Abstract-Nuclear factor-B (NF-B) regulates many genes involved in vascular physiopathology. We have previously observed in vivo NF-B activation in injured vessels that diminished by angiotensin-converting enzyme inhibition. In the present work, we investigated the effect of angiotensin II (Ang II) on NF-B activity in rat vascular smooth muscle cells, evaluating the molecular mechanisms and the specific receptor subtype involved. Ang II increased NF-B DNA binding (5-fold, 10 Ϫ9 mol/L at 1 hour; electrophoretic mobility shift assay), nuclear translocation of p50/p65 subunits, and cytosolic inhibitor B␣ (IB␣) degradation. Ang II elicited NF-B-mediated transcription (transfection of a reporter gene) and expression of NF-B-related genes (monocyte chemoattractant protein-1 and angiotensinogen). AT 1 (DUP753) and AT 2 (PD123319 and CGP42112) receptor antagonists inhibited Ang II-induced NF-B DNA binding in a dose-dependent manner (Ϸ85% for each one; 10 Ϫ5 mol/L at 1 hour). The AT 2 agonist p-aminophenylalanine 6 -Ang II augmented NF-B binding (4.6-fold, 10 Ϫ9 mol/L at 1 hour), p65 nuclear levels, and transcription of an NF-B reporter gene. AT 1 antagonist markedly inhibited NF-B-mediated transcription and gene expression. Some differences between AT 1 /AT 2 intracellular signals were found. Antioxidants and ceramide inhibitors, but not protein kinase C inhibitors, diminished NF-B activation elicited by both Ang II and the AT 2 agonist, while tyrosine kinase inhibitors only decreased Ang II-induced NF-B activity. Our results demonstrate that Ang II activates NF-B via AT 1 and AT 2 , although NF-B-mediated transcription occurred mainly through AT 1 . Both receptors share some signaling pathways (oxygen radicals and ceramide); however, tyrosine kinases only participate in AT 1 /NF-B responses. These data provide novel insights into Ang II actions, suggesting a potential implication of the AT 2 in the pathobiology of vascular cells.

A total of 3,050 German Angus (Aberdeen Angus x German dual-purpose breeds), Charolais, Hereford, Limousin, and German Simmental calves were used to examine temperament traits of beef cattle using 2 different test procedures. The chute test and the flight-speed test have been validated in terms of routine on-farm applicability. Behavior tests were performed in 2006 and 2007 on 24 commercial beef cattle farms located in the northern and eastern part of Germany. A single, trained observer assigned subjective scores to characterize the behavior of each animal during restraint in the head gate (calm, restless shifting, squirming, vigorous movement, violent struggling) and when leaving the chute (walk, trot, run, jumping out of the chute). Breed was a significant source of variation in chute scores and flight-speed scores (P < 0.001). Charolais and Limousin cattle had the greatest scores in both traits, whereas Herefords had the least (P < 0.001) chute scores. German Angus and Hereford calves had the least (P < 0.001) flight-speeds, indicating that these breeds have a more favorable temperament. Temperament scores differed significantly between male and female calves (P < 0.01), with females scoring better for both traits. Average daily BW gains of the calves were significantly influenced by effects of breed (P < 0.001) and sex (P < 0.001) of the calves. Heritabilities were estimated for chute- and flight-speed scores of beef cattle. They were least for chute score and flight-speed score of Limousin cattle with values of 0.11. In contrast, greatest heritabilities were 0.33 for chute score and 0.36 for flight-speed score of Hereford cattle. Genetic correlations were estimated among both temperament traits, with values between 0.57 and 0.98. Chute scores and visual flight-speed scores were negatively correlated with daily BW gain of the calves in most breeds. The results presented in this paper indicate that on-farm evaluation of beef cattle temperament is possible, either using the chute test or the flight-speed test. Genetic selection seems to be promising to improve temperament traits of beef cattle without decreasing production traits like ADG of the calves.

The objective of this study was to compare a conventional dairy cattle breeding program characterized by a progeny testing scheme with different scenarios of genomic breeding programs. The ultimate economic evaluation criterion was discounted profit reflecting discounted returns minus discounted costs per cow in a balanced breeding goal of production and functionality. A deterministic approach mainly based on the gene flow method and selection index calculations was used to model a conventional progeny testing program and different scenarios of genomic breeding programs. As a novel idea, the modeling of the genomic breeding program accounted for the proportion of farmers waiting for daughter records of genotyped young bulls before using them for artificial insemination. Technical and biological coefficients for modeling were chosen to correspond to a German breeding organization. The conventional breeding program for 50 test bulls per year within a population of 100,000 cows served as a base scenario. Scenarios of genomic breeding programs considered the variation of costs for genotyping, selection intensity of cow sires, proportion of farmers waiting for daughter records of genotyped young bulls, and different accuracies of genomic indices for bulls and cows. Given that the accuracies of genomic indices are greater than 0.70, a distinct economic advantage was found for all scenarios of genomic breeding programs up to factor 2.59, mainly due to the reduction in generation intervals. Costs for genotyping were negligible when focusing on a population-wide perspective and considering additional costs for herdbook registration, milk recording, or keeping of bulls, especially if there is no need for yearly recalculation of effects of single nucleotide polymorphisms. Genomic breeding programs generated a higher discounted profit than a conventional progeny testing program for all scenarios where at least 20% of the inseminations were done by genotyped young bulls without daughter records. Evaluation of levels of annual genetic gain for individual traits revealed the same potential for low heritable traits (h 2 = 0.05) compared with moderate heritable traits (h 2 = 0.30), preconditioning highly accurate genomic indices of 0.90. The final economic success of genomic breeding programs strongly depends on the complete abdication of any forms of progeny testing to reduce costs and generation intervals, but such a strategy implies the willingness of the participating milk producers.

Somatic cell counts (SCC) are generally used as an indicator of udder health. Currently in Germany, 100,000 cells/mL is the threshold differentiating infected and noninfected mammary glands. The aim of our study was the detailed analysis of udder health in a representative part of the dairy cow population in Hesse, Germany. Between 2000 and 2008, 615,187 quarter foremilk samples were analyzed. In addition to evaluation of distribution of SCC and prevalence of mastitis pathogens, pathogen prevalence was also calculated depending on SCC. The data indicated that 38% of all samples had SCC >100,000 cells/mL and 62% showed SCC ≤ 100,000 cells/mL; 31% of all samples revealed SCC ≤ 25,000 cells/mL. Coagulase-negative staphylococci were the dominant pathogens in the Hessian quarter foremilk samples (17.17% of all samples) followed by Corynebacterium spp. (13.56%), Streptococcus uberis (8.7%), and Staphylococcus aureus (5.01%). Mastitis pathogens were detected in 83% of all samples with SCC >100,000 cells/mL. However, the prevalence of mastitis pathogens in the SCC range from 1,000 to ≤ 100,000 cells/mL was 8.5% (5.51% minor pathogens, 2.01% major pathogens, and 0.98% other pathogens). For farms producing high quality milk, exceptional hygiene management is compulsory. One of the farms randomly selected showed clearly different results from the Hessian survey. Fifteen percent more samples lay in the SCC range ≤ 100,000 cells/mL with a lower prevalence of mastitis pathogens of 1.91% (1.03% minor pathogens, 0.83% major pathogens, and 0.05% other pathogens). Based on these results, inflammatory processes can obviously be detected in mammary glands of udder quarters healthy according to the current definitions. However, we argue that such inflammation can be detected by examination of the relationship of immune cells in milk.

The aims of the study were to evaluate the relationships among milk urea nitrogen and nonreturn rates at the phenotypic scale, and to estimate genetic parameters among milk urea nitrogen, milk yield, and fertility traits in the early period of lactation. Milk yield, protein percentage, the interval from calving to first service, and 56- and 90-d nonreturn rates were available from 73,344 Holstein cows from 2,178 different herds located in a region in northwestern Germany. Generalized linear models with a logit link function were applied to assess the phenotypic relationships. Bivariate threshold-threshold, linear-threshold, and linear-linear models, fitted in a Bayesian framework, were used to estimate genetic correlations among traits. Milk yield, protein percentage, and milk urea nitrogen were means from test-day 1 (on average 20.8 d in milk) and test-day 2 (on average 53.1 d in milk) after calving. An increase in milk urea nitrogen was associated with decreasing 56-d nonreturn rates on the phenotypic scale. At fixed levels of milk urea nitrogen, greater values of protein percentage, indicating a surplus of energy in the feed, were positively associated with nonreturn rates. Heritabilities were 0.03 for 56- and 90-d nonreturn rates, 0.07 for interval from calving to first service, 0.13 for milk urea nitrogen, and 0.19 for milk yield. Service sire explained a negligible part (below 0.15%) of the total variance for nonreturn rates. Genetic correlations between the interval from calving to first service and nonreturn rates were close to zero. The genetic correlation between nonreturn rates was 0.94, suggesting that a change from nonreturn after 90 d to nonreturn after 56 d in the national genetic evaluation would not result in any loss of information. The genetic correlation between milk yield and nonreturn after 56 d was -0.31, and between milk yield and calving to first service was 0.14, both indicating an antagonistic relationship between production and reproduction. The genetic correlation between milk yield and milk urea nitrogen was 0.44, reflecting an energy deficiency in early lactation. The genetic correlations between milk urea nitrogen and nonreturn rates were too weak (-0.19 for 56-d nonreturn rate, and -0.23 for 90-d nonreturn rate) to justify the use of milk urea nitrogen as an additional trait in genetic selection for fertility, as demonstrated by selection index calculations.

Somatic cell count (SCC) is generally regarded as an indicator of udder health. A cut-off value of 100×10(3) cells/ml is currently used in Germany to differentiate between normal and abnormal secretion of quarters. In addition to SCC, differential cell counts (DCC) can be applied for a more detailed analysis of the udder health status. The aim of this study was to differentiate somatic cells in foremilk samples of udder quarters classified as normal secreting by SCC <100×10(3) cells/ml. Twenty cows were selected and 72 normal secreting udder quarters were compared with a control group of six diseased quarters (SCC >100×10(3) cells/ml). In two severely diseased quarters of the control group (SCC of 967×10(3) cells/ml and 1824×10(3) cells/ml) Escherichia coli and Staphylococcus aureus were detected. DCC patterns of milk samples (n = 25) with very low SCC values of ≤6·25×10(3)cells/ml revealed high lymphocyte proportions of up to 92%. Milk cell populations in samples (n = 41) with SCC values of (>6·25 to ≤25)×10(3) cells/ml were also dominated by lymphocytes (mean value 47%), whereas DCC patterns of milk from udder quarters (n = 6) with SCC values (>25 to ≤100)×10(3)cells/ml changed. While in samples (n = 3) with SCC values of (27-33)×10(3) cells/ml macrophages were predominant (35-40%), three milk samples with (43-45)×10(3) cells/ml indicated already inflammatory reactions based on the predominance of polymorphonuclear leucocytes (PMN) (54-63%). In milk samples of diseased quarters PMN were categorically found as dominant cell population with proportions of ≥65%. Macrophages were the second predominant cell population in almost all samples tested in relationship to lymphocytes and PMN. To our knowledge, this is the first study evaluating cell populations in low SCC milk in detail. Udder quarters classified as normal secreting by SCC <100×10(3) cells/ml revealed already inflammatory processes based on DCC.

Relationships between claw disorders and test-day milk yield recorded in 2005 on 5,360 Holstein cows, kept on 11 large-scale dairy farms in eastern Germany, were analyzed in a Bayesian framework with standard linear and threshold models and recursive linear and threshold models. Four different claw disorders, digital dermatitis (DD), sole ulcer (SU), wall disorder (WD), and interdigital hyperplasia (IH), were scored as binary traits within 200 d after calving and analyzed separately. Incidences of disorders were 13.7% for DD, 16.5% for SU, 9.8% for WD, and 6.7% for IH. Heritabilities of disorders were greater when applying threshold or recursive threshold models than with linear or linear recursive models. Posterior means of genetic correlations between test-day milk production and claw disorders ranged from 0.17 to 0.44, suggesting that breeding strategies focusing on increased milk yield will increase incidences of disorders as a correlated response. A progressive path of lagged relationships was postulated for recursive models describing first the influence of test-day milk yield (MY1) on claw disorders and second, the effect of the disorder on milk production level at the following test day (MY2). In recursive models, structural coefficients describe recursive relationships at the phenotypic level. The structural coefficient lambda21 was the gradient of disease (trait 2) with respect to MY1 (trait 1) for a model with a recursive effect of trait 1 on trait 2. The increase of disease incidence of the 4 different disorders per 1-kg increase of MY1 ranged from lambda21 = 0.006 to lambda21 = 0.024 on the visible scale when applying recursive linear models, and from lambda21 = 0.003 to lambda21 = 0.016 on the underlying liability scale for recursive threshold models. The rate of change in MY2 (trait 3) with respect to the previous claw disorder is given by lambda32 for a model with a recursive effect from trait 2 to trait 3. Structural coefficients lambda32 ranged from -0.12 to -0.68 predicting that a 1-unit increase in the incidence of any disorder reduces milk yield at the following test day by up to 0.67 kg. Rank correlations between sire posterior means for the same claw disorders among different models were >0.84, but some changes in rank of sires in distinct top-10 lists were observed. Structural equation models are of increasing importance in genetic evaluations, and this study showed the possible application of recursive systems, even for categorical data.

In dairy cattle, resistance, tolerance and resilience refer to the adaptation ability to a broad range of environmental conditions, implying stable performances (e.g. production level, fertility status) independent from disease or infection pressure. All three mechanisms resistance, tolerance and resilience contribute to overall robustness, implying the evaluation of phenotyping and breeding strategies for improved robustness in dairy cattle populations. Classically, breeding approaches on improved robustness rely on simple production traits, in combination with detailed environmental descriptors and enhanced statistical modelling to infer possible genotype by environment interactions. In this regard, innovative environmental descriptors were heat stress indicators, and statistical modelling focussed on random regression or reaction norm methodology. A robust animal has high breeding values over a broad spectra of environmental levels. During the last years, direct health traits were included into selection indices, implying advances in genetic evaluations for traits being linked to resistance or tolerance against infectious and non-infectious diseases. Up to now, genetic evaluation for health traits is primarily based on subjectively measured producer-recorded data, with disease trait heritabilities in a low-to-moderate range. Thus, it is imperative to identify objectively measurable phenotypes as suitable biomarkers. New technologies (e.g. mid-infrared spectrometry) offer possibilities to determine potential biomarkers via laboratory analyses. Novel biomarkers include measurable physiological traits (e.g. serum metabolites, hormone levels) as indicators for a current infection, or the host’s reaction to environmental stressors. The rumen microbiome composition is proposed as a biomarker to detect interactions between host genotype and environmental effects. The understanding of host genetic variation in disease resistance and individual expression of robustness encourages analyses on the underlying immune response (IR) system. Recent advances have been made in order to infer the genetic background of IR traits and cows immunological competence in relation to functional and production traits. Thus, a last aspect of this review addresses the genetic background and current state of genetic control for resistance to economically relevant infectious and non-infectious dairy cattle diseases by considering immune-related factors.