Intra- and inter-observer analysis in the morphological assessment of early-stage embryos

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to determine the intra- and inter-observer variability in the evaluation of embryo quality. Multilevel images of embryos on day 1, day 2 and day 3, were analysed using different morphological parameters.</p> <p>Methods</p> <p>Multilevel images of embryos on day 1, day 2 and day 3, were analysed using a standard scoring system. The kappa coefficient was calculated to measure intra- and inter-observer variability before and after training sessions.</p> <p>Results</p> <p>Good to excellent intra-observer agreement was present for most parameters exceptions being scoring the position of pronuclei and the presence of a cytoplasmic halo on day 1, multinucleation on day 2 and the size of fragments on day 3. Inter-observer agreement was only good to excellent for the number of blastomeres on day 2 and day 3 and the orientation of the cleavage axes on day 2. Training sessions had a positive impact on inter-observer agreement.</p> <p>Conclusion</p> <p>In conclusion, assessment of morphological characteristics of early stage embryos using multilevel images was marked by a high intra-observer and a moderate inter-observer agreement. Training sessions were useful to increase inter-observer agreement.</p

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed

New radiocarbon dates show Early Neolithic date of flintmining and stone quarrying in Britain

New radiocarbon (14C) dates suggest a simultaneous appearance of two technologically and geographically distinct axe production practices in Neolithic Britain; igneous open-air quarries in Great Langdale, Cumbria, and from flint mines in southern England at ~4000–3700 cal BC. In light of the recent evidence that farming was introduced at this time by large-scale immigration from northwest Europe, and that expansion within Britain was extremely rapid, we argue that this synchronicity supports this speed of colonization and reflects a knowledge of complex extraction processes and associated exchange networks already possessed by the immigrant groups; long-range connections developed as colonization rapidly expanded. Although we can model the start of these new extraction activities, it remains difficult to estimate how long significant production activity lasted at these key sites given the nature of the record from which samples could be obtained

Acute psychosocial stress alters thalamic network centrality

Acute stress triggers a broad psychophysiological response that is adaptive if rapidly activated and terminated. While the brain controls the stress response, it is strongly affected by it. Previous research of stress effects on brain activation and connectivity has mainly focused on pre-defined brain regions or networks, potentially missing changes in the rest of the brain. We here investigated how both stress reactivity and stress recovery are reflected in whole-brain network topology and how changes in functional connectivity relate to other stress measures. Healthy young males (n = 67) completed the Trier Social Stress Test or a control task. From 60 min before until 105 min after stress onset, blocks of resting-state fMRI were acquired. Subjective, autonomic, and endocrine measures of the stress response were assessed throughout the experiment. Whole-brain network topology was quantified using Eigenvector centrality (EC) mapping, which detects central hubs of a network. Stress influenced subjective affect, autonomic activity, and endocrine measures. EC differences between groups as well as before and after stress exposure were found in the thalamus, due to widespread connectivity changes in the brain. Stress-driven EC increases in the thalamus were significantly correlated with subjective stress ratings and showed non-significant trends for a correlation with heart rate variability and saliva cortisol. Furthermore, increases in thalamic EC and in saliva cortisol persisted until 105 min after stress onset. We conclude that thalamic areas are central for information processing after stress exposure and may provide an interface for the stress response in the rest of the body and in the mind