Conduction System Pacing: Hope, Challenges, and the Journey Forward.

PURPOSE OF THE REVIEW: Cardiac pacing has evolved in recent years currently culminating in the specific stimulation of the cardiac conduction system (conduction system pacing, CSP). This review aims to provide a comprehensive overview of the available literature on CSP, focusing on a critical classification of studies comparing CSP with standard treatment in the two fields of pacing for bradycardia and cardiac resynchronization therapy in patients with heart failure. The article will also elaborate specific benefits and limitations associated with CSP modalities of His bundle pacing (HBP) and left bundle branch area pacing (LBBAP). RECENT FINDINGS: Based on a growing number of observational studies for different indications of pacing therapy, both CSP modalities investigated are advantageous over standard treatment in terms of narrowing the paced QRS complex and preserving or improving left ventricular systolic function. Less consistent evidence exists with regard to the improvement of heart failure-related rehospitalization rates or mortality, and effect sizes vary between HBP and LBBAP. LBBAP is superior over HBP in terms of lead measurements and procedural duration. With regard to all reported outcomes, evidence from large scale randomized controlled clinical trials (RCT) is still scarce. CSP has the potential to sustainably improve patient care in cardiac pacing therapy if patients are appropriately selected and limitations are considered. With this review, we offer not only a summary of existing data, but also an outlook on probable future developments in the field, as well as a detailed summary of upcoming RCTs that provide insights into how the journey of CSP continues.

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.

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.

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.

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.

Role of Chiral Two-Body Currents in

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.

Pro- and anti-inflammatory macrophages express a sub-type specific purinergic receptor profile.

Extracellular nucleotides act as danger signals that orchestrate inflammation by purinergic receptor activation. The expression pattern of different purinergic receptors may correlate with a pro- or anti-inflammatory phenotype. Macrophages function as pro-inflammatory M1 macrophages (M1) or anti-inflammatory M2 macrophages (M2). The present study found that murine bone marrow-derived macrophages express a unique purinergic receptor profile during in vitro polarization. As assessed by real-time polymerase chain reaction (PCR), Gαs-coupled P1 receptors A2A and A2B are upregulated in M1 and M2 compared to M0, but A2A 15 times higher in M1. The ionotropic P2 receptor P2X5 is selectively upregulated in M1- and M2-polarized macrophages. P2X7 is temporarily expressed in M1 macrophages. Metabotropic P2Y receptors showed a distinct expression profile in M1 and M2-polarized macrophages: Gαq coupled P2Y1 and P2Y6 are exclusively upregulated in M2, whereas Gαi P2Y13 and P2Y14 are overexpressed in M1. This consequently leads to functional differences between M1 and M2 in response to adenosine di-phosphate stimulation (ADP): In contrast to M1, M2 showed increased cytoplasmatic calcium after ADP stimulation. In the present study we show that bone marrow-derived macrophages express a unique repertoire of purinergic receptors. We show for the first time that the repertoire of purinergic receptors is highly flexible and quickly adapts upon pro- and anti-inflammatory macrophage differentiation with functional consequences to nucleotide stimulation.

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.

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.

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.

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.

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 (FST ). 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 FST 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.

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 (Wm), 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, Wm, 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.

Survival analyses in Holstein cows considering direct disease diagnoses and specific SNP marker effects.

The aim of the present study was to infer influences of health disorders and of specific SNP markers on longevity in Holstein cows via survival analyses. Longevity was defined as the length of productive life (LPL), reflecting the interval from first calving until the culling or censoring date. In this regard, we considered longevity records from 129,386 Holstein cows from 57 large-scale herds, with calving dates in first parity between January 2004 and December 2017 (30.27% censored records). We selected specific diseases from the overall categories claw disorders, udder diseases, metabolic disorders, and female fertility disorders within 3 stages of parities 1, 2, and 3. Lactation stage 1 was the period from calving to days in milk (DIM) 59, lactation stage 2 from DIM 60 to DIM 299, and lactation stage 3 from DIM 300 to the next calving date. The effects of the diseases on culling risk ratios were estimated via Weibull proportional hazards models. In this regard, we used 3 different modeling strategies. In modeling strategy M1S, binary diseases from different parities and lactation stages for the same diagnosis were modeled as explanatory variables in separate runs. Modeling strategy M3S included diseases for the same diagnosis from stage 1, 2, and 3 in the same parity simultaneously. Modeling strategy M9S implied consideration of diseases for the same diagnosis from different lactation stages and from all 3 parities simultaneously. The effect of the same diseases on culling risks from M1S and M3S were similar, with increasing detrimental effect of diseases recorded in later lactation stages and parities. The strongest disease effect on LPL was detected for clinical and subclinical mastitis recorded in the middle of the third lactation, with culling risks of 2.59 and 2.40, respectively, and for claw disorders from the last stage in third lactation (culling risks in the range from 1.85 to 2.29). The effective (ignoring the proportion of censoring; heff2) and equivalent (considering proportion of censoring; hequ2) heritabilities for LPL when considering diseases from specific stages in parities 1 and 3 were quite low ( heff2 0.02 - 0.17; hequ2 0.01 - 0.12). Simultaneous consideration of same disease diagnoses across stages (M3S) and across lactations (M9S) contributed to a LPL heritability increase. Ignoring diseases as explanatory variables in survival analyses was generally associated with a decline of genetic LPL variances and LPL heritabilities. A genome-wide association study for LPL was based on estimated de-regressed proofs from 17,362 genotyped cows. Six SNP located on Bos taurus autosomes 1, 4, 10, 13, and 28 were significantly associated with LPL (using a 5% false discovery rate). Gene annotations via Ensembl identified the 4 potential candidate genes ETV1, ONECUT1, MACROD2, and SIRT1, which directly (via disease resistance mechanisms) or indirectly (via milk productivity) influence dairy cow longevity. Genotypes of the 6 significantly associated SNP were considered as fixed effects in Weibull hazards models, but their effects on culling risks were nonsignificant. Heritabilities for LPL from all SNP-based survival models considering the single SNP separately or the 6 SNP simultaneously were 0.05 (hequ2) and 0.12 (heff2). The small number of significantly associated SNP in genome-wide associations and the minor effect of specific SNP on LPL in survival analyses underline the polygenetic nature of longevity.

Influence of common health disorders on the length of productive life and stayability in German Holstein cows.

The aim of this study was to infer phenotypic and genetic effects of health disorders on longevity traits, considering Holstein dairy cow records from large-scale co-operator herds. In this regard, we focused on 13 different disease traits and on 2 longevity definitions: length of productive life (LPL) and stayability (STAY). The LPL was defined as the interval in days from first calving to culling. For LPL, we considered 90,215 cows with known culling dates. For binary STAY, we defined 3 survival stages in the first 3 lactations: from calving to DIM 59, from DIM 60 to DIM 299, and from DIM 300 to the next calving date. Due to the earlier trait recording possibilities, 129,386 cows were considered for the STAY analysis. Accordingly, the presence or absence of diseases in lactation stages were defined as binary traits. A further data set for the 90,215 cows with a culling date included the subjective culling reasons defined by farmers. Comparison of culling reasons, as defined by farmers, with diagnoses from the disease data set indicated some disagreements. For example, only 18.71% of the cows with the farmer culling reason "metabolic diseases" were diagnosed with a metabolic disorder. Better agreements were identified for mastitis (84.09%). Phenotypically, in most cases, occurrence of diseases at different lactation stages had negative influence on LPL and STAY. In this regard, we identified strong detrimental effects of clinical mastitis and of metabolic disorders from early lactation stages on longevity traits. For example, the presence of clinical mastitis in the first stage of first lactation was associated with LPL decrease of 95.35 d. Using generalized linear mixed models for binary health disorders, heritabilities ranged from <0.01 (±0.079 standard error) for ruminal acidosis early in first, second, and third lactation to 0.24 (±0.039) for interdigital hyperplasia from the last stage in third lactation. Heritabilities from single-trait and bivariate animal models ranged from 0.03 (±0.003) to 0.10 (±0.007) for LPL, and from 0.01 (±0.002) to 0.06 (±0.007) for STAY. Genetic correlations between longevity traits and health disorders were mostly negative (i.e., favorable in a breeding sense). For improvements to longevity genetic evaluations for young bulls with a limited number of daughter culling dates, we suggest consideration of health traits from a well-organized co-operator herd monitoring system as early longevity predictors, especially for censored data. Genetic correlations between mastitis from different lactation stages with LPL and STAY ranged from -0.28 (±0.07) to -0.69 (±0.05), and from -0.26 (±0.08) to -0.77 (±0.08), respectively. Interestingly, only diagnoses for dermatitis digitalis showed opposite results phenotypically and genetically. Strong genetic associations between ruminal acidosis and STAY were observed (genetic correlations: -0.48 ± 0.18 to -0.98 ± 0.31), supporting the inferred phenotypic associations. Genetic correlations between longevity traits LPL and STAY were quite large, between 0.77 (±0.11) and 0.94 (±0.02) for the different lactation stages, suggesting utility of early STAY information when attempting genetic improvements for longevity.

Genetic and nongenetic profiling of milk ß-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 ß-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.

[Making innovation in teaching measurable : Psychometric validation of the "Radio-Prak": a questionnaire using the example of a clinical practical seminar in interventional radiology]. / Innovationen in der Lehre messbar machen : Psychometrische Validierung des Messinstrumentes "Radio-Prak" am Beispiel eines klinisch-praktischen Seminars der interventionellen Radiologie.

BACKGROUND: As part of the reform of medical education with a stronger focus on clinical-practical skills, a restructured seminar on interventional radiology was evaluated using a newly developed questionnaire. OBJECTIVES: Because knowledge in medical education is increasingly transferred by means of application-based teaching formats, a suitable evaluation tool is essential to assess the quality of newly implemented teaching courses. The aim of this study was to evaluate the seminar on interventional radiology and to validate the "Radio-Prak" questionnaire psychometrically in the process. MATERIALS AND METHODS: In the summer semester of 2018, 123 students participating in the newly established seminar were asked to document their satisfaction using the "Radio-Prak" questionnaire with 23 items employing a 5-point Likert scale. We evaluated the questionnaire psychometrically by performing exploratory factor (EFA) and reliability analysis and examined differential validity by group differences. RESULTS: The newly structured seminar on interventional radiology was met with great approval by students (mean global rating = 1.31, on a grading scale where 1 = very good, 5 = insufficient). EFA revealed that the questionnaire consisted of two main factors "didactic quality" and "practical quality" (five items each, α = 0.68). The seminar was rated more positively when students perceived the time for practice as sufficient (p < 0.05). Furthermore, female students demonstrated significantly less self-esteem, identified by the item "I have improved my spatial ability through the seminar," (p < 0.05). CONCLUSION: The "Radio-Prak" questionnaire is both reliable and valid as an instrument to evaluate the quality of a clinical-practical seminar. The students assessed the didactic dimension, but also rated the practical component as important in the assessment.

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.

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.