Prediction of sarcomere mutations in subclinical hypertrophic cardiomyopathy.

BACKGROUND: Sarcomere protein mutations in hypertrophic cardiomyopathy induce subtle cardiac structural changes before the development of left ventricular hypertrophy (LVH). We have proposed that myocardial crypts are part of this phenotype and independently associated with the presence of sarcomere gene mutations. We tested this hypothesis in genetic hypertrophic cardiomyopathy pre-LVH (genotype positive, LVH negative [G+LVH-]). METHODS AND RESULTS: A multicenter case-control study investigated crypts and 22 other cardiovascular magnetic resonance parameters in subclinical hypertrophic cardiomyopathy to determine their strength of association with sarcomere gene mutation carriage. The G+LVH- sample (n=73) was 29 ± 13 years old and 51% were men. Crypts were related to the presence of sarcomere mutations (for ≥1 crypt, β=2.5; 95% confidence interval [CI], 0.5-4.4; P=0.014 and for ≥2 crypts, β=3.0; 95% CI, 0.8-7.9; P=0.004). In combination with 3 other parameters: anterior mitral valve leaflet elongation (β=2.1; 95% CI, 1.7-3.1; P<0.001), abnormal LV apical trabeculae (β=1.6; 95% CI, 0.8-2.5; P<0.001), and smaller LV end-systolic volumes (β=1.4; 95% CI, 0.5-2.3; P=0.001), multiple crypts indicated the presence of sarcomere gene mutations with 80% accuracy and an area under the curve of 0.85 (95% CI, 0.8-0.9). In this G+LVH- population, cardiac myosin-binding protein C mutation carriers had twice the prevalence of crypts when compared with the other combined mutations (47 versus 23%; odds ratio, 2.9; 95% CI, 1.1-7.9; P=0.045). CONCLUSIONS: The subclinical hypertrophic cardiomyopathy phenotype measured by cardiovascular magnetic resonance in a multicenter environment and consisting of crypts (particularly multiple), anterior mitral valve leaflet elongation, abnormal trabeculae, and smaller LV systolic cavity is indicative of the presence of sarcomere gene mutations and highlights the need for further study

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology

We predicted residual fluid intelligence scores from T1-weighted MRI data available as part of the ABCD NP Challenge 2019, using morphological similarity of grey-matter regions across the cortex. Individual structural covariance networks (SCN) were abstracted into graph-theory metrics averaged over nodes across the brain and in data-driven communities/modules. Metrics included degree, path length, clustering coefficient, centrality, rich club coefficient, and small-worldness. These features derived from the training set were used to build various regression models for predicting residual fluid intelligence scores, with performance evaluated both using cross-validation within the training set and using the held-out validation set. Our predictions on the test set were generated with a support vector regression model trained on the training set. We found minimal improvement over predicting a zero residual fluid intelligence score across the sample population, implying that structural covariance networks calculated from T1-weighted MR imaging data provide little information about residual fluid intelligence.Comment: 8 pages plus references, 3 figures, 2 tables. Submission to the ABCD Neurocognitive Prediction Challenge at MICCAI 201

Anterior impingement syndrome in dancers

Anterior impingement is a common problem in dancers occurring primarily secondary to the repetitive forced ankle dorsiflexion inherent in ballet. Symptoms generally occur progressively and may respond to conservative treatment including addressing biomechanical faults that contribute to the problem. As impingement progresses, movements essential to ballet may become impossible and arthroscopic ankle surgery is often effective for both diagnosis and treatment, allowing athletes to return to dance

Elevated CO2 interacts with nutrient inputs to restructure plant communities in phosphorus-limited grasslands

This is the final version. Available on open access from Wiley via the DOI in this recordData availability statement: The data that support the findings of this study are openly available through Figshare at https://doi.org/10.6084/m9.figshare.23685921Globally pervasive increases in atmospheric CO2 and nitrogen (N) deposition could have substantial effects on plant communities, either directly or mediated by their interactions with soil nutrient limitation. While the direct consequences of N enrichment on plant communities are well documented, potential interactions with rising CO2 and globally widespread phosphorus (P) limitation remain poorly understood. We investigated the consequences of simultaneous elevated CO2 (eCO2 ) and N and P additions on grassland biodiversity, community and functional composition in P-limited grasslands. We exposed soil-turf monoliths from limestone and acidic grasslands that have received >25 years of N additions (3.5 and 14 g m-2  year-1 ) and 11 (limestone) or 25 (acidic) years of P additions (3.5 g m-2  year-1 ) to eCO2 (600 ppm) for 3 years. Across both grasslands, eCO2 , N and P additions significantly changed community composition. Limestone communities were more responsive to eCO2 and saw significant functional shifts resulting from eCO2 -nutrient interactions. Here, legume cover tripled in response to combined eCO2 and P additions, and combined eCO2 and N treatments shifted functional dominance from grasses to sedges. We suggest that eCO2 may disproportionately benefit P acquisition by sedges by subsidising the carbon cost of locally intense root exudation at the expense of co-occurring grasses. In contrast, the functional composition of the acidic grassland was insensitive to eCO2 and its interactions with nutrient additions. Greater diversity of P-acquisition strategies in the limestone grassland, combined with a more functionally even and diverse community, may contribute to the stronger responses compared to the acidic grassland. Our work suggests we may see large changes in the composition and biodiversity of P-limited grasslands in response to eCO2 and its interactions with nutrient loading, particularly where these contain a high diversity of P-acquisition strategies or developmentally young soils with sufficient bioavailable mineral P.Natural Environment Research Council (NERC

Effects of an exercise programme with people living with HIV: Research in a disadvantaged setting

This study aimed to analyse the physical health effects of a community based 10-week physical activity programme with people living with HIV. It was developed, implemented and evaluated in a disadvantaged community in South Africa. A pre-post research design was chosen. Major recruitment and adherence challenges resulted in a small sample. Among the 23 participants who took part in both baseline and final testing, compliant participants (n = 12) were compared to non-compliant participants (n = 11). Immunological (CD4, viral load), anthropometric (height, weight, skinfolds and waist to hip ratio), muscular strength (h1RM) and cardiopulmonary fitness (time on treadmill) parameters were measured. The compliant and non-compliant groups were not different at baseline. Muscular strength was the parameter most influenced by compliance with the physical activity programme (F = 4.516, p = 0.047). Weight loss and improvement in cardiopulmonary fitness were restricted by the duration of the programme, compliance and influencing factors (e.g. nutrition, medication). The increase in strength is significant and meaningful in the context, as the participants goals were to look healthy and strong to avoid HIV related stigma. The improvements in appearance were a motivational factor, especially since the changes were made visible in a short time. Practical implications for health promotion are described. More research contextualised in disadvantaged settings is needed.DHE

Subanesthetic ketamine treatment promotes abnormal interactions between neural subsystems and alters the properties of functional brain networks

Acute treatment with subanesthetic ketamine, a non-competitive N-methyl-D-aspartic acid (NMDA) receptor antagonist, is widely utilized as a translational model for schizophrenia. However, how acute NMDA receptor blockade impacts on brain functioning at a systems level, to elicit translationally relevant symptomatology and behavioral deficits, has not yet been determined. Here, for the first time, we apply established and recently validated topological measures from network science to brain imaging data gained from ketamine-treated mice to elucidate how acute NMDA receptor blockade impacts on the properties of functional brain networks. We show that the effects of acute ketamine treatment on the global properties of these networks are divergent from those widely reported in schizophrenia. Where acute NMDA receptor blockade promotes hyperconnectivity in functional brain networks, pronounced dysconnectivity is found in schizophrenia. We also show that acute ketamine treatment increases the connectivity and importance of prefrontal and thalamic brain regions in brain networks, a finding also divergent to alterations seen in schizophrenia. In addition, we characterize how ketamine impacts on bipartite functional interactions between neural subsystems. A key feature includes the enhancement of prefrontal cortex (PFC)-neuromodulatory subsystem connectivity in ketamine-treated animals, a finding consistent with the known effects of ketamine on PFC neurotransmitter levels. Overall, our data suggest that, at a systems level, acute ketamine-induced alterations in brain network connectivity do not parallel those seen in chronic schizophrenia. Hence, the mechanisms through which acute ketamine treatment induces translationally relevant symptomatology may differ from those in chronic schizophrenia. Future effort should therefore be dedicated to resolve the conflicting observations between this putative translational model and schizophrenia

Cognitive performance in healthy older adults relates to spontaneous switching between states of functional connectivity during rest

Growing evidence has shown that brain activity at rest slowly wanders through a repertoire of different states, where whole-brain functional connectivity (FC) temporarily settles into distinct FC patterns. Nevertheless, the functional role of resting-state activity remains unclear. Here, we investigate how the switching behavior of resting-state FC relates with cognitive performance in healthy older adults. We analyse resting-state fMRI data from 98 healthy adults previously categorized as being among the best or among the worst performers in a cohort study of >1000 subjects aged 50+ who underwent neuropsychological assessment. We use a novel approach focusing on the dominant FC pattern captured by the leading eigenvector of dynamic FC matrices. Recurrent FC patterns - or states - are detected and characterized in terms of lifetime, probability of occurrence and switching profiles. We find that poorer cognitive performance is associated with weaker FC temporal similarity together with altered switching between FC states. These results provide new evidence linking the switching dynamics of FC during rest with cognitive performance in later life, reinforcing the functional role of resting-state activity for effective cognitive processing.This project was financed by the Fundação Calouste Gulbenkian (Portugal) (Contract grant number: P-139977; project “Better mental health during ageing based on temporal prediction of individual brain ageing trajectories (TEMPO)”), co-financed by Portuguese North Regional Operational Program (ON.2) under the National Strategic Reference Framework (QREN), through the European Regional Development Fund (FEDER) as well as the Projecto Estratégico co-funded by FCT (PEst-C/SAU/LA0026-/2013) and the European Regional Development Fund COMPETE (FCOMP-01-0124-FEDER-037298) and under the scope of the project NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Programme (NORTE 2020) under the Portugal 2020 Partnership Agreement through the European Regional Development Fundinfo:eu-repo/semantics/publishedVersio

Effects of Different Correlation Metrics and Preprocessing Factors on Small-World Brain Functional Networks: A Resting-State Functional MRI Study

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01–0.027 Hz) versus slow-4 (0.027–0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the “best” network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027–0.073 Hz band exhibited greater reliability than those in the 0.01–0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific preprocessing choices on both the global and nodal topological properties of functional brain networks. This study also has important implications for how to choose reliable analytical schemes in brain network studies

Primordial Black Holes: sirens of the early Universe

Primordial Black Holes (PBHs) are, typically light, black holes which can form in the early Universe. There are a number of formation mechanisms, including the collapse of large density perturbations, cosmic string loops and bubble collisions. The number of PBHs formed is tightly constrained by the consequences of their evaporation and their lensing and dynamical effects. Therefore PBHs are a powerful probe of the physics of the early Universe, in particular models of inflation. They are also a potential cold dark matter candidate.Comment: 21 pages. To be published in "Quantum Aspects of Black Holes", ed. X. Calmet (Springer, 2014