Endurance Training Per Se Increases Metabolic Health in Young,Moderately Overweight Men

Health benefits of physical activity may depend on a concomitant weight loss. In a randomized, controlled trial, we compared the effects of endurance training with or without weight loss to the effect of weight loss induced by an energy‐reduced diet in 48 sedentary, moderately overweight men who completed a 12‐week intervention program of training (T), energy‐reduced diet (D), training and increased diet (T‐iD), or control (C). An energy deficit of 600 kcal/day was induced by endurance training or diet in T and D and a similar training regimen plus an increased dietary intake of 600 kcal/day defined the T‐iD group. Primary end point was insulin sensitivity as evaluated by HOMA‐IR (mainly reflecting hepatic insulin sensitivity) and hyperinsulinemic, isoglycemic clamps (primarily reflecting peripheral insulin sensitivity). Body mass decreased in T and D by 5.9 ± 0.7 and 5.3 ± 0.7 kg, respectively, whereas T‐iD and C remained weight stable. Total and abdominal fat mass were reduced in an additive manner in the T‐iD, D, and T groups by 1.9 ± 0.3/0.2 ± 0.1, 4.4 ± 0.7/0.5 ± 0.1, and 7.7 ± 0.8/0.9 ± 0.1 kg, respectively. HOMA‐IR was improved in T, D, and T‐iD, whereas insulin‐stimulated glucose clearance and suppression of plasma nonesterified fatty acids (NEFAs) were increased only in the two training groups. Thus, loss of fat mass (diet or training induced) improves hepatic insulin sensitivity, whereas peripheral insulin sensitivity in skeletal muscle and adipose tissue is increased by endurance training only. This demonstrates that endurance training per se increases various metabolic health parameters and that endurance training should preferably always be included in any intervention regimen for improving metabolic health in moderately overweight men.     

Age-Related Differences in Test-Retest Reliability in Resting-State Brain Functional Connectivity

Resting-state functional MRI (rs-fMRI) has emerged as a powerful tool for investigating brain functional connectivity (FC). Research in recent years has focused on assessing the reliability of FC across younger subjects within and between scan-sessions. Test-retest reliability in resting-state functional connectivity (RSFC) has not yet been examined in older adults. In this study, we investigated age-related differences in reliability and stability of RSFC across scans. In addition, we examined how global signal regression (GSR) affects RSFC reliability and stability. Three separate resting-state scans from 29 younger adults (18–35 yrs) and 26 older adults (55–85 yrs) were obtained from the International Consortium for Brain Mapping (ICBM) dataset made publically available as part of the 1000 Functional Connectomes project www.nitrc.org/projects/fcon_1000. 92 regions of interest (ROIs) with 5 cubic mm radius, derived from the default, cingulo-opercular, fronto-parietal and sensorimotor networks, were previously defined based on a recent study. Mean time series were extracted from each of the 92 ROIs from each scan and three matrices of z-transformed correlation coefficients were created for each subject, which were then used for evaluation of multi-scan reliability and stability. The young group showed higher reliability of RSFC than the old group with GSR (p-value = 0.028) and without GSR (p-value <0.001). Both groups showed a high degree of multi-scan stability of RSFC and no significant differences were found between groups. By comparing the test-retest reliability of RSFC with and without GSR across scans, we found significantly higher proportion of reliable connections in both groups without GSR, but decreased stability. Our results suggest that aging is associated with reduced reliability of RSFC which itself is highly stable within-subject across scans for both groups, and that GSR reduces the overall reliability but increases the stability in both age groups and could potentially alter group differences of RSFC.     

Materials Challenges for High Performance Magnetocaloric Refrigeration Devices

Magnetocaloric materials with a Curie temperature near room temperature have attracted significant interest for some time due to their possible application for high‐efficiency refrigeration devices. This review focuses on a number of key issues of relevance for the characterization, performance and implementation of such materials in actual devices. The phenomenology and fundamental thermodynamics of magnetocaloric materials is discussed, as well as the hysteresis behavior often found in first‐order materials. A number of theoretical and experimental approaches and their implications are reviewed. The question of how to evaluate the suitability of a given material for use in a magnetocaloric device is covered in some detail, including a critical assessment of a number of common performance metrics. Of particular interest is which non‐magnetocaloric properties need to be considered in this connection. An overview of several important materials classes is given before considering the performance of materials in actual devices. Finally, an outlook on further developments is presented.     

Distinguishing between Selective Sweeps from Standing Variation and from a De Novo Mutation

An outstanding question in human genetics has been the degree to which adaptation occurs from standing genetic variation or from de novo mutations. Here, we combine several common statistics used to detect selection in an Approximate Bayesian Computation (ABC) framework, with the goal of discriminating between models of selection and providing estimates of the age of selected alleles and the selection coefficients acting on them. We use simulations to assess the power and accuracy of our method and apply it to seven of the strongest sweeps currently known in humans. We identify two genes, ASPM and PSCA, that are most likely affected by selection on standing variation; and we find three genes, ADH1B, LCT, and EDAR, in which the adaptive alleles seem to have swept from a new mutation. We also confirm evidence of selection for one further gene, TRPV6. In one gene, G6PD, neither neutral models nor models of selective sweeps fit the data, presumably because this locus has been subject to balancing selection.     

Metabolite extraction from suspension-cultured mammalian cells for global metabolite profiling

Metabolite profiling of industrially important suspension-cultured mammalian cells is being increasingly used for rational improvement of bioprocesses. This requires the generation of global metabolite profiles that cover a broad range of metabolites and that are representative of the cells at the time of sampling. The protocol described here is a validated method for recovery of physiologically relevant amounts of key metabolites from suspension-cultured mammalian cells. The method is a two-step process consisting of initial quenching of the cells (to stop cellular metabolism and allow isolation of the cells) followed by extraction of the metabolites. The cells are quenched in 60% methanol supplemented with 0.85% (wt/vol) ammonium bicarbonate at -40 °C. Metabolites are then extracted from the quenched cells using two 100% methanol extractions followed by a single water extraction. Metabolite samples generated using this protocol are amenable to analysis by mass spectrometry-based techniques (e.g., gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry), NMR spectroscopy and enzymatic assays.     

A Model-Based Approach for Identifying Signatures of Ancient Balancing Selection in Genetic Data

While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates.     

Strategies for imputation to whole genome sequence using a single or multi-breed reference population in cattle

Background

The advent of low cost next generation sequencing has made it possible to sequence a large number of dairy and beef bulls which can be used as a reference for imputation of whole genome sequence data. The aim of this study was to investigate the accuracy and speed of imputation from a high density SNP marker panel to whole genome sequence level. Data contained 132 Holstein, 42 Jersey, 52 Nordic Red and 16 Brown Swiss bulls with whole genome sequence data; 16 Holstein, 27 Jersey and 29 Nordic Reds had previously been typed with the bovine high density SNP panel and were used for validation. We investigated the effect of enlarging the reference population by combining data across breeds on the accuracy of imputation, and the accuracy and speed of both IMPUTE2 and BEAGLE using either genotype probability reference data or pre-phased reference data. All analyses were done on Bovine autosome 29 using 387,436 bi-allelic variants and 13,612 SNP markers from the bovine HD panel.

Results

A combined breed reference population led to higher imputation accuracies than did a single breed reference. The highest accuracy of imputation for all three test breeds was achieved when using BEAGLE with un-phased reference data (mean genotype correlations of 0.90, 0.89 and 0.87 for Holstein, Jersey and Nordic Red respectively) but IMPUTE2 with un-phased reference data gave similar accuracies for Holsteins and Nordic Red. Pre-phasing the reference data only lead to a minor decrease in the imputation accuracy, but gave a large improvement in computation time. Pre-phasing with BEAGLE was substantially faster than pre-phasing with SHAPEIT2 (2.5 hours vs. 52 hours for 242 individuals), and imputation with pre-phased data was faster in IMPUTE2 than in BEAGLE (5 minutes vs. 50 minutes per individual).

Conclusion

Combining reference populations across breeds is a good option to increase the size of the reference data and in turn the accuracy of imputation when only few animals are available. Pre-phasing the reference data only slightly decreases the accuracy but gives substantial improvements in speed. Using BEAGLE for pre-phasing and IMPUTE2 for imputation is a fast and accurate strategy.     

A trypsin-like protease with apparent dual function in early Lepeophtheirus salmonis (Kr?yer) development

Background  

Trypsin-like serine proteases are involved in a large number of processes including digestive degradation, regulation of developmental processes, yolk degradation and yolk degradome activation. Trypsin like peptidases considered to be involved in digestion have been characterized in Lepeophtheirus salmonis. During these studies a trypsin-like peptidase which differed in a number of traits were identified.