An isotope dilution model for partitioning of phenylalanine and tyrosine uptake by the liver of lactating dairy cows

An isotope dilution model to describe the partitioning of phenylalanine (PHE) and tyrosine (TYR) in the bovine liver was developed. The model comprises four intracellular and six extracellular pools and various flows connecting these pools and external blood. Conservation of mass principles were applied to generate the fundamental equations describing the behaviour of the system in the steady state. The model was applied to datasets from multi-catheterised dairy cattle during a constant infusion of [1-13C] phenylalanine and [2,3,5,6-2H] tyrosine tracers. Model solutions described the extraction of PHE and TYR from the liver via the portal vein and hepatic artery. In addition, the exchange of free PHE and TYR between extracellular and intracellular pools was explained and the hydroxylation of PHE to TYR was estimated. The model was effective in providing information about the fates of PHE and TYR in the liver and could be used as part of a more complex system describing amino acid metabolism in the whole animal

The effect of alfalfa (Medicago sativa) silage chop length and inclusion rate within a total mixed ration on the ability of lactating dairy cows to cope with a feed withholding and refeeding challenge

Cows fed diets containing a lower concentration of alfalfa silage (replacing corn silage) experienced greater reductions in rumen pH following a six hour feed witholding/refeeding challenge than those fed higher alfalfa concentration diets and also suffered greater short-term milk loss on the day of the challenge. Lower rumen pH in animals fed a long chop length compared to a shorter chop length raised questions over the effect of long forage particles in the diet during and following short-term feed deprivation. This research highlights the importance of maintaining feeding routines and ensuring adequate feed access throughout the day in dairy systems

Effect of dietary seaweed (Ascophyllum nodosum) supplementation on milk mineral concentrations, transfer efficiency, and hematological parameters in lactating Holstein cows

This study investigated the effect of feeding seaweed (Ascophyllum nodosum) to dairy cows on milk mineral concentrations, feed-to-milk mineral transfer efficiencies and hematological parameters. Lactating Holstein cows (n = 46) were allocated to one of 2 diets (n = 23 each): (i) control (CON; without seaweed), and (ii) seaweed (SWD; replacing 330 g/d of dried corn meal in CON with 330 g/d dried A. nodosum). All cows were fed the CON diet for 4 weeks before the experiment (adaptation period); and animals were then fed the experimental diets for 9 weeks. Samples included sequential 3-week composite feed samples, a composite milk sample on the last day of each week, and a blood sample at the end of the study. Data were statistically analyzed using a linear mixed effects model with diet, week, and their interaction as fixed factors; cow (nested within diet) as a random factor and data collected on the last day of the adaptation period as covariates. Feeding SWD increased milk concentrations of Mg (+6.6 mg/kg), P (+56 mg/kg), and I (+1720 μg/kg). It also reduced transfer efficiency of Ca, Mg, P, K, Mn, and Zn, and increased transfer efficiency of Mo. Feeding SWD marginally reduced milk protein concentrations while there was no effect of SWD feeding on cows' hematological parameters. Feeding A. nodosum increased milk I concentrations, which can be beneficial when feed I concentration is limited or in demographics or populations with increased risk of I deficiency (e.g., female adolescents, pregnant women, nursing mothers). However, care should also be taken when feeding SWD to dairy cows because, in the present study, milk I concentrations were particularly high and could result in I intakes that pose a health risk for children consuming milk.The project leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 730924 (SmartCow). The analysis of macrominerals and trace elements in feed, milk, and blood plasma was funded by the University of Reading (Reading, UK); special thanks go to the laboratory personnel at the University of Reading who supported the analysis of feed, milk, and blood plasma. This output reflects only the authors' views, and the European Union cannot be held responsible for any use that may be made of the information contained therein. The data set supporting the conclusions of this article is available on request from the corresponding authors. Eric E. Newton: conceptualization, methodology, software, validation, formal analysis, investigation, data curation, writing–original draft, writing–review and editing, visualization. Katerina Theodoridou: conceptualization, methodology, resources, writing–review and editing, supervision, project administration, funding acquisition. Marta Terré: project administration, investigation, resources, writing–review and editing. Sharon Huws: writing–review and editing. Partha Ray: conceptualization, methodology, software, supervision. Christopher K. Reynolds: writing–review and editing, supervision. N. Prat: investigation, resources. D. Sabrià: investigation, resources. Sokratis Stergiadis: conceptualization, methodology, resources, data curation, writing–original draft, writing–review and editing, visualization, supervision, project administration. All authors reviewed and approved the manuscript. Animals were managed with common rearing conditions under the supervision of Institute of Agrifood Research and Technology (IRTA, Monells, Spain) technicians and the approval of the Animal Care Committee of the Government of Catalonia (authorization code 11392). The authors have not stated any conflicts of interest.info:eu-repo/semantics/publishedVersio

Full adoption of the most effective strategies to mitigate methane emissions by ruminants can help meet the 1.5 °C target by 2030 but not 2050

To meet the 1.5 °C target, methane (CH) from ruminants must be reduced by 11 to 30% by 2030 and 24 to 47% by 2050 compared to 2010 levels. A meta-analysis identified strategies to decrease product-based (PB; CH per unit meat or milk) and absolute (ABS) enteric CH emissions while maintaining or increasing animal productivity (AP; weight gain or milk yield). Next, the potential of different adoption rates of one PB or one ABS strategy to contribute to the 1.5 °C target was estimated. The database included findings from 430 peer-reviewed studies, which reported 98 mitigation strategies that can be classified into three categories: animal and feed management, diet formulation, and rumen manipulation. A random-effects meta-analysis weighted by inverse variance was carried out. Three PB strategies—namely, increasing feeding level, decreasing grass maturity, and decreasing dietary forage-to-concentrate ratio—decreased CH per unit meat or milk by on average 12% and increased AP by a median of 17%. Five ABS strategies—namely CH inhibitors, tanniferous forages, electron sinks, oils and fats, and oilseeds—decreased daily methane by on average 21%. Globally, only 100% adoption of the most effective PB and ABS strategies can meet the 1.5 °C target by 2030 but not 2050, because mitigation effects are offset by projected increases in CH due to increasing milk and meat demand. Notably, by 2030 and 2050, low- and middle-income countries may not meet their contribution to the 1.5 °C target for this same reason, whereas high-income countries could meet their contributions due to only a minor projected increase in enteric CH emissions.We thank the GLOBAL NETWORK project for generating part of the database. The GLOBAL NETWORK project (https://globalresearchalliance.org/research/livestock/collaborative-activities/global-research-project/; accessed 20 June 2020) was a multinational initiative funded by the Joint Programming Initiative on Food Security, Agriculture, and Climate Change and was coordinated by the Feed and Nutrition Network (https://globalresearchalliance.org/research/livestock/networks/feed-nutrition-network/; accessed 20 June 2020) within the Livestock Research Group of the Global Research Alliance on Agricultural GHG (https://globalresearchalliance.org; accessed 20 June 2020). We thank MitiGate, which was part of the Animal Change project funded by the EU under Grant Agreement FP7-266018 for sharing their database with us (http://mitigate.ibers.aber.ac.uk/, accessed 1 July 2017). Part of C.A., A.N.H., and S.C.M.’s time in the early stages of this project was funded by the Kravis Scientific Research Fund (New York) and a gift from Sue and Steve Mandel to the Environmental Defense Fund. Another part of C.A.’s work on this project was supported by the National Program for Scientific Research and Advanced Studies - PROCIENCIA within the framework of the "Project for the Improvement and Expansion of the Services of the National System of Science, Technology and Technological Innovation" (Contract No. 016-2019) and by the German Federal Ministry for Economic Cooperation and Development (issued through Deutsche Gesellschaft für Internationale Zusammenarbei) through the research “Programme of Climate Smart Livestock” (Programme 2017.0119.2). Part of A.N.H.’s work was funded by the US Department of Agriculture (Washington, DC) National Institute of Food and Agriculture Federal Appropriations under Project PEN 04539 and Accession no. 1000803. E.K. was supported by the Sesnon Endowed Chair Fund of the University of California, Davis

Assessing the accuracy of current near infra-red reflectance spectroscopy analysis for fresh grass-clover mixture silages and development of new equations for this purpose

The purpose of this study was to ascertain whether Near Infra-Red Reflectance Spectroscopy (NIRS) prediction equations calibrated on grass silage samples, could accurately predict the chemical composition of mixed grass-clover silage samples, and furthermore, to develop and calibrate new grass-clover equations should the grass-based equations be insufficiently accurate for these silages. A set of 94 silage samples from mixed grass-clover swards (clover concentration (CC) ranging from 4 to 1000 g/kg as fed; determined manually) were analysed for chemical composition using reference laboratory techniques, in vivo digestible organic matter in the dry matter (DOMD, in sheep), and in situ degradability of dry matter and crude protein (in cows). The same samples were scanned fresh (undried and unmilled, as is standard practice for silage analysis within UK laboratories) using NIRS (at AFBI, Northern Ireland) and grass-based prediction equations applied. Predicted and observed results were compared. Of 15 chemical components that were tested for prediction accuracy, only volatile-corrected dry matter and nitrogen were well predicted (RPD values of 4.9 and 2.4 respectively, with low root mean square errors of prediction (RMSEP)). Neutral detergent fibre and DOMD showed low RPD values, however the predicted and observed datasets had no significant bias between them and were therefore also considered as fit for purpose. Variables with significant bias between predicted and observed datasets that were not considered suitably accurate included crude protein, acid detergent fibre, microbial dry matter yield and the effective degradability of protein. For many components, bias could be attributed at least in part to CC and changes in the fractionation of nutrients present. For some variables such as crude protein, grass-based equations were sufficiently accurate at low CCs but became inaccurate as CC increased, as expected. In response to inadequate prediction accuracy of certain nutrients, new grass-clover equations were calibrated using the obtained spectra. These were validated and results indicated that the grass-clover-based equations outperformed their grass-based counterparts. The adoption of new grass-clover equations, or alternatively, with further development, the use of a CC correction factor to the existing grass-based equations, is recommended for commercial laboratories offering undried and unmilled silage analysis on samples containing clover

Effect of a whey protein and rapeseed oil gel feed supplement on milk fatty acid composition of Holstein cows

Isoenergetic replacement of dietary saturated fatty acids (SFA) with cis-monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA) can reduce cardiovascular disease (CVD) risk. Supplementing dairy cow diets with plant oils lowers milk fat SFA concentrations. However, this feeding strategy can also increase milk fat trans FA (TFA), and negatively impact rumen fermentation. Protection of oil supplements from the rumen environment is therefore needed. In the present study a whey protein gel (WPG) of rapeseed oil (RO) was produced for feeding to dairy cows, in two experiments. In Experiment 1 four multiparous Holstein-Friesian cows in mid-lactation were used in a change-over experiment, with 8-d treatment periods separated by a 5-day washout period. Total mixed ration diets containing 420 g RO or WPG providing 420 g of RO were fed and the effects on milk production, composition and FA concentration were measured. Experiment 2 involved four multiparous mid-lactation Holstein-Friesian cows in a 4 x 4 Latin square design experiment, with 28-d periods, to investigate the effect of incremental dietary inclusion (0, 271, 617 and 814 g/d supplemental oil) of WPG on milk production, composition and FA concentration in the last week of each period. There were minimal effects of WPG on milk FA profile in experiment 1, but trans-18:1 and total trans-MUFA were higher after 8 days of supplementation with RO than with WPG. Incremental diet inclusion of WPG in experiment 2 resulted in linear increases in milk yield, cis- and trans-MUFA and PUFA, and linear decreases in SFA (from 73 to 58 g/100 g FA), and milk fat concentration. The WPG supplement was effective at decreasing milk SFA concentration by replacement with MUFA and PUFA in experiment 2, but the increase in TFA suggested that protection was incomplete

An overview of jets and outflows in stellar mass black holes

In this book chapter, we will briefly review the current empirical understanding of the relation between accretion state and and outflows in accreting stellar mass black holes. The focus will be on the empirical connections between X-ray states and relativistic (`radio') jets, although we are now also able to draw accretion disc winds into the picture in a systematic way. We will furthermore consider the latest attempts to measure/order jet power, and to compare it to other (potentially) measurable quantities, most importantly black hole spin.Comment: Accepted for publication in Space Science Reviews. Also to appear in the Space Sciences Series of ISSI - The Physics of Accretion on to Black Holes (Springer Publisher

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types