–40% increase in genetic gain) and acted as an extra precaution against loss of the target QTL. However, for total merit index the advantage of gene-assisted genomic selection over genomic selection was lower (4–5% increase in genetic gain).</p> <p>Conclusion</p> <p>Substantial differences between introgression programs using classical and genomic selection were observed, and the former was generally inferior with respect to both genetic gain and the ability to preserve the target QTL. Combining genomic selection with gene-assisted selection for the target QTL acted as an extra precaution against loss of the target QTL and gave additional genetic gain for disease resistance. However, the effect on total merit index was limited.</p

Accuracy of breeding values of 'unrelated' individuals predicted by dense SNP genotyping

<p>Abstract</p> <p>Background</p> <p>Recent developments in SNP discovery and high throughput genotyping technology have made the use of high-density SNP markers to predict breeding values feasible. This involves estimation of the SNP effects in a training data set, and use of these estimates to evaluate the breeding values of other 'evaluation' individuals. Simulation studies have shown that these predictions of breeding values can be accurate, when training and evaluation individuals are (closely) related. However, many general applications of genomic selection require the prediction of breeding values of 'unrelated' individuals, i.e. individuals from the same population, but not particularly closely related to the training individuals.</p> <p>Methods</p> <p>Accuracy of selection was investigated by computer simulation of small populations. Using scaling arguments, the results were extended to different populations, training data sets and genome sizes, and different trait heritabilities.</p> <p>Results</p> <p>Prediction of breeding values of unrelated individuals required a substantially higher marker density and number of training records than when prediction individuals were offspring of training individuals. However, when the number of records was 2*N_e*L and the number of markers was 10*N_e*L, the breeding values of unrelated individuals could be predicted with accuracies of 0.88 – 0.93, where N_eis the effective population size and L the genome size in Morgan. Reducing this requirement to 1*N_e*L individuals, reduced prediction accuracies to 0.73–0.83.</p> <p>Conclusion</p> <p>For livestock populations, 1N_eL requires about ~30,000 training records, but this may be reduced if training and evaluation animals are related. A prediction equation is presented, that predicts accuracy when training and evaluation individuals are related. For humans, 1N_eL requires ~350,000 individuals, which means that human disease risk prediction is possible only for diseases that are determined by a limited number of genes. Otherwise, genotyping and phenotypic recording need to become very common in the future.</p