Prediction of nitrogen excretion from data on dairy cows fed a wide range of diets compiled in an intercontinental database: A meta-analysis.

Manure nitrogen (N) from cattle contributes to nitrous oxide and ammonia emissions and nitrate leaching. Measurement of manure N outputs on dairy farms is laborious, expensive, and impractical at large scales; therefore, models are needed to predict N excreted in urine and feces. Building robust prediction models requires extensive data from animals under different management systems worldwide. Thus, the study objectives were (1) to collate an international database of N excretion in feces and urine based on individual lactating dairy cow data from different continents; (2) to determine the suitability of key variables for predicting fecal, urinary, and total manure N excretion; and (3) to develop robust and reliable N excretion prediction models based on individual data from lactating dairy cows consuming various diets. A raw data set was created based on 5,483 individual cow observations, with 5,420 fecal N excretion and 3,621 urine N excretion measurements collected from 162 in vivo experiments conducted by 22 research institutes mostly located in Europe (n = 14) and North America (n = 5). A sequential approach was taken in developing models with increasing complexity by incrementally adding variables that had a significant individual effect on fecal, urinary, or total manure N excretion. Nitrogen excretion was predicted by fitting linear mixed models including experiment as a random effect. Simple models requiring dry matter intake (DMI) or N intake performed better for predicting fecal N excretion than simple models using diet nutrient composition or milk performance parameters. Simple models based on N intake performed better for urinary and total manure N excretion than those based on DMI, but simple models using milk urea N (MUN) and N intake performed even better for urinary N excretion. The full model predicting fecal N excretion had similar performance to simple models based on DMI but included several independent variables (DMI, diet crude protein content, diet neutral detergent fiber content, milk protein), depending on the location, and had root mean square prediction errors as a fraction of the observed mean values of 19.1% for intercontinental, 19.8% for European, and 17.7% for North American data sets. Complex total manure N excretion models based on N intake and MUN led to prediction errors of about 13.0% to 14.0%, which were comparable to models based on N intake alone. Intercepts and slopes of variables in optimal prediction equations developed on intercontinental, European, and North American bases differed from each other, and therefore region-specific models are preferred to predict N excretion. In conclusion, region-specific models that include information on DMI or N intake and MUN are required for good prediction of fecal, urinary, and total manure N excretion. In absence of intake data, region-specific complex equations using easily and routinely measured variables to predict fecal, urinary, or total manure N excretion may be used, but these equations have lower performance than equations based on intake.

Nitrogen isotopic discrimination as a biomarker of between-cow variation in the efficiency of nitrogen utilization for milk production: A meta-analysis.

Estimating the efficiency of N utilization for milk production (MNE) of individual cows at a large scale is difficult, particularly because of the cost of measuring feed intake. Nitrogen isotopic discrimination (Δ15N) between the animal (milk, plasma, or tissues) and its diet has been proposed as a biomarker of the efficiency of N utilization in a range of production systems and ruminant species. The aim of this study was to assess the ability of Δ15N to predict the between-animal variability in MNE in dairy cows using an extensive database. For this, 20 independent experiments conducted as either changeover (n = 14) or continuous (n = 6) trials were available and comprised an initial data set of 1,300 observations. Between-animal variability was defined as the variation observed among cows sharing the same contemporary group (CG; individuals from the same experimental site, sampling period, and dietary treatment). Milk N efficiency was calculated as the ratio between mean milk N (grams of N in milk per day) and mean N intake (grams of N intake per day) obtained from each sampling period, which lasted 9.0 ± 9.9 d (mean ± SD). Samples of milk (n = 604) or plasma (n = 696) and feeds (74 dietary treatments) were analyzed for natural 15N abundance (δ15N), and then the N isotopic discrimination between the animal and the dietary treatment was calculated (Δ15n = δ15Nanimal - δ15Ndiet). Data were analyzed through mixed-effect regression models considering the experiment, sampling period, and dietary treatment as random effects. In addition, repeatability estimates were calculated for each experiment to test the hypothesis of improved predictions when MNE and Δ15N measurements errors were lower. The considerable protein mobilization in early lactation artificially increased both MNE and Δ15N, leading to a positive rather than negative relationship, and this limited the implementation of this biomarker in early lactating cows. When the experimental errors of Δ15N and MNE decreased in a particular experiment (i.e., higher repeatability values), we observed a greater ability of Δ15N to predict MNE at the individual level. The predominant negative and significant correlation between Δ15N and MNE in mid- and late lactation demonstrated that on average Δ15N reflects MNE variations both across dietary treatments and between animals. The root mean squared prediction error as a percentage of average observed value was 6.8%, indicating that the model only allowed differentiation between 2 cows in terms of MNE within a CG if they differed by at least 0.112 g/g of MNE (95% confidence level), and this could represent a limitation in predicting MNE at the individual level. However, the one-way ANOVA performed to test the ability of Δ15N to differentiate within-CG the top 25% from the lowest 25% individuals in terms of MNE was significant, indicating that it is possible to distinguish extreme animals in terms of MNE from their N isotopic signature, which could be useful to group animals for precision feeding.

Invited review: Nitrogen in ruminant nutrition: A review of measurement techniques.

Nitrogen is a component of essential nutrients critical for the productivity of ruminants. If excreted in excess, N is also an important environmental pollutant contributing to acid deposition, eutrophication, human respiratory problems, and climate change. The complex microbial metabolic activity in the rumen and the effect on subsequent processes in the intestines and body tissues make the study of N metabolism in ruminants challenging compared with nonruminants. Therefore, using accurate and precise measurement techniques is imperative for obtaining reliable experimental results on N utilization by ruminants and evaluating the environmental impacts of N emission mitigation techniques. Changeover design experiments are as suitable as continuous ones for studying protein metabolism in ruminant animals, except when changes in body weight or carryover effects due to treatment are expected. Adaptation following a dietary change should be allowed for at least 2 (preferably 3) wk, and extended adaptation periods may be required if body pools can temporarily supply the nutrients studied. Dietary protein degradability in the rumen and intestines are feed characteristics determining the primary AA available to the host animal. They can be estimated using in situ, in vitro, or in vivo techniques with each having inherent advantages and disadvantages. Accurate, precise, and inexpensive laboratory assays for feed protein availability are still needed. Techniques used for direct determination of rumen microbial protein synthesis are laborious and expensive, and data variability can be unacceptably large; indirect approaches have not shown the level of accuracy required for widespread adoption. Techniques for studying postruminal digestion and absorption of nitrogenous compounds, urea recycling, and mammary AA metabolism are also laborious, expensive (especially the methods that use isotopes), and results can be variable, especially the methods based on measurements of digesta or blood flow. Volatile loss of N from feces and particularly urine can be substantial during collection, processing, and analysis of excreta, compromising the accuracy of measurements of total-tract N digestion and body N balance. In studying ruminant N metabolism, nutritionists should consider the longer term fate of manure N as well. Various techniques used to determine the effects of animal nutrition on total N, ammonia- or nitrous oxide-emitting potentials, as well as plant fertilizer value, of manure are available. Overall, methods to study ruminant N metabolism have been developed over 150 yr of animal nutrition research, but many of them are laborious and impractical for application on a large number of animals. The increasing environmental concerns associated with livestock production systems necessitate more accurate and reliable methods to determine manure N emissions in the context of feed composition and ruminant N metabolism.

Symposium review: Uncertainties in enteric methane inventories, measurement techniques, and prediction models.

Ruminant production systems are important contributors to anthropogenic methane (CH4) emissions, but there are large uncertainties in national and global livestock CH4 inventories. Sources of uncertainty in enteric CH4 emissions include animal inventories, feed dry matter intake (DMI), ingredient and chemical composition of the diets, and CH4 emission factors. There is also significant uncertainty associated with enteric CH4 measurements. The most widely used techniques are respiration chambers, the sulfur hexafluoride (SF6) tracer technique, and the automated head-chamber system (GreenFeed; C-Lock Inc., Rapid City, SD). All 3 methods have been successfully used in a large number of experiments with dairy or beef cattle in various environmental conditions, although studies that compare techniques have reported inconsistent results. Although different types of models have been developed to predict enteric CH4 emissions, relatively simple empirical (statistical) models have been commonly used for inventory purposes because of their broad applicability and ease of use compared with more detailed empirical and process-based mechanistic models. However, extant empirical models used to predict enteric CH4 emissions suffer from narrow spatial focus, limited observations, and limitations of the statistical technique used. Therefore, prediction models must be developed from robust data sets that can only be generated through collaboration of scientists across the world. To achieve high prediction accuracy, these data sets should encompass a wide range of diets and production systems within regions and globally. Overall, enteric CH4 prediction models are based on various animal or feed characteristic inputs but are dominated by DMI in one form or another. As a result, accurate prediction of DMI is essential for accurate prediction of livestock CH4 emissions. Analysis of a large data set of individual dairy cattle data showed that simplified enteric CH4 prediction models based on DMI alone or DMI and limited feed- or animal-related inputs can predict average CH4 emission with a similar accuracy to more complex empirical models. These simplified models can be reliably used for emission inventory purposes.

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 short-term feed withholding and refeeding challenge.

The objectives of the study were (1) to test whether 6 h of feed deprivation followed by refeeding induces an acidosis challenge in dairy cattle and (2) to quantify the acidosis challenge mitigation potential of increased alfalfa silage concentration in the diet. Alfalfa silage constituted either 25 or 75% of forage dry matter (DM) replacing corn silage [low (LA) or high alfalfa (HA)] and was chopped to either 14 or 19 mm theoretical length [short (S) or long (L)]. Dietary treatments LAS, LAL, HAS, or HAL were offered to 4 rumen-cannulated Holstein dairy cattle (161 d in milk; 5th or 6th parity) in a 4 × 4 Latin square design study with 21-d periods. Starch concentration was 69 g/kg of DM higher for LA diets than HA diets. Feed was withheld for 6 h followed by ad libitum refeeding on d 18 of each period. Measurements of DM intake, milk yield and composition, rumen pH, and eating and rumination behavior were taken on 1 baseline day, the challenge day, and 2 further recovery days. After refeeding, rumen pH was reduced in cows fed LA diets but not HA diets. Feeding LAL resulted in the greatest subclinical acidosis risk (pH <5.8 for 355 min on the first recovery day). Animals fed LA produced 4.4 L less milk on the challenge day in comparison to baseline. It was concluded that short-term feed deprivation detrimentally affected rumen health and milk yield in dairy cattle normally fed ad libitum, but had no effect on DM intake or milk composition. Feeding alfalfa silage in place of corn silage mitigated acidosis risk due to interrupted feed supply, likely due to a combination of lower starch concentration in HA diets, greater effective fiber concentration, and higher buffering capacity of alfalfa relative to corn silage.

Effect of selected plant species within biodiverse pasture on in vitro fatty acid biohydrogenation and tissue fatty acid composition of lamb.

The effect of botanical diversity on supply of polyunsaturated fatty acids (PUFA) to ruminants in vitro, and the fatty acid (FA) composition of muscle in lambs was investigated. Six plant species, commonly grown as part of UK herbal ley mixtures (Trifolium pratense, Lotus corniculatus, Achillea millefolium, Centaurea nigra, Plantago lanceolata and Prunella vulgaris), were assessed for FA profile, and in vitro biohydrogenation of constituent PUFA, to estimate intestinal supply of PUFA available for absorption by ruminants. Modelling the in vitro data suggested that L. corniculatus and P. vulgaris had the greatest potential to increase 18:3n-3 supply to ruminants, having the highest amounts escaping in vitro biohydrogenation. Biodiverse pastures were established using the six selected species, under-sown in a perennial ryegrass-based sward. Lambs were grazed (~50 days) on biodiverse or control pastures and the effects on the FA composition of musculus longissimus thoracis (lean and subcutaneous fat) and musculus semimembranosus (lean) were determined. Biodiverse pasture increased 18:2n-6 and 18:3n-3 contents of m. semimembranosus (+14.8 and +7.2 mg/100 g tissue, respectively) and the subcutaneous fat of m. longissimus thoracis (+158 and +166 mg/100 g tissue, respectively) relative to feeding a perennial ryegrass pasture. However, there was no effect on total concentrations of saturated FA in the tissues studied. It was concluded that enhancing biodiversity had a positive impact on muscle FA profile reflected by increased levels of total PUFA.

Comparative selective retention of particle size classes in the gastrointestinal tract of ponies and goats.

There is a discrepancy in the literature on potential digesta separation mechanisms in horses, with both a selective retention of fine and of large particles postulated in different publications. To assess the net effect of such mechanisms, we fed ponies on a hay-only diet a pulse dose of whole (unchopped) marked hay together with a solute marker, collected faeces on a regular basis, measured marker concentrations in whole faeces and in their large (2.0-16 mm), medium (0.5-1.0 mm) and small (0.063-0.25 mm) particle fraction, and calculated the corresponding mean retention times (MRTs). For comparison, the same experiment was performed in goats. In goats, as expected, MRTsolute (35 hr) was significantly shorter than MRTparticle (51 hr); only a very small fraction of particle marker was excreted as large particles (2%); and the MRT of these large particles was significantly shorter than that of small particles (with a relevant difference of 8.6 hr), indicating that those few large particles that escape the rumen do so mostly soon after ingestion. In ponies, MRTsolute (24 hr) did not differ from MRTparticle (24 hr); a higher fraction of particle marker was excreted as large particles (5%); and the MRT of these large particles was longer than that of small particles (but with a non-relevant difference of less than 1 hr). These results indicate that no relevant net separation of digesta phases occurs in horses and that selective particle retention mechanisms in the large intestine are unlikely to represent important characteristics of the horse's digestive physiology.

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 and tyrosine 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 phenylalanine and tyrosine from the liver via the portal vein and hepatic artery. In addition, the exchange of free phenylalanine and tyrosine between extracellular and intracellular pools was explained and the hydroxylation of phenylalanine to tyrosine was estimated. The model was effective in providing information about the fates of phenylalanine and tyrosine in the liver and could be used as part of a more complex system describing amino acid metabolism in the whole animal.

A mechanistic model of small intestinal starch digestion and glucose uptake in the cow.

The high contribution of postruminal starch digestion (up to 50%) to total-tract starch digestion on energy-dense, starch-rich diets demands that limitations to small intestinal starch digestion be identified. A mechanistic model of the small intestine was described and evaluated with regard to its ability to simulate observations from abomasal carbohydrate infusions in the dairy cow. The 7 state variables represent starch, oligosaccharide, glucose, and pancreatic amylase in the intestinal lumen, oligosaccharide and glucose in the unstirred water layer at the intestinal wall, and intracellular glucose of the enterocyte. Enzymatic hydrolysis of starch was modeled as a 2-stage process involving the activity of pancreatic amylase in the lumen and of oligosaccharidase at the brush border of the enterocyte confined within the unstirred water layer. The Na+-dependent glucose transport into the enterocyte was represented along with a facilitative glucose transporter 2 transport system on the basolateral membrane. The small intestine is subdivided into 3 main sections, representing the duodenum, jejunum, and ileum for parameterization. Further subsections are defined between which continual digesta flow is represented. The model predicted nonstructural carbohydrate disappearance in the small intestine for cattle unadapted to duodenal infusion with a coefficient of determination of 0.92 and a root mean square prediction error of 25.4%. Simulation of glucose disappearance for mature Holstein heifers adapted to various levels of duodenal glucose infusion yielded a coefficient of determination of 0.81 and a root mean square prediction error of 38.6%. Analysis of model behavior identified limitations to the efficiency of small intestinal starch digestion with high levels of duodenal starch flow. Limitations to individual processes, particularly starch digestion in the proximal section of the intestine, can create asynchrony between starch hydrolysis and glucose uptake capacity.

Prediction of portal and hepatic blood flow from intake level data in cattle.

Interest is growing in developing integrated postabsorptive metabolism models for dairy cattle. An integral part of linking a multi-organ postabsorptive model is the prediction of nutrient fluxes between organs, and thus blood flow. The purpose of this paper was to use a multivariate meta-analysis approach to model portal blood flow (PORBF) and hepatic venous blood flow (HEPBF) simultaneously, with evaluation of hepatic arterial blood flow (ARTBF; ARTBF=HEPBF - PORBF) and PORBF/HEPBF (%) as calculated values. The database used to develop equations consisted of 296 individual animal observations (lactating and dry dairy cows and beef cattle) and 55 treatments from 17 studies, and a separate evaluation database consisted of 34 treatment means (lactating dairy cows and beef cattle) from 9 studies obtained from the literature. Both databases had information on dry matter intake (DMI), metabolizable energy intake (MEI), body weight, and a basic description of the diet including crude protein intake and forage proportion of the diet (FP; %). Blood flow (L/h or L/kg of BW0.75/h) and either DMI or MEI (g or MJ/d or g or MJ/kg of BW0.75/d) were examined with linear and quadratic fits. Equations were developed using cow within experiment and experiment as random effects, and blood flow location as a repeated effect. Upon evaluation with the evaluation database, equations based on DMI typically resulted in lower root mean square prediction errors, expressed as a % of the observed mean (rMSPE%) and higher concordance correlation coefficient (CCC) values than equations based on MEI. Quadratic equation terms were frequently nonsignificant, and the quadratic equations did not outperform their linear counterparts. The best performing blood flow equations were PORBF (L/h)=202 (±45.6) + 83.6 (±3.11) × DMI (kg/d) and HEPBF (L/h)=186 (±45.4) + 103.8 (±3.10) × DMI (kg/d), with rMSPE% values of 17.5 and 16.6 and CCC values of 0.93 and 0.94, respectively. The residuals (predicted - observed) for PORBF/HEPBF were significantly related to the forage % of the diet, and thus equations for PORBF and HEPBF based on forage and concentrate DMI were developed: PORBF (L/h)=210 (±51.0) + 82.9 (±6.43) × forage (kg of DM/d) + 82.9 (±6.04) × concentrate (kg of DM/d), and HEPBF (L/h)=184 (±50.6) + 92.6 (±6.28) × forage (kg of DM/d) + 114.2 (±5.88) × concentrate (kg of DM/d), where rMSPE% values were 17.5 and 17.6 and CCC values were 0.93 and 0.94, respectively. Division of DMI into forage and concentrate fractions improved the joint Bayesian information criterion value for PORBF and HEPBF (Bayesian information criterion=6,512 vs. 7,303), as well as slightly improved the rMSPE and CCC for ARTBF and PORBF/HEPBF. This was despite minimal changes in PORBF and HEPBF predictions. Developed equations predicted blood flow well and can easily be used within a postabsorptive model of nutrient metabolism. Results also suggest different sensitivity of PORBF and HEPBF to the composition of DMI, and accounting for this difference resulted in improved ARTBF predictions.

Effects of diet forage source and neutral detergent fiber content on milk production of dairy cattle and methane emissions determined using GreenFeed and respiration chamber techniques.

Strategies to mitigate greenhouse gas emissions from dairy cattle are unlikely to be adopted if production or profitability is reduced. The primary objective of this study was to examine the effects of high maize silage (MS) versus high grass silage (GS) diets, without or with added neutral detergent fiber (NDF) on milk production and methane emission of dairy cattle, using GreenFeed (GF) or respiration chamber (RC) techniques for methane emission measurements. Experiment 1 was 12wk in duration with a randomized block continuous design and 40 Holstein cows (74d in milk) in free-stall housing, assigned to 1 of 4 dietary treatments (n=10 per treatment), according to calving date, parity, and milk yield. Milk production and dry matter intake (DMI) were measured daily, and milk composition measured weekly, with methane yield (g/kg of DMI) estimated using a GF unit (wk 10 to 12). Experiment 2 was a 4×4 Latin square design with 5-wk periods and 4 dairy cows (114d in milk) fed the same 4 dietary treatments as in experiment 1. Measurements of DMI, milk production, and milk composition occurred in wk 4, and DMI, milk production, and methane yield were measured for 2d in RC during wk 5. Dietary treatments for both experiments were fed as total mixed rations offered ad libitum and containing 500g of silage/kg of dry matter composed (DM basis) of either 75:25 MS:GS (MS) or 25:75 MS:GS (GS), without or with added NDF from chopped straw and soy hulls (+47g of NDF/kg of dry matter). In both experiments, compared with high GS, cows fed high MS had a higher DMI, greater milk production, and lower methane yield (24% lower in experiment 1 using GF and 8% lower in experiment 2 using RC). Added NDF increased (or tended to increase) methane yield for high MS, but not high GS diets. In the separate experiments, the GF and RC methods detected similar dietary treatment effects on methane emission (expressed as g/d and g/kg of DMI), although the magnitude of the differences varied between experiments. Overall methane emission and yield were 448g/d and 20.9g/kg of DMI for experiment 1 using GF and 458g/d and 23.8g/kg of DMI for experiment 2 using RC, respectively.

Effects of forage source and extruded linseed supplementation on methane emissions from growing dairy cattle of differing body weights.

Changes in diet carbohydrate amount and type (i.e., starch vs. fiber) and dietary oil supplements can affect ruminant methane emissions. Our objectives were to measure methane emissions, whole-tract digestibility, and energy and nitrogen utilization from growing dairy cattle at 2 body weight (BW) ranges, fed diets containing either high maize silage (MS) or high grass silage (GS), without or with supplemental oil from extruded linseed (ELS). Four Holstein-Friesian heifers aged 13 mo (BW range from start to finish of 382 to 526 kg) were used in experiment 1, whereas 4 lighter heifers aged 12 mo (BW range from start to finish of 292 to 419 kg) were used in experiment 2. Diets were fed as total mixed rations with forage dry matter (DM) containing high MS or high GS and concentrates in proportions (forage:concentrate, DM basis) of either 75:25 (experiment 1) or 60:40 (experiment 2), respectively. Diets were supplemented without or with ELS (Lintec, BOCM Pauls Ltd., Wherstead, UK; 260 g of oil/kg of DM) at 6% of ration DM. Each experiment was a 4 × 4 Latin square design with 33-d periods, with measurements during d 29 to 33 while animals were housed in respiration chambers. Heifers fed MS at a heavier BW (experiment 1) emitted 20% less methane per unit of DM intake (yield) compared with GS (21.4 vs. 26.6, respectively). However, when repeated with heifers of a lower BW (experiment 2), methane yield did not differ between the 2 diets (26.6g/kg of DM intake). Differences in heifer BW had no overall effect on methane emissions, except when expressed as grams per kilogram of digestible organic matter (OMD) intake (32.4 vs. 36.6, heavy vs. light heifers). Heavier heifers fed MS in experiment 1 had a greater DM intake (9.4kg/d) and lower OMD (755 g/kg), but no difference in N utilization (31% of N intake) compared with heifers fed GS (7.9 kg/d and 799 g/kg, respectively). Tissue energy retention was nearly double for heifers fed MS compared with GS in experiment 1 (15 vs. 8% of energy intake, respectively). Heifers fed MS in experiment 2 had similar DM intake (7.2 kg/d) and retention of energy (5% of intake energy) and N (28% of N intake), compared with GS-fed heifers, but OMD was lower (741 vs. 765 g/kg, respectively). No effect of ELS was noted on any of the variables measured, irrespective of animal BW, and this was likely due to the relatively low amount of supplemental oil provided. Differences in heifer BW did not markedly influence dietary effects on methane emissions. Differences in methane yield were attributable to differences in dietary starch and fiber composition associated with forage type and source.

Meta-analysis of relationships between enteric methane yield and milk fatty acid profile in dairy cattle.

Various studies have indicated a relationship between enteric methane (CH4) production and milk fatty acid (FA) profiles of dairy cattle. However, the number of studies investigating such a relationship is limited and the direct relationships reported are mainly obtained by variation in CH4 production and milk FA concentration induced by dietary lipid supplements. The aim of this study was to perform a meta-analysis to quantify relationships between CH4 yield (per unit of feed and unit of milk) and milk FA profile in dairy cattle and to develop equations to predict CH4 yield based on milk FA profile of cows fed a wide variety of diets. Data from 8 experiments encompassing 30 different dietary treatments and 146 observations were included. Yield of CH4 measured in these experiments was 21.5 ± 2.46 g/kg of dry matter intake (DMI) and 13.9 ± 2.30 g/kg of fat- and protein-corrected milk (FPCM). Correlation coefficients were chosen as effect size of the relationship between CH4 yield and individual milk FA concentration (g/100g of FA). Average true correlation coefficients were estimated by a random-effects model. Milk FA concentrations of C6:0, C8:0, C10:0, C16:0, and C16:0-iso were significantly or tended to be positively related to CH4 yield per unit of feed. Concentrations of trans-6+7+8+9 C18:1, trans-10+11 C18:1, cis-11 C18:1, cis-12 C18:1, cis-13 C18:1, trans-16+cis-14 C18:1, and cis-9,12 C18:2 in milk fat were significantly or tended to be negatively related to CH4 yield per unit of feed. Milk FA concentrations of C10:0, C12:0, C14:0-iso, C14:0, cis-9 C14:1, C15:0, and C16:0 were significantly or tended to be positively related to CH4 yield per unit of milk. Concentrations of C4:0, C18:0, trans-10+11 C18:1, cis-9 C18:1, cis-11 C18:1, and cis-9,12 C18:2 in milk fat were significantly or tended to be negatively related to CH4 yield per unit of milk. Mixed model multiple regression and a stepwise selection procedure of milk FA based on the Bayesian information criterion to predict CH4 yield with milk FA as input (g/100g of FA) resulted in the following prediction equations: CH4 (g/kg of DMI)=23.39 + 9.74 × C16:0-iso - 1.06 × trans-10+11 C18:1 - 1.75 × cis-9,12 C18:2 (R(2) = 0.54), and CH4 (g/kg of FPCM) = 21.13 - 1.38 × C4:0 + 8.53 × C16:0-iso - 0.22 × cis-9 C18:1 - 0.59 × trans-10+11 C18:1 (R(2) = 0.47). This indicated that milk FA profile has a moderate potential for predicting CH4 yield per unit of feed and a slightly lower potential for predicting CH4 yield per unit of milk.

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

An isotope dilution model for partitioning phenylalanine and tyrosine uptake by the mammary gland of the lactating dairy cow is constructed and solved in the steady state. The model contains four intracellular and four extracellular pools and conservation of mass principles are applied to generate the fundamental equations describing the behaviour of the system. The experimental measurements required for model solution are milk secretion and plasma flow rate across the gland in combination with phenylalanine and tyrosine concentrations and plateau isotopic enrichments in arterial and venous plasma and free and protein bound milk during a constant infusion of [1-(13)C]phenylalanine and [2,3,5,6-(2)H]tyrosine tracer. If assumptions are made, model solution enables determination of steady state flows for phenylalanine and tyrosine inflow to the gland, outflow from it and bypass, and flows representing the synthesis and degradation of constitutive protein and phenylalanine hydroxylation. The model is effective in providing information about the fates of phenylalanine and tyrosine in the mammary gland and could be used as part of a more complex system describing amino acid metabolism in the whole ruminant.

Short communication: plasma concentration of glucose-dependent insulinotropic polypeptide may regulate milk energy production in lactating dairy cows.

In dairy cows, an increase in plasma concentration of glucose-dependent insulinotropic polypeptide (GIP) is associated with an increase in metabolizable energy intake, but the role of GIP in energy partitioning of dairy cattle is not certain. The objective of this study was to examine the relationship between plasma GIP concentrations and energy partitioning toward milk production. Four mid-lactation, primiparous, rumen-fistulated Holstein-Friesian cows were fed a control diet of 55% forage and 45% concentrate [dry matter (DM) basis] in a 4×4 Latin square design with 4-wk periods. The 4 treatments were (1) control diet fed at 1000 and 1600h, and (2) once-daily (1000h) feeding, (3) twice-daily (1000 and 1600h) feeding, and (4) 4 times/d (1000, 1600, 2200 and 0400h) feeding of the control diet plus 1 dose (1.75kg on a DM basis at 0955h) into the rumen of supplemental vegetable proteins (Amino Green; SCA NuTec Ltd., Thirsk, UK). Measurements of respiratory exchange and energy balance were obtained over 4d during the last week of each period while cows were housed in open-circuit respiration chambers. Blood was collected from the jugular vein every 30min for 12h, using indwelling catheters, starting at 0800h on d 20 of each period. Plasma GIP concentration was measured in samples pooled over each 5 consecutive blood samplings. The relationships between plasma GIP, DM intake, heat production, respiratory quotient (RQ), milk yield, and milk energy output were analyzed using linear correlation procedures, with metabolizable intake as a partial variant. Plasma GIP concentration was not correlated with heat production, or milk yield, but was positively correlated with milk energy yield (correlation coefficient=0.67) and negatively correlated with RQ (correlation coefficient=-0.72). The correlations between GIP with RQ and milk energy output do not imply causality, but support a role for GIP in the regulation of energy metabolism in dairy cows.

A dynamic mechanistic model of lactic acid metabolism in the rumen.

Current feed evaluation systems for ruminants are too imprecise to describe diets in terms of their acidosis risk. The dynamic mechanistic model described herein arises from the integration of a lactic acid (La) metabolism module into an extant model of whole-rumen function. The model was evaluated using published data from cows and sheep fed a range of diets or infused with various doses of La. The model performed well in simulating peak rumen La concentrations (coefficient of determination = 0.96; root mean square prediction error = 16.96% of observed mean), although frequency of sampling for the published data prevented a comprehensive comparison of prediction of time to peak La accumulation. The model showed a tendency for increased La accumulation following feeding of diets rich in nonstructural carbohydrates, although less-soluble starch sources such as corn tended to limit rumen La concentration. Simulated La absorption from the rumen remained low throughout the feeding cycle. The competition between bacteria and protozoa for rumen La suggests a variable contribution of protozoa to total La utilization. However, the model was unable to simulate the effects of defaunation on rumen La metabolism, indicating a need for a more detailed description of protozoal metabolism. The model could form the basis of a feed evaluation system with regard to rumen La metabolism.

Cross-regulation of Connexin43 and ß-catenin influences differentiation of human neural progenitor cells.

Connexin43 (Cx43) is the most widely and abundantly expressed gap junction (GJ) protein and it is strongly associated with the regulation of cell cycle progression. Emerging roles for Cx43 in cell adhesion and migration during neural differentiation have also been recently recognized, and this has emphasized the involvement of Cx43 in different physiological process beyond its role as a GJ protein. In this study, we explore the function of Cx43 in the differentiation of human neural progenitor cells (hNPCs) using viral vectors that mediate the overexpression or knockdown of the protein. Results showed that in the absence of this protein fetal cortex-derived hNPCs differentiated toward a neuronal phenotype at expenses of a glial phenotype. Furthermore, the silencing of Cx43 did not affect hNPC proliferation rate or numbers of apoptotic cells. The increase in the number of neurons was not recapitulated when GJ intercellular communications were pharmacologically blocked, and this suggested that Cx43 was influencing hNPCs differentiation with a GJ-independent effect. In addition, Cx43 knockdown significantly increased ß-catenin signaling, which has been shown to regulate the transcription of pro-neuronal genes during embryonic neural development. Our results add further support to the hypothesis that Cx43 protein itself regulates key signaling pathways during development and neurogenesis beyond its role as GJ protein.

Signalling of DNA damage and cytokines across cell barriers exposed to nanoparticles depends on barrier thickness.

The use of nanoparticles in medicine is ever increasing, and it is important to understand their targeted and non-targeted effects. We have previously shown that nanoparticles can cause DNA damage to cells cultured below a cellular barrier without crossing this barrier. Here, we show that this indirect DNA damage depends on the thickness of the cellular barrier, and it is mediated by signalling through gap junction proteins following the generation of mitochondrial free radicals. Indirect damage was seen across both trophoblast and corneal barriers. Signalling, including cytokine release, occurred only across bilayer and multilayer barriers, but not across monolayer barriers. Indirect toxicity was also observed in mice and using ex vivo explants of the human placenta. If the importance of barrier thickness in signalling is a general feature for all types of barriers, our results may offer a principle with which to limit the adverse effects of nanoparticle exposure and offer new therapeutic approaches.

A model on biological flow of phosphorus in growing pigs / Modelo do fluxo do fósforo em suínos na fase de crescimento

Ten crossbred barrows weighting 20kg were allocated in five groups fed and on diets consisted of different total phosphorus (P) levels: 0.30 percent, 0.40 percent, 0.51 percent, 0.65 percent, and 0.73 percent. The animals were intravenously injected 7.4MBq of radioactive P (32P) and after seven days they were slaughtered for further analysis. The evaluated parameters were intake, excretion, specific activities, and flow of P in compartments (1-gut, 2-blood, 3-bone, and 4-soft tissue). Besides fecal losses, the kidneys played an import role in P regulation. The flows of P from tissue and gut to the blood were affected by P intake.

Foram usados 10 leitões machos castrados com média de peso vivo de 20kg, alojados em gaiolas metabólicas. O delineamento experimental foi inteiramente ao acaso e os tratamentos consistiram em níveis de fósforo (P) nas dietas: 0,30; 0,40; 0,51; 0,65 e 0,73 por cento. Os animais receberam injeção de 7,4 MBq de radiofósforo (32P) e após sete dias foram abatidos para posteriores análises. As variáveis avaliadas foram: ingestão, excreção, atividades específicas e fluxo de P nos compartimentos (1-trato digestivo, 2-corrente sanguínea, 3-tecidos moles e 4-ossos). Além das excreções fecais, os rins também representaram uma rota importante para a excreção do P. O fluxo de P dos tecidos e trato digestivo para o sangue não foi afetado pelo consumo de P. O modelo proposto foi eficiente para avaliar o fluxo de P.

Effects of phosphorus intake on phosphorus flow in growing pigs: application and comparison of two models.

A comparison of the models of Vitti et al. (2000, J. Anim. Sci. 78, 2706-2712) and Fernández (1995c, Livest. Prod. Sci. 41, 255-261) was carried out using two data sets on growing pigs as input. The two models compared were based on similar basic principles, although their aims and calculations differed. The Vitti model employs the rate:state formalism and describes phosphorus (P) flow between four pools representing P content in gut, blood, bone and soft tissue in growing goats. The Fernández model describes flow and fractional recirculation between P pools in gut, blood and bone in growing pigs. The results from both models showed similar trends for P absorption from gut to blood and net retention in bone with increasing P intake, with the exception of the 65 kg results from Date Set 2 calculated using the Fernández model. Endogenous loss from blood back to gut increased faster with increasing P intake in the Fernández than in the Vitti model for Data Set 1. However, for Data Set 2, endogenous loss increased with increasing P intake using the Vitti model, but decreased when calculated using the Fernández model. Incorporation of P into bone was not influenced by intake in the Fernández model, while in the Vitti model there was an increasing trend. The Fernández model produced a pattern of decreasing resorption in bone with increasing P intake, with one of the data sets, which was not observed when using the Vitti model. The pigs maintained their P homeostasis in blood by regulation of P excretion in urine.