[Digitalization and clinical decision tools]. / Digitalisierung und Clinical Decision Tools.

Digitalization in cardiovascular emergencies is rapidly evolving, analogous to the development in medicine, driven by the increasingly broader availability of digital structures and improved networks, electronic health records and the interconnectivity of systems. The potential use of digital health in patients with acute chest pain starts even in the prehospital phase with the transmission of a digital electrocardiogram (ECG) as well as telemedical support and digital emergency management, which facilitate optimization of the rescue pathways and reduce critical time intervals. The increasing dissemination and acceptance of guideline apps and clinical decision support tools as well as integrated calculators and electronic scores are anticipated to improve guideline adherence, translating into a better quality of treatment and improved outcomes. Implementation of artificial intelligence to support image analysis and also the prediction of coronary artery stenosis requiring interventional treatment or impending cardiovascular events, such as heart attacks or death, have an enormous potential especially as conventional instruments frequently yield suboptimal results; however, there are barriers to the rapid dissemination of corresponding decision aids, such as the regulatory rules related to approval as a medical product, data protection issues and other legal liability aspects, which must be considered.

Design and validation of a medical robotic device system to control two collaborative robots for ultrasound-guided needle insertions.

The percutaneous biopsy is a critical intervention for diagnosis and staging in cancer therapy. Robotic systems can improve the efficiency and outcome of such procedures while alleviating stress for physicians and patients. However, the high complexity of operation and the limited possibilities for robotic integration in the operating room (OR) decrease user acceptance and the number of deployed robots. Collaborative systems and standardized device communication may provide approaches to overcome named problems. Derived from the IEEE 11073 SDC standard terminology of medical device systems, we designed and validated a medical robotic device system (MERODES) to access and control a collaborative setup of two KUKA robots for ultrasound-guided needle insertions. The system is based on a novel standard for service-oriented device connectivity and utilizes collaborative principles to enhance user experience. Implementing separated workflow applications allows for a flexible system setup and configuration. The system was validated in three separate test scenarios to measure accuracies for 1) co-registration, 2) needle target planning in a water bath and 3) in an abdominal phantom. The co-registration accuracy averaged 0.94 ± 0.42 mm. The positioning errors ranged from 0.86 ± 0.42 to 1.19 ± 0.70 mm in the water bath setup and from 1.69 ± 0.92 to 1.96 ± 0.86 mm in the phantom. The presented results serve as a proof-of-concept and add to the current state of the art to alleviate system deployment and fast configuration for percutaneous robotic interventions.

Practical setting and potential applications of interventions guided by PET/MRI.

Multimodality imaging has emerged from a vision thirty years ago to routine clinical use today. Positron emission tomography (PET)/magnetic resonance imaging (MRI) is still relatively new in this arena and particularly suitable for clinical research and technical development. PET/MRI-guidance for interventions opens up opportunities for novel treatments but at the same time demands certain technical and organizational requirements to be fulfilled. In this work, we aimed to demonstrate a practical setting and potential application of PET/MRI guidance of interventional procedures. The superior quantitative physiologic information of PET, the various unique imaging characteristics of MRI, and the reduced radiation exposure are the most relevant advantages of this technique. As a noninvasive interventional tool, focused ultrasound (FUS) ablation of tumor cells would benefit from PET/MRI for diagnostics, treatment planning and intervention. Yet, technical limitations might impeed preclinical research, given that PET/MRI sites are per se not designed as interventional suites. Nonetheless, several approaches have been offered in the past years to upgrade MRI suites for interventional purposes. Taking advantage of state of the art and easy-to-use technology it is possible to create a supporting infrastructure that is suitable for broad preclinical adaption. Several aspects are to be addressed, including remote control of the imaging system, display of the imaging results, communication technology, and implementation of additional devices such as a FUS platform and an MR-compatible robotic system for positioning of the FUS equipment. Feasibility could be demostrated with an examplary experimental setup for interventional PET/MRI. Most PET/MRI sites could allow for interventions with just a few add-ons and modifications, such as comunication, in room image display and sytems control. By unlocking this feature, and driving preclinical research in interventional PET/MRI, translation of the protocol and methodology into clinical settings seems feasible.

Optimizing genomic prediction for Australian Red dairy cattle.

The reliability of genomic prediction is influenced by several factors, including the size of the reference population, which makes genomic prediction for breeds with a relatively small population size challenging, such as Australian Red dairy cattle. Including other breeds in the reference population may help to increase the size of the reference population, but the reliability of genomic prediction is also influenced by the relatedness between the reference and validation population. Our objective was to optimize the reference population for genomic prediction of Australian Red dairy cattle. A reference population comprising up to 3,248 Holstein bulls, 48,386 Holstein cows, 807 Jersey bulls, 8,734 Jersey cows, and 3,041 Australian Red cows and a validation population with between 208 and 224 Australian Red Bulls were used, with records for milk, fat, and protein yield, somatic cell count, fertility, and survival. Three different analyses were implemented: single-trait genomic best linear unbiased predictor (GBLUP), multi-trait GBLUP, and single-trait Bayes R, using 2 different medium-density SNP panels: the standard 50K chip and a custom array of variants that were expected to be enriched for causative mutations. Various reference populations were constructed containing the Australian Red cows and all Holstein and Jersey bulls and cows, all Holstein and Jersey bulls, all Holstein bulls and cows, all Holstein bulls, and a subset of the Holstein individuals varying the relatedness between Holsteins and Australian Reds and the number of Holsteins. Varying the relatedness between reference and validation populations only led to small changes in reliability. Whereas adding a limited number of closely related Holsteins increased reliabilities compared with within-breed prediction, increasing the number of Holsteins decreased the reliability. The multi-trait GBLUP, which considered the same trait in different breeds as correlated traits, yielded higher reliabilities than the single-trait GBLUP. Bayes R yielded lower reliabilities than multi-trait GBLUP and outperformed single-trait GBLUP for larger reference populations. Our results show that increasing the size of a multi-breed reference population may result in a reference population dominated by one breed and reduce the reliability to predict in other breeds.

Effect of clinical signs, endocrinopathies, timing of surgery, hyperlipidemia, and hyperbilirubinemia on outcome in dogs with gallbladder mucocele.

Gallbladder mucocele (GBM) is a common extra-hepatic biliary syndrome in dogs with death rates ranging from 7 to 45%. Therefore, the aim of this study was to identify the association of survival with variables that could be utilized to improve clinical decisions. A total of 1194 dogs with a gross and histopathological diagnosis of GBM were included from 41 veterinary referral hospitals in this retrospective study. Dogs with GBM that demonstrated abnormal clinical signs had significantly greater odds of death than subclinical dogs in a univariable analysis (OR, 4.2; 95% CI, 2.14-8.23; P<0.001). The multivariable model indicated that categorical variables including owner recognition of jaundice (OR, 2.12; 95% CI, 1.19-3.77; P=0.011), concurrent hyperadrenocorticism (OR 1.94; 95% CI, 1.08-3.47; P=0.026), and Pomeranian breed (OR, 2.46; 95% CI 1.10-5.50; P=0.029) were associated with increased odds of death, and vomiting was associated with decreased odds of death (OR, 0.48; 95% CI, 0.30-0.72; P=0.001). Continuous variables in the multivariable model, total serum/plasma bilirubin concentration (OR, 1.03; 95% CI, 1.01-1.04; P<0.001) and age (OR, 1.17; 95% CI, 1.08-1.26; P<0.001), were associated with increased odds of death. The clinical utility of total serum/plasma bilirubin concentration as a biomarker to predict death was poor with a sensitivity of 0.61 (95% CI, 0.54-0.69) and a specificity of 0.63 (95% CI, 0.59-0.66). This study identified several prognostic variables in dogs with GBM including total serum/plasma bilirubin concentration, age, clinical signs, concurrent hyperadrenocorticism, and the Pomeranian breed. The presence of hypothyroidism or diabetes mellitus did not impact outcome in this study.

Lipoprotein apheresis influences monocyte subpopulations.

BACKGROUND: Monocytes can be differentiated into subpopulations depending on their expression profile of CD14 and CD16. CD16-positive monocytes are associated with coronary artery disease. Up to now, no data exist about the effect of lipoprotein apheresis (LA) on the distribution of monocyte subpopulations. METHODS: 80 patients who underwent LA at the University Hospital Dresden were included in the study. 8 out of the 80 LA patients received LA for the first time at the time point of blood analysis. Six different methods of LA were used (H.E.L.P. n = 8; Liposorber D n = 10; LF n = 14; DALI n = 17; MONET n = 11; Therasorb® LDL n = 12). Blood samples were taken immediately before and after LA and analyzed for CD14 and CD16 expression on monocytes. A total of 42 patients with cardiovascular risk factors but no indication for LA served as control group. RESULTS: The composition of monocyte-population was analyzed in regard to the 3 subpopulations. After LA, an increase in classical monocytes (CD14++CD16-) (93.3% vs. 93.9%, p < 0.01) and a decrease in non-classical monocytes (CD14+CD16+) (1.5% vs 1.0%; p < 0.001) were observed. LA did not change the amount of intermediate monocytes (CD14++CD16+) (5.3% vs. 5.1%). Two methods (MONET and Therasorb® LDL) did not influence the distribution of monocyte subpopulations. Interestingly, patients with LDL-C above 2.5 mmol/l prior LA showed increased amounts of intermediate monocytes. CONCLUSION: The distribution of monocyte populations is influenced by LA but depends on the distinct method of LA. Influences of LA were mainly observed in the content of classical and non-classical monocytes, whereas the intermediate monocyte population remained unaltered by LA.

Genomic Selection Improves Heat Tolerance in Dairy Cattle.

Dairy products are a key source of valuable proteins and fats for many millions of people worldwide. Dairy cattle are highly susceptible to heat-stress induced decline in milk production, and as the frequency and duration of heat-stress events increases, the long term security of nutrition from dairy products is threatened. Identification of dairy cattle more tolerant of heat stress conditions would be an important progression towards breeding better adapted dairy herds to future climates. Breeding for heat tolerance could be accelerated with genomic selection, using genome wide DNA markers that predict tolerance to heat stress. Here we demonstrate the value of genomic predictions for heat tolerance in cohorts of Holstein cows predicted to be heat tolerant and heat susceptible using controlled-climate chambers simulating a moderate heatwave event. Not only was the heat challenge stimulated decline in milk production less in cows genomically predicted to be heat-tolerant, physiological indicators such as rectal and intra-vaginal temperatures had reduced increases over the 4 day heat challenge. This demonstrates that genomic selection for heat tolerance in dairy cattle is a step towards securing a valuable source of nutrition and improving animal welfare facing a future with predicted increases in heat stress events.

Genomic heritabilities and genomic estimated breeding values for methane traits in Angus cattle.

Enteric methane emissions from beef cattle are a significant component of total greenhouse gas emissions from agriculture. The variation between beef cattle in methane emissions is partly genetic, whether measured as methane production, methane yield (methane production/DMI), or residual methane production (observed methane production - expected methane production), with heritabilities ranging from 0.19 to 0.29. This suggests methane emissions could be reduced by selection. Given the high cost of measuring methane production from individual beef cattle, genomic selection is the most feasible approach to achieve this reduction in emissions. We derived genomic EBV (GEBV) for methane traits from a reference set of 747 Angus animals phenotyped for methane traits and genotyped for 630,000 SNP. The accuracy of GEBV was tested in a validation set of 273 Angus animals phenotyped for the same traits. Accuracies of GEBV ranged from 0.29 ± 0.06 for methane yield and 0.35 ± 0.06 for residual methane production. Selection on GEBV using the genomic prediction equations derived here could reduce emissions for Angus cattle by roughly 5% over 10 yr.

Polyceraty (multi-horns) in Damara sheep maps to ovine chromosome 2.

Polyceraty (presence of multiple horns) is rare in modern day ungulates. Although not found in wild sheep, polyceraty does occur in a small number of domestic sheep breeds covering a wide geographical region. Damara are fat-tailed hair sheep, from the south-western region of Africa, which display polyceraty, with horn number ranging from zero to four. We conducted a genome-wide association study for horn number with 43 Damara genotyped with 606 006 SNP markers. The analysis revealed a region with multiple significant SNPs on ovine chromosome 2, in a location different from the mutation for polled in sheep on chromosome 10. The causal mutation for polyceraty was not identified; however, the region associated with polyceraty spans nine HOXD genes, which are critical in embryonic development of appendages. Mutations in HOXD genes are implicated in polydactly phenotypes in mice and humans. There was no evidence for epistatic interactions contributing to polyceraty. This is the first report on the genetic mechanisms underlying polyceraty in the under-studied Damara.

DCE-MRI of the breast in a stand-alone setting outside a complementary strategy - results of the TK-study.

OBJECTIVES: To evaluate the accuracy of MRI of the breast (DCE-MRI) in a stand-alone setting with extended indications. MATERIALS AND METHODS: According to the inclusion criteria, breast specialists were invited to refer patients to our institution for DCE-MRI. Depending on the MR findings, patients received either a follow-up or biopsy. Between 04/2006 and 12/2011 a consecutive total of 1,488 women were prospectively examined. RESULTS: Of 1,488 included patients, 393 patients were lost to follow-up, 1,095 patients were evaluated. 124 patients were diagnosed with malignancy by DCE-MRI (76 TP, 48 FP, 971 TN, 0 FN cases). Positive cases were confirmed by histology, negative cases by MR follow-ups or patient questionnaires over the next 5 years in 1,737 cases (sensitivity 100 %; specificity 95.2 %; PPV 61.3 %; NPV 100 %; accuracy 95.5 %). For invasive cancers only (DCIS excluded), the results were 63 TP; 27 FP; 971 TP and 0 FN (sensitivity 100 %; specificity 97.2 %; PPV 70 %; NPV 100 %; accuracy 97.5 %). CONCLUSION: The DCE-MRI indications tested imply that negative results in DCE-MRI reliably exclude cancer. The results were achieved in a stand-alone setting (single modality diagnosis). However, these results are strongly dependent on reader experience and adequate technical standards as prerequisites for optimal diagnoses. KEY POINTS: • DCE-MRI of the breast has a high accuracy in finding breast cancer. • The set of indications for DCE-MRI of the breast is still very limited. • DCE-MRI can achieve a high accuracy in a 'screening-like' setting. • Accuracy of breast DCE-MRI is strongly dependent on technique and reader experience. • A negative DCE-MRI effectively excludes cancer.

Tensile Ge microstructures for lasing fabricated by means of a silicon complementary metal-oxide-semiconductor process.

In this work we study, using experiments and theoretical modeling, the mechanical and optical properties of tensile strained Ge microstructures directly fabricated in a state-of-the art complementary metal-oxide-semiconductor fabrication line, using fully qualified materials and methods. We show that these microstructures can be used as active lasing materials in mm-long Fabry-Perot cavities, taking advantage of strain-enhanced direct band gap recombination. The results of our study can be realistically applied to the fabrication of a prototype platform for monolithic integration of near infrared laser sources for silicon photonics.

Adolescent chronic mild stress alters hippocampal CB1 receptor-mediated excitatory neurotransmission and plasticity.

Endocannabinoids (eCBs) are involved in the stress response and alterations in eCB signaling may contribute to the etiology of mood disorders. Exposure to chronic mild stress (CMS), a model of depression, produces downregulation of the cannabinoid 1 (CB1) receptor in the hippocampus of male rats. However, it is unknown how this stress-induced change in CB1 levels affects eCB-mediated neurotransmission. In vitro, field potential recordings from CMS-exposed (21-days) rats were performed to assess the effects of stress on eCB-regulated glutamatergic neurotransmission in/on hippocampal area CA1. We observed that application of the CB1 agonist, WIN 55,212-5 (1 µM), in stress animals resulted in a ∼135% increase in excitatory neurotransmission, whereas CB1 activation in non-stress animals leads to a ∼30% decrease. However, during blockade of GABA(A) neurotransmission with picrotoxin, CB1 activation yielded a ∼35% decrease in stress animals. These findings indicate that CMS does not directly affect glutamatergic neurotransmission. Rather, CMS sensitizes CB1 function on GABAergic terminals, leading to less inhibition and an increase in excitatory neurotransmission. This finding is reinforced in that induction of weak long-term-potentiation (LTP) is enhanced in CMS-exposed animals compared to controls and this enhancement is CB1-dependent. Lastly, we observed that the LTP-blocking property of WIN 55,212-5 shifts from being glutamate-dependent in non-stress animals to being GABA-dependent in stress animals. These results effectively demonstrate that CMS significantly alters hippocampal eCB-mediated neurotransmission and synaptic plasticity.

Accuracy of prediction of genomic breeding values for residual feed intake and carcass and meat quality traits in Bos taurus, Bos indicus, and composite beef cattle.

The aim of this study was to assess the accuracy of genomic predictions for 19 traits including feed efficiency, growth, and carcass and meat quality traits in beef cattle. The 10,181 cattle in our study had real or imputed genotypes for 729,068 SNP although not all cattle were measured for all traits. Animals included Bos taurus, Brahman, composite, and crossbred animals. Genomic EBV (GEBV) were calculated using 2 methods of genomic prediction [BayesR and genomic BLUP (GBLUP)] either using a common training dataset for all breeds or using a training dataset comprising only animals of the same breed. Accuracies of GEBV were assessed using 5-fold cross-validation. The accuracy of genomic prediction varied by trait and by method. Traits with a large number of recorded and genotyped animals and with high heritability gave the greatest accuracy of GEBV. Using GBLUP, the average accuracy was 0.27 across traits and breeds, but the accuracies between breeds and between traits varied widely. When the training population was restricted to animals from the same breed as the validation population, GBLUP accuracies declined by an average of 0.04. The greatest decline in accuracy was found for the 4 composite breeds. The BayesR accuracies were greater by an average of 0.03 than GBLUP accuracies, particularly for traits with known genes of moderate to large effect mutations segregating. The accuracies of 0.43 to 0.48 for IGF-I traits were among the greatest in the study. Although accuracies are low compared with those observed in dairy cattle, genomic selection would still be beneficial for traits that are hard to improve by conventional selection, such as tenderness and residual feed intake. BayesR identified many of the same quantitative trait loci as a genomewide association study but appeared to map them more precisely. All traits appear to be highly polygenic with thousands of SNP independently associated with each trait.

Sensing glucose concentrations at GHz frequencies with a fully embedded Biomicro-electromechanical system (BioMEMS).

The progressive scaling in semiconductor technology allows for advanced miniaturization of intelligent systems like implantable biosensors for low-molecular weight analytes. A most relevant application would be the monitoring of glucose in diabetic patients, since no commercial solution is available yet for the continuous and drift-free monitoring of blood sugar levels. We report on a biosensor chip that operates via the binding competition of glucose and dextran to concanavalin A. The sensor is prepared as a fully embedded micro-electromechanical system and operates at GHz frequencies. Glucose concentrations derive from the assay viscosity as determined by the deflection of a 50 nm TiN actuator beam excited by quasi-electrostatic attraction. The GHz detection scheme does not rely on the resonant oscillation of the actuator and safely operates in fluidic environments. This property favorably combines with additional characteristics-(i) measurement times of less than a second, (ii) usage of biocompatible TiN for bio-milieu exposed parts, and (iii) small volume of less than 1 mm3-to qualify the sensor chip as key component in a continuous glucose monitor for the interstitial tissue.

Single-particle structure determination by correlations of snapshot X-ray diffraction patterns.

Diffractive imaging with free-electron lasers allows structure determination from ensembles of weakly scattering identical nanoparticles. The ultra-short, ultra-bright X-ray pulses provide snapshots of the randomly oriented particles frozen in time, and terminate before the onset of structural damage. As signal strength diminishes for small particles, the synthesis of a three-dimensional diffraction volume requires simultaneous involvement of all data. Here we report the first application of a three-dimensional spatial frequency correlation analysis to carry out this synthesis from noisy single-particle femtosecond X-ray diffraction patterns of nearly identical samples in random and unknown orientations, collected at the Linac Coherent Light Source. Our demonstration uses unsupported test particles created via aerosol self-assembly, and composed of two polystyrene spheres of equal diameter. The correlation analysis avoids the need for orientation determination entirely. This method may be applied to the structural determination of biological macromolecules in solution.

Nanoplasma dynamics of single large xenon clusters irradiated with superintense x-ray pulses from the linac coherent light source free-electron laser.

The plasma dynamics of single mesoscopic Xe particles irradiated with intense femtosecond x-ray pulses exceeding 10(16) W/cm2 from the Linac Coherent Light Source free-electron laser are investigated. Simultaneous recording of diffraction patterns and ion spectra allows eliminating the influence of the laser focal volume intensity and particle size distribution. The data show that for clusters illuminated with intense x-ray pulses, highly charged ionization fragments in a narrow distribution are created and that the nanoplasma recombination is efficiently suppressed.

Fractal morphology, imaging and mass spectrometry of single aerosol particles in flight.

The morphology of micrometre-size particulate matter is of critical importance in fields ranging from toxicology to climate science, yet these properties are surprisingly difficult to measure in the particles' native environment. Electron microscopy requires collection of particles on a substrate; visible light scattering provides insufficient resolution; and X-ray synchrotron studies have been limited to ensembles of particles. Here we demonstrate an in situ method for imaging individual sub-micrometre particles to nanometre resolution in their native environment, using intense, coherent X-ray pulses from the Linac Coherent Light Source free-electron laser. We introduced individual aerosol particles into the pulsed X-ray beam, which is sufficiently intense that diffraction from individual particles can be measured for morphological analysis. At the same time, ion fragments ejected from the beam were analysed using mass spectrometry, to determine the composition of single aerosol particles. Our results show the extent of internal dilation symmetry of individual soot particles subject to non-equilibrium aggregation, and the surprisingly large variability in their fractal dimensions. More broadly, our methods can be extended to resolve both static and dynamic morphology of general ensembles of disordered particles. Such general morphology has implications in topics such as solvent accessibilities in proteins, vibrational energy transfer by the hydrodynamic interaction of amino acids, and large-scale production of nanoscale structures by flame synthesis.

Femtosecond dark-field imaging with an X-ray free electron laser.

The emergence of femtosecond diffractive imaging with X-ray lasers has enabled pioneering structural studies of isolated particles, such as viruses, at nanometer length scales. However, the issue of missing low frequency data significantly limits the potential of X-ray lasers to reveal sub-nanometer details of micrometer-sized samples. We have developed a new technique of dark-field coherent diffractive imaging to simultaneously overcome the missing data issue and enable us to harness the unique contrast mechanisms available in dark-field microscopy. Images of airborne particulate matter (soot) up to two microns in length were obtained using single-shot diffraction patterns obtained at the Linac Coherent Light Source, four times the size of objects previously imaged in similar experiments. This technique opens the door to femtosecond diffractive imaging of a wide range of micrometer-sized materials that exhibit irreproducible complexity down to the nanoscale, including airborne particulate matter, small cells, bacteria and gold-labeled biological samples.

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

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