Methane emissions and rumen metabolite concentrations in cattle fed two different silages.

In this study, 18 animals were fed two forage-based diets: red clover (RC) and grass silage (GS), in a crossover-design experiment in which methane (CH4) emissions were recorded in respiration chambers. Rumen samples obtained through naso-gastric sampling tubes were analysed by NMR. Methane yield (g/kg DM) was significantly lower from animals fed RC (17.8 ± 3.17) compared to GS (21.2 ± 4.61) p = 0.008. In total 42 metabolites were identified, 6 showing significant differences between diets (acetate, propionate, butyrate, valerate, 3-phenylopropionate, and 2-hydroxyvalerate). Partial least squares discriminant analysis (PLS-DA) was used to assess which metabolites were more important to distinguish between diets and partial least squares (PLS) regressions were used to assess which metabolites were more strongly associated with the variation in CH4 emissions. Acetate, butyrate and propionate along with dimethylamine were important for the distinction between diets according to the PLS-DA results. PLS regression revealed that diet and dry matter intake are key factors to explain CH4 variation when included in the model. Additionally, PLS was conducted within diet, revealing that the association between metabolites and CH4 emissions can be conditioned by diet. These results provide new insights into the methylotrophic methanogenic pathway, confirming that metabolite profiles change according to diet composition, with consequences for CH4 emissions.

Nuclear Magnetic Resonance to Detect Rumen Metabolites Associated with Enteric Methane Emissions from Beef Cattle.

This study presents the application of metabolomics to evaluate changes in the rumen metabolites of beef cattle fed with three different diet types: forage-rich, mixed and concentrate-rich. Rumen fluid samples were analysed by 1H-NMR spectroscopy and the resulting spectra were used to characterise and compare metabolomic profiles between diet types and assess the potential for NMR metabolite signals to be used as proxies of methane emissions (CH4 in g/kg DMI). The dataset available consisted of 128 measurements taken from 4 experiments with CH4 measurements taken in respiration chambers. Predictive modelling of CH4 was conducted by partial least squares (PLS) regression, fitting calibration models either using metabolite signals only as predictors or using metabolite signals as well as other diet and animal covariates (DMI, ME, weight, BW0.75, DMI/BW0.75). Cross-validated R2 were 0.57 and 0.70 for the two models respectively. The cattle offered the concentrate-rich diet showed increases in alanine, valerate, propionate, glucose, tyrosine, proline and isoleucine. Lower methane yield was associated with the concentrate-rich diet (p < 0.001). The results provided new insight into the relationship between rumen metabolites, CH4 production and diets, as well as showing that metabolites alone have an acceptable association with the variation in CH4 production from beef cattle.

Cox regression survival analysis with compositional covariates: Application to modelling mortality risk from 24-h physical activity patterns.

Survival analysis is commonly conducted in medical and public health research to assess the association of an exposure or intervention with a hard end outcome such as mortality. The Cox (proportional hazards) regression model is probably the most popular statistical tool used in this context. However, when the exposure includes compositional covariables (that is, variables representing a relative makeup such as a nutritional or physical activity behaviour composition), some basic assumptions of the Cox regression model and associated significance tests are violated. Compositional variables involve an intrinsic interplay between one another which precludes results and conclusions based on considering them in isolation as is ordinarily done. In this work, we introduce a formulation of the Cox regression model in terms of log-ratio coordinates which suitably deals with the constraints of compositional covariates, facilitates the use of common statistical inference methods, and allows for scientifically meaningful interpretations. We illustrate its practical application to a public health problem: the estimation of the mortality hazard associated with the composition of daily activity behaviour (physical activity, sitting time and sleep) using data from the U.S. National Health and Nutrition Examination Survey (NHANES).

Differences in physical activity time-use composition associated with cardiometabolic risks.

This study investigates the association between the overall physical activity composition of the day (sedentary behavior (SB), light intensity physical activity (LIPA) and moderate-to-vigorous physical activity (MVPA)) and cardiometabolic health, and examines whether improved health can be associated with replacing SB with LIPA. A cross-sectional analysis of the Health Survey for England 2008 on N = 1411 adults was undertaken using a compositional analysis approach to examine the relationship between cardiometabolic risk biomarkers and physical activity accounting for co-dependency between relative amounts of time spent in different behavior. Daily time spent in SB, LIPA and MVPA was determined from waist-mounted accelerometry data (Actigraph GT1M) and modelled against BMI, waist circumference, waist-to-hip ratio, blood pressure, total and HDL cholesterol, HbA1c, and VO2 maximum. The composition of time spent in SB, LIPA and MVPA was statistically significantly associated with BMI, waist circumference, waist-to-hips ratio, HDL cholesterol and VO2 maximum (p < 0.001), but not HbA1c, systolic and diastolic blood pressure, or total cholesterol. Increase of relative time spent in MVPA was beneficially associated with obesity markers, HDL cholesterol, and VO2 maximum, and SB with poorer outcomes. The association of changes in LIPA depended on whether it displaced MVPA or SB. Increasing the proportion of MVPA alone may have the strongest potential association with adiposity outcomes and HDL cholesterol but similar outcomes could also be associated with a lower quantity of MVPA provided a greater quantity of SB is replaced overall with LIPA (around 10.5 min of LIPA is equivalent to 1 min of MVPA).

Compositional mixed modeling of methane emissions and ruminal volatile fatty acids from individual cattle and multiple experiments.

The aim of the study was to investigate the association of methane (CH) yields (g/kg DMI) with rumen VFA molar proportions and animal and diet-related covariates from individual animals and multiple experiments. The dataset available consisted of 284 measurements of CH yields for beef cattle from 6 experiments measured in indirect respiration chambers. A compositional modeling approach was employed where VFA measurements were considered as a whole, instead of in isolation, emphasizing their multivariate relative scale. The analysis revealed expected close groupings of acetate and butyrate; propionate and valerate; iso-butyrate and iso-valerate. Linear mixed models were then fitted to examine relationships between CH yield and VFA, represented by meaningful log-contrasts of components called compositional balances, while accounting for other animal and diet-related covariates and random variability between experiments. A compositional balance representing (acetate × butyrate)/propionate best explained the contribution of VFA to variation in CH yield. The covariates DMI, forage:concentrate proportion (expressed as a categorical variable diet type: high concentrate, mixed forage:concentrate or high forage), and diet ME were also statistically significant. These results provided new insights into the relative inter-relationships among VFA measurements and also between VFA and CH yield. In conclusion, VFA molar proportions as represented by compositional balances were a significant contributor to explaining variation in CH yields from individual cattle.

Characterization of Immune System Cell Subsets in Fixed Tissues from Alpine Chamois (Rupicapra rupicapra).

Immune system cell subsets in lymph nodes and spleen from alpine chamois (Rupicapra rupicapra subspecies rupicapra) living in the Italian Alps were characterized immunohistochemically. Seven primary antibodies (against human CD3, CD79αcy, CD68, or ovine CD4, CD8, CD21 and γδ T-cell receptor [TCR] epitopes) were tested on tissues fixed either in formalin or in zinc salts (ZS) and cross-reactivity with chamois immune cell epitopes was shown. ZS fixation allowed wider identification of immune cells, without the need for antigen retrieval. CD4(+) and CD21(+) cells were labelled only in ZS-fixed tissues. Reagents specific for human CD3, CD79 and CD68 antigens successfully detected chamois immune cells, both in ZS-fixed and formalin-fixed tissues. The reactivity and distribution of immune cells in lymph nodes and spleen were similar to those described in other domestic and wild ruminants. Results from this study may allow future investigation of the immune response and pathogenesis of diseases in the chamois.

Characterization of immune cell infiltration in the placentome of water buffaloes (Bubalus bubalis) infected with neospora caninum during pregnancy.

Neospora caninum infection in cattle stimulates host immune responses, which may be responsible for placental damage leading to abortion. Susceptibility of water buffaloes (Bubalus bubalis) to neosporosis is not well understood, although vertical transmission and fetal death have been documented. The aim of this study was to characterize the immune response in the placentome of water buffalo following experimental infection in early gestation with the Nc-1 strain of N. caninum. Placentomes were examined by immunohistochemistry using antibodies specific for T-cell subsets, natural killer cells and CD79(αcy) cells. Placental inflammation was characterized by the infiltration of CD3(+) and CD4(+) T cells and T cells expressing the γδ T-cell receptor. The distribution of these cellular subsets in buffalo placentomes was similar to that previously described in cattle infected with N. caninum in early gestation, but the lesions were milder, which may explain the lower number of abortions observed in this species after infection.

Values below detection limit in compositional chemical data.

Samples representing part of a whole, usually called compositional data in statistics, are commonplace in analytical chemistry--say chemical data in percentage, ppm, or µg g(-1). Their distinctive feature is that there is an inherent relationship between all the analytes constituting a chemical sample as they only convey relative information. Some compositional data analysis principles and the log-ratio based methodology are outlined here in practical terms. Besides, one often finds that some analytes are not present in sufficient concentration in a sample to allow the measuring instruments to effectively detect them. These non-detects are usually labelled as "