Femtosecond Transfer and Manipulation of Persistent Hot-Trion Coherence in a Single CdSe/ZnSe Quantum Dot.

Ultrafast transmission changes around the fundamental trion resonance are studied after exciting a p-shell exciton in a negatively charged II-VI quantum dot. The biexcitonic induced absorption reveals quantum beats between hot-trion states at 133 GHz. While interband dephasing is dominated by relaxation of the P-shell hole within 390 fs, trionic coherence remains stored in the spin system for 85 ps due to Pauli blocking of the triplet electron. The complex spectrotemporal evolution of transmission is explained analytically by solving the Maxwell-Liouville equations. Pump and probe polarizations provide full control over amplitude and phase of the quantum beats.

Investigation of the crystallization process of CSD-ErBCO on IBAD-substrate via DSD approach.

REBa2Cu3O7-δ (REBCO, RE: rare earth, such as Y and Gd) compounds have been extensively studied as a superconducting layer in coated conductors. Although ErBCO potentially has better superconducting properties than YBCO and GdBCO, little research has been made on it, especially in chemical solution deposition (CSD). In this work, ErBCO films were deposited on IBAD (ion-beam-assisted-deposition) substrates by CSD with low-fluorine solutions. The crystallization process was optimized to achieve the highest self-field critical current density (Jc) at 77 K. Commonly, for the investigation of a CSD process involving numerous process factors, one factor is changed keeping the others constant, requiring much time and cost. For more efficient investigation, this study adopted a novel design-of-experiment technique, definitive screening design (DSD), for the first time in CSD process. Two different types of solutions containing Er-propionate or Er-acetate were used to make two types of samples, Er-P and Er-A, respectively. Within the investigated range, we found that crystallization temperature, dew point, and oxygen partial pressure play a key role in Er-P, while the former two factors are significant for Er-A. DSD revealed these significant factors among six process factors with only 14 trials. Moreover, the DSD approach allowed us to create models that predict Jc accurately. These models revealed the optimum conditions giving the highest Jc values of 3.6 MA/cm2 for Er-P and 3.0 MA/cm2 for Er-A. These results indicate that DSD is an attractive approach to optimize CSD process.

Phasing quality assessment in a brown layer population through family- and population-based software.

BACKGROUND: Haplotype data contains more information than genotype data and provides possibilities such as imputing low frequency variants, inferring points of recombination, detecting recurrent mutations, mapping linkage disequilibrium (LD), studying selection signatures, estimating IBD probabilities, etc. In addition, haplotype structure is used to assess genetic diversity and expected accuracy in genomic selection programs. Nevertheless, the quality and efficiency of phasing has rarely been a subject of thorough study but was assessed mainly as a by-product in imputation quality studies. Moreover, phasing studies based on data of a poultry population are non-existent. The aim of this study was to evaluate the phasing quality of FImpute and Beagle, two of the most used phasing software. RESULTS: We simulated ten replicated samples of a layer population comprising 888 individuals from a real SNP dataset of 580 k and a pedigree of 12 generations. Chromosomes analyzed were 1, 7 and 20. We measured the percentage of SNPs that were phased equally between true and phased haplotypes (Eqp), proportion of individuals completely correctly phased, number of incorrectly phased SNPs or Breakpoints (Bkp) and the length of inverted haplotype segments. Results were obtained for three different groups of individuals, with no parents or offspring genotyped in the dataset, with only one parent, and with both parents, respectively. The phasing was performed with Beagle (v3.3 and v4.1) and FImpute v2.2 (with and without pedigree). Eqp values ranged from 88 to 100%, with the best results from haplotypes phased with Beagle v4.1 and FImpute with pedigree information and at least one parent genotyped. FImpute haplotypes showed a higher number of Bkp than Beagle. As a consequence, switched haplotype segments were longer for Beagle than for FImpute. CONCLUSION: We concluded that for the dataset applied in this study Beagle v4.1 or FImpute with pedigree information and at least one parent genotyped in the data set were the best alternatives for obtaining high quality phased haplotypes.

Short communication: Calculating analytical reliabilities for single-step predictions.

It has been shown that single-step genomic BLUP (ssGBLUP) can be reformulated, resulting in an equivalent SNP model that includes the explicit imputation of gene contents of all ungenotyped animals in the pedigree. This reformulation reveals the underlying mechanism enabling ungenotyped animals to contribute information to genotyped animals via estimates of marker effects and consequently to the reliability of genomic predictions, a key feature generally associated with the single-step approach. Irrespective of which BLUP formulation is used for genomic prediction, with increasing numbers of genotyped animals, the marker-oriented model is recommended when calculating the reliabilities of genomic predictions. This approach has the advantage of a manageable and stable size of the model matrix that needs to be inverted to calculate analytical prediction error variances of marker effects, an advantage that also holds for prediction with the single-step model. However, when including imputed genotypes in the design matrix of marker effects, an additional imputation residual term has to be considered to account for the prediction error of imputation. We summarize some of the theoretical aspects associated with the calculation of analytical reliabilities of single-step predictions. Derivations are based on the equivalent reformulation of ssGBLUP as a marker-oriented model and the calculation of prediction error variances of marker effects. We propose 2 approximations that allow for a substantial reduction of the complexity of the matrix operations involved, while retaining most of the relevant information required for reliability calculations. We additionally provide a general framework for an implementation of single-step reliability approximation using standard animal model reliabilities as a starting point. Finally, we demonstrate the effectiveness of the proposed approach using a small example extracted from data of the routine evaluation on dual-purpose Fleckvieh (Simmental) cattle.

Empirical comparison between different methods for genomic prediction of number of piglets born alive in moderate sized breeding populations.

Currently used multi-step methods to incorporate genomic information in the prediction of breeding values (BV) implicitly involve many assumptions which, if violated, may result in loss of information, inaccuracies and bias. To overcome this, single-step genomic best linear unbiased prediction (ssGBLUP) was proposed combining pedigree, phenotype and genotype of all individuals for genetic evaluation. Our objective was to implement ssGBLUP for genomic predictions in pigs and to compare the accuracy of ssGBLUP with that of multi-step methods with empirical data of moderately sized pig breeding populations. Different predictions were performed: conventional parent average (PA), direct genomic value (DGV) calculated with genomic BLUP (GBLUP), a GEBV obtained by blending the DGV with PA, and ssGBLUP. Data comprised individuals from a German Landrace (LR) and Large White (LW) population. The trait 'number of piglets born alive' (NBA) was available for 182,054 litters of 41,090 LR sows and 15,750 litters from 4534 LW sows. The pedigree contained 174,021 animals, of which 147,461 (26,560) animals were LR (LW) animals. In total, 526 LR and 455 LW animals were genotyped with the Illumina PorcineSNP60 BeadChip. After quality control and imputation, 495 LR (424 LW) animals with 44,368 (43,678) SNP on 18 autosomes remained for the analysis. Predictive abilities, i.e., correlations between de-regressed proofs and genomic BV, were calculated with a five-fold cross validation and with a forward prediction for young genotyped validation animals born after 2011. Generally, predictive abilities for LR were rather small (0.08 for GBLUP, 0.19 for GEBV and 0.18 for ssGBLUP). For LW, ssGBLUP had the greatest predictive ability (0.45). For both breeds, assessment of reliabilities for young genotyped animals indicated that genomic prediction outperforms PA with ssGBLUP providing greater reliabilities (0.40 for LR and 0.32 for LW) than GEBV (0.35 for LR and 0.29 for LW). Grouping of animals according to information sources revealed that genomic prediction had the highest potential benefit for genotyped animals without their own phenotype. Although, ssGBLUP did not generally outperform GBLUP or GEBV, the results suggest that ssGBLUP can be a useful and conceptually convincing approach for practical genomic prediction of NBA in moderately sized LR and LW populations.

Accuracy of genomic breeding values revisited: Assessment of two established approaches and a novel one to determine the accuracy in two-step genomic prediction.

Selection decisions in genomic selection schemes are made based on genomic breeding values (GBV) of candidates. Thus, the accuracy of GBV is a relevant parameter, as it reflects the stability of prediction and the possibility that the GBV might change when more information becomes available. Accuracy of genomic prediction defined as the correlation between GBV and true breeding values (TBV), however, is difficult to assess, considering TBV of the candidates are not available in reality. In previous studies, several methods were proposed to assess the accuracy of GBV including methods using population parameters or parameters inferred from mixed-model equations. In practice, most approaches tended to overestimate the accuracy of genomic prediction. We thus tested approaches used in previous studies in order to assess the magnitude of bias. Analyses were performed based on simulated data under a variety of scenarios mimicking different livestock breeding programmes. Furthermore, we proposed a novel method and tested it both with simulated data and in a real Holstein data set. The new method provided a better prediction for the accuracy of GBV in the simulated scenarios.

Using the variability of linkage disequilibrium between subpopulations to infer sweeps and epistatic selection in a diverse panel of chickens.

A whole-genome scan for identifying selection acting on pairs of linked loci is proposed and implemented. The scan is based on , one of Ohta's 1982 measures of between-population linkage disequilibrium (LD). An approximate empirical null distribution for the statistic is suggested. Although the partitioning of LD into between-population components was originally used to investigate epistatic selection, we demonstrate that values of may also be influenced by single-locus selective sweeps with linkage but no epistasis. The proposed scan is implemented in a diverse panel of chickens including 72 distinct breeds genotyped at 538 298 single-nucleotide polymorphisms. In all, 1723 locus pairs are identified as putatively corresponding to a selective sweep or epistatic selection. These pairs of loci generally cluster to form overlapping or neighboring signals of selection. Known variants that were expected to have been under selection in the panel are identified, as well as an assortment of novel regions that have putatively been under selection in chickens. Notably, a promising pair of genes located 8 MB apart on chromosome 9 are identified based on as demonstrating strong evidence of dispersive epistatic selection between populations.

Can multi-subpopulation reference sets improve the genomic predictive ability for pigs?

In most countries and for most livestock species, genomic evaluations are obtained from within-breed analyses. To achieve reliable breeding values, however, a sufficient reference sample size is essential. To increase this size, the use of multibreed reference populations for small populations is considered a suitable option in other species. Over decades, the separate breeding work of different pig breeding organizations in Germany has led to stratified subpopulations in the breed German Large White. Due to this fact and the limited number of Large White animals available in each organization, there was a pressing need for ascertaining if multi-subpopulation genomic prediction is superior compared with within-subpopulation prediction in pigs. Direct genomic breeding values were estimated with genomic BLUP for the trait "number of piglets born alive" using genotype data (Illumina Porcine 60K SNP BeadChip) from 2,053 German Large White animals from five different commercial pig breeding companies. To assess the prediction accuracy of within- and multi-subpopulation reference sets, a random 5-fold cross-validation with 20 replications was performed. The five subpopulations considered were only slightly differentiated from each other. However, the prediction accuracy of the multi-subpopulations approach was not better than that of the within-subpopulation evaluation, for which the predictive ability was already high. Reference sets composed of closely related multi-subpopulation sets performed better than sets of distantly related subpopulations but not better than the within-subpopulation approach. Despite the low differentiation of the five subpopulations, the genetic connectedness between these different subpopulations seems to be too small to improve the prediction accuracy by applying multi-subpopulation reference sets. Consequently, resources should be used for enlarging the reference population within subpopulation, for example, by adding genotyped females.

Accuracy of direct genomic values for functional traits in Brown Swiss cattle.

In this study, direct genomic values for the functional traits general temperament, milking temperament, aggressiveness, rank order in herd, milking speed, udder depth, position of labia, and days to first heat in Brown Swiss dairy cattle were estimated based on ~777,000 (777 K) single nucleotide polymorphism (SNP) information from 1,126 animals. Accuracy of direct genomic values was assessed by a 5-fold cross-validation with 10 replicates. Correlations between deregressed proofs and direct genomic values were 0.63 for general temperament, 0.73 for milking temperament, 0.69 for aggressiveness, 0.65 for rank order in herd, 0.69 for milking speed, 0.71 for udder depth, 0.66 for position of labia, and 0.74 for days to first heat. Using the information of ~54,000 (54K) SNP led to only marginal deviations in the observed accuracy. Trying to predict the 20% youngest bulls led to correlations of 0.55, 0.77, 0.73, 0.55, 0.64, 0.59, 0.67, and 0.77, respectively, for the traits listed above. Using a novel method to estimate the accuracy of a direct genomic value (defined as correlation between direct genomic value and true breeding value and accounting for the correlation between direct genomic values and conventional breeding values) revealed accuracies of 0.37, 0.20, 0.19, 0.27, 0.48, 0.45, 0.36, and 0.12, respectively, for the traits listed above. These values are much smaller but probably also more realistic than accuracies based on correlations, given the heritabilities and samples sizes in this study. Annotation of the largest estimated SNP effects revealed 2 candidate genes affecting the traits general temperament and days to first heat.

Interplay between heritability, genetic correlation and economic weighting in a selection index with and without genomic information.

The availability of genomic information demands proper evaluation on how the kind (phenotypic versus genomic) and the amount of information influences the interplay of heritability (h(2)), genetic correlation (r(GiGj)) and economic weighting of traits with regard to the standard deviation of the index (σI). As σI is directly proportional to response to selection, it was the chosen parameter for comparing the indices. Three selection indices incorporating conventional and genomic information for a two trait (i and j) breeding goal were compared. Information sources were chosen corresponding to pig breeding applications. Index I incorporating an own performance in trait j served as reference scenario. In index II, additional information in both traits was contributed by a varying number of full-sibs (2, 7, 50). In index III, the conventional own performance in trait j was combined with genomic information for both traits. The number of animals in the reference population (NP = 1000, 5000, 10,000) and thus the accuracy of GBVs were varied. With more information included in the index, σI became more independent of r(GiGj), h(j)(2) and relative economic weighting. This applied for index II (more full-sibs) and for index III (more accurate GBVs). Standard deviations of index II with seven full-sibs and index III with NP = 1000 were similar when both traits had the same heritability. If the heritability of trait j was reduced (h(j)(2) = 0.1), σI of index III with NP = 1000 was clearly higher than for index II with seven full-sibs. When enhancing the relative economic weight of trait j, the decrease in σI of the conventional full-sib index was much stronger than for index III. Our results imply that NP = 1000 can be considered a minimum size for a reference population in pig breeding. These conclusions also hold for comparing the accuracies of the indices.

Estimation of genetic parameters for individual udder quarter milk content traits in Brown Swiss cattle.

The aim of this study was to estimate genetic parameters and accuracies of breeding values for milk content traits of individual udder quarters in Brown Swiss cattle. Data of 1,799 phenotyped cows from 40 Swiss dairy herds were analyzed, taking the complete pedigree into account. Fat, protein, lactose, and urea contents, somatic cell score (SCS), and information about hyperkeratosis were available for each udder quarter. The milk of rear udder quarters was found to have significantly higher lactose content and significantly lower fat content than milk of the front udder quarters. The same trend found for fat content was observed for protein content, whereas no differences between the udder quarters were observed for urea content, SCS, or hyperkeratosis. Heritabilities for each udder quarter were in the following ranges: fat content 0.09±0.06 to 0.14±0.06, protein content 0.20±0.09 to 0.33±0.07, lactose content 0.04±0.03 to 0.16±0.07, urea content 0.13±0.07 to 0.22±0.08, SCS 0.18±0.06 to 0.32±0.07, and hyperkeratosis 0.12±0.04 to 0.26±0.05. In our study, hyperkeratosis, protein content, and SCS showed higher heritabilities in the front udder quarters, fat content had higher heritabilities in the rear udder quarters, and no systematic pattern in heritability was observed for lactose content or urea content. Additive genetic correlations between all udder quarters were >0.90 for protein and urea contents, whereas they were remarkably low (<0.60) for SCS. For fat and lactose contents, the genetic correlations between the 2 front or between the 2 rear quarters, respectively, were notably higher than correlations between 1 front and 1 rear quarter, suggesting that the front and the rear udders could be considered as partly genetically different organs. The variability within the udder as such was found to be of low heritability (<0.10) in general, but repeatability was moderate to high for some traits (lactose content: 0.33±0.05, protein content: 0.53±0.05). Some of these findings can be explained by differences in the physiological background of the traits.

Estimation of genetic parameters for novel functional traits in Brown Swiss cattle.

The aim of this study was to estimate genetic parameters and accuracies of breeding values for a set of functional, behavior, and conformation traits in Brown Swiss cattle. These traits were milking speed, udder depth, position of labia, rank order in herd, general temperament, aggressiveness, milking temperament, and days to first heat. Data of 1,799 phenotyped Brown Swiss cows from 40 Swiss dairy herds were analyzed taking the complete pedigree into account. Estimated heritabilities were within the ranges reported in literature, with results at the high end of the reported values for some traits (e.g., milking speed: 0.42±0.06, udder depth: 0.42±0.06), whereas other traits were of low heritability and heritability estimates were of low accuracy (e.g., milking temperament: 0.04±0.04, days to first heat: 0.02±0.04). For most behavior traits, we found relatively high heritabilities (general temperament: 0.38±0.07, aggressiveness: 0.12±0.08, and rank order in herd: 0.16±0.06). Position of labia, arguably an indicator trait for pathological urovagina, was genetically analyzed in this study for the first time, and a moderate heritability (0.28±0.06) was estimated.

LDSO: a program to simulate pedigrees and molecular information under various evolutionary forces.

Simulations are a major tool to evaluate new statistical methods and optimize experimental designs in the genomic era. However, this can only be achieved when the simulations are close enough to reality, as well as diverse enough to be realistic. For mapping studies, it is thus critical to re-create as much as possible the forces generating linkage (mutation, random drift, changes in population sizes, selection and pedigree structure) and the mechanisms producing trait genetic architecture (additivity, dominance, epistasis). We present here a computer program (ldso) simulating these phenomena. Optional outputs provide statistics on the linkage disequilibrium (LD) structure and the identity by descent between chromosomal segments, facilitating further data analyses. Furthermore, ldso enables the simulation of genomic data in known pedigrees, which sticks as precisely as possible to recent population history and structures of the long-range LD, allowing optimization of fine-mapping strategies.

Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels.

Achieving accurate genomic estimated breeding values for dairy cattle requires a very large reference population of genotyped and phenotyped individuals. Assembling such reference populations has been achieved for breeds such as Holstein, but is challenging for breeds with fewer individuals. An alternative is to use a multi-breed reference population, such that smaller breeds gain some advantage in accuracy of genomic estimated breeding values (GEBV) from information from larger breeds. However, this requires that marker-quantitative trait loci associations persist across breeds. Here, we assessed the gain in accuracy of GEBV in Jersey cattle as a result of using a combined Holstein and Jersey reference population, with either 39,745 or 624,213 single nucleotide polymorphism (SNP) markers. The surrogate used for accuracy was the correlation of GEBV with daughter trait deviations in a validation population. Two methods were used to predict breeding values, either a genomic BLUP (GBLUP_mod), or a new method, BayesR, which used a mixture of normal distributions as the prior for SNP effects, including one distribution that set SNP effects to zero. The GBLUP_mod method scaled both the genomic relationship matrix and the additive relationship matrix to a base at the time the breeds diverged, and regressed the genomic relationship matrix to account for sampling errors in estimating relationship coefficients due to a finite number of markers, before combining the 2 matrices. Although these modifications did result in less biased breeding values for Jerseys compared with an unmodified genomic relationship matrix, BayesR gave the highest accuracies of GEBV for the 3 traits investigated (milk yield, fat yield, and protein yield), with an average increase in accuracy compared with GBLUP_mod across the 3 traits of 0.05 for both Jerseys and Holsteins. The advantage was limited for either Jerseys or Holsteins in using 624,213 SNP rather than 39,745 SNP (0.01 for Holsteins and 0.03 for Jerseys, averaged across traits). Even this limited and nonsignificant advantage was only observed when BayesR was used. An alternative panel, which extracted the SNP in the transcribed part of the bovine genome from the 624,213 SNP panel (to give 58,532 SNP), performed better, with an increase in accuracy of 0.03 for Jerseys across traits. This panel captures much of the increased genomic content of the 624,213 SNP panel, with the advantage of a greatly reduced number of SNP effects to estimate. Taken together, using this panel, a combined breed reference and using BayesR rather than GBLUP_mod increased the accuracy of GEBV in Jerseys from 0.43 to 0.52, averaged across the 3 traits.

[Magnetic particle imaging (MPI)]. / Magnetic Particle Imaging (MPI).

Magnetic particle imaging (MPI) displays the spatial distribution and concentration of superparamagnetic iron oxides (SPIOs). It is a quantitative, tomographic imaging method with high temporal and spatial resolution and allows work with high sensitivity yet without ionizing radiation. Thus, it may be a very promising tool for medical imaging. In this review, we describe the physical and technical basics and various concepts for clinical scanners. Furthermore, clinical applications such as cardiovascular imaging, interventional procedures, imaging and therapy of malignancies as well as molecular imaging are presented.

Power and robustness of three whole genome association mapping approaches in selected populations.

Selection is known to influence the linkage disequilibrium (LD) pattern in livestock populations. Spurious LD may lead to a higher number of false-positive signals in whole genome association mapping experiments. We compared three approaches for whole genome association mapping in a simulation study: single marker regression (SMR), a two-step approach, which analyses residuals corrected for family effects with an SMR (GRAMMAR), and a combined linkage and LD approach, which applies the quantitative transmission disequilibrium test to the Mendelian sampling term (MTDT). Three different scenarios were simulated: idealized random mating, limited number of parents and directional selection. The number of false-positive associations increased when the number of parents was limited. Mapping accuracy was the worst in the scenario with directional selection for all approaches. As SMR produced a high number of false-positive signals in small populations, results of whole genome scans in livestock analysed with SMR should be considered with caution. GRAMMAR was the most accurate approach, but also the least powerful one. The Bonferroni-corrected significance threshold seemed to be too stringent for this approach. Results obtained with MTDT changed only slightly with selected populations. MTDT combined sufficient power with a manageable number of false-positive associations in all scenarios.

Use of native or platelet count adjusted platelet rich plasma for platelet aggregation measurements.

BACKGROUND: It is still not clear whether native or platelet count adjusted platelet rich plasma (PRP) should be used for platelet aggregation measurements. AIM: To evaluate the necessity of using adjusted PRP in platelet function testing. METHODS: Platelet aggregation with native PRP and adjusted PRP (platelet count: 250/nl, obtained by diluting native PRP with platelet poor plasma) was performed on the Behring Coagulation Timer (BCT(R)) using ADP, collagen, and arachidonic acid as agonists. Healthy subjects, patients on antiplatelet treatment, and patients with thrombocytosis (platelet counts in PRP > 1250/nl) were investigated. RESULTS: No significant differences in the maximum aggregation response were seen when using either native or adjusted PRP from healthy subjects and patients on antiplatelet treatment. Nevertheless, some patients taking aspirin or clopidogrel showed reduced inhibition of ADP and arachidonic acid induced aggregation in adjusted PRP but not in native PRP. The maximum velocity of healthy subjects and patients on antiplatelet treatment varied significantly as a result of the degree of dilution of the adjusted PRP. Surprisingly, the BCT provided good results when measuring platelet aggregation of native PRP from patients with thrombocytosis, whereas commonly used aggregometers could not analyse platelet aggregation of native PRP in these patients. CONCLUSION: The time consuming process of PRP adjustment may not be necessary for platelet aggregation measurements. Moreover, using adjusted PRP for monitoring aspirin or clopidogrel treatment may falsify results. Therefore, it may be better to use native PRP for platelet aggregation measurements, even in patients with thrombocytosis.

[Solitary nontuberculous mycobacterial infection of a cervical lymph node caused by Bartonella henselae (cat scratch disease)]. / Solitäre lymphogranulomatöse Entzündung eines Halslymphknotens. Erreger: Bartonella henselae (Katzenkratzkrankheit).

Cat scratch disease (CSD) is a common cause of subacute regional lymphadenopathy. Cats are the principal reservoir of Bartonella henselae, the etiologic agent in most cases of CSD. Because the histopathological findings are typical but not specific, a wide range of other agents must be considered in differential diagnosis. We report on a patient with a solitary swelling of the neck which remained over months with initial features suggestive of unspecific lymphadenitis, but who, after careful history taking and further serological testing, had cat scratch disease.