Effects of prenatal heat stress on birth weight and birth weight genetic parameters in German Holstein calves

The aim of this study was to infer the effects of heat stress (HS) during late gestation of dams on phenotypes and on direct and maternal genetic parameters for birth weight (BiW). We considered 171,221 Holstein calves kept in 56 large-scale co-operator herds. For a clear separation of maternal effects, only calves from dams with at least 3 offspring were included in the analyses. The genotype data set comprised 41,143 SNPs from 1,883 Holstein bulls. Temperature-humidity indices (THI) during the last 8 wk of gestation were calculated in each herd to reflect prenatal HS. A further prenatal HS descriptor was the first principal component (PC1) from principal component analysis considering the daily THI during the last 56 d of gestation. Regression coefficients of BiW on prenatal THI during the last 12 wk of gestation and PC1 were estimated in 13 consecutive phenotypic analyses. The strongest BiW decline was -0.63 kg per standardized THI, identified during 50 to 56 d before birth. A reaction norm model with weekly prenatal THI or PC1 nested within maternal genetic and maternal permanent environmental effects was defined to infer maternal sensitivity in response to prenatal THI alterations. Direct BiW heritabilities were close to 0.33 in the course of prenatal THI. Maternal BiW heritabilities marginally increased from 0.07 to 0.08 with increasing THI. Genetic correlations between maternal genetic effects at maximum HS levels and remaining THI were larger than 0.95, indicating the absence of genotype by time-lagged HS interactions. In contrast, maternal permanent environmental correlations between BiW at prenatal THI indicating HS with BiW at remaining THI substantially declined with increasing THI distances. Hence, from a herd management perspective, avoiding HS during the dry period of the dams will contribute to a slight increase in fetus growth.

Effects of temperature-humidity index on blood metabolites of German dairy cows and their female calves

Heat stress (HS) impairs productivity, health, and welfare in dairy cows, and additionally causes metabolic changes. Hence, specific metabolites could be used as HS biomarkers. Consequently, the aim of the present study was to compare blood metabolite concentrations of German Holstein dairy cows and of their female calves suffering from high temperature-humidity index (THI) during late gestation (cows) or during their first week of life (calves) or not. According to the mean daily THI (mTHI) at the day before blood sampling, animals were classified into 2 groups: high mTHI ≥60 (hmTHI) and low mTHI <60 (lmTHI). To perform a standard cross-sectional 2-group study, cow groups (n = 48) and calf groups (n = 47) were compared separately. Differences in metabolite concentrations between hmTHI and lmTHI animals were inferred based on a targeted metabolomics approach. In the first step, processed metabolomics data were evaluated by multivariate data analysis techniques, and were visualized using the web-based platform MetaboAnalyst V5.0. The most important metabolites with pronounced differences between groups were further analyzed in a second step using linear mixed models. We identified 9 thermally sensitive metabolites for the cows [dodecanedioic acid; 3-indolepropionic acid; sarcosine; triglycerides (14:0_34:0), (16:0_38:7), (18:0_32:1), and (18:0_36:2); phosphatidylcholine aa C38:1; and lysophosphatidylcholine a C20:3] and for the calves [phosphatidylcholines aa C38:1, ae C38:3, ae C36:0, and ae C36:2; cholesteryl esters (17:1) and (20:3); sphingomyelins C18:0 and C18:1; and p-cresol sulfate], most of them related to lipid metabolism. Apart from 2 metabolites (3-indolepropionic acid and sarcosine) in cows, the metabolite plasma concentrations were lower in hmTHI than in lmTHI groups. In our heat-stressed dry cows, results indicate an altered lipid metabolism compared with lactating heat-stressed cows, due to the missing antilipolytic effect of HS. The results also indicate alterations in lipid metabolism of calves due to high mTHI in the first week of life. From a cross-generation perspective, high mTHI directly before calving seems to reduce colostrum quality, with detrimental effects on metabolite concentrations in offspring.

Wound-induced triacylglycerol biosynthesis is jasmonoy-l-isoleucin and abscisic acid independent

Triacylglycerol (TAG) plays a significant role during plant stress - it maintains lipid homeostasis. Upon wounding plants accumulate TAG, likely as a storage form of fatty acids (FAs) that originate from damaged membranes. This study asked if this process depends on the two phytohormones jasmonoyl-isoleucine (JA-Ile) and abscisic acid (ABA), which are involved in wound signalling. To analyse regulation of wound-induced TAG accumulation, we used mutants deficient in JA-Ile, with reduced ABA and the myb96 mutant, which is deficient in an ABA-dependent transcription factor. The expression of genes involved in TAG biosynthesis, and TAG content after wounding were analysed via LC-MS and GC-FID, plastidial lipid content in all mentioned mutant lines was also determined. The localization of newly synthesized TAG was investigated using lipid droplet staining. TAG accumulation upon wounding was confirmed as well as the fact that the newly synthesized TAG are mostly composed of polyunsaturated fatty acids. Nevertheless, all tested mutant lines were able to accumulate TAG similar to the WT. We observed differences in reduction of plastidial lipids - in WT plants this was higher than in mutant lines. Newly synthesized TAGs were stored in lipid droplets at and around the wounded area. Our results show that TAG accumulation upon wounding is not dependent on JA-Ile or ABA. The newly synthesized TAG species are composed of unsaturated fatty acids of membrane origin, and most likely serves as a transient energy store.

Invited review: From heat stress to disease-Immune response and candidate genes involved in cattle thermotolerance

Heat stress implies unfavorable effects on primary and functional traits in dairy cattle and, in consequence, on the profitability of the whole production system. The increasing number of days with extreme hot temperatures suggests that it is imperative to detect the heat stress status of animals based on adequate measures. However, confirming the heat stress status of an individual is still challenging, and, in consequence, the identification of novel heat stress biomarkers, including molecular biomarkers, remains a very relevant issue. Currently, it is known that heat stress seems to have unfavorable effects on immune system mechanisms, but this information is of limited use in the context of heat stress phenotyping. In addition, there is a lack of knowledge addressing the molecular mechanisms linking the relevant genes to the observed phenotype. In this review, we explored the potential molecular mechanisms explaining how heat stress affects the immune system and, therefore, increases the occurrence of immune-related diseases in cattle. In this regard, 2 relatively opposite hypotheses are under focus: the immunosuppressive action of cortisol, and the proinflammatory effect of heat stress. In both hypotheses, the modulation of the immune response during heat stress is highlighted. Moreover, it is possible to link candidate genes to these potential mechanisms. In this context, immune markers are very valuable indicators for the detection of heat stress in dairy cattle, broadening the portfolio of potential biomarkers for heat stress.

AAV-mediated gene transfer of a checkpoint inhibitor in combination with HER2-targeted CAR-NK cells as experimental therapy for glioblastoma

Glioblastoma (GB) is the most common primary brain tumor, which is characterized by low immunogenicity of tumor cells and prevalent immunosuppression in the tumor microenvironment (TME). Targeted local combination immunotherapy is a promising strategy to overcome these obstacles. Here, we evaluated tumor-cell specific delivery of an anti-PD-1 immunoadhesin (aPD-1) via a targeted adeno-associated viral vector (AAV) as well as HER2-specific NK-92/5.28.z (anti-HER2.CAR/NK-92) cells as components for a combination immunotherapy. In co-culture experiments, target-activated anti-HER2.CAR/NK-92 cells modified surrounding tumor cells and bystander immune cells by triggering the release of inflammatory cytokines and upregulation of PD-L1. Tumor cell-specific delivery of aPD-1 was achieved by displaying a HER2-specific designed ankyrin repeat protein (DARPin) on the AAV surface. HER2-AAV mediated gene transfer into GB cells correlated with HER2 expression levels, without inducing anti-viral responses in transduced cells. Furthermore, AAV-transduction did not interfere with anti-HER2.CAR/NK-92 cell-mediated tumor cell lysis. After selective transduction of HER2⁺ cells, aPD-1 expression was detected at the mRNA and protein level. The aPD-1 immunoadhesin was secreted in a time-dependent manner, bound its target on PD-1-expressing cells and was able to re-activate T cells by efficiently disrupting the PD-1/PD-L1 axis. Moreover, high intratumoral and low systemic aPD-1 concentrations were achieved following local injection of HER2-AAV into orthotopic tumor grafts in vivo. aPD-1 was selectively produced in tumor tissue and could be detected up to 10 days after a single HER2-AAV injection. In subcutaneous GL261-HER2 and Tu2449-HER2 immunocompetent mouse models, administration of the combination therapy significantly prolonged survival, including complete tumor control in several animals in the GL261-HER2 model. In summary, local therapy with aPD-1 encoding HER2-AAVs in combination with anti-HER2.CAR/NK-92 cells may be a promising novel strategy for GB immunotherapy with the potential to enhance efficacy and reduce systemic side effects of immune-checkpoint inhibitors.

Optimizing laparoscopic training efficacy by 'deconstruction into key steps': a randomized controlled trial with novice medical students

BACKGROUND

Simulator training is an effective way of acquiring laparoscopic skills but there remains a need to optimize teaching methods to accelerate learning. We evaluated the effect of the mental exercise 'deconstruction into key steps' (DIKS) on the time required to acquire laparoscopic skills.

METHODS

A randomized controlled trial with undergraduate medical students was implemented into a structured curricular laparoscopic training course. The intervention group (IG) was trained using the DIKS approach, while the control group (CG) underwent the standard course. Laparoscopic performance of all participants was video-recorded at baseline (t0), after the first session (t1) and after the second session (t2) nine days later. Two double-blinded raters assessed the videos. The Impact of potential covariates on performance (gender, age, prior laparoscopic experience, self-assessed motivation and self-assessed dexterity) was evaluated with a self-report questionnaire.

RESULTS

Both the IG (n = 58) and the CG (n = 68) improved their performance after each training session (p < 0.001) but with notable differences between sessions. Whereas the CG significantly improved their performance from t0 -t1 (p < 0.05), DIKS shortened practical exercise time by 58% so that the IG outperformed the CG from t1 -t2, (p < 0.05). High self-assessed motivation and dexterity associated with significantly better performance (p < 0.05). Male participants demonstrated significantly higher overall performance (p < 0.05).

CONCLUSION

Mental exercises like DIKS can improve laparoscopic performance and shorten practice times. Given the limited exposure of surgical residents to simulator training, implementation of mental exercises like DIKS is highly recommended. Gender, self-assessed dexterity, and motivation all appreciably influence performance in laparoscopic training.

Direct genetic effects, maternal genetic effects, and maternal genetic sensitivity on prenatal heat stress for calf diseases and corresponding genomic loci in German Holsteins

The aim of this study was to infer the effects of heat stress (HS) of dams during late gestation on direct and maternal genetic parameters for pneumonia (PNEU, 112,563 observations), diarrhea (DIAR, 176,904 observations), and omphalitis (OMPH, 176,872 observations) in Holstein calves kept in large-scale co-operator herds. The genotype dataset included 41,135 SNPs from 19,247 male and female cattle. Temperature-humidity indices (THI) during the last 8 wk of pregnancy were calculated, using the climate data from the nearest public weather station for each herd. Heat load effects were considered for average weekly THI larger than 60. Phenotypically, regression coefficients of calf diseases on prenatal THI during the last 8 wk of gestation were estimated in 8 consecutive runs. The strongest detrimental effects of prenatal HS on PNEU and DIAR were identified for the last week of pregnancy (wk 1). Thus, only wk 1 was considered in ongoing genetic and genomic analyses. In an advanced model considering prenatal HS, random regression coefficients on THI in wk 1 nested within maternal genetic effects (maternal slope effects for heat load) were considered as parameters to infer maternal sensitivity in response to prenatal THI alterations. Direct heritabilities from the advanced model ranged from 0.10 (THI 60) to 0.08 (THI 74) for PNEU and were close to 0.16 for DIAR. Maternal heritabilities for PNEU increased from 0.03 to 0.10 along the THI gradient. For DIAR, the maternal heritability was largest (0.07) at the minimum THI (THI = 60) and decreased to 0.05 at THI 74. Genetic correlations smaller than 0.80 for PNEU and DIAR recorded at THI 60 with corresponding diseases at THI 74 indicated genotype by climate interactions for maternal genetic effects. Genome-wide associations studies were performed using de-regressed proofs of genotyped sires for direct genetic, maternal genetic, and maternal slope effects. Thirty suggestive and 2 significant SNPs were identified from the GWAS. Forty-three genes located close to the suggestive SNPs (±100 kb) were annotated as potential candidate genes. Three biological processes were inferred on the basis of the these genes, addressing the negative regulation of the viral life cycle, innate immune response, and protein ubiquitination. Hence, the genetics of prenatal heat stress mechanisms are associated with immune physiology and disease resistance mechanisms.

Estimation of direct and maternal genetic effects and annotation of potential candidate genes for weight and meat quality traits in a genotyped outdoor dual-purpose cattle breed

With regard to potential applications of genomic selection in small numbered breeds, we evaluated genomic models and focused on potential candidate gene annotations for weight and meat quality traits in the local Rotes Höhenvieh (RHV) breed. Traits included 6,003 birth weights (BWT), 5,719 200 d-weights (200dw), 4,594 365 d-weights (365dw), and 547 records for intramuscular fat content (IMF). A total of 581,304 SNP from 370 genotyped cattle with phenotypic records were included in genomic analyses. Model evaluations focused on single- and multiple-trait models with direct and with direct and maternal genetic effects. Genetic relationship matrices were based on pedigree (A-matrix), SNP markers (G-matrix), or both (H-matrix). Genome-wide association studies (GWASs) were carried out using linear mixed models to identify potential candidate genes for the traits of interest. De-regressed proofs (DRP) for direct and maternal genetic components were used as pseudo-phenotypes in the GWAS. Accuracies of direct breeding values were higher from models based on G or on H compared to A. Highest accuracies (> 0.89) were obtained for IMF with multiple-trait models using the G-matrix. Direct heritabilities with maternal genetic effects ranged from 0.62 to 0.66 for BWT, from 0.45 to 0.55 for 200dW, from 0.40 to 0.44 for 365dW, and from 0.48 to 0.75 for IMF. Maternal heritabilities for BWT, 200dW, and 365dW were in a narrow range from 0.21 to 0.24, 0.24 to 0.27, and 0.21 to 0.25, respectively, and from 0.25 to 0.65 for IMF. Direct genetic correlations among body weight traits were positive and favorable, and very similar from different models but showed a stronger variation with 0.31 (A), −0.13 (G), and 0.45 (H) between BWT and IMF. In gene annotations, we identified 6, 3, 1, and 6 potential candidate genes for direct genetic effect on BWT, 200dW, 365dW, and IMF traits, respectively. Regarding maternal genetic effects, four (SHROOM3, ZNF609, PECAM1, and TEX2) and two (TMEM182 and SEC11A) genes were detected as potential candidate genes for BWT and 365dW, respectively. Potential candidate genes for maternal effect on IMF were GRHL2, FGA, FGB, and CTNNA3. As the most important finding from a practical breeding perspective, a small number of genotyped RHV cattle enabled accurate breeding values for high heritability IMF.

Genome-wide associations for heat stress response suggest potential candidate genes underlying milk fatty acid composition in dairy cattle

Contents of milk fatty acids (FA) display remarkable alterations along climatic gradients. Detecting candidate genes underlying such alterations might be beneficial for the exploration of climate sensitivity in dairy cattle. Consequently, we aimed on the definition of FA heat stress indicators, considering FA breeding values in response to temperature-humidity index (THI) alterations. Indicators were used in GWAS, in ongoing gene annotations and for the estimation of chromosome-wide variance components. The phenotypic data set consisted of 39,600 test-day milk FA records from 5,757 first-lactation Holstein dairy cows kept in 16 large-scale German cooperator herds. The FA traits were C18:0, polyunsaturated fatty acids (PUFA), saturated fatty acids (SFA), and unsaturated fatty acids (UFA). After genotype quality control, 40,523 SNP markers from 3,266 cows and 930 sires were considered. Meteorological data from the weather station in closest herd distance were used for the calculation of maximum hourly daily THI, which were allocated to 10 different THI classes. The same FA from 3 stages of lactation were considered as different, but genetically correlated traits. Consequently, a 3-trait reaction norm model was used to estimate genetic parameters and breeding values for FA along THI classes, considering either pedigree (A) or genomic (G) relationship matrices. De-regressed proofs and genomic estimated breeding values at the intermediate THI class 5 and at the extreme THI class 10 were used as pseudophenotypes in ongoing genomic analyses for thermoneutral (TNC) and heat stress conditions (HSC), respectively. The differences in de-regressed proofs and in genomic estimated breeding values from both THI classes were pseudophenotypes for heat stress response (HSR). Genetic correlations between the same FA under TNC and HSC were smallest in the first lactation stage and ranged from 0.20 for PUFA to 0.87 for SFA when modeling with the A matrix, and from 0.35 for UFA to 0.86 for SFA when modeling with the G matrix. In the first lactation stage, larger additive genetic variances under HSC compared with TNC indicate climate sensitivity for C18:0, PUFA, and UFA. Climate sensitivity was also reflected by pronounced chromosome-wide genetic variances for HSR of PUFA and UFA in the first stage of lactation. For all FA under TNC, HSC, and HSR, quite large genetic variance proportions were explained by BTA14. In GWAS, 30 SNP (within or close to 38 potential candidate genes) overlapped for HSR of the different FA. One unique potential candidate gene (AMFR) was detected for HSR of PUFA, 15 for HSR of SFA (ADGRB1, DENND3, DUSP16, EFR3A, EMP1, ENSBTAG00000003838, EPS8, MGP, PIK3C2G, STYK1, TMEM71, GSG1, SMARCE1, CCDC57, and FASN) and 3 for HSR of UFA (ENSBTAG00000048091, PAEP, and EPPK1). The identified unique genes play key roles in milk FA synthesis and are associated with disease resistance in dairy cattle. The results suggest consideration of FA in combination with climatic responses when inferring genetic mechanisms of heat stress in dairy cows.

Non-neutral plasma manipulation techniques in development of a high-capacity positron trap

Preliminary experiments have been performed toward the development of a multi-cell Penning-Malmberg trap for the storage of large numbers of positrons (≥10¹⁰ e⁺). We introduce the master-cell test trap and the diagnostic tools for first experiments with electrons. The usage of a phosphor screen to measure the z-integrated plasma distribution and the number of confined particles is demonstrated, as well as the trap alignment to the magnetic field (B = 3.1 T) using the m = 1 diocotron mode. The plasma parameters and expansion are described along with the autoresonant excitation of the diocotron mode using rotating dipole fields and frequency chirped sinusoidal drive signals. We analyze the reproducibility of the excitation and use these findings to settle on the path for the next generation multi-cell test device.

Single-step genomic best linear unbiased predictor genetic parameter estimations and genome-wide associations for milk fatty acid profiles, interval from calving to first insemination, and ketosis in Holstein cattle

Milk fatty acids (FA) have been suggested as biomarkers for early-lactation metabolic diseases and for female fertility status. The aim of the present study was to infer associations between FA, the metabolic disorder ketosis (KET), and the interval from calving to first insemination (ICF) genetically and genomically. In this regard, we focused on a single-step genomic BLUP approach, allowing consideration of genotyped and ungenotyped cows simultaneously. The phenotypic data set considered 38,375 first-lactation Holstein cows, kept in 45 large-scale co-operator herds from 2 federal states in Germany. The calving years for these cows were from 2014 to 2017. Concentrations in milk from the first official milk recording test-day for saturated, unsaturated (UFA), monounsaturated (MUFA), polyunsaturated, palmitic, and stearic (C18:0) FA were determined via Fourier-transform infrared spectroscopy. Ketosis was defined as a binary trait according to a veterinarian diagnosis key, considering diagnoses within a 6-wk interval after calving. A subset of 9,786 cows was genotyped for 40,989 SNP markers. Variance components and heritabilities for all Gaussian distributed FA and for ICF, and for binary KET were estimated by applying single-step genomic BLUP single-trait linear and threshold models, respectively. Genetic correlations were estimated in series of bivariate runs. Genomic breeding values for the single-step genomic BLUP estimations were dependent traits in single-step GWAS. Heritabilities for FA were moderate in the range from 0.09 to 0.20 (standard error = 0.02-0.03), but quite small for ICF (0.08, standard error = 0.01) and for KET (0.05 on the underlying liability scale, posterior standard deviation = 0.02). Genetic correlations between KET and UFA, MUFA, and C18:0 were large (0.74 to 0.85, posterior standard deviation = 0.14-0.19), and low positive between KET and ICF (0.17, posterior standard deviation = 0.22). Genetic correlations between UFA, MUFA, and C18:0 with ICF ranged from 0.34 to 0.46 (standard error = 0.12). In single-step GWAS, we identified a large proportion of overlapping genomic regions for the different FA, especially for UFA and MUFA, and for saturated and palmitic FA. One identical significantly associated SNP was identified for C18:0 and KET on BTA 15. However, there was no genomic segment simultaneously significantly affecting all trait categories ICF, FA, and KET. Nevertheless, some of the annotated potential candidate genes DGKA, IGFBP4, and CXCL8 play a role in lipid metabolism and fertility mechanisms, and influence production diseases in early lactation. Genetic and genomic associations indicate that Fourier-transform infrared spectroscopy FA concentrations in milk from the first official test-day are valuable predictors for KET and for ICF.

Genotype by heat stress interactions for production and functional traits in dairy cows from an across-generation perspective

The aim of this study was to analyze time-lagged heat stress (HS) effects during late gestation on genetic co(variance) components in dairy cattle across generations for production, female fertility, and health traits. The data set for production and female fertility traits considered 162,492 Holstein Friesian cows from calving years 2003 to 2012, kept in medium-sized family farms. The health data set included 69,986 cows from calving years 2008 to 2016, kept in participating large-scale co-operator herds. Production traits were milk yield (MKG), fat percentage (fat%), and somatic cell score (SCS) from the first official test-day in first lactation. Female fertility traits were the nonreturn rate after 56 d (NRR56) in heifers and the interval from calving to first insemination (ICFI) in first-parity cows. Health traits included clinical mastitis (MAST), digital dermatitis (DD), and endometritis (EM) in the early lactation period in first-parity cows. Meteorological data included temperature and humidity from public weather stations in closest herd distance. The HS indicator was the temperature-humidity index (THI) during dams' late gestation, also defined as in utero HS. For the genetic analyses of production, female fertility, and health traits in the offspring generation, a sire-maternal grandsire random regression model with Legendre polynomials of order 3 for the production and of order 2 for the fertility and health traits on prenatal THI, was applied. All statistical models additionally considered a random maternal effect. THI from late gestation (i.e., prenatal climate conditions), influenced genetic parameter estimates in the offspring generation. For MKG, heritabilities and additive genetic variances decreased in a wave-like pattern with increasing THI. Especially for THI >58, the decrease was very obvious with a minimal heritability of 0.08. For fat% and SCS, heritabilities increased slightly subjected to prenatal HS conditions at THI >67. The ICFI heritabilities differed marginally across THI [heritability (h²) = 0.02-0.04]. For NRR56, MAST, and DD, curves for heritabilities and genetic variances were U-shaped, with largest estimates at the extreme ends of the THI scale. For EM, heritability increased from THI 25 (h² = 0.13) to THI 71 (h² = 0.39). The trait-specific alterations of genetic parameters along the THI gradient indicate pronounced genetic differentiation due to intrauterine HS for NRR56, MAST, DD, and EM, but decreasing genetic variation for MKG and ICFI. Genetic correlations smaller than 0.80 for NRR56, MAST, DD, and EM between THI 65 with corresponding traits at remaining THI indicated genotype by environment interactions. The lowest genetic correlations were identified when considering the most distant THI. For MKG, fat%, SCS, and ICFI, genetic correlations throughout were larger than 0.80, disproving concerns for any genotype by environment interactions. Variations in genetic (co)variance components across prenatal THI may be due to epigenetic modifications in the offspring genome, triggered by in utero HS. Epigenetic modifications have a persistent effect on phenotypic responses, even for traits recorded late in life. However, it is imperative to infer the underlying epigenetic mechanisms in ongoing molecular experiments.

Climate sensitivity of milk production traits and milk fatty acids in genotyped Holstein dairy cows

The aim of this study was the evaluation of climate sensitivity via genomic reaction norm models [i.e., to infer cow milk production and milk fatty acid (FA) responses on temperature-humidity index (THI) alterations]. Test-day milk traits were recorded between 2010 and 2016 from 5,257 first-lactation genotyped Holstein dairy cows. The cows were kept in 16 large-scale cooperator herds, being daughters of 344 genotyped sires. The longitudinal data consisted of 47,789 test-day records for the production traits milk yield (MY), fat yield (FY), and protein yield (PY), and of 20,742 test-day records for 6 FA including C16:0, C18:0, saturated fatty acids (SFA), unsaturated fatty acids (UFA), monounsaturated fatty acids (MUFA), and polyunsaturated fatty acids (PUFA). After quality control of the genotypic data, 41,057 SNP markers remained for genomic analyses. Meteorological data from the weather station in closest herd distance were used for the calculation of maximum hourly daily THI. Genomic reaction norm models were applied to estimate genetic parameters in a single-step approach for production traits and FA in dependency of THI at different lactation stages, and to evaluate the model stability. In a first evaluation strategy (New_sire), all phenotypic records from daughters of genotyped sires born after 2010 were masked, to mimic a validation population. In the second strategy (New_env), only daughter records of the new sires recorded in the most extreme THI classes were masked, aiming at predicting sire genomic estimated breeding values (GEBV) under heat stress conditions. Model stability was the correlation between GEBV of the new sires in the reduced data set with respective GEBV estimated from all phenotypic data. Among all test-day production traits, PY responded as the most sensitive to heat stress. As observed for the remaining production traits, genetic variances were quite stable across THI, but genetic correlations between PY from temperate climates with PY from extreme THI classes dropped to 0.68. Genetic variances in dependency of THI were very similar for C16:0 and SFA, indicating marginal climatic sensitivity. In the early lactation stage, genetic variances for C18:0, MUFA, PUFA, and UFA were significantly larger in the extreme THI classes compared with the estimates under thermoneutral conditions. For C18:0 and MUFA, PUFA, and UFA in the middle THI classes, genetic correlations in same traits from the early and the later lactation stages were lower than 0.50, indicating strong days in milk influence. Interestingly, within lactation stages, genetic correlations for C18:0 and UFA recorded at low and high THI were quite large, indicating similar genetic mechanisms under stress conditions. The model stability was improved when applying the New_env instead of New_sire strategy, especially for FA in the first stage of lactation. Results indicate moderately accurate genomic predictions for milk traits in extreme THI classes when considering phenotypic data from a broad range of remaining THI. Phenotypically, thermal stress conditions contributed to an increase of UFA, suggesting value as a heat stress biomarker. Furthermore, the quite large genetic variances for UFA at high THI suggest the consideration of UFA in selection strategies for improved heat stress resistance.

Role of Chiral Two-Body Currents in ^{6}Li Magnetic Properties in Light of a New Precision Measurement with the Relative Self-Absorption Technique

A direct measurement of the decay width of the excited 0_{1}^{+} state of ^{6}Li using the relative self-absorption technique is reported. Our value of Γ_{γ,0_{1}^{+}→1_{1}^{+}}=8.17(14)_{stat.}(11)_{syst.}  eV provides sufficiently low experimental uncertainties to test modern theories of nuclear forces. The corresponding transition rate is compared to the results of ab initio calculations based on chiral effective field theory that take into account contributions to the magnetic dipole operator beyond leading order. This enables a precision test of the impact of two-body currents that enter at next-to-leading order.

Associations between minerals and metabolic indicators in maternal blood pre- and postpartum with ewe body condition, methane emissions, and lamb body weight development

In sheep production, economic efficiency strongly depends on the maternal health and feed efficiency status and on weaning performances of their offspring. Accordingly, an optimal level for the supply with macro- and microelements and the ewe energy status has impact on the fetal development during gestation and on maternal milk production during lactation. Furthermore, this study addressed intergenerational aspects, i.e., on associations between maternal energy metabolism profiles considering the macro- and microelement status, metabolic indicators (e.g. β-hydroxybutyrate (BHB)), body condition and methane (CH4) emissions with lamb BW (LBW) in two sheep breeds. Traits were recorded at the beginning of gestation (ewe traits), at lambing, three weeks postpartum, and at weaning (ewe and lamb traits). Trait recording included CH4 emissions (recorded via laser methane detector (LMD)), ewe BW (EBW), backfat thickness (BFT), and body condition score (BCS) from 46 ewes (24 Merinoland- (ML), 22 Rhönsheep (RH)), and LBW of their 87 (35 ML, 52 RH) purebred lambs. Serum levels of the following ewe blood parameters were determined: calcium (Ca), sodium (Na), potassium (K), phosphate (P), nonesterified fatty acids (NEFA), BHB, glutamate dehydrogenase (GLDH), selenium (Se), copper (Cu), iron (Fe), zinc (Zn), and magnesium (Mg). Mixed models were applied to infer associations between ewe blood parameters with EBW, BFT, BCS, and CH4 and with LBW recorded in offspring. At weaning, a maternal serum Mg level > 1.0 mmol/L was significantly associated with an increase of 13% in LBW in ML, compared to offspring from ML ewes with a serum Mg concentration within the lower reference range (0.8 mmol/L). Furthermore, higher Cu levels were favorably associated with ewe BCS and BFT at weaning in both breeds. In RH ewes, a Se level > 2.4 μmol/l was significantly associated with increased BCS. In the ML breed, high Zn levels during lactation were associated with reduced CH4 emissions. Ewe EBW was significantly larger for ML ewes representing low Ca levels. A low BHB level was associated with decreasing CH4 emissions in RH and ML. Serum levels for Na, K, P, GLDH, and Fe did not significantly affect the traits of interest. Trait associations from the present study indicate the importance of the mineral supply and metabolic status of the ewe with regard to body condition, CH4 emissions, and LBW development, but depending on the breed. Identified associations might contribute to energy efficiency in sheep production systems.

Proofs for genotype by environment interactions considering pedigree and genomic data from organic and conventional cow reference populations

The aim of the present study was to prove genotype by environment interactions (G × E) for production, longevity, and health traits considering conventional and organic German Holstein dairy cattle subpopulations. The full data set included 141,778 Holstein cows from 57 conventional herds and 7,915 cows from 9 organic herds. The analyzed traits were first-lactation milk yield and fat percentage (FP), the length of productive life (LPL) and the health traits mastitis, ovarian cycle disorders, and digital dermatitis in first lactation. A subset of phenotyped cows was genotyped and used for the implementation of separate cow reference populations. After SNP quality controls, the cow reference sets considered 40,830 SNP from 19,700 conventional cows and the same 40,830 SNP from 1,282 organic cows. The proof of possible G × E was made via multiple-trait model applications, considering same traits from the conventional and organic population as different traits. In this regard, pedigree (A), genomic (G) and combined relationship (H) matrices were constructed. For the production traits, heritabilities were very similar in both organic and conventional populations (i.e., close to 0.70 for FP and close to 0.40 for milk yield). For low heritability health traits and LPL, stronger heritability fluctuations were observed, especially for digital dermatitis with 0.05 ± 0.01 (organic, A matrix) to 0.33 ± 0.04 (conventional, G matrix). Quite large genetic correlations between same traits from the 2 environments were estimated for production traits, especially for high heritability FP. For LPL, the genetic correlation was 0.67 (A matrix) and 0.66 (H matrix). The genetic correlation between LPL organic with LPL conventional was 0.94 when considering the G matrix, but only 213 genotyped cows were included. For health traits, genetic correlations were throughout lower than 0.80, indicating possible G × E. Genetic correlations from the different matrices A, G, and H for health and production traits followed the same pattern, but the estimates from G for health traits were associated with quite large standard errors. In genome-wide association studies, significantly associated SNP for production traits overlapped in the conventional and organic population. In contrast, for low heritability LPL and health traits, significantly associated SNP and annotated potential candidate genes differed in both populations. In this regard, significantly associated SNP for mastitis from conventional cows were located on Bos taurus autosomes 6 and 19, but on Bos taurus autosomes 1, 10, and 22 in the organic population. For the remaining health traits and LPL, different potential candidate genes were annotated, but the different genes reflect similar physiological pathways. We found evidence of G × E for low heritability functional traits, suggesting different breeding approaches in organic and conventional populations. Nevertheless, for a verification of results and implementation of alternative breeding strategies, it is imperative to increase the organic cow reference population.

Genetic and nongenetic profiling of milk β-hydroxybutyrate and acetone and their associations with ketosis in Holstein cows

Ketosis is a metabolic disorder of increasing importance in high-yielding dairy cows, but accurate population-wide binary health trait recording is difficult to implement. Against this background, proper Gaussian indicator traits, which can be routinely measured in milk, are needed. Consequently, we focused on the ketone bodies acetone and β-hydroxybutyrate (BHB), measured via Fourier-transform infrared spectroscopy (FTIR) in milk. In the present study, 62,568 Holstein cows from large-scale German co-operator herds were phenotyped for clinical ketosis (KET) according to a veterinarian diagnosis key. A sub-sample of 16,861 cows additionally had first test-day observations for FTIR acetone and BHB. Associations between FTIR acetone and BHB with KET and with test-day traits were studied phenotypically and quantitative genetically. Furthermore, we estimated SNP marker effects for acetone and BHB (application of genome-wide association studies) based on 40,828 SNP markers from 4,384 genotyped cows, and studied potential candidate genes influencing body fat mobilization. Generalized linear mixed models were applied to infer the influence of binary KET on Gaussian-distributed acetone and BHB (definition of an identity link function), and vice versa, such as the influence of acetone and BHB on KET (definition of a logit link function). Additionally, linear models were applied to study associations between BHB, acetone and test-day traits (milk yield, fat percentage, protein percentage, fat-to-protein ratio and somatic cell score) from the first test-day after calving. An increasing KET incidence was statistically significant associated with increasing FTIR acetone and BHB milk concentrations. Acetone and BHB concentrations were positively associated with fat percentage, fat-to-protein ratio and somatic cell score. Bivariate linear animal models were applied to estimate genetic (co)variance components for KET, acetone, BHB and test-day traits within parities 1 to 3, and considering all parities simultaneously in repeatability models. Pedigree-based heritabilities were quite small (i.e., in the range from 0.01 in parity 3 to 0.07 in parity 1 for acetone, and from 0.03-0.04 for BHB). Heritabilites from repeatability models were 0.05 for acetone, and 0.03 for BHB. Genetic correlations between acetone and BHB were moderate to large within parities and considering all parities simultaneously (0.69-0.98). Genetic correlations between acetone and BHB with KET from different parities ranged from 0.71 to 0.99. Genetic correlations between acetone across parities, and between BHB across parities, ranged from 0.55 to 0.66. Genetic correlations between KET, acetone, and BHB with fat-to-protein ratio and with fat percentage were large and positive, but negative with milk yield. In genome-wide association studies, we identified SNP on BTA 4, 10, 11, and 29 significantly influencing acetone, and on BTA 1 and 16 significantly influencing BHB. The identified potential candidate genes NRXN3, ACOXL, BCL2L11, HIBADH, KCNJ1, and PRG4 are involved in lipid and glucose metabolism pathways.

Genomic predictions of growth curves in Holstein dairy cattle based on parameter estimates from nonlinear models combined with different kernel functions

Availability of longitudinal body weight (BW) records allows the application of nonlinear models (NLINM) to predict phenotypic and genomic growth curves in dairy cattle. In this regard, we considered a data set including 31,722 BW records from 4,952 female Holstein cattle, during the period from birth (mo 0) to approximately age at first calving (mo 24). Parameters of the growth curves were estimated using 3 NLINM: the logistic (LOG), the Gompertz (GOM), and the Richards (RICH) functions. Residuals for the growth curve parameters from the NLINM applications were used as pseudo-phenotypes in the ongoing genomic analyses with different similarity matrices, including 2 genomic relationship matrices (G1 and G2), a combined pedigree and genomic relationship matrix (H), and 3 kernel matrices. The kernels were a weighted "alike by state" kernel function (K1), an exponential dissimilarity kernel (K2), and a Gaussian kernel (K3). On the basis of G1 and G2 matrices, genomic heritabilities for the growth curve parameters birth weight (W₀), mature weight (W_m), and growth rate (k), and the shape parameter (m; only available from RICH) were moderate to large, in the range from 0.29 (m from RICH) to 0.46 (k from RICH). Fitting the similarity matrices based on kernel functions contributed to an increase of the ratio of the variance explained by the similarity matrix in relation to the total variance (compared with the heritability when modeling G1 or G2). Genetic correlations between W₀, W_m, and k were always positive (>0.30), especially for the same growth curve parameters estimated from different NLINM (>0.90). The shape parameter m from RICH was negatively correlated with other growth curve parameters, from -0.29 to -0.95. In a next step, estimated genomic breeding values for growth curve parameters were input data for the respective NLINM, aiming to construct genomic growth curves. Prediction accuracies were correlations between genomic growth curves and genomic breeding values from random regression models for sires and female cattle. Considering all genotyped female cattle with pseudo-phenotypes, prediction accuracies were larger from RICH than from LOG and GOM. However, differences in prediction accuracies from the NLINM × similarity matrix combinations were quite small. Accordingly, in 5-fold cross-validations using heifer groups with masked phenotypes, very similar prediction accuracies across modeling approaches were identified. Especially for specific age months, genomic growth curve predictions were more accurate for sires than for female cattle, indicating that the relationships between animals in training and validation sets are more important than the selection of specific NLINM × similarity matrix combinations.

Assessing selection signatures within and between selected lines of dual-purpose black and white and German Holstein cattle

The aim of this study was to detect selection signatures considering cows from the German Holstein (GH) and the local dual-purpose black and white (DSN) population, as well as from generated sub-populations. The 4654 GH and 261 DSN cows were genotyped with the BovineSNP50 Genotyping BeadChip. The geographical herd location was used as an environmental descriptor to create the East-DSN and West-DSN sub-populations. In addition, two further sub-populations of GH cows were generated, using the extreme values for solutions of residual effects of cows for the claw disorder dermatitis digitalis. These groups represented the most susceptible and most resistant cows. We used cross-population extended haplotype homozygosity methodology (XP-EHH) to identify the most recent selection signatures. Furthermore, we calculated Wright's fixation index (F_ST ). Chromosomal segments for the top 0.1 percentile of negative or positive XP-EHH scores were studied in detail. For gene annotations, we used the Ensembl database and we considered a window of 250 kbp downstream and upstream of each core SNP corresponding to peaks of XP-EHH. In addition, functional interactions among potential candidate genes were inferred via gene network analyses. The most outstanding XP-EHH score was on chromosome 12 (at 77.34 Mb) for DSN and on chromosome 20 (at 36.29-38.42 Mb) for GH. Selection signature locations harbored QTL for several economically important milk and meat quality traits, reflecting the different breeding goals for GH and DSN. The average F_ST value between GH and DSN was quite low (0.068), indicating shared founders. For group stratifications according to cow health, several identified potential candidate genes influence disease resistance, especially to dermatitis digitalis.

Incisional hernia repair in a high-fidelity silicone model for open retro-muscular mesh implantation with preparation of the fatty triangle: validation and educational impact study

BACKGROUND

Incisional hernia repair requires detailed anatomic knowledge. Regarding median subxiphoidal hernias, the proper preparation of the fatty triangle is challenging. To foster proficiency-based training, a cost-efficient model for open median retromuscular mesh repair resembling the human body was developed, including the main anatomical structures related to the procedure. The aim is to create and validate a high-fidelity model on open retromuscular mesh repair suitable for "training before doing".

MATERIALS AND METHODS

Different types of fabrics for imitation of connective tissue and 2-component silicones were used to construct the incisional hernia model. Sample size for validation of the model was determined by a triangular testing approach. Operations from six beginners and six experts were assessed by three blinded-raters. Reliability and construct-validity were evaluated on a behaviorally anchored rating scale (highest score: 4) for the criteria: "instrument use", "tissue handling", "near misses and errors", and "end-product quality".

RESULTS

The model authentically mimicked an open median retromuscular mesh repair. Participants considered the procedure realistic. Reliability was excellent, ranging from 0.811 to 0.974 for "end-product quality", and "tissue handling" respectively. Construct-validity was confirmed with experts significantly outperforming beginners in the "use of instruments" (M_beg. = 2.33, M_exp. = 3.94, p < 0.001), "tissue handling" (M_beg. = 2.11, M_exp. = 3.72, p < 0.001), "near misses and errors" (M_beg. = 2.67, M_exp. = 3.67, p < 0.001), and "end-product quality" (M_beg. = 2.78, M_exp. = 3.72, p < 0.001). Criterion-validity revealed a paradox effect: beginners performed significantly better than experts (p < 0.05) when preparing the fatty triangle.

CONCLUSIONS

The model covers all relevant aspects involved in median-open retromuscular incisional hernia mesh repair. Performance differences between beginners and experts confirm construct-validity and thereby realism of the model. It enables to efficiently improve and practice technical skills of the demanding surgery.

Influence of on-farm measurements for heat stress indicators on dairy cow productivity, female fertility, and health

The aim of the present study was to quantify the effect of heat stress (HS) from different points in time on production, female fertility, and health traits. In this regard, on-farm measurements for temperature and relative humidity were combined into temperature-humidity indexes (THI), and merged with longitudinal cow traits from electronic recording systems. The study included traits from 22,212 Holstein cows kept in 15 large-scale dairy co-operator herds. Trait and meteorological data recording spanned a period between May 2013 and November 2015. Longitudinal production traits considered 191,911 test-day records for protein yield, protein percentage, and milk urea nitrogen (MUN). Female fertility traits were the pregnancies per AI (P/AI) and the number of daily inseminations per herd cow (INS/HCOW). Health traits considered clinical mastitis (MAST), retained placenta, puerperal disorders (PD) from d 0 to 10 postpartum, and the claw disorders digital phlegmona, digital dermatitis (DD), and interdigital hyperplasia from d 0 to 360 postpartum. For all traits, we analyzed the THI influence from the trait-recording day. In addition, we studied the time-lagged THI effect from the previous week. Linear mixed models were applied to estimate THI effects on Gaussian distributed production traits. For binary health and fertility traits, generalized linear mixed models with a logit link function were used. The continuous THI effect was either modeled linear, or via Legendre polynomials of order 4. Regression models for THI were validated via THI class effects (i.e., 5% percentiles for THI). Protein percentage decreased with increasing test-day THI, and with increasing THI from the previous week. Protein yield obviously decreased beyond THI 68 for both THI measurements (test-day THI and THI from previous week). For MUN, the visually identified test-day HS threshold was THI 70. Time-lagged THI effects on MUN were less obvious. For both THI measuring dates, INS/HCOW was highest at THI 57. Beyond THI 57, INS/HCOW substantially decreased. For P/AI, the visually identified HS threshold at the insemination date was THI 65. Temperature-humidity indexes from the previous week had a moderate detrimental effect on P/AI. Incidences for MAST, retained placenta, and PD during d 0 to 10 postpartum increased with increasing average THI from this period. Studying the whole lactation period, incidences for interdigital hyperplasia also increased with increasing THI from the previous week. An opposite THI response was identified for DD: DD decreased with increasing THI. For all health traits, associations between disease incidences and THI were almost linear. Hence, for health traits, no obvious HS thresholds were detected. Especially in early lactation, HS had a detrimental effect on cow productivity and female fertility. The influence of HS on cow health differed, depending on the disease pathogenesis.

Phenotypic relationships, genetic parameters, genome-wide associations, and identification of potential candidate genes for ketosis and fat-to-protein ratio in German Holstein cows

Energy demand for milk production in early lactation exceeds energy intake, especially in high-yielding Holstein cows. Energy deficiency causes increasing susceptibility to metabolic disorders. In addition to several blood parameters, the fat-to-protein ratio (FPR) is suggested as an indicator for ketosis, because a FPR >1.5 refers to high lipolysis. The aim of this study was to analyze phenotypic, quantitative genetic, and genomic associations between FPR and ketosis. In this regard, 8,912 first-lactation Holstein cows were phenotyped for ketosis according to a veterinarian diagnosis key. Ketosis was diagnosed if the cow showed an abnormal carbohydrate metabolism with increased content of ketone bodies in the blood or urine. At least one entry for ketosis in the first 6 wk after calving implied a score = 1 (diseased); otherwise, a score = 0 (healthy) was assigned. The FPR from the first test-day was defined as a Gaussian distributed trait (FPRgauss), and also as a binary response trait (FPRbin), considering a threshold of FPR = 1.5. After imputation and quality controls, 45,613 SNP markers from the 8,912 genotyped cows were used for genomic studies. Phenotypically, an increasing ketosis incidence was associated with significantly higher FPR, and vice versa. Hence, from a practical trait recording perspective, first test-day FPR is suggested as an indicator for ketosis. The ketosis heritability was slightly larger when modeling the pedigree-based relationship matrix (pedigree-based: 0.17; SNP-based: 0.11). For FPRbin, heritabilities were larger when modeling the genomic relationship matrix (pedigree-based: 0.09; SNP-based: 0.15). For FPRgauss, heritabilities were almost identical for both pedigree and genomic relationship matrices (pedigree-based: 0.14; SNP-based: 0.15). Genetic correlations between ketosis with FPRbin and FPRgauss using either pedigree- or genomic-based relationship matrices were in a moderate range from 0.39 to 0.71. Applying genome-wide association studies, we identified the specific SNP rs109896020 (BTA 5, position: 115,456,438 bp) significantly contributing to ketosis. The identified potential candidate gene PARVB in close chromosomal distance is associated with nonalcoholic fatty liver disease in humans. The most important SNP contributing to FPRbin was located within the DGAT1 gene. Different SNP significantly contributed to ketosis and FPRbin, indicating different mechanisms for both traits genomically.

Four-Body Scale in Universal Few-Boson Systems

The role of an intrinsic four-body scale in universal few-boson systems is the subject of active debate. We study these systems within the framework of effective field theory. For systems of up to six bosons we establish that no four-body scale appears at leading order (LO). However, we find that at next-to-leading order (NLO) a four-body force is needed to obtain renormalized results for binding energies. With the associated parameter fixed to the binding energy of the four-boson system, this force is shown to renormalize the five- and six-body systems as well. We present an original ansatz for the short-distance limit of the bosonic A-body wave function from which we conjecture that new A-body scales appear at N^{A-3} LO. As a specific example, calculations are presented for clusters of helium atoms. Our results apply more generally to other few-body systems governed by a large scattering length, such as light nuclei and halo states, the low-energy properties of which are independent of the detailed internal structure of the constituents.

Fission of Polyanionic Metal Clusters

Size-selected dianionic lead clusters Pb_{n}^{2-}, n=34-56, are stored in a Penning trap and studied with respect to their decay products upon photoexcitation. Contrary to the decay of other dianionic metal clusters, these lead clusters show a variety of decay channels. The mass spectra of the fragments are compared to the corresponding spectra of the monoanionic precursors. This comparison leads to the conclusion that, in the cluster size region below about n=48, the fission reaction Pb_{n}^{2-}→Pb_{n-10}^{-}+Pb_{10}^{-} is the major decay process. Its disappearance at larger cluster sizes may be an indication of a nonmetal to metal transition. Recently, the pair of Pb_{10}^{-} and Pb_{n-10}^{-} were observed as pronounced fragments in electron-attachment studies [S. König et al., Int. J. Mass Spectrom. 421, 129 (2017)IMSPF81387-380610.1016/j.ijms.2017.06.009]. The present findings suggest that this combination is the fingerprint of the decay of doubly charged lead clusters. With this assumption, the dianion clusters have been traced down to Pb_{21}^{2-}, whereas the smallest size for the direct observation was as high as n=28.

Genomic breeding values, SNP effects and gene identification for disease traits in cow training sets

Holstein Friesian cow training sets were created according to disease incidences. The different datasets were used to investigate the impact of random forest (RF) and genomic BLUP (GBLUP) methodology on genomic prediction accuracies. In addition, for further verifications of some specific scenarios, single-step genomic BLUP was applied. Disease traits included the overall trait categories of (i) claw disorders, (ii) clinical mastitis and (iii) infertility from 80 741 first lactation Holstein cows kept in 58 large-scale herds. A subset of 6744 cows was genotyped (50K SNP panel). Response variables for all scenarios were de-regressed proofs (DRPs) and pre-corrected phenotypes (PCPs). Initially, all sick cows were allocated to the testing set, and healthy cows represented the training set. For the ongoing cow allocation schemes, the number of sick cows in the training set increased stepwise by moving 10% of the sick cows from the testing to the training set in each step. The size of training and testing sets was kept constant by replacing the same number of cows in the testing set with (randomly selected) healthy cows from the training set. For both the RF and GBLUP methods, prediction accuracies were larger for DRPs compared to PCPs. For PCPs as a response variable, the largest prediction accuracies were observed when the disease incidences in training sets reflected the disease incidence in the whole population. A further increase in prediction accuracies for some selected cow allocation schemes (i.e. larger prediction accuracies compared to corresponding scenarios with RF or GBLUB) was achieved via single-step GBLUP applications. Correlations between genome-wide association study SNP effects and RF importance criteria for single SNPs were in a moderate range, from 0.42 to 0.57, when considering SNPs from all chromosomes or from specific chromosome segments. RF identified significant SNPs close to potential positional candidate genes: GAS1, GPAT3 and CYP2R1 for clinical mastitis; SPINK5 and SLC26A2 for laminitis; and FGF12 for endometritis.

Genome-wide pleiotropy and shared biological pathways for resistance to bovine pathogens

Host genetic architecture is a major factor in resistance to pathogens and parasites. The collection and analysis of sufficient data on both disease resistance and host genetics has, however, been a major obstacle to dissection the genetics of resistance to single or multiple pathogens. A severe challenge in the estimation of heritabilities and genetic correlations from pedigree-based studies has been the confounding effects of the common environment shared among relatives which are difficult to model in pedigree analyses, especially for health traits with low incidence rates. To circumvent this problem we used genome-wide single-nucleotide polymorphism data and implemented the Genomic-Restricted Maximum Likelihood (G-REML) method to estimate the heritabilities and genetic correlations for resistance to 23 different infectious pathogens in calves and cows in populations undergoing natural pathogen challenge. Furthermore, we conducted gene-based analysis and generalized gene-set analysis to understand the biological background of resistance to infectious diseases. The results showed relatively higher heritabilities of resistance in calves than in cows and significant pleiotropy (both positive and negative) among some calf and cow resistance traits. We also found significant pleiotropy between resistance and performance in both calves and cows. Finally, we confirmed the role of the B-lymphocyte pathway as one of the most important biological pathways associated with resistance to all pathogens. These results both illustrate the potential power of these approaches to illuminate the genetics of pathogen resistance in cattle and provide foundational information for future genomic selection aimed at improving the overall production fitness of cattle.

Live-Wires Using Path-Graphs

Objectives: This article discusses our new Path-Graph approach for the interactive Live-Wire segmentation method in 2D applied to pre-segmented data. Furthermore, we examine whether or not the Live-Lane extension provides advantages in combination with pre-segmentation.

Methods: We automatically over-segment the image data in a preprocessing step, using region growing with an automatic seed point generation. The Live-Wire algorithm is applied on this mosaic data by using the outlines of the homogeneous regions as the basis for graph building. We present a new definition of this underlying graph where the edges of the standard graphs are turning into vertices and the vertices of the new graph are defined by the edge connectivity in the standard graph. For better differentiation we name our new graph Path-Graph and the original defined graph Node-Graph.

Results: The quality evaluation is done by comparing our segmentation results with existing model data. We show that using the Path-Graph as basis for the Live-Wire algorithm instead of the Node-Graph allows for a finer segmentation. We achieve a reduction of incorrectly classified pixels by 20.66 per cent and a decrease of the mean boundary deviation by 11.61 per cent. Since savings on cost tree calculations are compensated by additional computation time required to compute the Live-Lanes, a performance loss of 2.41 per cent is measured.

Conclusions: Our redefinition of the underlying graph increases the quality of the Live-Wire segmentation. The Live-Lane extension in combination with pre-segmentation is not justified for our data.

Sub-arcsecond imaging of the water emission in Arp 220

AIMS

Extragalactic observations of water emission can provide valuable insights into the excitation of the interstellar medium. In particular they allow us to investigate the excitation mechanisms in obscured nuclei, i.e. whether an active galactic nucleus or a starburst dominate.

METHODS

We use sub-arcsecond resolution observations to tackle the nature of the water emission in Arp 220. ALMA Band 5 science verification observations of the 183 GHz H₂O 3₁₃-2₂₀ line, in conjunction with new ALMA Band 7 H₂O 5₁₅-4₂₂ data at 325 GHz, and supplementary 22 GHz H₂O 6₁₆ - 5₂₃ VLA observations, are used to better constrain the parameter space in the excitation modelling of the water lines.

RESULTS

We detect 183 GHz H₂O and 325 GHz water emission towards the two compact nuclei at the center of Arp 220, being brighter in Arp 220 West. The emission at these two frequencies is compared to previous single-dish data and does not show evidence of variability. The 183 and 325 GHz lines show similar spectra and kinematics, but the 22 GHz profile is significantly different in both nuclei due to a blend with an NH₃ absorption line.

CONCLUSIONS

Our findings suggest that the most likely scenario to cause the observed water emission in Arp 220 is a large number of independent masers originating from numerous star-forming regions.

A comprehensive and efficient daily quality assurance for PBS proton therapy

There are several general recommendations for quality assurance (QA) measures, which have to be performed at proton therapy centres. However, almost each centre uses a different therapy system. In particular, there is no standard procedure for centres employing pencil beam scanning and each centre applies a specific QA program. Gantry 2 is an operating therapy system which was developed at PSI and relies on the most advanced technological innovations. We developed a comprehensive daily QA program in order to verify the main beam characteristics to assure the functionality of the therapy delivery system and the patient safety system. The daily QA program entails new hardware and software solutions for a highly efficient clinical operation. In this paper, we describe a dosimetric phantom used for verifying the most critical beam parameters and the software architecture developed for a fully automated QA procedure. The connection between our QA software and the database allows us to store the data collected on a daily basis and use it for trend analysis over longer periods of time. All the data presented here have been collected during a time span of over two years, since the beginning of the Gantry 2 clinical operation in 2013. Our procedure operates in a stable way and delivers the expected beam quality. The daily QA program takes only 20 min. At the same time, the comprehensive approach allows us to avoid most of the weekly and monthly QA checks and increases the clinical beam availability.