A Basic Model to Predict Enteric Methane Emission from Dairy Cows and Its Application to Update Operational Models for the National Inventory in Norway.

The aim of this study was to develop a basic model to predict enteric methane emission from dairy cows and to update operational calculations for the national inventory in Norway. Development of basic models utilized information that is available only from feeding experiments. Basic models were developed using a database with 63 treatment means from 19 studies and were evaluated against an external database (n = 36, from 10 studies) along with other extant models. In total, the basic model database included 99 treatment means from 29 studies with records for enteric CH4 production (MJ/day), dry matter intake (DMI) and dietary nutrient composition. When evaluated by low root mean square prediction errors and high concordance correlation coefficients, the developed basic models that included DMI, dietary concentrations of fatty acids and neutral detergent fiber performed slightly better in predicting CH4 emissions than extant models. In order to propose country-specific values for the CH4 conversion factor Ym (% of gross energy intake partitioned into CH4) and thus to be able to carry out the national inventory for Norway, the existing operational model was updated for the prediction of Ym over a wide range of feeding situations. A simulated operational database containing CH4 production (predicted by the basic model), feed intake and composition, Ym and gross energy intake (GEI), in addition to the predictor variables energy corrected milk yield and dietary concentrate share were used to develop an operational model. Input values of Ym were updated based on the results from the basic models. The predicted Ym ranged from 6.22 to 6.72%. In conclusion, the prediction accuracy of CH4 production from dairy cows was improved with the help of newly published data, which enabled an update of the operational model for calculating the national inventory of CH4 in Norway.

Effect of nisin on microbiome-brain-gut axis neurochemicals by Escherichia coli-induced diarrhea in mice.

The effects of nisin on the neurochemicals, Aquaporin-3 (AQP-3) and intestinal microorganisms in the brain-gut axis of mice were analyzed by using enzyme linked immune sorbent assay (ELISA) and high throughput sequencing in this investigation, to further revealed the relationship between intestinal flora abundance in mice and neurochemicals in the brain-gut axis. Using HE staining found damage of structure of small intestine villi in the model group (Escherichia coli O1, E. coli O1). Compared with normal control and ciprofloxacin groups, using ELISA showed that nisin increased the highest norepinephrine (NE) expression in the brain, expression of 5-hydroxytryptamine (5-HT) and dopamine (DA) in the duodenum, and increased the expression of AQP-3 in jejunum. Using high-throughput sequencing showed the highest diversity of cecal microflora in nisin group (ACE-index = 1417.25, Chao1-index = 1378.45), but the cecal microflora in the negative control group (ACE-index = 969.54, Chao1-index = 340.29) exhibited the lowest species diversity. Our data indicated that nisin regulates neurochemicals, AQP-3 and cecal microflora imbalance in mice.